The Hadoop Distributed File System (HDFS) is a distributed file system designed to run on commodity hardware. It has many similarities with existing distributed file systems. However, the differences from other distributed file systems are significant.
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HDFS is highly fault-tolerant and is designed to be deployed on low-cost hardware. HDFS provides high throughput access to application data and is suitable for applications that have large data sets.
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HDFS is part of the Apache Hadoop Core project.
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1. NameNode: is the arbitrator and central repository of file namespace in the cluster. The NameNode executes the operations such as opening, closing, and renaming files and directories.
-2. DataNode: manages the storage attached to the node on which it runs. It is responsible for serving all the read and write requests. It performs operations on instructions on NameNode such as creation, deletion, and replications of blocks.
-3. Client: Responsible for getting the required metadata from the namenode and then communicating with the datanodes for reads and writes.
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YARN
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YARN stands for “Yet Another Resource Negotiator“. It was introduced in Hadoop 2.0 to remove the bottleneck on Job Tracker which was present in Hadoop 1.0. YARN was described as a “Redesigned Resource Manager” at the time of its launching, but it has now evolved to be known as a large-scale distributed operating system used for Big Data processing.
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The main components of YARN architecture include:
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1. Client: It submits map-reduce jobs to the resource manager.
-2. Resource Manager: It is the master daemon of YARN and is responsible for resource assignment and management among all the applications. Whenever it receives a processing request, it forwards it to the corresponding node manager and allocates resources for the completion of the request accordingly. It has two major components:
-3. Scheduler: It performs scheduling based on the allocated application and available resources. It is a pure scheduler, which means that it does not perform other tasks such as monitoring or tracking and does not guarantee a restart if a task fails. The YARN scheduler supports plugins such as Capacity Scheduler and Fair Scheduler to partition the cluster resources.
-4. Application manager: It is responsible for accepting the application and negotiating the first container from the resource manager. It also restarts the Application Manager container if a task fails.
-5. Node Manager: It takes care of individual nodes on the Hadoop cluster and manages application and workflow and that particular node. Its primary job is to keep-up with the Node Manager. It monitors resource usage, performs log management and also kills a container based on directions from the resource manager. It is also responsible for creating the container process and starting it on the request of the Application master.
-6. Application Master: An application is a single job submitted to a framework. The application manager is responsible for negotiating resources with the resource manager, tracking the status and monitoring progress of a single application. The application master requests the container from the node manager by sending a Container Launch Context(CLC) which includes everything an application needs to run. Once the application is started, it sends the health report to the resource manager from time-to-time.
-7. Container: It is a collection of physical resources such as RAM, CPU cores and disk on a single node. The containers are invoked by Container Launch Context(CLC) which is a record that contains information such as environment variables, security tokens, dependencies etc.
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MapReduce framework
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1. The term MapReduce represents two separate and distinct tasks Hadoop programs perform-Map Job and Reduce Job. Map jobs take data sets as input and process them to produce key value pairs. Reduce job takes the output of the Map job i.e. the key value pairs and aggregates them to produce desired results.
-2. Hadoop MapReduce (Hadoop Map/Reduce) is a software framework for distributed processing of large data sets on computing clusters. Mapreduce helps to split the input data set into a number of parts and run a program on all data parts parallel at once.
-3. Please find the below Word count example demonstrating the usage of MapReduce framework:
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Other tooling around hadoop
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Hive
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Uses a language called HQL which is very SQL like. Gives non-programmers the ability to query and analyze data in Hadoop. Is basically an abstraction layer on top of map-reduce.
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Ex. HQL query:
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SELECT pet.name, comment FROM pet JOIN event ON (pet.name = event.name);
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In mysql:
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SELECT pet.name, comment FROM pet, event WHERE pet.name = event.name;
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Pig
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Uses a scripting language called Pig Latin, which is more workflow driven. Don't need to be an expert Java programmer but need a few coding skills. Is also an abstraction layer on top of map-reduce.
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Here is a quick question for you:
-What is the output of running the pig queries in the right column against the data present in the left column in the below image?
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Output:
-mysql
-7,Komal,Nayak,24,9848022334,trivendram
-8,Bharathi,Nambiayar,24,9848022333,Chennai
-5,Trupthi,Mohanthy,23,9848022336,Bhuwaneshwar
-6,Archana,Mishra,23,9848022335,Chennai
-3. Spark
-1. Spark provides primitives for in-memory cluster computing that allows user programs to load data into a cluster’s memory and query it repeatedly, making it well suited to machine learning algorithms.
-4. Presto
-1. Presto is a high performance, distributed SQL query engine for Big Data.
-2. Its architecture allows users to query a variety of data sources such as Hadoop, AWS S3, Alluxio, MySQL, Cassandra, Kafka, and MongoDB.
-3. Example presto query:
- mysql
- use studentDB;
- show tables;
- SELECT roll_no, name FROM studentDB.studentDetails where section=’A’ limit 5;
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Data Serialisation and storage
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In order to transport the data over the network or to store on some persistent storage, we use the process of translating data structures or objects state into binary or textual form. We call this process serialization..
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Avro data is stored in a container file (a .avro file) and its schema (the .avsc file) is stored with the data file.
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Apache Hive provides support to store a table as Avro and can also query data in this serialisation format.
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The concept of Big Data has been around for years; most organizations now understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value from it.
-This training material covers the basics of Big Data(using Hadoop) for beginners, who would like to quickly get started and get their hands dirty in this domain.
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What to expect from this training
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This course covers the basics of Big Data and how it has evolved to become what it is today. We will take a look at a few realistic scenarios where Big Data would be a perfect fit. An interesting assignment on designing a Big Data system is followed by understanding the architecture of Hadoop and the tooling around it.
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What is not covered under this training
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Writing programs to draw analytics from data.
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TOC:
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Overview of Big Data
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Usage of Big Data techniques
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Evolution of Hadoop
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Architecture of hadoop
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HDFS
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Yarn
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MapReduce framework
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Other tooling around hadoop
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Hive
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Pig
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Spark
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Presto
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Data Serialisation and storage
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Big Data is a collection of large datasets that cannot be processed using traditional computing techniques. It is not a single technique or a tool, rather it has become a complete subject, which involves various tools, techniques and frameworks.
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Big Data could consist of
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Structured data
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Unstructured data
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Semi-structured data
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Characteristics of Big Data:
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Volume
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Variety
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Velocity
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Variability
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Examples of Big Data generation include stock exchanges, social media sites, jet engines, etc.
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There are more than 300,000 traffic lights in the US as of 2018.
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Let us assume that we placed a device on each of them to collect metrics and send it to a central metrics collection system.
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If each of the IOT devices sends 10 events per minute, we have 300000x10x60x24 = 432x10^7 events per day.
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How would you go about processing that and telling me how many of the signals were “green” at 10:45 am on a particular day?
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Consider the next example on Unified Payments Interface (UPI) transactions:
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We had about 1.15 billion UPI transactions in the month of October, 2019 in India.
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If we try to extrapolate this data to about a year and try to find out some common payments that were happening through a particular UPI ID, how do you suggest we go about that?
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Coming back to our local repo which has two commits. So far, what we have is a single line of history. Commits are chained in a single line. But sometimes you may have a need to work on two different features in parallel in the same repo. Now one option here could be making a new folder/repo with the same code and use that for another feature development. But there's a better way. Use branches. Since git follows tree like structure for commits, we can use branches to work on different sets of features. From a commit, two or more branches can be created and branches can also be merged.
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Using branches, there can exist multiple lines of histories and we can checkout to any of them and work on it. Checking out, as we discussed earlier, would simply mean replacing contents of the directory (repo) with contents snapshot at the checked out version.
We create a branch called b1. Git log tells us that b1 also points to the last commit (7f3b00e) but the HEAD is still pointing to master. If you remember, HEAD points to the commit/reference wherever you are checkout to. So if we checkout to b1, HEAD should point to that. Let's confirm:
b1 still points to the same commit but HEAD now points to b1. Since we create a branch at commit 7f3b00e, there will be two lines of histories starting this commit. Depending on which branch you are checked out on, the line of history will progress.
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At this moment, we are checked out on branch b1, so making a new commit will advance branch reference b1 to that commit and current b1 commit will become its parent. Let's do that.
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# Creating a file and making a commit
-spatel1-mn1:school-of-sre spatel1$ echo "I am a file in b1 branch" > b1.txt
-spatel1-mn1:school-of-sre spatel1$ git add b1.txt
-spatel1-mn1:school-of-sre spatel1$ git commit -m "adding b1 file"
-[b1 872a38f] adding b1 file
-1 file changed, 1 insertion(+)
-create mode 100644 b1.txt
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-# The new line of history
-spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph
-* 872a38f (HEAD -> b1) adding b1 file
-* 7f3b00e (master) adding file 2
-* df2fb7a adding file 1
-spatel1-mn1:school-of-sre spatel1$
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Do note that master is still pointing to the old commit it was pointing to. We can now checkout to master branch and make commits there. This will result in another line of history starting from commit 7f3b00e.
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# checkout to master branch
-spatel1-mn1:school-of-sre spatel1$ git checkout master
-Switched to branch 'master'
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-# Creating a new commit on master branch
-spatel1-mn1:school-of-sre spatel1$ echo "new file in master branch" > master.txt
-spatel1-mn1:school-of-sre spatel1$ git add master.txt
-spatel1-mn1:school-of-sre spatel1$ git commit -m "adding master.txt file"
-[master 60dc441] adding master.txt file
-1 file changed, 1 insertion(+)
-create mode 100644 master.txt
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-# The history line
-spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph
-* 60dc441 (HEAD -> master) adding master.txt file
-* 7f3b00e adding file 2
-* df2fb7a adding file 1
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Notice how branch b1 is not visible here since we are checkout on master. Let's try to visualize both to get the whole picture:
Above tree structure should make things clear. Notice a clear branch/fork on commit 7f3b00e. This is how we create branches. Now they both are two separate lines of history on which feature development can be done independently.
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To reiterate, internally, git is just a tree of commits. Branch names (human readable) are pointers to those commits in the tree. We use various git commands to work with the tree structure and references. Git accordingly modifies contents of our repo.
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Merges
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Now say the feature you were working on branch b1 is complete. And you need to merge it on master branch, where all the final version of code goes. So first you will checkout to branch master and then you will pull the latest code from upstream (eg: GitHub). Then you need to merge your code from b1 into master. And there could be two ways this can be done.
Option 1: Directly merge the branch. Merging the branch b1 into master will result in a new merge commit which will merge changes from two different lines of history and create a new commit of the result.
You can see a new merge commit created (8fc28f9). You will be prompted for the commit message. If there are a lot of branches in the repo, this result will end-up with a lot of merge commits. Which looks ugly compared to a single line of history of development. So let's look at an alternative approach
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First let's reset our last merge and go to the previous state.
Option 2: Rebase. Now, instead of merging two branches which has a similar base (commit: 7f3b00e), let us rebase branch b1 on to current master. What this means is take branch b1 (from commit 7f3b00e to commit 872a38f) and rebase (put them on top of) master (60dc441).
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# Switch to b1
-spatel1-mn1:school-of-sre spatel1$ git checkout b1
-Switched to branch 'b1'
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-# Rebase (b1 which is current branch) on master
-spatel1-mn1:school-of-sre spatel1$ git rebase master
-First, rewinding head to replay your work on top of it...
-Applying: adding b1 file
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-# The result
-spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all
-* 5372c8f (HEAD -> b1) adding b1 file
-* 60dc441 (master) adding master.txt file
-* 7f3b00e adding file 2
-* df2fb7a adding file 1
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You can see b1 which had 1 commit. That commit's parent was 7f3b00e. But since we rebase it on master (60dc441). That becomes the parent now. As a side effect, you also see it has become a single line of history. Now if we were to merge b1 into master, it would simply mean change master to point to 5372c8f which is b1. Let's try it:
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# checkout to master since we want to merge code into master
-spatel1-mn1:school-of-sre spatel1$ git checkout master
-Switched to branch 'master'
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-# the current history, where b1 is based on master
-spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all
-* 5372c8f (b1) adding b1 file
-* 60dc441 (HEAD -> master) adding master.txt file
-* 7f3b00e adding file 2
-* df2fb7a adding file 1
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-# Performing the merge, notice the "fast-forward" message
-spatel1-mn1:school-of-sre spatel1$ git merge b1
-Updating 60dc441..5372c8f
-Fast-forward
-b1.txt | 1 +
-1 file changed, 1 insertion(+)
-create mode 100644 b1.txt
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-# The Result
-spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all
-* 5372c8f (HEAD -> master, b1) adding b1 file
-* 60dc441 adding master.txt file
-* 7f3b00e adding file 2
-* df2fb7a adding file 1
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Now you see both b1 and master are pointing to the same commit. Your code has been merged to the master branch and it can be pushed. Also we have clean line of history! :D
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As an engineer in the field of computer science, having knowledge of version control tools becomes almost a requirement. While there are a lot of version control tools that exist today, Git perhaps is the most used one and this course we will be working with Git. While this course does not start with Git 101 and expects basic knowledge of git as a prerequisite, it will reintroduce the git concepts known by you with details covering what is happening under the hood as you execute various git commands. So that next time you run a git command, you will be able to press enter more confidently!
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What is not covered under this training
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Advanced usage and specifics of internal implementation details of Git.
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Training Content
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Table of Contents
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Git Basics
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Working with Branches
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Git with Github
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Hooks
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Git Basics
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Though you might be aware already, let's revisit why we need a version control system. As the project grows and multiple developers start working on it, an efficient method for collaboration is warranted. Git helps the team collaborate easily and also maintains history of the changes happened with the codebase.
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Creating a Git Repo
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Any folder can be converted into a git repository. After executing the following command, we will see a .git folder within the folder, which makes our folder a git repository. All the magic that git does, .git folder is the enabler for the same.
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# creating an empty folder and changing current dir to it
-spatel1-mn1:~ spatel1$ cd /tmp
-spatel1-mn1:tmp spatel1$ mkdir school-of-sre
-spatel1-mn1:tmp spatel1$ cd school-of-sre/
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-# initialize a git repo
-spatel1-mn1:school-of-sre spatel1$ git init
-Initialized empty Git repository in /private/tmp/school-of-sre/.git/
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As the output says, an empty git repo has been initialized in our folder. Let's take a look at what is there.
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spatel1-mn1:school-of-sre spatel1$ ls .git/
-HEAD config description hooks info objects refs
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There are a bunch of folders and files in the .git folder. As I said, all these enables git to do its magic. We will look into some of these folders and files. But for now, what we have is an empty git repository.
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Tracking a File
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Now as you might already know, let us create a new file in our repo (we will refer to the folder as repo now.) And see git status
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spatel1-mn1:school-of-sre spatel1$ echo "I am file 1" > file1.txt
-spatel1-mn1:school-of-sre spatel1$ git status
-On branch master
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-No commits yet
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-Untracked files:
- (use "git add <file>..." to include in what will be committed)
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- file1.txt
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-nothing added to commit but untracked files present (use "git add" to track)
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The current git status says No commits yet and there is one untracked file. Since we just created the file, git is not tracking that file. We explicitly need to ask git to track files and folders. (also checkout gitignore) And how we do that is via git add command as suggested in the above output. Then we go ahead and create a commit.
Notice how after adding the file, git status says Changes to be commited:. What it means is whatever is listed there, will be included in the next commit. Then we go ahead and create a commit, with an attached messaged via -m.
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More About a Commit
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Commit is a snapshot of the repo. Whenever a commit is made, a snapshot of the current state of repo (the folder) is taken and saved. Each commit has a unique ID. (df2fb7a for the commit we made in the previous step). As we keep adding/changing more and more contents and keep making commits, all those snapshots are stored by git. Again, all this magic happens inside the .git folder. This is where all this snapshot or versions are stored. In an efficient manner.
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Adding More Changes
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Let us create one more file and commit the change. It would look the same as the previous commit we made.
A new commit with ID 7f3b00e has been created. You can issue git status at any time to see the state of the repository.
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**IMPORTANT: Note that commit IDs are long string (SHA) but we can refer to a commit by its initial few (8 or more) characters too. We will interchangeably using shorter and longer commit IDs.**
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Now that we have two commits, let's visualize them:
git log, as the name suggests, prints the log of all the git commits. Here you see two additional arguments, --oneline prints the shorter version of the log, ie: the commit message only and not the person who made the commit and when. --graph prints it in graph format.
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Now at this moment the commits might look like just one in each line but all commits are stored as a tree like data structure internally by git. That means there can be two or more children commits of a given commit. And not just a single line of commits. We will look more into this part when we get to the Branches section. For now this is our commit history:
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df2fb7a ===> 7f3b00e
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Are commits really linked?
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As I just said, the two commits we just made are linked via tree like data structure and we saw how they are linked. But let's actually verify it. Everything in git is an object. Newly created files are stored as an object. Changes to file are stored as an objects and even commits are objects. To view contents of an object we can use the following command with the object's ID. We will take a look at content of the contents of the second commit
Take a note of parent attribute in the above output. It points to the commit id of the first commit we made. So this proves that they are linked! Additionally you can see the second commit's message in this object. As I said all this magic is enabled by .git folder and the object to which we are looking at also is in that folder.
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spatel1-mn1:school-of-sre spatel1$ ls .git/objects/7f/3b00eaa957815884198e2fdfec29361108d6a9
-.git/objects/7f/3b00eaa957815884198e2fdfec29361108d6a9
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It is stored in .git/objects/ folder. All the files and changes to them as well are stored in this folder.
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The Version Control part of Git
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We already can see two commits (versions) in our git log. One thing a version control tool gives you is ability to browse back and forth in history. For example: some of your users are running an old version of code and they are reporting an issue. In order to debug the issue, you need access to the old code. The one in your current repo is the latest code. In this example, you are working on the second commit (7f3b00e) and someone reported an issue with the code snapshot at commit (df2fb7a). This is how you would get access to the code at any older commit
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# Current contents, two files present
-patel1-mn1:school-of-sre spatel1$ ls
-file1.txt file2.txt
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-# checking out to (an older) commit
-spatel1-mn1:school-of-sre spatel1$ git checkout df2fb7a
-Note: checking out 'df2fb7a'.
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-You are in 'detached HEAD' state. You can look around, make experimental
-changes and commit them, and you can discard any commits you make in this
-state without impacting any branches by performing another checkout.
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-If you want to create a new branch to retain commits you create, you may
-do so (now or later) by using -b with the checkout command again. Example:
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- git checkout -b <new-branch-name>
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-HEAD is now at df2fb7a adding file 1
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-# checking contents, can verify it has old contents
-spatel1-mn1:school-of-sre spatel1$ ls
-file1.txt
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So this is how we would get access to old versions/snapshots. All we need is a reference to that snapshot. Upon executing git checkout ..., what git does for you is use the .git folder, see what was the state of things (files and folders) at that version/reference and replace the contents of current directory with those contents. The then-existing content will no longer be present in the local dir (repo) but we can and will still get access to them because they are tracked via git commit and .git folder has them stored/tracked.
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Reference
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I mention in the previous section that we need a reference to the version. By default, git repo is made of tree of commits. And each commit has a unique IDs. But the unique ID is not the only thing we can reference commits via. There are multiple ways to reference commits. For example: HEAD is a reference to current commit. Whatever commit your repo is checked out at, HEAD will point to that.HEAD~1 is reference to previous commit. So while checking out previous version in section above, we could have done git checkout HEAD~1.
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Similarly, master is also a reference (to a branch). Since git uses tree like structure to store commits, there of course will be branches. And the default branch is called master. Master (or any branch reference) will point to the latest commit in the branch. Even though we have checked out to the previous commit in out repo, master still points to the latest commit. And we can get back to the latest version by checkout at master reference
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spatel1-mn1:school-of-sre spatel1$ git checkout master
-Previous HEAD position was df2fb7a adding file 1
-Switched to branch 'master'
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-# now we will see latest code, with two files
-spatel1-mn1:school-of-sre spatel1$ ls
-file1.txt file2.txt
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Note, instead of master in above command, we could have used commit's ID as well.
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References and The Magic
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Let's look at the state of things. Two commits, master and HEAD references are pointing to the latest commit
Viola! Where master is pointing to is stored in a file. Whenever git needs to know where master reference is pointing to, or if git needs to update where master points, it just needs to update the file above. So when you create a new commit, a new commit is created on top of the current commit and the master file is updated with the new commit's ID.
We just edited the master reference file and now we can see only the first commit in git log. Undoing the change to the file brings the state back to original. Not so much of magic, isn't it?
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Till now all the operations we did were in our local repo while git also helps us in a collaborative environment. GitHub is one place on the internet where you can centrally host your git repos and collaborate with other developers.
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Most of the workflow will remain the same as we discussed, with addition of couple of things:
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Pull: to pull latest changes from github (the central) repo
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Push: to push your changes to github repo so that it's available to all people
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GitHub has written nice guides and tutorials about this and you can refer them here:
Git has another nice feature called hooks. Hooks are basically scripts which will be called when a certain event happens. Here is where hooks are located:
Names are self explanatory. These hooks are useful when you want to do certain things when a certain event happens. Ie: if you want to run tests before pushing code, you would want to setup pre-push hooks. Let's try to create a pre commit hook.
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spatel1-mn1:school-of-sre spatel1$ echo "echo this is from pre commit hook" > .git/hooks/pre-commit
-spatel1-mn1:school-of-sre spatel1$ chmod +x .git/hooks/pre-commit
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We basically create a file called pre-commit in hooks folder and make it executable. Now if we make a commit, we should see the message getting printed.
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spatel1-mn1:school-of-sre spatel1$ echo "sample file" > sample.txt
-spatel1-mn1:school-of-sre spatel1$ git add sample.txt
-spatel1-mn1:school-of-sre spatel1$ git commit -m "adding sample file"
-this is from pre commit hook # <===== THE MESSAGE FROM HOOK EXECUTION
-[master 9894e05] adding sample file
-1 file changed, 1 insertion(+)
-create mode 100644 sample.txt
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What next from here?
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There are a lot of git commands and features which we have not explored here. But with the base built-up, be sure to explore concepts like
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This course is divided into two high level parts. In the first part, assuming familiarity with python language’s basic operations and syntax usage, we will dive a little deeper into understanding python as a language. We will compare python with other programming languages that you might already know like Java and C. We will also explore concepts of Python objects and with help of that, explore python features like decorators.
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In the second part which will revolve around the web, and also assume familiarity with the Flask framework, we will start from the socket module and work with HTTP requests. This will demystify how frameworks like flask work internally.
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And to introduce SRE flavour to the course, we will design, develop and deploy (in theory) a URL shortening application. We will emphasize parts of the whole process that are more important as an SRE of the said app/service.
-
What is not covered under this training
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Extensive knowledge of python internals and advanced python.
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Training Content
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Lab Environment Setup
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Have latest version of python installed
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TOC
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-
The Python Language
-
Some Python Concepts
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Python Gotchas
-
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Python and Web
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Sockets
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Flask
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The URL Shortening App
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Design
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Scaling The App
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Monitoring The App
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The Python Language
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Assuming you know a little bit of C/C++ and Java, let's try to discuss the following questions in context of those two languages and python. You might have heard that C/C++ is a compiled language while python is an interpreted language. Generally, with compiled language we first compile the program and then run the executable while in case of python we run the source code directly like python hello_world.py. While Java, being an interpreted language, still has a separate compilation step and then its run. So what's really the difference?
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Compiled vs. Interpreted
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This might sound a little weird to you: python, in a way is a compiled language! Python has a compiler built-in! It is obvious in the case of java since we compile it using a separate command ie: javac helloWorld.java and it will produce a .class file which we know as a bytecode. Well, python is very similar to that. One difference here is that there is no separate compile command/binary needed to run a python program.
-
What is the difference then, between java and python?
-Well, Java's compiler is more strict and sophisticated. As you might know Java is a statically typed language. So the compiler is written in a way that it can verify types related errors during compile time. While python being a dynamic language, types are not known until a program is run. So in a way, python compiler is dumb (or, less strict). But there indeed is a compile step involved when a python program is run. You might have seen python bytecode files with .pyc extension. Here is how you can see bytecode for a given python program.
-
# Create a Hello World
-spatel1-mn1:tmp spatel1$ echo "print('hello world')" > hello_world.py
-
-# Making sure it runs
-spatel1-mn1:tmp spatel1$ python3 hello_world.py
-hello world
-
-# The bytecode of the given program
-spatel1-mn1:tmp spatel1$ python -m dis hello_world.py
- 1 0 LOAD_NAME 0 (print)
- 2 LOAD_CONST 0 ('hello world')
- 4 CALL_FUNCTION 1
- 6 POP_TOP
- 8 LOAD_CONST 1 (None)
- 10 RETURN_VALUE
-
Now coming to C/C++, there of course is a compiler. But the output is different than what java/python compiler would produce. Compiling a C program would produce what we also know as machine code. As opposed to bytecode.
-
Running The Programs
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We know compilation is involved in all 3 languages we are discussing. Just that the compilers are different in nature and they output different types of content. In case of C/C++, the output is machine code which can be directly read by your operating system. When you execute that program, your OS will know how exactly to run it. But this is not the case with bytecode.
-
Those bytecodes are language specific. Python has its own set of bytecode defined (more in dis module) and so does java. So naturally, your operating system will not know how to run it. To run this bytecode, we have something called Virtual Machines. Ie: The JVM or the Python VM (CPython, Jython). These so called Virtual Machines are the programs which can read the bytecode and run it on a given operating system. Python has multiple VMs available. Cpython is a python VM implemented in C language, similarly Jython is a Java implementation of python VM. At the end of the day, what they should be capable of is to understand python language syntax, be able to compile it to bytecode and be able to run that bytecode. You can implement a python VM in any language! (And people do so, just because it can be done)
Generally, when we run a python program, a python VM process is started which reads the python source code, compiles it to byte code and run it in a single step. Compiling is not a separate step. Shown only for illustration purpose.
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Binaries generated for C like languages are not exactly run as is. Since there are multiple types of binaries (eg: ELF), there are more complicated steps involved in order to run a binary but we will not go into that since all that is done at OS level.
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Though you are expected to know python and its syntax at basic level, let us discuss some fundamental concepts that will help you understand the python language better.
-
Everything in Python is an object.
-
That includes the functions, lists, dicts, classes, modules, a running function (instance of function definition), everything. In the CPython, it would mean there is an underlying struct variable for each object.
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In python's current execution context, all the variables are stored in a dict. It'd be a string to object mapping. If you have a function and a float variable defined in the current context, here is how it is handled internally.
-
>>> float_number=42.0
->>> def foo_func():
-... pass
-...
-
-# NOTICE HOW VARIABLE NAMES ARE STRINGS, stored in a dict
->>> locals()
-{'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': <class '_frozen_importlib.BuiltinImporter'>, '__spec__': None, '__annotations__': {}, '__builtins__': <module 'builtins' (built-in)>, 'float_number': 42.0, 'foo_func': <function foo_func at 0x1055847a0>}
-
-
-
Python Functions
-
Since functions too are objects, we can see what all attributes a function contains as following
While there are a lot of them, let's look at some interesting ones
-
globals
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This attribute, as the name suggests, has references of global variables. If you ever need to know what all global variables are in the scope of this function, this will tell you. See how the function start seeing the new variable in globals
This is an interesting one! As everything in python is an object, this includes the bytecode too. The compiled python bytecode is a python code object. Which is accessible via __code__ attribute here. A function has an associated code object which carries some interesting information.
-
# the file in which function is defined
-# stdin here since this is run in an interpreter
->>> hello.__code__.co_filename
-'<stdin>'
-
-# number of arguments the function takes
->>> hello.__code__.co_argcount
-1
-
-# local variable names
->>> hello.__code__.co_varnames
-('name',)
-
-# the function code's compiled bytecode
->>> hello.__code__.co_code
-b't\x00d\x01|\x00\x9b\x00d\x02\x9d\x03\x83\x01\x01\x00d\x00S\x00'
-
-
-
There are more code attributes which you can enlist by >>> dir(hello.__code__)
-
Decorators
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Related to functions, python has another feature called decorators. Let's see how that works, keeping everything is an object in mind.
What goes inside the deco function might seem complex. Let's try to uncover it.
-
-
Function hello_world is created
-
It is passed to deco function
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deco create a new function
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This new function is calls hello_world function
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And does a couple other things
-
-
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deco returns the newly created function
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hello_world is replaced with above function
-
-
Let's visualize it for better understanding
-
BEFORE function_object (ID: 100)
-
- "hello_world" +--------------------+
- + |print("hello_world")|
- | | |
- +--------------> | |
- | |
- +--------------------+
-
-
- WHAT DECORATOR DOES
-
- creates a new function (ID: 101)
- +---------------------------------+
- |input arg: function with id: 100 |
- | |
- |print("before") |
- |call function object with id 100 |
- |print("after") |
- | |
- +---------------------------^-----+
- |
- |
- AFTER |
- |
- |
- "hello_world" +-------------+
-
-
-
Note how the hello_world name points to a new function object but that new function object knows the reference (ID) of the original function.
-
Some Gotchas
-
-
While it is very quick to build prototypes in python and there are tons of libraries available, as the codebase complexity increases, type errors become more common and will get hard to deal with. (There are solutions to that problem like type annotations in python. Checkout mypy.)
-
Because python is dynamically typed language, that means all types are determined at runtime. And that makes python run very slow compared to other statically typed languages.
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Python has something called GIL (global interpreter lock) which is a limiting factor for utilizing multiple CPI cores for parallel computation.
-
Some weird things that python does: https://github.com/satwikkansal/wtfpython
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Back in the old days, websites were simple. They were simple static html contents. A webserver would be listening on a defined port and according to the HTTP request received, it would read files from disk and return them in response. But since then, complexity has evolved and websites are now dynamic. Depending on the request, multiple operations need to be performed like reading from database or calling other API and finally returning some response (HTML data, JSON content etc.)
-
Since serving web requests is no longer a simple task like reading files from disk and return contents, we need to process each http request, perform some operations programmatically and construct a response.
-
Sockets
-
Though we have frameworks like flask, HTTP is still a protocol that works over TCP protocol. So let us setup a TCP server and send an HTTP request and inspect the request's payload. Note that this is not a tutorial on socket programming but what we are doing here is inspecting HTTP protocol at its ground level and look at what its contents look like. (Ref: Socket Programming in Python (Guide) on RealPython)
-
import socket
-
-HOST = '127.0.0.1' # Standard loopback interface address (localhost)
-PORT = 65432 # Port to listen on (non-privileged ports are > 1023)
-
-with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
- s.bind((HOST, PORT))
- s.listen()
- conn, addr = s.accept()
- with conn:
- print('Connected by', addr)
- while True:
- data = conn.recv(1024)
- if not data:
- break
- print(data)
-
-
-
Then we open localhost:65432 in our web browser and following would be the output:
-
Connected by ('127.0.0.1', 54719)
-b'GET / HTTP/1.1\r\nHost: localhost:65432\r\nConnection: keep-alive\r\nDNT: 1\r\nUpgrade-Insecure-Requests: 1\r\nUser-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/85.0.4183.83 Safari/537.36 Edg/85.0.564.44\r\nAccept: text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9\r\nSec-Fetch-Site: none\r\nSec-Fetch-Mode: navigate\r\nSec-Fetch-User: ?1\r\nSec-Fetch-Dest: document\r\nAccept-Encoding: gzip, deflate, br\r\nAccept-Language: en-US,en;q=0.9\r\n\r\n'
-
-
-
Examine closely and the content will look like the HTTP protocol's format. ie:
So though it's a blob of bytes, knowing http protocol specification, you can parse that string (ie: split by \r\n) and get meaningful information out of it.
-
Flask
-
Flask, and other such frameworks does pretty much what we just discussed in the last section (with added more sophistication). They listen on a port on a TCP socket, receive an HTTP request, parse the data according to protocol format and make it available to you in a convenient manner.
-
ie: you can access headers in flask by request.headers which is made available to you by splitting above payload by /r/n, as defined in http protocol.
-
Another example: we register routes in flask by @app.route("/hello"). What flask will do is maintain a registry internally which will map /hello with the function you decorated with. Now whenever a request comes with the /hello route (second component in the first line, split by space), flask calls the registered function and returns whatever the function returned.
-
Same with all other web frameworks in other languages too. They all work on similar principles. What they basically do is understand the HTTP protocol, parses the HTTP request data and gives us programmers a nice interface to work with HTTP requests.
-
Not so much of magic, innit?
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The design and development is just a part of the journey. We will need to setup continuous integration and continuous delivery pipelines sooner or later. And we have to deploy this app somewhere.
-
Initially we can start with deploying this app on one virtual machine on any cloud provider. But this is a Single point of failure which is something we never allow as an SRE (or even as an engineer). So an improvement here can be having multiple instances of applications deployed behind a load balancer. This certainly prevents problems of one machine going down.
-
Scaling here would mean adding more instances behind the load balancer. But this is scalable upto only a certain point. After that, other bottlenecks in the system will start appearing. ie: DB will become the bottleneck, or perhaps the load balancer itself. How do you know what is the bottleneck? You need to have observability into each aspects of the application architecture.
-
Only after you have metrics, you will be able to know what is going wrong where. What gets measured, gets fixed!
-
Get deeper insights into scaling from School Of SRE's Scalability module and post going through it, apply your learnings and takeaways to this app. Think how will we make this app geographically distributed and highly available and scalable.
-
Monitoring Strategy
-
Once we have our application deployed. It will be working ok. But not forever. Reliability is in the title of our job and we make systems reliable by making the design in a certain way. But things still will go down. Machines will fail. Disks will behave weirdly. Buggy code will get pushed to production. And all these possible scenarios will make the system less reliable. So what do we do? We monitor!
-
We keep an eye on the system's health and if anything is not going as expected, we want ourselves to get alerted.
-
Now let's think in terms of the given url shortening app. We need to monitor it. And we would want to get notified in case something goes wrong. But we first need to decide what is that something that we want to keep an eye on.
-
-
Since it's a web app serving HTTP requests, we want to keep an eye on HTTP Status codes and latencies
-
Request volume again is a good candidate, if the app is receiving an unusual amount of traffic, something might be off.
-
We also want to keep an eye on the database so depending on the database solution chosen. Query times, volumes, disk usage etc.
-
Finally, there also needs to be some external monitoring which runs periodic tests from devices outside of your data centers. This emulates customers and ensures that from customer point of view, the system is working as expected.
-
-
SRE Use-cases
-
In the world of SRE, python is a widely used language. For small scripts and tooling developed for various purposes. Since tooling developed by SRE works with critical pieces of infrastructure and has great power (to bring things down), it is important to know what you are doing while using a programming language and its features. Also it is equally important to know the language and its characteristics while debugging the issues. As an SRE having a deeper understanding of python language, it has helped me a lot to debug very sneaky bugs and be generally more aware and informed while making certain design decisions.
-
While developing tools may or may not be part of SRE job, supporting tools or services is more likely to be a daily duty. Building an application or tool is just a small part of productionization. While there is certainly that goes in the design of the application itself to make it more robust, as an SRE you are responsible for its reliability and stability once it is deployed and running. And to ensure that, you’d need to understand the application first and then come up with a strategy to monitor it properly and be prepared for various failure scenarios.
-
Optional Exercises
-
-
Make a decorator that will cache function return values depending on input parameters.
-
Host the URL shortening app on any cloud provider.
-
Setup monitoring using many of the tools available like catchpoint, datadog etc.
-
Create a minimal flask-like framework on top of TCP sockets.
-
-
Conclusion
-
This module, in the first part, aims to make you more aware of the things that will happen when you choose python as your programming language and what happens when you run a python program. With the knowledge of how python handles things internally as objects, lot of seemingly magic things in python will start to make more sense.
-
The second part will first explain how a framework like flask works using the existing knowledge of protocols like TCP and HTTP. It then touches the whole lifecycle of an application development lifecycle including the SRE parts of it. While the design and areas in architecture considered will not be exhaustive, it will give a good overview of things that are also important being an SRE and why they are important.
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Let's build a very simple URL shortening app using flask and try to incorporate all aspects of the development process including the reliability aspects. We will not be building the UI and we will come up with a minimal set of API that will be enough for the app to function well.
-
Design
-
We don't jump directly to coding. First thing we do is gather requirements. Come up with an approach. Have the approach/design reviewed by peers. Evolve, iterate, document the decisions and tradeoffs. And then finally implement. While we will not do the full blown design document here, we will raise certain questions here that are important to the design.
-
1. High Level Operations and API Endpoints
-
Since it's a URL shortening app, we will need an API for generating the shorten link given an original link. And an API/Endpoint which will accept the shorten link and redirect to original URL. We are not including the user aspect of the app to keep things minimal. These two API should make app functional and usable by anyone.
-
2. How to shorten?
-
Given a url, we will need to generate a shortened version of it. One approach could be using random characters for each link. Another thing that can be done is to use some sort of hashing algorithm. The benefit here is we will reuse the same hash for the same link. ie: if lot of people are shortening https://www.linkedin.com they all will have the same value, compared to multiple entries in DB if chosen random characters.
-
What about hash collisions? Even in random characters approach, though there is a less probability, hash collisions can happen. And we need to be mindful of them. In that case we might want to prepend/append the string with some random value to avoid conflict.
-
Also, choice of hash algorithm matters. We will need to analyze algorithms. Their CPU requirements and their characteristics. Choose one that suits the most.
-
3. Is URL Valid?
-
Given a URL to shorten, how do we verify if the URL is valid? Do we even verify or validate? One basic check that can be done is see if the URL matches a regex of a URL. To go even further we can try opening/visiting the URL. But there are certain gotchas here.
-
-
We need to define success criteria. ie: HTTP 200 means it is valid.
-
What is the URL is in private network?
-
What if URL is temporarily down?
-
-
4. Storage
-
Finally, storage. Where will we store the data that we will generate over time? There are multiple database solutions available and we will need to choose the one that suits this app the most. Relational database like MySQL would be a fair choice but be sure to checkout School of SRE's database section for deeper insights into making a more informed decision.
-
5. Other
-
We are not accounting for users into our app and other possible features like rate limiting, customized links etc but it will eventually come up with time. Depending on the requirements, they too might need to get incorporated.
-
The minimal working code is given below for reference but I'd encourage you to come up with your own.
-
from flask import Flask, redirect, request
-
-from hashlib import md5
-
-app = Flask("url_shortener")
-
-mapping = {}
-
-@app.route("/shorten", methods=["POST"])
-def shorten():
- global mapping
- payload = request.json
-
- if "url" not in payload:
- return "Missing URL Parameter", 400
-
- # TODO: check if URL is valid
-
- hash_ = md5()
- hash_.update(payload["url"].encode())
- digest = hash_.hexdigest()[:5] # limiting to 5 chars. Less the limit more the chances of collission
-
- if digest not in mapping:
- mapping[digest] = payload["url"]
- return f"Shortened: r/{digest}\n"
- else:
- # TODO: check for hash collission
- return f"Already exists: r/{digest}\n"
-
-
-@app.route("/r/<hash_>")
-def redirect_(hash_):
- if hash_ not in mapping:
- return "URL Not Found", 404
- return redirect(mapping[hash_])
-
-
-if __name__ == "__main__":
- app.run(debug=True)
-
-"""
-OUTPUT:
-
-
-===> SHORTENING
-
-spatel1-mn1:tmp spatel1$ curl localhost:5000/shorten -H "content-type: application/json" --data '{"url":"https://linkedin.com"}'
-Shortened: r/a62a4
-
-
-===> REDIRECTING, notice the response code 302 and the location header
-
-spatel1-mn1:tmp spatel1$ curl localhost:5000/r/a62a4 -v
-* Uses proxy env variable NO_PROXY == '127.0.0.1'
-* Trying ::1...
-* TCP_NODELAY set
-* Connection failed
-* connect to ::1 port 5000 failed: Connection refused
-* Trying 127.0.0.1...
-* TCP_NODELAY set
-* Connected to localhost (127.0.0.1) port 5000 (#0)
-> GET /r/a62a4 HTTP/1.1
-> Host: localhost:5000
-> User-Agent: curl/7.64.1
-> Accept: */*
->
-* HTTP 1.0, assume close after body
-< HTTP/1.0 302 FOUND
-< Content-Type: text/html; charset=utf-8
-< Content-Length: 247
-< Location: https://linkedin.com
-< Server: Werkzeug/0.15.4 Python/3.7.7
-< Date: Tue, 27 Oct 2020 09:37:12 GMT
-<
-<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 3.2 Final//EN">
-<title>Redirecting...</title>
-<h1>Redirecting...</h1>
-* Closing connection 0
-<p>You should be redirected automatically to target URL: <a href="https://linkedin.com">https://linkedin.com</a>. If not click the link.
-"""
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diff --git a/site/search/lunr.js b/site/search/lunr.js
deleted file mode 100644
index c218cc8..0000000
--- a/site/search/lunr.js
+++ /dev/null
@@ -1,2986 +0,0 @@
-/**
- * lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.1.6
- * Copyright (C) 2018 Oliver Nightingale
- * @license MIT
- */
-
-;(function(){
-
-/**
- * A convenience function for configuring and constructing
- * a new lunr Index.
- *
- * A lunr.Builder instance is created and the pipeline setup
- * with a trimmer, stop word filter and stemmer.
- *
- * This builder object is yielded to the configuration function
- * that is passed as a parameter, allowing the list of fields
- * and other builder parameters to be customised.
- *
- * All documents _must_ be added within the passed config function.
- *
- * @example
- * var idx = lunr(function () {
- * this.field('title')
- * this.field('body')
- * this.ref('id')
- *
- * documents.forEach(function (doc) {
- * this.add(doc)
- * }, this)
- * })
- *
- * @see {@link lunr.Builder}
- * @see {@link lunr.Pipeline}
- * @see {@link lunr.trimmer}
- * @see {@link lunr.stopWordFilter}
- * @see {@link lunr.stemmer}
- * @namespace {function} lunr
- */
-var lunr = function (config) {
- var builder = new lunr.Builder
-
- builder.pipeline.add(
- lunr.trimmer,
- lunr.stopWordFilter,
- lunr.stemmer
- )
-
- builder.searchPipeline.add(
- lunr.stemmer
- )
-
- config.call(builder, builder)
- return builder.build()
-}
-
-lunr.version = "2.1.6"
-/*!
- * lunr.utils
- * Copyright (C) 2018 Oliver Nightingale
- */
-
-/**
- * A namespace containing utils for the rest of the lunr library
- */
-lunr.utils = {}
-
-/**
- * Print a warning message to the console.
- *
- * @param {String} message The message to be printed.
- * @memberOf Utils
- */
-lunr.utils.warn = (function (global) {
- /* eslint-disable no-console */
- return function (message) {
- if (global.console && console.warn) {
- console.warn(message)
- }
- }
- /* eslint-enable no-console */
-})(this)
-
-/**
- * Convert an object to a string.
- *
- * In the case of `null` and `undefined` the function returns
- * the empty string, in all other cases the result of calling
- * `toString` on the passed object is returned.
- *
- * @param {Any} obj The object to convert to a string.
- * @return {String} string representation of the passed object.
- * @memberOf Utils
- */
-lunr.utils.asString = function (obj) {
- if (obj === void 0 || obj === null) {
- return ""
- } else {
- return obj.toString()
- }
-}
-lunr.FieldRef = function (docRef, fieldName, stringValue) {
- this.docRef = docRef
- this.fieldName = fieldName
- this._stringValue = stringValue
-}
-
-lunr.FieldRef.joiner = "/"
-
-lunr.FieldRef.fromString = function (s) {
- var n = s.indexOf(lunr.FieldRef.joiner)
-
- if (n === -1) {
- throw "malformed field ref string"
- }
-
- var fieldRef = s.slice(0, n),
- docRef = s.slice(n + 1)
-
- return new lunr.FieldRef (docRef, fieldRef, s)
-}
-
-lunr.FieldRef.prototype.toString = function () {
- if (this._stringValue == undefined) {
- this._stringValue = this.fieldName + lunr.FieldRef.joiner + this.docRef
- }
-
- return this._stringValue
-}
-/**
- * A function to calculate the inverse document frequency for
- * a posting. This is shared between the builder and the index
- *
- * @private
- * @param {object} posting - The posting for a given term
- * @param {number} documentCount - The total number of documents.
- */
-lunr.idf = function (posting, documentCount) {
- var documentsWithTerm = 0
-
- for (var fieldName in posting) {
- if (fieldName == '_index') continue // Ignore the term index, its not a field
- documentsWithTerm += Object.keys(posting[fieldName]).length
- }
-
- var x = (documentCount - documentsWithTerm + 0.5) / (documentsWithTerm + 0.5)
-
- return Math.log(1 + Math.abs(x))
-}
-
-/**
- * A token wraps a string representation of a token
- * as it is passed through the text processing pipeline.
- *
- * @constructor
- * @param {string} [str=''] - The string token being wrapped.
- * @param {object} [metadata={}] - Metadata associated with this token.
- */
-lunr.Token = function (str, metadata) {
- this.str = str || ""
- this.metadata = metadata || {}
-}
-
-/**
- * Returns the token string that is being wrapped by this object.
- *
- * @returns {string}
- */
-lunr.Token.prototype.toString = function () {
- return this.str
-}
-
-/**
- * A token update function is used when updating or optionally
- * when cloning a token.
- *
- * @callback lunr.Token~updateFunction
- * @param {string} str - The string representation of the token.
- * @param {Object} metadata - All metadata associated with this token.
- */
-
-/**
- * Applies the given function to the wrapped string token.
- *
- * @example
- * token.update(function (str, metadata) {
- * return str.toUpperCase()
- * })
- *
- * @param {lunr.Token~updateFunction} fn - A function to apply to the token string.
- * @returns {lunr.Token}
- */
-lunr.Token.prototype.update = function (fn) {
- this.str = fn(this.str, this.metadata)
- return this
-}
-
-/**
- * Creates a clone of this token. Optionally a function can be
- * applied to the cloned token.
- *
- * @param {lunr.Token~updateFunction} [fn] - An optional function to apply to the cloned token.
- * @returns {lunr.Token}
- */
-lunr.Token.prototype.clone = function (fn) {
- fn = fn || function (s) { return s }
- return new lunr.Token (fn(this.str, this.metadata), this.metadata)
-}
-/*!
- * lunr.tokenizer
- * Copyright (C) 2018 Oliver Nightingale
- */
-
-/**
- * A function for splitting a string into tokens ready to be inserted into
- * the search index. Uses `lunr.tokenizer.separator` to split strings, change
- * the value of this property to change how strings are split into tokens.
- *
- * This tokenizer will convert its parameter to a string by calling `toString` and
- * then will split this string on the character in `lunr.tokenizer.separator`.
- * Arrays will have their elements converted to strings and wrapped in a lunr.Token.
- *
- * @static
- * @param {?(string|object|object[])} obj - The object to convert into tokens
- * @returns {lunr.Token[]}
- */
-lunr.tokenizer = function (obj) {
- if (obj == null || obj == undefined) {
- return []
- }
-
- if (Array.isArray(obj)) {
- return obj.map(function (t) {
- return new lunr.Token(lunr.utils.asString(t).toLowerCase())
- })
- }
-
- var str = obj.toString().trim().toLowerCase(),
- len = str.length,
- tokens = []
-
- for (var sliceEnd = 0, sliceStart = 0; sliceEnd <= len; sliceEnd++) {
- var char = str.charAt(sliceEnd),
- sliceLength = sliceEnd - sliceStart
-
- if ((char.match(lunr.tokenizer.separator) || sliceEnd == len)) {
-
- if (sliceLength > 0) {
- tokens.push(
- new lunr.Token (str.slice(sliceStart, sliceEnd), {
- position: [sliceStart, sliceLength],
- index: tokens.length
- })
- )
- }
-
- sliceStart = sliceEnd + 1
- }
-
- }
-
- return tokens
-}
-
-/**
- * The separator used to split a string into tokens. Override this property to change the behaviour of
- * `lunr.tokenizer` behaviour when tokenizing strings. By default this splits on whitespace and hyphens.
- *
- * @static
- * @see lunr.tokenizer
- */
-lunr.tokenizer.separator = /[\s\-]+/
-/*!
- * lunr.Pipeline
- * Copyright (C) 2018 Oliver Nightingale
- */
-
-/**
- * lunr.Pipelines maintain an ordered list of functions to be applied to all
- * tokens in documents entering the search index and queries being ran against
- * the index.
- *
- * An instance of lunr.Index created with the lunr shortcut will contain a
- * pipeline with a stop word filter and an English language stemmer. Extra
- * functions can be added before or after either of these functions or these
- * default functions can be removed.
- *
- * When run the pipeline will call each function in turn, passing a token, the
- * index of that token in the original list of all tokens and finally a list of
- * all the original tokens.
- *
- * The output of functions in the pipeline will be passed to the next function
- * in the pipeline. To exclude a token from entering the index the function
- * should return undefined, the rest of the pipeline will not be called with
- * this token.
- *
- * For serialisation of pipelines to work, all functions used in an instance of
- * a pipeline should be registered with lunr.Pipeline. Registered functions can
- * then be loaded. If trying to load a serialised pipeline that uses functions
- * that are not registered an error will be thrown.
- *
- * If not planning on serialising the pipeline then registering pipeline functions
- * is not necessary.
- *
- * @constructor
- */
-lunr.Pipeline = function () {
- this._stack = []
-}
-
-lunr.Pipeline.registeredFunctions = Object.create(null)
-
-/**
- * A pipeline function maps lunr.Token to lunr.Token. A lunr.Token contains the token
- * string as well as all known metadata. A pipeline function can mutate the token string
- * or mutate (or add) metadata for a given token.
- *
- * A pipeline function can indicate that the passed token should be discarded by returning
- * null. This token will not be passed to any downstream pipeline functions and will not be
- * added to the index.
- *
- * Multiple tokens can be returned by returning an array of tokens. Each token will be passed
- * to any downstream pipeline functions and all will returned tokens will be added to the index.
- *
- * Any number of pipeline functions may be chained together using a lunr.Pipeline.
- *
- * @interface lunr.PipelineFunction
- * @param {lunr.Token} token - A token from the document being processed.
- * @param {number} i - The index of this token in the complete list of tokens for this document/field.
- * @param {lunr.Token[]} tokens - All tokens for this document/field.
- * @returns {(?lunr.Token|lunr.Token[])}
- */
-
-/**
- * Register a function with the pipeline.
- *
- * Functions that are used in the pipeline should be registered if the pipeline
- * needs to be serialised, or a serialised pipeline needs to be loaded.
- *
- * Registering a function does not add it to a pipeline, functions must still be
- * added to instances of the pipeline for them to be used when running a pipeline.
- *
- * @param {lunr.PipelineFunction} fn - The function to check for.
- * @param {String} label - The label to register this function with
- */
-lunr.Pipeline.registerFunction = function (fn, label) {
- if (label in this.registeredFunctions) {
- lunr.utils.warn('Overwriting existing registered function: ' + label)
- }
-
- fn.label = label
- lunr.Pipeline.registeredFunctions[fn.label] = fn
-}
-
-/**
- * Warns if the function is not registered as a Pipeline function.
- *
- * @param {lunr.PipelineFunction} fn - The function to check for.
- * @private
- */
-lunr.Pipeline.warnIfFunctionNotRegistered = function (fn) {
- var isRegistered = fn.label && (fn.label in this.registeredFunctions)
-
- if (!isRegistered) {
- lunr.utils.warn('Function is not registered with pipeline. This may cause problems when serialising the index.\n', fn)
- }
-}
-
-/**
- * Loads a previously serialised pipeline.
- *
- * All functions to be loaded must already be registered with lunr.Pipeline.
- * If any function from the serialised data has not been registered then an
- * error will be thrown.
- *
- * @param {Object} serialised - The serialised pipeline to load.
- * @returns {lunr.Pipeline}
- */
-lunr.Pipeline.load = function (serialised) {
- var pipeline = new lunr.Pipeline
-
- serialised.forEach(function (fnName) {
- var fn = lunr.Pipeline.registeredFunctions[fnName]
-
- if (fn) {
- pipeline.add(fn)
- } else {
- throw new Error('Cannot load unregistered function: ' + fnName)
- }
- })
-
- return pipeline
-}
-
-/**
- * Adds new functions to the end of the pipeline.
- *
- * Logs a warning if the function has not been registered.
- *
- * @param {lunr.PipelineFunction[]} functions - Any number of functions to add to the pipeline.
- */
-lunr.Pipeline.prototype.add = function () {
- var fns = Array.prototype.slice.call(arguments)
-
- fns.forEach(function (fn) {
- lunr.Pipeline.warnIfFunctionNotRegistered(fn)
- this._stack.push(fn)
- }, this)
-}
-
-/**
- * Adds a single function after a function that already exists in the
- * pipeline.
- *
- * Logs a warning if the function has not been registered.
- *
- * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline.
- * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline.
- */
-lunr.Pipeline.prototype.after = function (existingFn, newFn) {
- lunr.Pipeline.warnIfFunctionNotRegistered(newFn)
-
- var pos = this._stack.indexOf(existingFn)
- if (pos == -1) {
- throw new Error('Cannot find existingFn')
- }
-
- pos = pos + 1
- this._stack.splice(pos, 0, newFn)
-}
-
-/**
- * Adds a single function before a function that already exists in the
- * pipeline.
- *
- * Logs a warning if the function has not been registered.
- *
- * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline.
- * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline.
- */
-lunr.Pipeline.prototype.before = function (existingFn, newFn) {
- lunr.Pipeline.warnIfFunctionNotRegistered(newFn)
-
- var pos = this._stack.indexOf(existingFn)
- if (pos == -1) {
- throw new Error('Cannot find existingFn')
- }
-
- this._stack.splice(pos, 0, newFn)
-}
-
-/**
- * Removes a function from the pipeline.
- *
- * @param {lunr.PipelineFunction} fn The function to remove from the pipeline.
- */
-lunr.Pipeline.prototype.remove = function (fn) {
- var pos = this._stack.indexOf(fn)
- if (pos == -1) {
- return
- }
-
- this._stack.splice(pos, 1)
-}
-
-/**
- * Runs the current list of functions that make up the pipeline against the
- * passed tokens.
- *
- * @param {Array} tokens The tokens to run through the pipeline.
- * @returns {Array}
- */
-lunr.Pipeline.prototype.run = function (tokens) {
- var stackLength = this._stack.length
-
- for (var i = 0; i < stackLength; i++) {
- var fn = this._stack[i]
- var memo = []
-
- for (var j = 0; j < tokens.length; j++) {
- var result = fn(tokens[j], j, tokens)
-
- if (result === void 0 || result === '') continue
-
- if (result instanceof Array) {
- for (var k = 0; k < result.length; k++) {
- memo.push(result[k])
- }
- } else {
- memo.push(result)
- }
- }
-
- tokens = memo
- }
-
- return tokens
-}
-
-/**
- * Convenience method for passing a string through a pipeline and getting
- * strings out. This method takes care of wrapping the passed string in a
- * token and mapping the resulting tokens back to strings.
- *
- * @param {string} str - The string to pass through the pipeline.
- * @returns {string[]}
- */
-lunr.Pipeline.prototype.runString = function (str) {
- var token = new lunr.Token (str)
-
- return this.run([token]).map(function (t) {
- return t.toString()
- })
-}
-
-/**
- * Resets the pipeline by removing any existing processors.
- *
- */
-lunr.Pipeline.prototype.reset = function () {
- this._stack = []
-}
-
-/**
- * Returns a representation of the pipeline ready for serialisation.
- *
- * Logs a warning if the function has not been registered.
- *
- * @returns {Array}
- */
-lunr.Pipeline.prototype.toJSON = function () {
- return this._stack.map(function (fn) {
- lunr.Pipeline.warnIfFunctionNotRegistered(fn)
-
- return fn.label
- })
-}
-/*!
- * lunr.Vector
- * Copyright (C) 2018 Oliver Nightingale
- */
-
-/**
- * A vector is used to construct the vector space of documents and queries. These
- * vectors support operations to determine the similarity between two documents or
- * a document and a query.
- *
- * Normally no parameters are required for initializing a vector, but in the case of
- * loading a previously dumped vector the raw elements can be provided to the constructor.
- *
- * For performance reasons vectors are implemented with a flat array, where an elements
- * index is immediately followed by its value. E.g. [index, value, index, value]. This
- * allows the underlying array to be as sparse as possible and still offer decent
- * performance when being used for vector calculations.
- *
- * @constructor
- * @param {Number[]} [elements] - The flat list of element index and element value pairs.
- */
-lunr.Vector = function (elements) {
- this._magnitude = 0
- this.elements = elements || []
-}
-
-
-/**
- * Calculates the position within the vector to insert a given index.
- *
- * This is used internally by insert and upsert. If there are duplicate indexes then
- * the position is returned as if the value for that index were to be updated, but it
- * is the callers responsibility to check whether there is a duplicate at that index
- *
- * @param {Number} insertIdx - The index at which the element should be inserted.
- * @returns {Number}
- */
-lunr.Vector.prototype.positionForIndex = function (index) {
- // For an empty vector the tuple can be inserted at the beginning
- if (this.elements.length == 0) {
- return 0
- }
-
- var start = 0,
- end = this.elements.length / 2,
- sliceLength = end - start,
- pivotPoint = Math.floor(sliceLength / 2),
- pivotIndex = this.elements[pivotPoint * 2]
-
- while (sliceLength > 1) {
- if (pivotIndex < index) {
- start = pivotPoint
- }
-
- if (pivotIndex > index) {
- end = pivotPoint
- }
-
- if (pivotIndex == index) {
- break
- }
-
- sliceLength = end - start
- pivotPoint = start + Math.floor(sliceLength / 2)
- pivotIndex = this.elements[pivotPoint * 2]
- }
-
- if (pivotIndex == index) {
- return pivotPoint * 2
- }
-
- if (pivotIndex > index) {
- return pivotPoint * 2
- }
-
- if (pivotIndex < index) {
- return (pivotPoint + 1) * 2
- }
-}
-
-/**
- * Inserts an element at an index within the vector.
- *
- * Does not allow duplicates, will throw an error if there is already an entry
- * for this index.
- *
- * @param {Number} insertIdx - The index at which the element should be inserted.
- * @param {Number} val - The value to be inserted into the vector.
- */
-lunr.Vector.prototype.insert = function (insertIdx, val) {
- this.upsert(insertIdx, val, function () {
- throw "duplicate index"
- })
-}
-
-/**
- * Inserts or updates an existing index within the vector.
- *
- * @param {Number} insertIdx - The index at which the element should be inserted.
- * @param {Number} val - The value to be inserted into the vector.
- * @param {function} fn - A function that is called for updates, the existing value and the
- * requested value are passed as arguments
- */
-lunr.Vector.prototype.upsert = function (insertIdx, val, fn) {
- this._magnitude = 0
- var position = this.positionForIndex(insertIdx)
-
- if (this.elements[position] == insertIdx) {
- this.elements[position + 1] = fn(this.elements[position + 1], val)
- } else {
- this.elements.splice(position, 0, insertIdx, val)
- }
-}
-
-/**
- * Calculates the magnitude of this vector.
- *
- * @returns {Number}
- */
-lunr.Vector.prototype.magnitude = function () {
- if (this._magnitude) return this._magnitude
-
- var sumOfSquares = 0,
- elementsLength = this.elements.length
-
- for (var i = 1; i < elementsLength; i += 2) {
- var val = this.elements[i]
- sumOfSquares += val * val
- }
-
- return this._magnitude = Math.sqrt(sumOfSquares)
-}
-
-/**
- * Calculates the dot product of this vector and another vector.
- *
- * @param {lunr.Vector} otherVector - The vector to compute the dot product with.
- * @returns {Number}
- */
-lunr.Vector.prototype.dot = function (otherVector) {
- var dotProduct = 0,
- a = this.elements, b = otherVector.elements,
- aLen = a.length, bLen = b.length,
- aVal = 0, bVal = 0,
- i = 0, j = 0
-
- while (i < aLen && j < bLen) {
- aVal = a[i], bVal = b[j]
- if (aVal < bVal) {
- i += 2
- } else if (aVal > bVal) {
- j += 2
- } else if (aVal == bVal) {
- dotProduct += a[i + 1] * b[j + 1]
- i += 2
- j += 2
- }
- }
-
- return dotProduct
-}
-
-/**
- * Calculates the cosine similarity between this vector and another
- * vector.
- *
- * @param {lunr.Vector} otherVector - The other vector to calculate the
- * similarity with.
- * @returns {Number}
- */
-lunr.Vector.prototype.similarity = function (otherVector) {
- return this.dot(otherVector) / (this.magnitude() * otherVector.magnitude())
-}
-
-/**
- * Converts the vector to an array of the elements within the vector.
- *
- * @returns {Number[]}
- */
-lunr.Vector.prototype.toArray = function () {
- var output = new Array (this.elements.length / 2)
-
- for (var i = 1, j = 0; i < this.elements.length; i += 2, j++) {
- output[j] = this.elements[i]
- }
-
- return output
-}
-
-/**
- * A JSON serializable representation of the vector.
- *
- * @returns {Number[]}
- */
-lunr.Vector.prototype.toJSON = function () {
- return this.elements
-}
-/* eslint-disable */
-/*!
- * lunr.stemmer
- * Copyright (C) 2018 Oliver Nightingale
- * Includes code from - http://tartarus.org/~martin/PorterStemmer/js.txt
- */
-
-/**
- * lunr.stemmer is an english language stemmer, this is a JavaScript
- * implementation of the PorterStemmer taken from http://tartarus.org/~martin
- *
- * @static
- * @implements {lunr.PipelineFunction}
- * @param {lunr.Token} token - The string to stem
- * @returns {lunr.Token}
- * @see {@link lunr.Pipeline}
- */
-lunr.stemmer = (function(){
- var step2list = {
- "ational" : "ate",
- "tional" : "tion",
- "enci" : "ence",
- "anci" : "ance",
- "izer" : "ize",
- "bli" : "ble",
- "alli" : "al",
- "entli" : "ent",
- "eli" : "e",
- "ousli" : "ous",
- "ization" : "ize",
- "ation" : "ate",
- "ator" : "ate",
- "alism" : "al",
- "iveness" : "ive",
- "fulness" : "ful",
- "ousness" : "ous",
- "aliti" : "al",
- "iviti" : "ive",
- "biliti" : "ble",
- "logi" : "log"
- },
-
- step3list = {
- "icate" : "ic",
- "ative" : "",
- "alize" : "al",
- "iciti" : "ic",
- "ical" : "ic",
- "ful" : "",
- "ness" : ""
- },
-
- c = "[^aeiou]", // consonant
- v = "[aeiouy]", // vowel
- C = c + "[^aeiouy]*", // consonant sequence
- V = v + "[aeiou]*", // vowel sequence
-
- mgr0 = "^(" + C + ")?" + V + C, // [C]VC... is m>0
- meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$", // [C]VC[V] is m=1
- mgr1 = "^(" + C + ")?" + V + C + V + C, // [C]VCVC... is m>1
- s_v = "^(" + C + ")?" + v; // vowel in stem
-
- var re_mgr0 = new RegExp(mgr0);
- var re_mgr1 = new RegExp(mgr1);
- var re_meq1 = new RegExp(meq1);
- var re_s_v = new RegExp(s_v);
-
- var re_1a = /^(.+?)(ss|i)es$/;
- var re2_1a = /^(.+?)([^s])s$/;
- var re_1b = /^(.+?)eed$/;
- var re2_1b = /^(.+?)(ed|ing)$/;
- var re_1b_2 = /.$/;
- var re2_1b_2 = /(at|bl|iz)$/;
- var re3_1b_2 = new RegExp("([^aeiouylsz])\\1$");
- var re4_1b_2 = new RegExp("^" + C + v + "[^aeiouwxy]$");
-
- var re_1c = /^(.+?[^aeiou])y$/;
- var re_2 = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;
-
- var re_3 = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;
-
- var re_4 = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;
- var re2_4 = /^(.+?)(s|t)(ion)$/;
-
- var re_5 = /^(.+?)e$/;
- var re_5_1 = /ll$/;
- var re3_5 = new RegExp("^" + C + v + "[^aeiouwxy]$");
-
- var porterStemmer = function porterStemmer(w) {
- var stem,
- suffix,
- firstch,
- re,
- re2,
- re3,
- re4;
-
- if (w.length < 3) { return w; }
-
- firstch = w.substr(0,1);
- if (firstch == "y") {
- w = firstch.toUpperCase() + w.substr(1);
- }
-
- // Step 1a
- re = re_1a
- re2 = re2_1a;
-
- if (re.test(w)) { w = w.replace(re,"$1$2"); }
- else if (re2.test(w)) { w = w.replace(re2,"$1$2"); }
-
- // Step 1b
- re = re_1b;
- re2 = re2_1b;
- if (re.test(w)) {
- var fp = re.exec(w);
- re = re_mgr0;
- if (re.test(fp[1])) {
- re = re_1b_2;
- w = w.replace(re,"");
- }
- } else if (re2.test(w)) {
- var fp = re2.exec(w);
- stem = fp[1];
- re2 = re_s_v;
- if (re2.test(stem)) {
- w = stem;
- re2 = re2_1b_2;
- re3 = re3_1b_2;
- re4 = re4_1b_2;
- if (re2.test(w)) { w = w + "e"; }
- else if (re3.test(w)) { re = re_1b_2; w = w.replace(re,""); }
- else if (re4.test(w)) { w = w + "e"; }
- }
- }
-
- // Step 1c - replace suffix y or Y by i if preceded by a non-vowel which is not the first letter of the word (so cry -> cri, by -> by, say -> say)
- re = re_1c;
- if (re.test(w)) {
- var fp = re.exec(w);
- stem = fp[1];
- w = stem + "i";
- }
-
- // Step 2
- re = re_2;
- if (re.test(w)) {
- var fp = re.exec(w);
- stem = fp[1];
- suffix = fp[2];
- re = re_mgr0;
- if (re.test(stem)) {
- w = stem + step2list[suffix];
- }
- }
-
- // Step 3
- re = re_3;
- if (re.test(w)) {
- var fp = re.exec(w);
- stem = fp[1];
- suffix = fp[2];
- re = re_mgr0;
- if (re.test(stem)) {
- w = stem + step3list[suffix];
- }
- }
-
- // Step 4
- re = re_4;
- re2 = re2_4;
- if (re.test(w)) {
- var fp = re.exec(w);
- stem = fp[1];
- re = re_mgr1;
- if (re.test(stem)) {
- w = stem;
- }
- } else if (re2.test(w)) {
- var fp = re2.exec(w);
- stem = fp[1] + fp[2];
- re2 = re_mgr1;
- if (re2.test(stem)) {
- w = stem;
- }
- }
-
- // Step 5
- re = re_5;
- if (re.test(w)) {
- var fp = re.exec(w);
- stem = fp[1];
- re = re_mgr1;
- re2 = re_meq1;
- re3 = re3_5;
- if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) {
- w = stem;
- }
- }
-
- re = re_5_1;
- re2 = re_mgr1;
- if (re.test(w) && re2.test(w)) {
- re = re_1b_2;
- w = w.replace(re,"");
- }
-
- // and turn initial Y back to y
-
- if (firstch == "y") {
- w = firstch.toLowerCase() + w.substr(1);
- }
-
- return w;
- };
-
- return function (token) {
- return token.update(porterStemmer);
- }
-})();
-
-lunr.Pipeline.registerFunction(lunr.stemmer, 'stemmer')
-/*!
- * lunr.stopWordFilter
- * Copyright (C) 2018 Oliver Nightingale
- */
-
-/**
- * lunr.generateStopWordFilter builds a stopWordFilter function from the provided
- * list of stop words.
- *
- * The built in lunr.stopWordFilter is built using this generator and can be used
- * to generate custom stopWordFilters for applications or non English languages.
- *
- * @param {Array} token The token to pass through the filter
- * @returns {lunr.PipelineFunction}
- * @see lunr.Pipeline
- * @see lunr.stopWordFilter
- */
-lunr.generateStopWordFilter = function (stopWords) {
- var words = stopWords.reduce(function (memo, stopWord) {
- memo[stopWord] = stopWord
- return memo
- }, {})
-
- return function (token) {
- if (token && words[token.toString()] !== token.toString()) return token
- }
-}
-
-/**
- * lunr.stopWordFilter is an English language stop word list filter, any words
- * contained in the list will not be passed through the filter.
- *
- * This is intended to be used in the Pipeline. If the token does not pass the
- * filter then undefined will be returned.
- *
- * @implements {lunr.PipelineFunction}
- * @params {lunr.Token} token - A token to check for being a stop word.
- * @returns {lunr.Token}
- * @see {@link lunr.Pipeline}
- */
-lunr.stopWordFilter = lunr.generateStopWordFilter([
- 'a',
- 'able',
- 'about',
- 'across',
- 'after',
- 'all',
- 'almost',
- 'also',
- 'am',
- 'among',
- 'an',
- 'and',
- 'any',
- 'are',
- 'as',
- 'at',
- 'be',
- 'because',
- 'been',
- 'but',
- 'by',
- 'can',
- 'cannot',
- 'could',
- 'dear',
- 'did',
- 'do',
- 'does',
- 'either',
- 'else',
- 'ever',
- 'every',
- 'for',
- 'from',
- 'get',
- 'got',
- 'had',
- 'has',
- 'have',
- 'he',
- 'her',
- 'hers',
- 'him',
- 'his',
- 'how',
- 'however',
- 'i',
- 'if',
- 'in',
- 'into',
- 'is',
- 'it',
- 'its',
- 'just',
- 'least',
- 'let',
- 'like',
- 'likely',
- 'may',
- 'me',
- 'might',
- 'most',
- 'must',
- 'my',
- 'neither',
- 'no',
- 'nor',
- 'not',
- 'of',
- 'off',
- 'often',
- 'on',
- 'only',
- 'or',
- 'other',
- 'our',
- 'own',
- 'rather',
- 'said',
- 'say',
- 'says',
- 'she',
- 'should',
- 'since',
- 'so',
- 'some',
- 'than',
- 'that',
- 'the',
- 'their',
- 'them',
- 'then',
- 'there',
- 'these',
- 'they',
- 'this',
- 'tis',
- 'to',
- 'too',
- 'twas',
- 'us',
- 'wants',
- 'was',
- 'we',
- 'were',
- 'what',
- 'when',
- 'where',
- 'which',
- 'while',
- 'who',
- 'whom',
- 'why',
- 'will',
- 'with',
- 'would',
- 'yet',
- 'you',
- 'your'
-])
-
-lunr.Pipeline.registerFunction(lunr.stopWordFilter, 'stopWordFilter')
-/*!
- * lunr.trimmer
- * Copyright (C) 2018 Oliver Nightingale
- */
-
-/**
- * lunr.trimmer is a pipeline function for trimming non word
- * characters from the beginning and end of tokens before they
- * enter the index.
- *
- * This implementation may not work correctly for non latin
- * characters and should either be removed or adapted for use
- * with languages with non-latin characters.
- *
- * @static
- * @implements {lunr.PipelineFunction}
- * @param {lunr.Token} token The token to pass through the filter
- * @returns {lunr.Token}
- * @see lunr.Pipeline
- */
-lunr.trimmer = function (token) {
- return token.update(function (s) {
- return s.replace(/^\W+/, '').replace(/\W+$/, '')
- })
-}
-
-lunr.Pipeline.registerFunction(lunr.trimmer, 'trimmer')
-/*!
- * lunr.TokenSet
- * Copyright (C) 2018 Oliver Nightingale
- */
-
-/**
- * A token set is used to store the unique list of all tokens
- * within an index. Token sets are also used to represent an
- * incoming query to the index, this query token set and index
- * token set are then intersected to find which tokens to look
- * up in the inverted index.
- *
- * A token set can hold multiple tokens, as in the case of the
- * index token set, or it can hold a single token as in the
- * case of a simple query token set.
- *
- * Additionally token sets are used to perform wildcard matching.
- * Leading, contained and trailing wildcards are supported, and
- * from this edit distance matching can also be provided.
- *
- * Token sets are implemented as a minimal finite state automata,
- * where both common prefixes and suffixes are shared between tokens.
- * This helps to reduce the space used for storing the token set.
- *
- * @constructor
- */
-lunr.TokenSet = function () {
- this.final = false
- this.edges = {}
- this.id = lunr.TokenSet._nextId
- lunr.TokenSet._nextId += 1
-}
-
-/**
- * Keeps track of the next, auto increment, identifier to assign
- * to a new tokenSet.
- *
- * TokenSets require a unique identifier to be correctly minimised.
- *
- * @private
- */
-lunr.TokenSet._nextId = 1
-
-/**
- * Creates a TokenSet instance from the given sorted array of words.
- *
- * @param {String[]} arr - A sorted array of strings to create the set from.
- * @returns {lunr.TokenSet}
- * @throws Will throw an error if the input array is not sorted.
- */
-lunr.TokenSet.fromArray = function (arr) {
- var builder = new lunr.TokenSet.Builder
-
- for (var i = 0, len = arr.length; i < len; i++) {
- builder.insert(arr[i])
- }
-
- builder.finish()
- return builder.root
-}
-
-/**
- * Creates a token set from a query clause.
- *
- * @private
- * @param {Object} clause - A single clause from lunr.Query.
- * @param {string} clause.term - The query clause term.
- * @param {number} [clause.editDistance] - The optional edit distance for the term.
- * @returns {lunr.TokenSet}
- */
-lunr.TokenSet.fromClause = function (clause) {
- if ('editDistance' in clause) {
- return lunr.TokenSet.fromFuzzyString(clause.term, clause.editDistance)
- } else {
- return lunr.TokenSet.fromString(clause.term)
- }
-}
-
-/**
- * Creates a token set representing a single string with a specified
- * edit distance.
- *
- * Insertions, deletions, substitutions and transpositions are each
- * treated as an edit distance of 1.
- *
- * Increasing the allowed edit distance will have a dramatic impact
- * on the performance of both creating and intersecting these TokenSets.
- * It is advised to keep the edit distance less than 3.
- *
- * @param {string} str - The string to create the token set from.
- * @param {number} editDistance - The allowed edit distance to match.
- * @returns {lunr.Vector}
- */
-lunr.TokenSet.fromFuzzyString = function (str, editDistance) {
- var root = new lunr.TokenSet
-
- var stack = [{
- node: root,
- editsRemaining: editDistance,
- str: str
- }]
-
- while (stack.length) {
- var frame = stack.pop()
-
- // no edit
- if (frame.str.length > 0) {
- var char = frame.str.charAt(0),
- noEditNode
-
- if (char in frame.node.edges) {
- noEditNode = frame.node.edges[char]
- } else {
- noEditNode = new lunr.TokenSet
- frame.node.edges[char] = noEditNode
- }
-
- if (frame.str.length == 1) {
- noEditNode.final = true
- } else {
- stack.push({
- node: noEditNode,
- editsRemaining: frame.editsRemaining,
- str: frame.str.slice(1)
- })
- }
- }
-
- // deletion
- // can only do a deletion if we have enough edits remaining
- // and if there are characters left to delete in the string
- if (frame.editsRemaining > 0 && frame.str.length > 1) {
- var char = frame.str.charAt(1),
- deletionNode
-
- if (char in frame.node.edges) {
- deletionNode = frame.node.edges[char]
- } else {
- deletionNode = new lunr.TokenSet
- frame.node.edges[char] = deletionNode
- }
-
- if (frame.str.length <= 2) {
- deletionNode.final = true
- } else {
- stack.push({
- node: deletionNode,
- editsRemaining: frame.editsRemaining - 1,
- str: frame.str.slice(2)
- })
- }
- }
-
- // deletion
- // just removing the last character from the str
- if (frame.editsRemaining > 0 && frame.str.length == 1) {
- frame.node.final = true
- }
-
- // substitution
- // can only do a substitution if we have enough edits remaining
- // and if there are characters left to substitute
- if (frame.editsRemaining > 0 && frame.str.length >= 1) {
- if ("*" in frame.node.edges) {
- var substitutionNode = frame.node.edges["*"]
- } else {
- var substitutionNode = new lunr.TokenSet
- frame.node.edges["*"] = substitutionNode
- }
-
- if (frame.str.length == 1) {
- substitutionNode.final = true
- } else {
- stack.push({
- node: substitutionNode,
- editsRemaining: frame.editsRemaining - 1,
- str: frame.str.slice(1)
- })
- }
- }
-
- // insertion
- // can only do insertion if there are edits remaining
- if (frame.editsRemaining > 0) {
- if ("*" in frame.node.edges) {
- var insertionNode = frame.node.edges["*"]
- } else {
- var insertionNode = new lunr.TokenSet
- frame.node.edges["*"] = insertionNode
- }
-
- if (frame.str.length == 0) {
- insertionNode.final = true
- } else {
- stack.push({
- node: insertionNode,
- editsRemaining: frame.editsRemaining - 1,
- str: frame.str
- })
- }
- }
-
- // transposition
- // can only do a transposition if there are edits remaining
- // and there are enough characters to transpose
- if (frame.editsRemaining > 0 && frame.str.length > 1) {
- var charA = frame.str.charAt(0),
- charB = frame.str.charAt(1),
- transposeNode
-
- if (charB in frame.node.edges) {
- transposeNode = frame.node.edges[charB]
- } else {
- transposeNode = new lunr.TokenSet
- frame.node.edges[charB] = transposeNode
- }
-
- if (frame.str.length == 1) {
- transposeNode.final = true
- } else {
- stack.push({
- node: transposeNode,
- editsRemaining: frame.editsRemaining - 1,
- str: charA + frame.str.slice(2)
- })
- }
- }
- }
-
- return root
-}
-
-/**
- * Creates a TokenSet from a string.
- *
- * The string may contain one or more wildcard characters (*)
- * that will allow wildcard matching when intersecting with
- * another TokenSet.
- *
- * @param {string} str - The string to create a TokenSet from.
- * @returns {lunr.TokenSet}
- */
-lunr.TokenSet.fromString = function (str) {
- var node = new lunr.TokenSet,
- root = node,
- wildcardFound = false
-
- /*
- * Iterates through all characters within the passed string
- * appending a node for each character.
- *
- * As soon as a wildcard character is found then a self
- * referencing edge is introduced to continually match
- * any number of any characters.
- */
- for (var i = 0, len = str.length; i < len; i++) {
- var char = str[i],
- final = (i == len - 1)
-
- if (char == "*") {
- wildcardFound = true
- node.edges[char] = node
- node.final = final
-
- } else {
- var next = new lunr.TokenSet
- next.final = final
-
- node.edges[char] = next
- node = next
-
- // TODO: is this needed anymore?
- if (wildcardFound) {
- node.edges["*"] = root
- }
- }
- }
-
- return root
-}
-
-/**
- * Converts this TokenSet into an array of strings
- * contained within the TokenSet.
- *
- * @returns {string[]}
- */
-lunr.TokenSet.prototype.toArray = function () {
- var words = []
-
- var stack = [{
- prefix: "",
- node: this
- }]
-
- while (stack.length) {
- var frame = stack.pop(),
- edges = Object.keys(frame.node.edges),
- len = edges.length
-
- if (frame.node.final) {
- words.push(frame.prefix)
- }
-
- for (var i = 0; i < len; i++) {
- var edge = edges[i]
-
- stack.push({
- prefix: frame.prefix.concat(edge),
- node: frame.node.edges[edge]
- })
- }
- }
-
- return words
-}
-
-/**
- * Generates a string representation of a TokenSet.
- *
- * This is intended to allow TokenSets to be used as keys
- * in objects, largely to aid the construction and minimisation
- * of a TokenSet. As such it is not designed to be a human
- * friendly representation of the TokenSet.
- *
- * @returns {string}
- */
-lunr.TokenSet.prototype.toString = function () {
- // NOTE: Using Object.keys here as this.edges is very likely
- // to enter 'hash-mode' with many keys being added
- //
- // avoiding a for-in loop here as it leads to the function
- // being de-optimised (at least in V8). From some simple
- // benchmarks the performance is comparable, but allowing
- // V8 to optimize may mean easy performance wins in the future.
-
- if (this._str) {
- return this._str
- }
-
- var str = this.final ? '1' : '0',
- labels = Object.keys(this.edges).sort(),
- len = labels.length
-
- for (var i = 0; i < len; i++) {
- var label = labels[i],
- node = this.edges[label]
-
- str = str + label + node.id
- }
-
- return str
-}
-
-/**
- * Returns a new TokenSet that is the intersection of
- * this TokenSet and the passed TokenSet.
- *
- * This intersection will take into account any wildcards
- * contained within the TokenSet.
- *
- * @param {lunr.TokenSet} b - An other TokenSet to intersect with.
- * @returns {lunr.TokenSet}
- */
-lunr.TokenSet.prototype.intersect = function (b) {
- var output = new lunr.TokenSet,
- frame = undefined
-
- var stack = [{
- qNode: b,
- output: output,
- node: this
- }]
-
- while (stack.length) {
- frame = stack.pop()
-
- // NOTE: As with the #toString method, we are using
- // Object.keys and a for loop instead of a for-in loop
- // as both of these objects enter 'hash' mode, causing
- // the function to be de-optimised in V8
- var qEdges = Object.keys(frame.qNode.edges),
- qLen = qEdges.length,
- nEdges = Object.keys(frame.node.edges),
- nLen = nEdges.length
-
- for (var q = 0; q < qLen; q++) {
- var qEdge = qEdges[q]
-
- for (var n = 0; n < nLen; n++) {
- var nEdge = nEdges[n]
-
- if (nEdge == qEdge || qEdge == '*') {
- var node = frame.node.edges[nEdge],
- qNode = frame.qNode.edges[qEdge],
- final = node.final && qNode.final,
- next = undefined
-
- if (nEdge in frame.output.edges) {
- // an edge already exists for this character
- // no need to create a new node, just set the finality
- // bit unless this node is already final
- next = frame.output.edges[nEdge]
- next.final = next.final || final
-
- } else {
- // no edge exists yet, must create one
- // set the finality bit and insert it
- // into the output
- next = new lunr.TokenSet
- next.final = final
- frame.output.edges[nEdge] = next
- }
-
- stack.push({
- qNode: qNode,
- output: next,
- node: node
- })
- }
- }
- }
- }
-
- return output
-}
-lunr.TokenSet.Builder = function () {
- this.previousWord = ""
- this.root = new lunr.TokenSet
- this.uncheckedNodes = []
- this.minimizedNodes = {}
-}
-
-lunr.TokenSet.Builder.prototype.insert = function (word) {
- var node,
- commonPrefix = 0
-
- if (word < this.previousWord) {
- throw new Error ("Out of order word insertion")
- }
-
- for (var i = 0; i < word.length && i < this.previousWord.length; i++) {
- if (word[i] != this.previousWord[i]) break
- commonPrefix++
- }
-
- this.minimize(commonPrefix)
-
- if (this.uncheckedNodes.length == 0) {
- node = this.root
- } else {
- node = this.uncheckedNodes[this.uncheckedNodes.length - 1].child
- }
-
- for (var i = commonPrefix; i < word.length; i++) {
- var nextNode = new lunr.TokenSet,
- char = word[i]
-
- node.edges[char] = nextNode
-
- this.uncheckedNodes.push({
- parent: node,
- char: char,
- child: nextNode
- })
-
- node = nextNode
- }
-
- node.final = true
- this.previousWord = word
-}
-
-lunr.TokenSet.Builder.prototype.finish = function () {
- this.minimize(0)
-}
-
-lunr.TokenSet.Builder.prototype.minimize = function (downTo) {
- for (var i = this.uncheckedNodes.length - 1; i >= downTo; i--) {
- var node = this.uncheckedNodes[i],
- childKey = node.child.toString()
-
- if (childKey in this.minimizedNodes) {
- node.parent.edges[node.char] = this.minimizedNodes[childKey]
- } else {
- // Cache the key for this node since
- // we know it can't change anymore
- node.child._str = childKey
-
- this.minimizedNodes[childKey] = node.child
- }
-
- this.uncheckedNodes.pop()
- }
-}
-/*!
- * lunr.Index
- * Copyright (C) 2018 Oliver Nightingale
- */
-
-/**
- * An index contains the built index of all documents and provides a query interface
- * to the index.
- *
- * Usually instances of lunr.Index will not be created using this constructor, instead
- * lunr.Builder should be used to construct new indexes, or lunr.Index.load should be
- * used to load previously built and serialized indexes.
- *
- * @constructor
- * @param {Object} attrs - The attributes of the built search index.
- * @param {Object} attrs.invertedIndex - An index of term/field to document reference.
- * @param {Object} attrs.documentVectors - Document vectors keyed by document reference.
- * @param {lunr.TokenSet} attrs.tokenSet - An set of all corpus tokens.
- * @param {string[]} attrs.fields - The names of indexed document fields.
- * @param {lunr.Pipeline} attrs.pipeline - The pipeline to use for search terms.
- */
-lunr.Index = function (attrs) {
- this.invertedIndex = attrs.invertedIndex
- this.fieldVectors = attrs.fieldVectors
- this.tokenSet = attrs.tokenSet
- this.fields = attrs.fields
- this.pipeline = attrs.pipeline
-}
-
-/**
- * A result contains details of a document matching a search query.
- * @typedef {Object} lunr.Index~Result
- * @property {string} ref - The reference of the document this result represents.
- * @property {number} score - A number between 0 and 1 representing how similar this document is to the query.
- * @property {lunr.MatchData} matchData - Contains metadata about this match including which term(s) caused the match.
- */
-
-/**
- * Although lunr provides the ability to create queries using lunr.Query, it also provides a simple
- * query language which itself is parsed into an instance of lunr.Query.
- *
- * For programmatically building queries it is advised to directly use lunr.Query, the query language
- * is best used for human entered text rather than program generated text.
- *
- * At its simplest queries can just be a single term, e.g. `hello`, multiple terms are also supported
- * and will be combined with OR, e.g `hello world` will match documents that contain either 'hello'
- * or 'world', though those that contain both will rank higher in the results.
- *
- * Wildcards can be included in terms to match one or more unspecified characters, these wildcards can
- * be inserted anywhere within the term, and more than one wildcard can exist in a single term. Adding
- * wildcards will increase the number of documents that will be found but can also have a negative
- * impact on query performance, especially with wildcards at the beginning of a term.
- *
- * Terms can be restricted to specific fields, e.g. `title:hello`, only documents with the term
- * hello in the title field will match this query. Using a field not present in the index will lead
- * to an error being thrown.
- *
- * Modifiers can also be added to terms, lunr supports edit distance and boost modifiers on terms. A term
- * boost will make documents matching that term score higher, e.g. `foo^5`. Edit distance is also supported
- * to provide fuzzy matching, e.g. 'hello~2' will match documents with hello with an edit distance of 2.
- * Avoid large values for edit distance to improve query performance.
- *
- * To escape special characters the backslash character '\' can be used, this allows searches to include
- * characters that would normally be considered modifiers, e.g. `foo\~2` will search for a term "foo~2" instead
- * of attempting to apply a boost of 2 to the search term "foo".
- *
- * @typedef {string} lunr.Index~QueryString
- * @example
Simple single term query
- * hello
- * @example
Multiple term query
- * hello world
- * @example
term scoped to a field
- * title:hello
- * @example
term with a boost of 10
- * hello^10
- * @example
term with an edit distance of 2
- * hello~2
- */
-
-/**
- * Performs a search against the index using lunr query syntax.
- *
- * Results will be returned sorted by their score, the most relevant results
- * will be returned first.
- *
- * For more programmatic querying use lunr.Index#query.
- *
- * @param {lunr.Index~QueryString} queryString - A string containing a lunr query.
- * @throws {lunr.QueryParseError} If the passed query string cannot be parsed.
- * @returns {lunr.Index~Result[]}
- */
-lunr.Index.prototype.search = function (queryString) {
- return this.query(function (query) {
- var parser = new lunr.QueryParser(queryString, query)
- parser.parse()
- })
-}
-
-/**
- * A query builder callback provides a query object to be used to express
- * the query to perform on the index.
- *
- * @callback lunr.Index~queryBuilder
- * @param {lunr.Query} query - The query object to build up.
- * @this lunr.Query
- */
-
-/**
- * Performs a query against the index using the yielded lunr.Query object.
- *
- * If performing programmatic queries against the index, this method is preferred
- * over lunr.Index#search so as to avoid the additional query parsing overhead.
- *
- * A query object is yielded to the supplied function which should be used to
- * express the query to be run against the index.
- *
- * Note that although this function takes a callback parameter it is _not_ an
- * asynchronous operation, the callback is just yielded a query object to be
- * customized.
- *
- * @param {lunr.Index~queryBuilder} fn - A function that is used to build the query.
- * @returns {lunr.Index~Result[]}
- */
-lunr.Index.prototype.query = function (fn) {
- // for each query clause
- // * process terms
- // * expand terms from token set
- // * find matching documents and metadata
- // * get document vectors
- // * score documents
-
- var query = new lunr.Query(this.fields),
- matchingFields = Object.create(null),
- queryVectors = Object.create(null),
- termFieldCache = Object.create(null)
-
- fn.call(query, query)
-
- for (var i = 0; i < query.clauses.length; i++) {
- /*
- * Unless the pipeline has been disabled for this term, which is
- * the case for terms with wildcards, we need to pass the clause
- * term through the search pipeline. A pipeline returns an array
- * of processed terms. Pipeline functions may expand the passed
- * term, which means we may end up performing multiple index lookups
- * for a single query term.
- */
- var clause = query.clauses[i],
- terms = null
-
- if (clause.usePipeline) {
- terms = this.pipeline.runString(clause.term)
- } else {
- terms = [clause.term]
- }
-
- for (var m = 0; m < terms.length; m++) {
- var term = terms[m]
-
- /*
- * Each term returned from the pipeline needs to use the same query
- * clause object, e.g. the same boost and or edit distance. The
- * simplest way to do this is to re-use the clause object but mutate
- * its term property.
- */
- clause.term = term
-
- /*
- * From the term in the clause we create a token set which will then
- * be used to intersect the indexes token set to get a list of terms
- * to lookup in the inverted index
- */
- var termTokenSet = lunr.TokenSet.fromClause(clause),
- expandedTerms = this.tokenSet.intersect(termTokenSet).toArray()
-
- for (var j = 0; j < expandedTerms.length; j++) {
- /*
- * For each term get the posting and termIndex, this is required for
- * building the query vector.
- */
- var expandedTerm = expandedTerms[j],
- posting = this.invertedIndex[expandedTerm],
- termIndex = posting._index
-
- for (var k = 0; k < clause.fields.length; k++) {
- /*
- * For each field that this query term is scoped by (by default
- * all fields are in scope) we need to get all the document refs
- * that have this term in that field.
- *
- * The posting is the entry in the invertedIndex for the matching
- * term from above.
- */
- var field = clause.fields[k],
- fieldPosting = posting[field],
- matchingDocumentRefs = Object.keys(fieldPosting),
- termField = expandedTerm + "/" + field
-
- /*
- * To support field level boosts a query vector is created per
- * field. This vector is populated using the termIndex found for
- * the term and a unit value with the appropriate boost applied.
- *
- * If the query vector for this field does not exist yet it needs
- * to be created.
- */
- if (queryVectors[field] === undefined) {
- queryVectors[field] = new lunr.Vector
- }
-
- /*
- * Using upsert because there could already be an entry in the vector
- * for the term we are working with. In that case we just add the scores
- * together.
- */
- queryVectors[field].upsert(termIndex, 1 * clause.boost, function (a, b) { return a + b })
-
- /**
- * If we've already seen this term, field combo then we've already collected
- * the matching documents and metadata, no need to go through all that again
- */
- if (termFieldCache[termField]) {
- continue
- }
-
- for (var l = 0; l < matchingDocumentRefs.length; l++) {
- /*
- * All metadata for this term/field/document triple
- * are then extracted and collected into an instance
- * of lunr.MatchData ready to be returned in the query
- * results
- */
- var matchingDocumentRef = matchingDocumentRefs[l],
- matchingFieldRef = new lunr.FieldRef (matchingDocumentRef, field),
- metadata = fieldPosting[matchingDocumentRef],
- fieldMatch
-
- if ((fieldMatch = matchingFields[matchingFieldRef]) === undefined) {
- matchingFields[matchingFieldRef] = new lunr.MatchData (expandedTerm, field, metadata)
- } else {
- fieldMatch.add(expandedTerm, field, metadata)
- }
-
- }
-
- termFieldCache[termField] = true
- }
- }
- }
- }
-
- var matchingFieldRefs = Object.keys(matchingFields),
- results = [],
- matches = Object.create(null)
-
- for (var i = 0; i < matchingFieldRefs.length; i++) {
- /*
- * Currently we have document fields that match the query, but we
- * need to return documents. The matchData and scores are combined
- * from multiple fields belonging to the same document.
- *
- * Scores are calculated by field, using the query vectors created
- * above, and combined into a final document score using addition.
- */
- var fieldRef = lunr.FieldRef.fromString(matchingFieldRefs[i]),
- docRef = fieldRef.docRef,
- fieldVector = this.fieldVectors[fieldRef],
- score = queryVectors[fieldRef.fieldName].similarity(fieldVector),
- docMatch
-
- if ((docMatch = matches[docRef]) !== undefined) {
- docMatch.score += score
- docMatch.matchData.combine(matchingFields[fieldRef])
- } else {
- var match = {
- ref: docRef,
- score: score,
- matchData: matchingFields[fieldRef]
- }
- matches[docRef] = match
- results.push(match)
- }
- }
-
- /*
- * Sort the results objects by score, highest first.
- */
- return results.sort(function (a, b) {
- return b.score - a.score
- })
-}
-
-/**
- * Prepares the index for JSON serialization.
- *
- * The schema for this JSON blob will be described in a
- * separate JSON schema file.
- *
- * @returns {Object}
- */
-lunr.Index.prototype.toJSON = function () {
- var invertedIndex = Object.keys(this.invertedIndex)
- .sort()
- .map(function (term) {
- return [term, this.invertedIndex[term]]
- }, this)
-
- var fieldVectors = Object.keys(this.fieldVectors)
- .map(function (ref) {
- return [ref, this.fieldVectors[ref].toJSON()]
- }, this)
-
- return {
- version: lunr.version,
- fields: this.fields,
- fieldVectors: fieldVectors,
- invertedIndex: invertedIndex,
- pipeline: this.pipeline.toJSON()
- }
-}
-
-/**
- * Loads a previously serialized lunr.Index
- *
- * @param {Object} serializedIndex - A previously serialized lunr.Index
- * @returns {lunr.Index}
- */
-lunr.Index.load = function (serializedIndex) {
- var attrs = {},
- fieldVectors = {},
- serializedVectors = serializedIndex.fieldVectors,
- invertedIndex = {},
- serializedInvertedIndex = serializedIndex.invertedIndex,
- tokenSetBuilder = new lunr.TokenSet.Builder,
- pipeline = lunr.Pipeline.load(serializedIndex.pipeline)
-
- if (serializedIndex.version != lunr.version) {
- lunr.utils.warn("Version mismatch when loading serialised index. Current version of lunr '" + lunr.version + "' does not match serialized index '" + serializedIndex.version + "'")
- }
-
- for (var i = 0; i < serializedVectors.length; i++) {
- var tuple = serializedVectors[i],
- ref = tuple[0],
- elements = tuple[1]
-
- fieldVectors[ref] = new lunr.Vector(elements)
- }
-
- for (var i = 0; i < serializedInvertedIndex.length; i++) {
- var tuple = serializedInvertedIndex[i],
- term = tuple[0],
- posting = tuple[1]
-
- tokenSetBuilder.insert(term)
- invertedIndex[term] = posting
- }
-
- tokenSetBuilder.finish()
-
- attrs.fields = serializedIndex.fields
-
- attrs.fieldVectors = fieldVectors
- attrs.invertedIndex = invertedIndex
- attrs.tokenSet = tokenSetBuilder.root
- attrs.pipeline = pipeline
-
- return new lunr.Index(attrs)
-}
-/*!
- * lunr.Builder
- * Copyright (C) 2018 Oliver Nightingale
- */
-
-/**
- * lunr.Builder performs indexing on a set of documents and
- * returns instances of lunr.Index ready for querying.
- *
- * All configuration of the index is done via the builder, the
- * fields to index, the document reference, the text processing
- * pipeline and document scoring parameters are all set on the
- * builder before indexing.
- *
- * @constructor
- * @property {string} _ref - Internal reference to the document reference field.
- * @property {string[]} _fields - Internal reference to the document fields to index.
- * @property {object} invertedIndex - The inverted index maps terms to document fields.
- * @property {object} documentTermFrequencies - Keeps track of document term frequencies.
- * @property {object} documentLengths - Keeps track of the length of documents added to the index.
- * @property {lunr.tokenizer} tokenizer - Function for splitting strings into tokens for indexing.
- * @property {lunr.Pipeline} pipeline - The pipeline performs text processing on tokens before indexing.
- * @property {lunr.Pipeline} searchPipeline - A pipeline for processing search terms before querying the index.
- * @property {number} documentCount - Keeps track of the total number of documents indexed.
- * @property {number} _b - A parameter to control field length normalization, setting this to 0 disabled normalization, 1 fully normalizes field lengths, the default value is 0.75.
- * @property {number} _k1 - A parameter to control how quickly an increase in term frequency results in term frequency saturation, the default value is 1.2.
- * @property {number} termIndex - A counter incremented for each unique term, used to identify a terms position in the vector space.
- * @property {array} metadataWhitelist - A list of metadata keys that have been whitelisted for entry in the index.
- */
-lunr.Builder = function () {
- this._ref = "id"
- this._fields = []
- this.invertedIndex = Object.create(null)
- this.fieldTermFrequencies = {}
- this.fieldLengths = {}
- this.tokenizer = lunr.tokenizer
- this.pipeline = new lunr.Pipeline
- this.searchPipeline = new lunr.Pipeline
- this.documentCount = 0
- this._b = 0.75
- this._k1 = 1.2
- this.termIndex = 0
- this.metadataWhitelist = []
-}
-
-/**
- * Sets the document field used as the document reference. Every document must have this field.
- * The type of this field in the document should be a string, if it is not a string it will be
- * coerced into a string by calling toString.
- *
- * The default ref is 'id'.
- *
- * The ref should _not_ be changed during indexing, it should be set before any documents are
- * added to the index. Changing it during indexing can lead to inconsistent results.
- *
- * @param {string} ref - The name of the reference field in the document.
- */
-lunr.Builder.prototype.ref = function (ref) {
- this._ref = ref
-}
-
-/**
- * Adds a field to the list of document fields that will be indexed. Every document being
- * indexed should have this field. Null values for this field in indexed documents will
- * not cause errors but will limit the chance of that document being retrieved by searches.
- *
- * All fields should be added before adding documents to the index. Adding fields after
- * a document has been indexed will have no effect on already indexed documents.
- *
- * @param {string} field - The name of a field to index in all documents.
- */
-lunr.Builder.prototype.field = function (field) {
- this._fields.push(field)
-}
-
-/**
- * A parameter to tune the amount of field length normalisation that is applied when
- * calculating relevance scores. A value of 0 will completely disable any normalisation
- * and a value of 1 will fully normalise field lengths. The default is 0.75. Values of b
- * will be clamped to the range 0 - 1.
- *
- * @param {number} number - The value to set for this tuning parameter.
- */
-lunr.Builder.prototype.b = function (number) {
- if (number < 0) {
- this._b = 0
- } else if (number > 1) {
- this._b = 1
- } else {
- this._b = number
- }
-}
-
-/**
- * A parameter that controls the speed at which a rise in term frequency results in term
- * frequency saturation. The default value is 1.2. Setting this to a higher value will give
- * slower saturation levels, a lower value will result in quicker saturation.
- *
- * @param {number} number - The value to set for this tuning parameter.
- */
-lunr.Builder.prototype.k1 = function (number) {
- this._k1 = number
-}
-
-/**
- * Adds a document to the index.
- *
- * Before adding fields to the index the index should have been fully setup, with the document
- * ref and all fields to index already having been specified.
- *
- * The document must have a field name as specified by the ref (by default this is 'id') and
- * it should have all fields defined for indexing, though null or undefined values will not
- * cause errors.
- *
- * @param {object} doc - The document to add to the index.
- */
-lunr.Builder.prototype.add = function (doc) {
- var docRef = doc[this._ref]
-
- this.documentCount += 1
-
- for (var i = 0; i < this._fields.length; i++) {
- var fieldName = this._fields[i],
- field = doc[fieldName],
- tokens = this.tokenizer(field),
- terms = this.pipeline.run(tokens),
- fieldRef = new lunr.FieldRef (docRef, fieldName),
- fieldTerms = Object.create(null)
-
- this.fieldTermFrequencies[fieldRef] = fieldTerms
- this.fieldLengths[fieldRef] = 0
-
- // store the length of this field for this document
- this.fieldLengths[fieldRef] += terms.length
-
- // calculate term frequencies for this field
- for (var j = 0; j < terms.length; j++) {
- var term = terms[j]
-
- if (fieldTerms[term] == undefined) {
- fieldTerms[term] = 0
- }
-
- fieldTerms[term] += 1
-
- // add to inverted index
- // create an initial posting if one doesn't exist
- if (this.invertedIndex[term] == undefined) {
- var posting = Object.create(null)
- posting["_index"] = this.termIndex
- this.termIndex += 1
-
- for (var k = 0; k < this._fields.length; k++) {
- posting[this._fields[k]] = Object.create(null)
- }
-
- this.invertedIndex[term] = posting
- }
-
- // add an entry for this term/fieldName/docRef to the invertedIndex
- if (this.invertedIndex[term][fieldName][docRef] == undefined) {
- this.invertedIndex[term][fieldName][docRef] = Object.create(null)
- }
-
- // store all whitelisted metadata about this token in the
- // inverted index
- for (var l = 0; l < this.metadataWhitelist.length; l++) {
- var metadataKey = this.metadataWhitelist[l],
- metadata = term.metadata[metadataKey]
-
- if (this.invertedIndex[term][fieldName][docRef][metadataKey] == undefined) {
- this.invertedIndex[term][fieldName][docRef][metadataKey] = []
- }
-
- this.invertedIndex[term][fieldName][docRef][metadataKey].push(metadata)
- }
- }
-
- }
-}
-
-/**
- * Calculates the average document length for this index
- *
- * @private
- */
-lunr.Builder.prototype.calculateAverageFieldLengths = function () {
-
- var fieldRefs = Object.keys(this.fieldLengths),
- numberOfFields = fieldRefs.length,
- accumulator = {},
- documentsWithField = {}
-
- for (var i = 0; i < numberOfFields; i++) {
- var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]),
- field = fieldRef.fieldName
-
- documentsWithField[field] || (documentsWithField[field] = 0)
- documentsWithField[field] += 1
-
- accumulator[field] || (accumulator[field] = 0)
- accumulator[field] += this.fieldLengths[fieldRef]
- }
-
- for (var i = 0; i < this._fields.length; i++) {
- var field = this._fields[i]
- accumulator[field] = accumulator[field] / documentsWithField[field]
- }
-
- this.averageFieldLength = accumulator
-}
-
-/**
- * Builds a vector space model of every document using lunr.Vector
- *
- * @private
- */
-lunr.Builder.prototype.createFieldVectors = function () {
- var fieldVectors = {},
- fieldRefs = Object.keys(this.fieldTermFrequencies),
- fieldRefsLength = fieldRefs.length,
- termIdfCache = Object.create(null)
-
- for (var i = 0; i < fieldRefsLength; i++) {
- var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]),
- field = fieldRef.fieldName,
- fieldLength = this.fieldLengths[fieldRef],
- fieldVector = new lunr.Vector,
- termFrequencies = this.fieldTermFrequencies[fieldRef],
- terms = Object.keys(termFrequencies),
- termsLength = terms.length
-
- for (var j = 0; j < termsLength; j++) {
- var term = terms[j],
- tf = termFrequencies[term],
- termIndex = this.invertedIndex[term]._index,
- idf, score, scoreWithPrecision
-
- if (termIdfCache[term] === undefined) {
- idf = lunr.idf(this.invertedIndex[term], this.documentCount)
- termIdfCache[term] = idf
- } else {
- idf = termIdfCache[term]
- }
-
- score = idf * ((this._k1 + 1) * tf) / (this._k1 * (1 - this._b + this._b * (fieldLength / this.averageFieldLength[field])) + tf)
- scoreWithPrecision = Math.round(score * 1000) / 1000
- // Converts 1.23456789 to 1.234.
- // Reducing the precision so that the vectors take up less
- // space when serialised. Doing it now so that they behave
- // the same before and after serialisation. Also, this is
- // the fastest approach to reducing a number's precision in
- // JavaScript.
-
- fieldVector.insert(termIndex, scoreWithPrecision)
- }
-
- fieldVectors[fieldRef] = fieldVector
- }
-
- this.fieldVectors = fieldVectors
-}
-
-/**
- * Creates a token set of all tokens in the index using lunr.TokenSet
- *
- * @private
- */
-lunr.Builder.prototype.createTokenSet = function () {
- this.tokenSet = lunr.TokenSet.fromArray(
- Object.keys(this.invertedIndex).sort()
- )
-}
-
-/**
- * Builds the index, creating an instance of lunr.Index.
- *
- * This completes the indexing process and should only be called
- * once all documents have been added to the index.
- *
- * @returns {lunr.Index}
- */
-lunr.Builder.prototype.build = function () {
- this.calculateAverageFieldLengths()
- this.createFieldVectors()
- this.createTokenSet()
-
- return new lunr.Index({
- invertedIndex: this.invertedIndex,
- fieldVectors: this.fieldVectors,
- tokenSet: this.tokenSet,
- fields: this._fields,
- pipeline: this.searchPipeline
- })
-}
-
-/**
- * Applies a plugin to the index builder.
- *
- * A plugin is a function that is called with the index builder as its context.
- * Plugins can be used to customise or extend the behaviour of the index
- * in some way. A plugin is just a function, that encapsulated the custom
- * behaviour that should be applied when building the index.
- *
- * The plugin function will be called with the index builder as its argument, additional
- * arguments can also be passed when calling use. The function will be called
- * with the index builder as its context.
- *
- * @param {Function} plugin The plugin to apply.
- */
-lunr.Builder.prototype.use = function (fn) {
- var args = Array.prototype.slice.call(arguments, 1)
- args.unshift(this)
- fn.apply(this, args)
-}
-/**
- * Contains and collects metadata about a matching document.
- * A single instance of lunr.MatchData is returned as part of every
- * lunr.Index~Result.
- *
- * @constructor
- * @param {string} term - The term this match data is associated with
- * @param {string} field - The field in which the term was found
- * @param {object} metadata - The metadata recorded about this term in this field
- * @property {object} metadata - A cloned collection of metadata associated with this document.
- * @see {@link lunr.Index~Result}
- */
-lunr.MatchData = function (term, field, metadata) {
- var clonedMetadata = Object.create(null),
- metadataKeys = Object.keys(metadata)
-
- // Cloning the metadata to prevent the original
- // being mutated during match data combination.
- // Metadata is kept in an array within the inverted
- // index so cloning the data can be done with
- // Array#slice
- for (var i = 0; i < metadataKeys.length; i++) {
- var key = metadataKeys[i]
- clonedMetadata[key] = metadata[key].slice()
- }
-
- this.metadata = Object.create(null)
- this.metadata[term] = Object.create(null)
- this.metadata[term][field] = clonedMetadata
-}
-
-/**
- * An instance of lunr.MatchData will be created for every term that matches a
- * document. However only one instance is required in a lunr.Index~Result. This
- * method combines metadata from another instance of lunr.MatchData with this
- * objects metadata.
- *
- * @param {lunr.MatchData} otherMatchData - Another instance of match data to merge with this one.
- * @see {@link lunr.Index~Result}
- */
-lunr.MatchData.prototype.combine = function (otherMatchData) {
- var terms = Object.keys(otherMatchData.metadata)
-
- for (var i = 0; i < terms.length; i++) {
- var term = terms[i],
- fields = Object.keys(otherMatchData.metadata[term])
-
- if (this.metadata[term] == undefined) {
- this.metadata[term] = Object.create(null)
- }
-
- for (var j = 0; j < fields.length; j++) {
- var field = fields[j],
- keys = Object.keys(otherMatchData.metadata[term][field])
-
- if (this.metadata[term][field] == undefined) {
- this.metadata[term][field] = Object.create(null)
- }
-
- for (var k = 0; k < keys.length; k++) {
- var key = keys[k]
-
- if (this.metadata[term][field][key] == undefined) {
- this.metadata[term][field][key] = otherMatchData.metadata[term][field][key]
- } else {
- this.metadata[term][field][key] = this.metadata[term][field][key].concat(otherMatchData.metadata[term][field][key])
- }
-
- }
- }
- }
-}
-
-/**
- * Add metadata for a term/field pair to this instance of match data.
- *
- * @param {string} term - The term this match data is associated with
- * @param {string} field - The field in which the term was found
- * @param {object} metadata - The metadata recorded about this term in this field
- */
-lunr.MatchData.prototype.add = function (term, field, metadata) {
- if (!(term in this.metadata)) {
- this.metadata[term] = Object.create(null)
- this.metadata[term][field] = metadata
- return
- }
-
- if (!(field in this.metadata[term])) {
- this.metadata[term][field] = metadata
- return
- }
-
- var metadataKeys = Object.keys(metadata)
-
- for (var i = 0; i < metadataKeys.length; i++) {
- var key = metadataKeys[i]
-
- if (key in this.metadata[term][field]) {
- this.metadata[term][field][key] = this.metadata[term][field][key].concat(metadata[key])
- } else {
- this.metadata[term][field][key] = metadata[key]
- }
- }
-}
-/**
- * A lunr.Query provides a programmatic way of defining queries to be performed
- * against a {@link lunr.Index}.
- *
- * Prefer constructing a lunr.Query using the {@link lunr.Index#query} method
- * so the query object is pre-initialized with the right index fields.
- *
- * @constructor
- * @property {lunr.Query~Clause[]} clauses - An array of query clauses.
- * @property {string[]} allFields - An array of all available fields in a lunr.Index.
- */
-lunr.Query = function (allFields) {
- this.clauses = []
- this.allFields = allFields
-}
-
-/**
- * Constants for indicating what kind of automatic wildcard insertion will be used when constructing a query clause.
- *
- * This allows wildcards to be added to the beginning and end of a term without having to manually do any string
- * concatenation.
- *
- * The wildcard constants can be bitwise combined to select both leading and trailing wildcards.
- *
- * @constant
- * @default
- * @property {number} wildcard.NONE - The term will have no wildcards inserted, this is the default behaviour
- * @property {number} wildcard.LEADING - Prepend the term with a wildcard, unless a leading wildcard already exists
- * @property {number} wildcard.TRAILING - Append a wildcard to the term, unless a trailing wildcard already exists
- * @see lunr.Query~Clause
- * @see lunr.Query#clause
- * @see lunr.Query#term
- * @example
- * query.term('foo', {
- * wildcard: lunr.Query.wildcard.LEADING | lunr.Query.wildcard.TRAILING
- * })
- */
-lunr.Query.wildcard = new String ("*")
-lunr.Query.wildcard.NONE = 0
-lunr.Query.wildcard.LEADING = 1
-lunr.Query.wildcard.TRAILING = 2
-
-/**
- * A single clause in a {@link lunr.Query} contains a term and details on how to
- * match that term against a {@link lunr.Index}.
- *
- * @typedef {Object} lunr.Query~Clause
- * @property {string[]} fields - The fields in an index this clause should be matched against.
- * @property {number} [boost=1] - Any boost that should be applied when matching this clause.
- * @property {number} [editDistance] - Whether the term should have fuzzy matching applied, and how fuzzy the match should be.
- * @property {boolean} [usePipeline] - Whether the term should be passed through the search pipeline.
- * @property {number} [wildcard=0] - Whether the term should have wildcards appended or prepended.
- */
-
-/**
- * Adds a {@link lunr.Query~Clause} to this query.
- *
- * Unless the clause contains the fields to be matched all fields will be matched. In addition
- * a default boost of 1 is applied to the clause.
- *
- * @param {lunr.Query~Clause} clause - The clause to add to this query.
- * @see lunr.Query~Clause
- * @returns {lunr.Query}
- */
-lunr.Query.prototype.clause = function (clause) {
- if (!('fields' in clause)) {
- clause.fields = this.allFields
- }
-
- if (!('boost' in clause)) {
- clause.boost = 1
- }
-
- if (!('usePipeline' in clause)) {
- clause.usePipeline = true
- }
-
- if (!('wildcard' in clause)) {
- clause.wildcard = lunr.Query.wildcard.NONE
- }
-
- if ((clause.wildcard & lunr.Query.wildcard.LEADING) && (clause.term.charAt(0) != lunr.Query.wildcard)) {
- clause.term = "*" + clause.term
- }
-
- if ((clause.wildcard & lunr.Query.wildcard.TRAILING) && (clause.term.slice(-1) != lunr.Query.wildcard)) {
- clause.term = "" + clause.term + "*"
- }
-
- this.clauses.push(clause)
-
- return this
-}
-
-/**
- * Adds a term to the current query, under the covers this will create a {@link lunr.Query~Clause}
- * to the list of clauses that make up this query.
- *
- * @param {string} term - The term to add to the query.
- * @param {Object} [options] - Any additional properties to add to the query clause.
- * @returns {lunr.Query}
- * @see lunr.Query#clause
- * @see lunr.Query~Clause
- * @example
adding a single term to a query
- * query.term("foo")
- * @example
adding a single term to a query and specifying search fields, term boost and automatic trailing wildcard
- * query.term("foo", {
- * fields: ["title"],
- * boost: 10,
- * wildcard: lunr.Query.wildcard.TRAILING
- * })
- */
-lunr.Query.prototype.term = function (term, options) {
- var clause = options || {}
- clause.term = term
-
- this.clause(clause)
-
- return this
-}
-lunr.QueryParseError = function (message, start, end) {
- this.name = "QueryParseError"
- this.message = message
- this.start = start
- this.end = end
-}
-
-lunr.QueryParseError.prototype = new Error
-lunr.QueryLexer = function (str) {
- this.lexemes = []
- this.str = str
- this.length = str.length
- this.pos = 0
- this.start = 0
- this.escapeCharPositions = []
-}
-
-lunr.QueryLexer.prototype.run = function () {
- var state = lunr.QueryLexer.lexText
-
- while (state) {
- state = state(this)
- }
-}
-
-lunr.QueryLexer.prototype.sliceString = function () {
- var subSlices = [],
- sliceStart = this.start,
- sliceEnd = this.pos
-
- for (var i = 0; i < this.escapeCharPositions.length; i++) {
- sliceEnd = this.escapeCharPositions[i]
- subSlices.push(this.str.slice(sliceStart, sliceEnd))
- sliceStart = sliceEnd + 1
- }
-
- subSlices.push(this.str.slice(sliceStart, this.pos))
- this.escapeCharPositions.length = 0
-
- return subSlices.join('')
-}
-
-lunr.QueryLexer.prototype.emit = function (type) {
- this.lexemes.push({
- type: type,
- str: this.sliceString(),
- start: this.start,
- end: this.pos
- })
-
- this.start = this.pos
-}
-
-lunr.QueryLexer.prototype.escapeCharacter = function () {
- this.escapeCharPositions.push(this.pos - 1)
- this.pos += 1
-}
-
-lunr.QueryLexer.prototype.next = function () {
- if (this.pos >= this.length) {
- return lunr.QueryLexer.EOS
- }
-
- var char = this.str.charAt(this.pos)
- this.pos += 1
- return char
-}
-
-lunr.QueryLexer.prototype.width = function () {
- return this.pos - this.start
-}
-
-lunr.QueryLexer.prototype.ignore = function () {
- if (this.start == this.pos) {
- this.pos += 1
- }
-
- this.start = this.pos
-}
-
-lunr.QueryLexer.prototype.backup = function () {
- this.pos -= 1
-}
-
-lunr.QueryLexer.prototype.acceptDigitRun = function () {
- var char, charCode
-
- do {
- char = this.next()
- charCode = char.charCodeAt(0)
- } while (charCode > 47 && charCode < 58)
-
- if (char != lunr.QueryLexer.EOS) {
- this.backup()
- }
-}
-
-lunr.QueryLexer.prototype.more = function () {
- return this.pos < this.length
-}
-
-lunr.QueryLexer.EOS = 'EOS'
-lunr.QueryLexer.FIELD = 'FIELD'
-lunr.QueryLexer.TERM = 'TERM'
-lunr.QueryLexer.EDIT_DISTANCE = 'EDIT_DISTANCE'
-lunr.QueryLexer.BOOST = 'BOOST'
-
-lunr.QueryLexer.lexField = function (lexer) {
- lexer.backup()
- lexer.emit(lunr.QueryLexer.FIELD)
- lexer.ignore()
- return lunr.QueryLexer.lexText
-}
-
-lunr.QueryLexer.lexTerm = function (lexer) {
- if (lexer.width() > 1) {
- lexer.backup()
- lexer.emit(lunr.QueryLexer.TERM)
- }
-
- lexer.ignore()
-
- if (lexer.more()) {
- return lunr.QueryLexer.lexText
- }
-}
-
-lunr.QueryLexer.lexEditDistance = function (lexer) {
- lexer.ignore()
- lexer.acceptDigitRun()
- lexer.emit(lunr.QueryLexer.EDIT_DISTANCE)
- return lunr.QueryLexer.lexText
-}
-
-lunr.QueryLexer.lexBoost = function (lexer) {
- lexer.ignore()
- lexer.acceptDigitRun()
- lexer.emit(lunr.QueryLexer.BOOST)
- return lunr.QueryLexer.lexText
-}
-
-lunr.QueryLexer.lexEOS = function (lexer) {
- if (lexer.width() > 0) {
- lexer.emit(lunr.QueryLexer.TERM)
- }
-}
-
-// This matches the separator used when tokenising fields
-// within a document. These should match otherwise it is
-// not possible to search for some tokens within a document.
-//
-// It is possible for the user to change the separator on the
-// tokenizer so it _might_ clash with any other of the special
-// characters already used within the search string, e.g. :.
-//
-// This means that it is possible to change the separator in
-// such a way that makes some words unsearchable using a search
-// string.
-lunr.QueryLexer.termSeparator = lunr.tokenizer.separator
-
-lunr.QueryLexer.lexText = function (lexer) {
- while (true) {
- var char = lexer.next()
-
- if (char == lunr.QueryLexer.EOS) {
- return lunr.QueryLexer.lexEOS
- }
-
- // Escape character is '\'
- if (char.charCodeAt(0) == 92) {
- lexer.escapeCharacter()
- continue
- }
-
- if (char == ":") {
- return lunr.QueryLexer.lexField
- }
-
- if (char == "~") {
- lexer.backup()
- if (lexer.width() > 0) {
- lexer.emit(lunr.QueryLexer.TERM)
- }
- return lunr.QueryLexer.lexEditDistance
- }
-
- if (char == "^") {
- lexer.backup()
- if (lexer.width() > 0) {
- lexer.emit(lunr.QueryLexer.TERM)
- }
- return lunr.QueryLexer.lexBoost
- }
-
- if (char.match(lunr.QueryLexer.termSeparator)) {
- return lunr.QueryLexer.lexTerm
- }
- }
-}
-
-lunr.QueryParser = function (str, query) {
- this.lexer = new lunr.QueryLexer (str)
- this.query = query
- this.currentClause = {}
- this.lexemeIdx = 0
-}
-
-lunr.QueryParser.prototype.parse = function () {
- this.lexer.run()
- this.lexemes = this.lexer.lexemes
-
- var state = lunr.QueryParser.parseFieldOrTerm
-
- while (state) {
- state = state(this)
- }
-
- return this.query
-}
-
-lunr.QueryParser.prototype.peekLexeme = function () {
- return this.lexemes[this.lexemeIdx]
-}
-
-lunr.QueryParser.prototype.consumeLexeme = function () {
- var lexeme = this.peekLexeme()
- this.lexemeIdx += 1
- return lexeme
-}
-
-lunr.QueryParser.prototype.nextClause = function () {
- var completedClause = this.currentClause
- this.query.clause(completedClause)
- this.currentClause = {}
-}
-
-lunr.QueryParser.parseFieldOrTerm = function (parser) {
- var lexeme = parser.peekLexeme()
-
- if (lexeme == undefined) {
- return
- }
-
- switch (lexeme.type) {
- case lunr.QueryLexer.FIELD:
- return lunr.QueryParser.parseField
- case lunr.QueryLexer.TERM:
- return lunr.QueryParser.parseTerm
- default:
- var errorMessage = "expected either a field or a term, found " + lexeme.type
-
- if (lexeme.str.length >= 1) {
- errorMessage += " with value '" + lexeme.str + "'"
- }
-
- throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)
- }
-}
-
-lunr.QueryParser.parseField = function (parser) {
- var lexeme = parser.consumeLexeme()
-
- if (lexeme == undefined) {
- return
- }
-
- if (parser.query.allFields.indexOf(lexeme.str) == -1) {
- var possibleFields = parser.query.allFields.map(function (f) { return "'" + f + "'" }).join(', '),
- errorMessage = "unrecognised field '" + lexeme.str + "', possible fields: " + possibleFields
-
- throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)
- }
-
- parser.currentClause.fields = [lexeme.str]
-
- var nextLexeme = parser.peekLexeme()
-
- if (nextLexeme == undefined) {
- var errorMessage = "expecting term, found nothing"
- throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)
- }
-
- switch (nextLexeme.type) {
- case lunr.QueryLexer.TERM:
- return lunr.QueryParser.parseTerm
- default:
- var errorMessage = "expecting term, found '" + nextLexeme.type + "'"
- throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)
- }
-}
-
-lunr.QueryParser.parseTerm = function (parser) {
- var lexeme = parser.consumeLexeme()
-
- if (lexeme == undefined) {
- return
- }
-
- parser.currentClause.term = lexeme.str.toLowerCase()
-
- if (lexeme.str.indexOf("*") != -1) {
- parser.currentClause.usePipeline = false
- }
-
- var nextLexeme = parser.peekLexeme()
-
- if (nextLexeme == undefined) {
- parser.nextClause()
- return
- }
-
- switch (nextLexeme.type) {
- case lunr.QueryLexer.TERM:
- parser.nextClause()
- return lunr.QueryParser.parseTerm
- case lunr.QueryLexer.FIELD:
- parser.nextClause()
- return lunr.QueryParser.parseField
- case lunr.QueryLexer.EDIT_DISTANCE:
- return lunr.QueryParser.parseEditDistance
- case lunr.QueryLexer.BOOST:
- return lunr.QueryParser.parseBoost
- default:
- var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'"
- throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)
- }
-}
-
-lunr.QueryParser.parseEditDistance = function (parser) {
- var lexeme = parser.consumeLexeme()
-
- if (lexeme == undefined) {
- return
- }
-
- var editDistance = parseInt(lexeme.str, 10)
-
- if (isNaN(editDistance)) {
- var errorMessage = "edit distance must be numeric"
- throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)
- }
-
- parser.currentClause.editDistance = editDistance
-
- var nextLexeme = parser.peekLexeme()
-
- if (nextLexeme == undefined) {
- parser.nextClause()
- return
- }
-
- switch (nextLexeme.type) {
- case lunr.QueryLexer.TERM:
- parser.nextClause()
- return lunr.QueryParser.parseTerm
- case lunr.QueryLexer.FIELD:
- parser.nextClause()
- return lunr.QueryParser.parseField
- case lunr.QueryLexer.EDIT_DISTANCE:
- return lunr.QueryParser.parseEditDistance
- case lunr.QueryLexer.BOOST:
- return lunr.QueryParser.parseBoost
- default:
- var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'"
- throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)
- }
-}
-
-lunr.QueryParser.parseBoost = function (parser) {
- var lexeme = parser.consumeLexeme()
-
- if (lexeme == undefined) {
- return
- }
-
- var boost = parseInt(lexeme.str, 10)
-
- if (isNaN(boost)) {
- var errorMessage = "boost must be numeric"
- throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)
- }
-
- parser.currentClause.boost = boost
-
- var nextLexeme = parser.peekLexeme()
-
- if (nextLexeme == undefined) {
- parser.nextClause()
- return
- }
-
- switch (nextLexeme.type) {
- case lunr.QueryLexer.TERM:
- parser.nextClause()
- return lunr.QueryParser.parseTerm
- case lunr.QueryLexer.FIELD:
- parser.nextClause()
- return lunr.QueryParser.parseField
- case lunr.QueryLexer.EDIT_DISTANCE:
- return lunr.QueryParser.parseEditDistance
- case lunr.QueryLexer.BOOST:
- return lunr.QueryParser.parseBoost
- default:
- var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'"
- throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)
- }
-}
-
- /**
- * export the module via AMD, CommonJS or as a browser global
- * Export code from https://github.com/umdjs/umd/blob/master/returnExports.js
- */
- ;(function (root, factory) {
- if (typeof define === 'function' && define.amd) {
- // AMD. Register as an anonymous module.
- define(factory)
- } else if (typeof exports === 'object') {
- /**
- * Node. Does not work with strict CommonJS, but
- * only CommonJS-like enviroments that support module.exports,
- * like Node.
- */
- module.exports = factory()
- } else {
- // Browser globals (root is window)
- root.lunr = factory()
- }
- }(this, function () {
- /**
- * Just return a value to define the module export.
- * This example returns an object, but the module
- * can return a function as the exported value.
- */
- return lunr
- }))
-})();
diff --git a/site/search/main.js b/site/search/main.js
deleted file mode 100644
index 0a82ab5..0000000
--- a/site/search/main.js
+++ /dev/null
@@ -1,96 +0,0 @@
-function getSearchTermFromLocation() {
- var sPageURL = window.location.search.substring(1);
- var sURLVariables = sPageURL.split('&');
- for (var i = 0; i < sURLVariables.length; i++) {
- var sParameterName = sURLVariables[i].split('=');
- if (sParameterName[0] == 'q') {
- return decodeURIComponent(sParameterName[1].replace(/\+/g, '%20'));
- }
- }
-}
-
-function joinUrl (base, path) {
- if (path.substring(0, 1) === "/") {
- // path starts with `/`. Thus it is absolute.
- return path;
- }
- if (base.substring(base.length-1) === "/") {
- // base ends with `/`
- return base + path;
- }
- return base + "/" + path;
-}
-
-function formatResult (location, title, summary) {
- return '
';
-}
-
-function displayResults (results) {
- var search_results = document.getElementById("mkdocs-search-results");
- while (search_results.firstChild) {
- search_results.removeChild(search_results.firstChild);
- }
- if (results.length > 0){
- for (var i=0; i < results.length; i++){
- var result = results[i];
- var html = formatResult(result.location, result.title, result.summary);
- search_results.insertAdjacentHTML('beforeend', html);
- }
- } else {
- search_results.insertAdjacentHTML('beforeend', "
No results found
");
- }
-}
-
-function doSearch () {
- var query = document.getElementById('mkdocs-search-query').value;
- if (query.length > 2) {
- if (!window.Worker) {
- displayResults(search(query));
- } else {
- searchWorker.postMessage({query: query});
- }
- } else {
- // Clear results for short queries
- displayResults([]);
- }
-}
-
-function initSearch () {
- var search_input = document.getElementById('mkdocs-search-query');
- if (search_input) {
- search_input.addEventListener("keyup", doSearch);
- }
- var term = getSearchTermFromLocation();
- if (term) {
- search_input.value = term;
- doSearch();
- }
-}
-
-function onWorkerMessage (e) {
- if (e.data.allowSearch) {
- initSearch();
- } else if (e.data.results) {
- var results = e.data.results;
- displayResults(results);
- }
-}
-
-if (!window.Worker) {
- console.log('Web Worker API not supported');
- // load index in main thread
- $.getScript(joinUrl(base_url, "search/worker.js")).done(function () {
- console.log('Loaded worker');
- init();
- window.postMessage = function (msg) {
- onWorkerMessage({data: msg});
- };
- }).fail(function (jqxhr, settings, exception) {
- console.error('Could not load worker.js');
- });
-} else {
- // Wrap search in a web worker
- var searchWorker = new Worker(joinUrl(base_url, "search/worker.js"));
- searchWorker.postMessage({init: true});
- searchWorker.onmessage = onWorkerMessage;
-}
diff --git a/site/search/search_index.json b/site/search/search_index.json
deleted file mode 100644
index 7b39438..0000000
--- a/site/search/search_index.json
+++ /dev/null
@@ -1 +0,0 @@
-{"config":{"lang":["en"],"prebuild_index":false,"separator":"[\\s\\-]+"},"docs":[{"location":"","text":"Hello, World!!!","title":"Home"},{"location":"big_data/architecture/","text":"Architecture of Hadoop HDFS The Hadoop Distributed File System (HDFS) is a distributed file system designed to run on commodity hardware. It has many similarities with existing distributed file systems. However, the differences from other distributed file systems are significant. HDFS is highly fault-tolerant and is designed to be deployed on low-cost hardware. HDFS provides high throughput access to application data and is suitable for applications that have large data sets. HDFS is part of the Apache Hadoop Core project. 1. NameNode: is the arbitrator and central repository of file namespace in the cluster. The NameNode executes the operations such as opening, closing, and renaming files and directories. 2. DataNode: manages the storage attached to the node on which it runs. It is responsible for serving all the read and write requests. It performs operations on instructions on NameNode such as creation, deletion, and replications of blocks. 3. Client: Responsible for getting the required metadata from the namenode and then communicating with the datanodes for reads and writes. YARN YARN stands for \u201cYet Another Resource Negotiator\u201c. It was introduced in Hadoop 2.0 to remove the bottleneck on Job Tracker which was present in Hadoop 1.0. YARN was described as a \u201cRedesigned Resource Manager\u201d at the time of its launching, but it has now evolved to be known as a large-scale distributed operating system used for Big Data processing. The main components of YARN architecture include: 1. Client: It submits map-reduce jobs to the resource manager. 2. Resource Manager: It is the master daemon of YARN and is responsible for resource assignment and management among all the applications. Whenever it receives a processing request, it forwards it to the corresponding node manager and allocates resources for the completion of the request accordingly. It has two major components: 3. Scheduler: It performs scheduling based on the allocated application and available resources. It is a pure scheduler, which means that it does not perform other tasks such as monitoring or tracking and does not guarantee a restart if a task fails. The YARN scheduler supports plugins such as Capacity Scheduler and Fair Scheduler to partition the cluster resources. 4. Application manager: It is responsible for accepting the application and negotiating the first container from the resource manager. It also restarts the Application Manager container if a task fails. 5. Node Manager: It takes care of individual nodes on the Hadoop cluster and manages application and workflow and that particular node. Its primary job is to keep-up with the Node Manager. It monitors resource usage, performs log management and also kills a container based on directions from the resource manager. It is also responsible for creating the container process and starting it on the request of the Application master. 6. Application Master: An application is a single job submitted to a framework. The application manager is responsible for negotiating resources with the resource manager, tracking the status and monitoring progress of a single application. The application master requests the container from the node manager by sending a Container Launch Context(CLC) which includes everything an application needs to run. Once the application is started, it sends the health report to the resource manager from time-to-time. 7. Container: It is a collection of physical resources such as RAM, CPU cores and disk on a single node. The containers are invoked by Container Launch Context(CLC) which is a record that contains information such as environment variables, security tokens, dependencies etc. MapReduce framework 1. The term MapReduce represents two separate and distinct tasks Hadoop programs perform-Map Job and Reduce Job. Map jobs take data sets as input and process them to produce key value pairs. Reduce job takes the output of the Map job i.e. the key value pairs and aggregates them to produce desired results. 2. Hadoop MapReduce (Hadoop Map/Reduce) is a software framework for distributed processing of large data sets on computing clusters. Mapreduce helps to split the input data set into a number of parts and run a program on all data parts parallel at once. 3. Please find the below Word count example demonstrating the usage of MapReduce framework: Other tooling around hadoop Hive Uses a language called HQL which is very SQL like. Gives non-programmers the ability to query and analyze data in Hadoop. Is basically an abstraction layer on top of map-reduce. Ex. HQL query: SELECT pet.name, comment FROM pet JOIN event ON (pet.name = event.name); In mysql: SELECT pet.name, comment FROM pet, event WHERE pet.name = event.name; Pig Uses a scripting language called Pig Latin, which is more workflow driven. Don't need to be an expert Java programmer but need a few coding skills. Is also an abstraction layer on top of map-reduce. Here is a quick question for you: What is the output of running the pig queries in the right column against the data present in the left column in the below image? Output: mysql 7,Komal,Nayak,24,9848022334,trivendram 8,Bharathi,Nambiayar,24,9848022333,Chennai 5,Trupthi,Mohanthy,23,9848022336,Bhuwaneshwar 6,Archana,Mishra,23,9848022335,Chennai 3. Spark 1. Spark provides primitives for in-memory cluster computing that allows user programs to load data into a cluster\u2019s memory and query it repeatedly, making it well suited to machine learning algorithms. 4. Presto 1. Presto is a high performance, distributed SQL query engine for Big Data. 2. Its architecture allows users to query a variety of data sources such as Hadoop, AWS S3, Alluxio, MySQL, Cassandra, Kafka, and MongoDB. 3. Example presto query: mysql use studentDB; show tables; SELECT roll_no, name FROM studentDB.studentDetails where section=\u2019A\u2019 limit 5; Data Serialisation and storage In order to transport the data over the network or to store on some persistent storage, we use the process of translating data structures or objects state into binary or textual form. We call this process serialization.. Avro data is stored in a container file (a .avro file) and its schema (the .avsc file) is stored with the data file. Apache Hive provides support to store a table as Avro and can also query data in this serialisation format.","title":"Architecture of Hadoop"},{"location":"big_data/architecture/#architecture-of-hadoop","text":"HDFS The Hadoop Distributed File System (HDFS) is a distributed file system designed to run on commodity hardware. It has many similarities with existing distributed file systems. However, the differences from other distributed file systems are significant. HDFS is highly fault-tolerant and is designed to be deployed on low-cost hardware. HDFS provides high throughput access to application data and is suitable for applications that have large data sets. HDFS is part of the Apache Hadoop Core project. 1. NameNode: is the arbitrator and central repository of file namespace in the cluster. The NameNode executes the operations such as opening, closing, and renaming files and directories. 2. DataNode: manages the storage attached to the node on which it runs. It is responsible for serving all the read and write requests. It performs operations on instructions on NameNode such as creation, deletion, and replications of blocks. 3. Client: Responsible for getting the required metadata from the namenode and then communicating with the datanodes for reads and writes. YARN YARN stands for \u201cYet Another Resource Negotiator\u201c. It was introduced in Hadoop 2.0 to remove the bottleneck on Job Tracker which was present in Hadoop 1.0. YARN was described as a \u201cRedesigned Resource Manager\u201d at the time of its launching, but it has now evolved to be known as a large-scale distributed operating system used for Big Data processing. The main components of YARN architecture include: 1. Client: It submits map-reduce jobs to the resource manager. 2. Resource Manager: It is the master daemon of YARN and is responsible for resource assignment and management among all the applications. Whenever it receives a processing request, it forwards it to the corresponding node manager and allocates resources for the completion of the request accordingly. It has two major components: 3. Scheduler: It performs scheduling based on the allocated application and available resources. It is a pure scheduler, which means that it does not perform other tasks such as monitoring or tracking and does not guarantee a restart if a task fails. The YARN scheduler supports plugins such as Capacity Scheduler and Fair Scheduler to partition the cluster resources. 4. Application manager: It is responsible for accepting the application and negotiating the first container from the resource manager. It also restarts the Application Manager container if a task fails. 5. Node Manager: It takes care of individual nodes on the Hadoop cluster and manages application and workflow and that particular node. Its primary job is to keep-up with the Node Manager. It monitors resource usage, performs log management and also kills a container based on directions from the resource manager. It is also responsible for creating the container process and starting it on the request of the Application master. 6. Application Master: An application is a single job submitted to a framework. The application manager is responsible for negotiating resources with the resource manager, tracking the status and monitoring progress of a single application. The application master requests the container from the node manager by sending a Container Launch Context(CLC) which includes everything an application needs to run. Once the application is started, it sends the health report to the resource manager from time-to-time. 7. Container: It is a collection of physical resources such as RAM, CPU cores and disk on a single node. The containers are invoked by Container Launch Context(CLC) which is a record that contains information such as environment variables, security tokens, dependencies etc.","title":"Architecture of Hadoop"},{"location":"big_data/architecture/#mapreduce-framework","text":"1. The term MapReduce represents two separate and distinct tasks Hadoop programs perform-Map Job and Reduce Job. Map jobs take data sets as input and process them to produce key value pairs. Reduce job takes the output of the Map job i.e. the key value pairs and aggregates them to produce desired results. 2. Hadoop MapReduce (Hadoop Map/Reduce) is a software framework for distributed processing of large data sets on computing clusters. Mapreduce helps to split the input data set into a number of parts and run a program on all data parts parallel at once. 3. Please find the below Word count example demonstrating the usage of MapReduce framework:","title":"MapReduce framework"},{"location":"big_data/architecture/#other-tooling-around-hadoop","text":"Hive Uses a language called HQL which is very SQL like. Gives non-programmers the ability to query and analyze data in Hadoop. Is basically an abstraction layer on top of map-reduce. Ex. HQL query: SELECT pet.name, comment FROM pet JOIN event ON (pet.name = event.name); In mysql: SELECT pet.name, comment FROM pet, event WHERE pet.name = event.name; Pig Uses a scripting language called Pig Latin, which is more workflow driven. Don't need to be an expert Java programmer but need a few coding skills. Is also an abstraction layer on top of map-reduce. Here is a quick question for you: What is the output of running the pig queries in the right column against the data present in the left column in the below image? Output: mysql 7,Komal,Nayak,24,9848022334,trivendram 8,Bharathi,Nambiayar,24,9848022333,Chennai 5,Trupthi,Mohanthy,23,9848022336,Bhuwaneshwar 6,Archana,Mishra,23,9848022335,Chennai 3. Spark 1. Spark provides primitives for in-memory cluster computing that allows user programs to load data into a cluster\u2019s memory and query it repeatedly, making it well suited to machine learning algorithms. 4. Presto 1. Presto is a high performance, distributed SQL query engine for Big Data. 2. Its architecture allows users to query a variety of data sources such as Hadoop, AWS S3, Alluxio, MySQL, Cassandra, Kafka, and MongoDB. 3. Example presto query: mysql use studentDB; show tables; SELECT roll_no, name FROM studentDB.studentDetails where section=\u2019A\u2019 limit 5;","title":"Other tooling around hadoop"},{"location":"big_data/architecture/#data-serialisation-and-storage","text":"In order to transport the data over the network or to store on some persistent storage, we use the process of translating data structures or objects state into binary or textual form. We call this process serialization.. Avro data is stored in a container file (a .avro file) and its schema (the .avsc file) is stored with the data file. Apache Hive provides support to store a table as Avro and can also query data in this serialisation format.","title":"Data Serialisation and storage"},{"location":"big_data/evolution/","text":"Evolution of Hadoop","title":"Evolution of Hadoop"},{"location":"big_data/evolution/#evolution-of-hadoop","text":"","title":"Evolution of Hadoop"},{"location":"big_data/intro/","text":"School of SRE: Big Data Pre - Reads Basics of Linux File systems. Basic understanding of System Design. Target Audience The concept of Big Data has been around for years; most organizations now understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value from it. This training material covers the basics of Big Data(using Hadoop) for beginners, who would like to quickly get started and get their hands dirty in this domain. What to expect from this training This course covers the basics of Big Data and how it has evolved to become what it is today. We will take a look at a few realistic scenarios where Big Data would be a perfect fit. An interesting assignment on designing a Big Data system is followed by understanding the architecture of Hadoop and the tooling around it. What is not covered under this training Writing programs to draw analytics from data. TOC: Overview of Big Data Usage of Big Data techniques Evolution of Hadoop Architecture of hadoop HDFS Yarn MapReduce framework Other tooling around hadoop Hive Pig Spark Presto Data Serialisation and storage","title":"Intro"},{"location":"big_data/intro/#school-of-sre-big-data","text":"","title":"School of SRE: Big Data"},{"location":"big_data/intro/#pre-reads","text":"Basics of Linux File systems. Basic understanding of System Design.","title":"Pre - Reads"},{"location":"big_data/intro/#target-audience","text":"The concept of Big Data has been around for years; most organizations now understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value from it. This training material covers the basics of Big Data(using Hadoop) for beginners, who would like to quickly get started and get their hands dirty in this domain.","title":"Target Audience"},{"location":"big_data/intro/#what-to-expect-from-this-training","text":"This course covers the basics of Big Data and how it has evolved to become what it is today. We will take a look at a few realistic scenarios where Big Data would be a perfect fit. An interesting assignment on designing a Big Data system is followed by understanding the architecture of Hadoop and the tooling around it.","title":"What to expect from this training"},{"location":"big_data/intro/#what-is-not-covered-under-this-training","text":"Writing programs to draw analytics from data.","title":"What is not covered under this training"},{"location":"big_data/intro/#toc","text":"Overview of Big Data Usage of Big Data techniques Evolution of Hadoop Architecture of hadoop HDFS Yarn MapReduce framework Other tooling around hadoop Hive Pig Spark Presto Data Serialisation and storage","title":"TOC:"},{"location":"big_data/overview/","text":"Overview of Big Data Big Data is a collection of large datasets that cannot be processed using traditional computing techniques. It is not a single technique or a tool, rather it has become a complete subject, which involves various tools, techniques and frameworks. Big Data could consist of Structured data Unstructured data Semi-structured data Characteristics of Big Data: Volume Variety Velocity Variability Examples of Big Data generation include stock exchanges, social media sites, jet engines, etc.","title":"Overview of Big Data"},{"location":"big_data/overview/#overview-of-big-data","text":"Big Data is a collection of large datasets that cannot be processed using traditional computing techniques. It is not a single technique or a tool, rather it has become a complete subject, which involves various tools, techniques and frameworks. Big Data could consist of Structured data Unstructured data Semi-structured data Characteristics of Big Data: Volume Variety Velocity Variability Examples of Big Data generation include stock exchanges, social media sites, jet engines, etc.","title":"Overview of Big Data"},{"location":"big_data/tasks/","text":"Tasks and conclusion Post training tasks: Try setting up your own 3 node hadoop cluster. A VM based solution can be found here Write a simple spark/MR job of your choice and understand how to generate analytics from data. Sample dataset can be found here References: Hadoop documentation HDFS Architecture YARN Architecture Google GFS paper","title":"Tasks and conclusion"},{"location":"big_data/tasks/#tasks-and-conclusion","text":"","title":"Tasks and conclusion"},{"location":"big_data/tasks/#post-training-tasks","text":"Try setting up your own 3 node hadoop cluster. A VM based solution can be found here Write a simple spark/MR job of your choice and understand how to generate analytics from data. Sample dataset can be found here","title":"Post training tasks:"},{"location":"big_data/tasks/#references","text":"Hadoop documentation HDFS Architecture YARN Architecture Google GFS paper","title":"References:"},{"location":"big_data/usage/","text":"Usage of Big Data techniques Take the example of the traffic lights problem. There are more than 300,000 traffic lights in the US as of 2018. Let us assume that we placed a device on each of them to collect metrics and send it to a central metrics collection system. If each of the IOT devices sends 10 events per minute, we have 300000x10x60x24 = 432x10^7 events per day. How would you go about processing that and telling me how many of the signals were \u201cgreen\u201d at 10:45 am on a particular day? Consider the next example on Unified Payments Interface (UPI) transactions: We had about 1.15 billion UPI transactions in the month of October, 2019 in India. If we try to extrapolate this data to about a year and try to find out some common payments that were happening through a particular UPI ID, how do you suggest we go about that?","title":"Usage of Big Data techniques"},{"location":"big_data/usage/#usage-of-big-data-techniques","text":"Take the example of the traffic lights problem. There are more than 300,000 traffic lights in the US as of 2018. Let us assume that we placed a device on each of them to collect metrics and send it to a central metrics collection system. If each of the IOT devices sends 10 events per minute, we have 300000x10x60x24 = 432x10^7 events per day. How would you go about processing that and telling me how many of the signals were \u201cgreen\u201d at 10:45 am on a particular day? Consider the next example on Unified Payments Interface (UPI) transactions: We had about 1.15 billion UPI transactions in the month of October, 2019 in India. If we try to extrapolate this data to about a year and try to find out some common payments that were happening through a particular UPI ID, how do you suggest we go about that?","title":"Usage of Big Data techniques"},{"location":"git/branches/","text":"Working With Branches Coming back to our local repo which has two commits. So far, what we have is a single line of history. Commits are chained in a single line. But sometimes you may have a need to work on two different features in parallel in the same repo. Now one option here could be making a new folder/repo with the same code and use that for another feature development. But there's a better way. Use branches. Since git follows tree like structure for commits, we can use branches to work on different sets of features. From a commit, two or more branches can be created and branches can also be merged. Using branches, there can exist multiple lines of histories and we can checkout to any of them and work on it. Checking out, as we discussed earlier, would simply mean replacing contents of the directory (repo) with contents snapshot at the checked out version. Let's create a branch and see how it looks like: spatel1-mn1:school-of-sre spatel1$ git branch b1 spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 7f3b00e (HEAD - master, b1) adding file 2 * df2fb7a adding file 1 We create a branch called b1 . Git log tells us that b1 also points to the last commit (7f3b00e) but the HEAD is still pointing to master. If you remember, HEAD points to the commit/reference wherever you are checkout to. So if we checkout to b1 , HEAD should point to that. Let's confirm: spatel1-mn1:school-of-sre spatel1$ git checkout b1 Switched to branch 'b1' spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 7f3b00e (HEAD - b1, master) adding file 2 * df2fb7a adding file 1 b1 still points to the same commit but HEAD now points to b1 . Since we create a branch at commit 7f3b00e , there will be two lines of histories starting this commit. Depending on which branch you are checked out on, the line of history will progress. At this moment, we are checked out on branch b1 , so making a new commit will advance branch reference b1 to that commit and current b1 commit will become its parent. Let's do that. # Creating a file and making a commit spatel1-mn1:school-of-sre spatel1$ echo I am a file in b1 branch b1.txt spatel1-mn1:school-of-sre spatel1$ git add b1.txt spatel1-mn1:school-of-sre spatel1$ git commit -m adding b1 file [b1 872a38f] adding b1 file 1 file changed, 1 insertion(+) create mode 100644 b1.txt # The new line of history spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 872a38f (HEAD - b1) adding b1 file * 7f3b00e (master) adding file 2 * df2fb7a adding file 1 spatel1-mn1:school-of-sre spatel1$ Do note that master is still pointing to the old commit it was pointing to. We can now checkout to master branch and make commits there. This will result in another line of history starting from commit 7f3b00e. # checkout to master branch spatel1-mn1:school-of-sre spatel1$ git checkout master Switched to branch 'master' # Creating a new commit on master branch spatel1-mn1:school-of-sre spatel1$ echo new file in master branch master.txt spatel1-mn1:school-of-sre spatel1$ git add master.txt spatel1-mn1:school-of-sre spatel1$ git commit -m adding master.txt file [master 60dc441] adding master.txt file 1 file changed, 1 insertion(+) create mode 100644 master.txt # The history line spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 60dc441 (HEAD - master) adding master.txt file * 7f3b00e adding file 2 * df2fb7a adding file 1 Notice how branch b1 is not visible here since we are checkout on master. Let's try to visualize both to get the whole picture: spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 60dc441 (HEAD - master) adding master.txt file | * 872a38f (b1) adding b1 file |/ * 7f3b00e adding file 2 * df2fb7a adding file 1 Above tree structure should make things clear. Notice a clear branch/fork on commit 7f3b00e. This is how we create branches. Now they both are two separate lines of history on which feature development can be done independently. To reiterate, internally, git is just a tree of commits. Branch names (human readable) are pointers to those commits in the tree. We use various git commands to work with the tree structure and references. Git accordingly modifies contents of our repo. Merges Now say the feature you were working on branch b1 is complete. And you need to merge it on master branch, where all the final version of code goes. So first you will checkout to branch master and then you will pull the latest code from upstream (eg: GitHub). Then you need to merge your code from b1 into master. And there could be two ways this can be done. Here is the current history: spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 60dc441 (HEAD - master) adding master.txt file | * 872a38f (b1) adding b1 file |/ * 7f3b00e adding file 2 * df2fb7a adding file 1 Option 1: Directly merge the branch. Merging the branch b1 into master will result in a new merge commit which will merge changes from two different lines of history and create a new commit of the result. spatel1-mn1:school-of-sre spatel1$ git merge b1 Merge made by the 'recursive' strategy. b1.txt | 1 + 1 file changed, 1 insertion(+) create mode 100644 b1.txt spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 8fc28f9 (HEAD - master) Merge branch 'b1' |\\ | * 872a38f (b1) adding b1 file * | 60dc441 adding master.txt file |/ * 7f3b00e adding file 2 * df2fb7a adding file 1 You can see a new merge commit created (8fc28f9). You will be prompted for the commit message. If there are a lot of branches in the repo, this result will end-up with a lot of merge commits. Which looks ugly compared to a single line of history of development. So let's look at an alternative approach First let's reset our last merge and go to the previous state. spatel1-mn1:school-of-sre spatel1$ git reset --hard 60dc441 HEAD is now at 60dc441 adding master.txt file spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 60dc441 (HEAD - master) adding master.txt file | * 872a38f (b1) adding b1 file |/ * 7f3b00e adding file 2 * df2fb7a adding file 1 Option 2: Rebase. Now, instead of merging two branches which has a similar base (commit: 7f3b00e), let us rebase branch b1 on to current master. What this means is take branch b1 (from commit 7f3b00e to commit 872a38f) and rebase (put them on top of) master (60dc441). # Switch to b1 spatel1-mn1:school-of-sre spatel1$ git checkout b1 Switched to branch 'b1' # Rebase (b1 which is current branch) on master spatel1-mn1:school-of-sre spatel1$ git rebase master First, rewinding head to replay your work on top of it... Applying: adding b1 file # The result spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 5372c8f (HEAD - b1) adding b1 file * 60dc441 (master) adding master.txt file * 7f3b00e adding file 2 * df2fb7a adding file 1 You can see b1 which had 1 commit. That commit's parent was 7f3b00e . But since we rebase it on master ( 60dc441 ). That becomes the parent now. As a side effect, you also see it has become a single line of history. Now if we were to merge b1 into master , it would simply mean change master to point to 5372c8f which is b1 . Let's try it: # checkout to master since we want to merge code into master spatel1-mn1:school-of-sre spatel1$ git checkout master Switched to branch 'master' # the current history, where b1 is based on master spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 5372c8f (b1) adding b1 file * 60dc441 (HEAD - master) adding master.txt file * 7f3b00e adding file 2 * df2fb7a adding file 1 # Performing the merge, notice the fast-forward message spatel1-mn1:school-of-sre spatel1$ git merge b1 Updating 60dc441..5372c8f Fast-forward b1.txt | 1 + 1 file changed, 1 insertion(+) create mode 100644 b1.txt # The Result spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 5372c8f (HEAD - master, b1) adding b1 file * 60dc441 adding master.txt file * 7f3b00e adding file 2 * df2fb7a adding file 1 Now you see both b1 and master are pointing to the same commit. Your code has been merged to the master branch and it can be pushed. Also we have clean line of history! :D","title":"Working With Branches"},{"location":"git/branches/#working-with-branches","text":"Coming back to our local repo which has two commits. So far, what we have is a single line of history. Commits are chained in a single line. But sometimes you may have a need to work on two different features in parallel in the same repo. Now one option here could be making a new folder/repo with the same code and use that for another feature development. But there's a better way. Use branches. Since git follows tree like structure for commits, we can use branches to work on different sets of features. From a commit, two or more branches can be created and branches can also be merged. Using branches, there can exist multiple lines of histories and we can checkout to any of them and work on it. Checking out, as we discussed earlier, would simply mean replacing contents of the directory (repo) with contents snapshot at the checked out version. Let's create a branch and see how it looks like: spatel1-mn1:school-of-sre spatel1$ git branch b1 spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 7f3b00e (HEAD - master, b1) adding file 2 * df2fb7a adding file 1 We create a branch called b1 . Git log tells us that b1 also points to the last commit (7f3b00e) but the HEAD is still pointing to master. If you remember, HEAD points to the commit/reference wherever you are checkout to. So if we checkout to b1 , HEAD should point to that. Let's confirm: spatel1-mn1:school-of-sre spatel1$ git checkout b1 Switched to branch 'b1' spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 7f3b00e (HEAD - b1, master) adding file 2 * df2fb7a adding file 1 b1 still points to the same commit but HEAD now points to b1 . Since we create a branch at commit 7f3b00e , there will be two lines of histories starting this commit. Depending on which branch you are checked out on, the line of history will progress. At this moment, we are checked out on branch b1 , so making a new commit will advance branch reference b1 to that commit and current b1 commit will become its parent. Let's do that. # Creating a file and making a commit spatel1-mn1:school-of-sre spatel1$ echo I am a file in b1 branch b1.txt spatel1-mn1:school-of-sre spatel1$ git add b1.txt spatel1-mn1:school-of-sre spatel1$ git commit -m adding b1 file [b1 872a38f] adding b1 file 1 file changed, 1 insertion(+) create mode 100644 b1.txt # The new line of history spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 872a38f (HEAD - b1) adding b1 file * 7f3b00e (master) adding file 2 * df2fb7a adding file 1 spatel1-mn1:school-of-sre spatel1$ Do note that master is still pointing to the old commit it was pointing to. We can now checkout to master branch and make commits there. This will result in another line of history starting from commit 7f3b00e. # checkout to master branch spatel1-mn1:school-of-sre spatel1$ git checkout master Switched to branch 'master' # Creating a new commit on master branch spatel1-mn1:school-of-sre spatel1$ echo new file in master branch master.txt spatel1-mn1:school-of-sre spatel1$ git add master.txt spatel1-mn1:school-of-sre spatel1$ git commit -m adding master.txt file [master 60dc441] adding master.txt file 1 file changed, 1 insertion(+) create mode 100644 master.txt # The history line spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 60dc441 (HEAD - master) adding master.txt file * 7f3b00e adding file 2 * df2fb7a adding file 1 Notice how branch b1 is not visible here since we are checkout on master. Let's try to visualize both to get the whole picture: spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 60dc441 (HEAD - master) adding master.txt file | * 872a38f (b1) adding b1 file |/ * 7f3b00e adding file 2 * df2fb7a adding file 1 Above tree structure should make things clear. Notice a clear branch/fork on commit 7f3b00e. This is how we create branches. Now they both are two separate lines of history on which feature development can be done independently. To reiterate, internally, git is just a tree of commits. Branch names (human readable) are pointers to those commits in the tree. We use various git commands to work with the tree structure and references. Git accordingly modifies contents of our repo.","title":"Working With Branches"},{"location":"git/branches/#merges","text":"Now say the feature you were working on branch b1 is complete. And you need to merge it on master branch, where all the final version of code goes. So first you will checkout to branch master and then you will pull the latest code from upstream (eg: GitHub). Then you need to merge your code from b1 into master. And there could be two ways this can be done. Here is the current history: spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 60dc441 (HEAD - master) adding master.txt file | * 872a38f (b1) adding b1 file |/ * 7f3b00e adding file 2 * df2fb7a adding file 1 Option 1: Directly merge the branch. Merging the branch b1 into master will result in a new merge commit which will merge changes from two different lines of history and create a new commit of the result. spatel1-mn1:school-of-sre spatel1$ git merge b1 Merge made by the 'recursive' strategy. b1.txt | 1 + 1 file changed, 1 insertion(+) create mode 100644 b1.txt spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 8fc28f9 (HEAD - master) Merge branch 'b1' |\\ | * 872a38f (b1) adding b1 file * | 60dc441 adding master.txt file |/ * 7f3b00e adding file 2 * df2fb7a adding file 1 You can see a new merge commit created (8fc28f9). You will be prompted for the commit message. If there are a lot of branches in the repo, this result will end-up with a lot of merge commits. Which looks ugly compared to a single line of history of development. So let's look at an alternative approach First let's reset our last merge and go to the previous state. spatel1-mn1:school-of-sre spatel1$ git reset --hard 60dc441 HEAD is now at 60dc441 adding master.txt file spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 60dc441 (HEAD - master) adding master.txt file | * 872a38f (b1) adding b1 file |/ * 7f3b00e adding file 2 * df2fb7a adding file 1 Option 2: Rebase. Now, instead of merging two branches which has a similar base (commit: 7f3b00e), let us rebase branch b1 on to current master. What this means is take branch b1 (from commit 7f3b00e to commit 872a38f) and rebase (put them on top of) master (60dc441). # Switch to b1 spatel1-mn1:school-of-sre spatel1$ git checkout b1 Switched to branch 'b1' # Rebase (b1 which is current branch) on master spatel1-mn1:school-of-sre spatel1$ git rebase master First, rewinding head to replay your work on top of it... Applying: adding b1 file # The result spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 5372c8f (HEAD - b1) adding b1 file * 60dc441 (master) adding master.txt file * 7f3b00e adding file 2 * df2fb7a adding file 1 You can see b1 which had 1 commit. That commit's parent was 7f3b00e . But since we rebase it on master ( 60dc441 ). That becomes the parent now. As a side effect, you also see it has become a single line of history. Now if we were to merge b1 into master , it would simply mean change master to point to 5372c8f which is b1 . Let's try it: # checkout to master since we want to merge code into master spatel1-mn1:school-of-sre spatel1$ git checkout master Switched to branch 'master' # the current history, where b1 is based on master spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 5372c8f (b1) adding b1 file * 60dc441 (HEAD - master) adding master.txt file * 7f3b00e adding file 2 * df2fb7a adding file 1 # Performing the merge, notice the fast-forward message spatel1-mn1:school-of-sre spatel1$ git merge b1 Updating 60dc441..5372c8f Fast-forward b1.txt | 1 + 1 file changed, 1 insertion(+) create mode 100644 b1.txt # The Result spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph --all * 5372c8f (HEAD - master, b1) adding b1 file * 60dc441 adding master.txt file * 7f3b00e adding file 2 * df2fb7a adding file 1 Now you see both b1 and master are pointing to the same commit. Your code has been merged to the master branch and it can be pushed. Also we have clean line of history! :D","title":"Merges"},{"location":"git/git-basics/","text":"School Of SRE: Git Pre - Reads Have Git installed https://git-scm.com/downloads Have taken any git high level tutorial or following LinkedIn learning courses https://www.linkedin.com/learning/git-essential-training-the-basics/ https://www.linkedin.com/learning/git-branches-merges-and-remotes/ The Official Git Docs What to expect from this training As an engineer in the field of computer science, having knowledge of version control tools becomes almost a requirement. While there are a lot of version control tools that exist today, Git perhaps is the most used one and this course we will be working with Git. While this course does not start with Git 101 and expects basic knowledge of git as a prerequisite, it will reintroduce the git concepts known by you with details covering what is happening under the hood as you execute various git commands. So that next time you run a git command, you will be able to press enter more confidently! What is not covered under this training Advanced usage and specifics of internal implementation details of Git. Training Content Table of Contents Git Basics Working with Branches Git with Github Hooks Git Basics Though you might be aware already, let's revisit why we need a version control system. As the project grows and multiple developers start working on it, an efficient method for collaboration is warranted. Git helps the team collaborate easily and also maintains history of the changes happened with the codebase. Creating a Git Repo Any folder can be converted into a git repository. After executing the following command, we will see a .git folder within the folder, which makes our folder a git repository. All the magic that git does, .git folder is the enabler for the same. # creating an empty folder and changing current dir to it spatel1-mn1:~ spatel1$ cd /tmp spatel1-mn1:tmp spatel1$ mkdir school-of-sre spatel1-mn1:tmp spatel1$ cd school-of-sre/ # initialize a git repo spatel1-mn1:school-of-sre spatel1$ git init Initialized empty Git repository in /private/tmp/school-of-sre/.git/ As the output says, an empty git repo has been initialized in our folder. Let's take a look at what is there. spatel1-mn1:school-of-sre spatel1$ ls .git/ HEAD config description hooks info objects refs There are a bunch of folders and files in the .git folder. As I said, all these enables git to do its magic. We will look into some of these folders and files. But for now, what we have is an empty git repository. Tracking a File Now as you might already know, let us create a new file in our repo (we will refer to the folder as repo now.) And see git status spatel1-mn1:school-of-sre spatel1$ echo I am file 1 file1.txt spatel1-mn1:school-of-sre spatel1$ git status On branch master No commits yet Untracked files: (use git add file ... to include in what will be committed) file1.txt nothing added to commit but untracked files present (use git add to track) The current git status says No commits yet and there is one untracked file. Since we just created the file, git is not tracking that file. We explicitly need to ask git to track files and folders. (also checkout gitignore ) And how we do that is via git add command as suggested in the above output. Then we go ahead and create a commit. spatel1-mn1:school-of-sre spatel1$ git add file1.txt spatel1-mn1:school-of-sre spatel1$ git status On branch master No commits yet Changes to be committed: (use git rm --cached file ... to unstage) new file: file1.txt spatel1-mn1:school-of-sre spatel1$ git commit -m adding file 1 [master (root-commit) df2fb7a] adding file 1 1 file changed, 1 insertion(+) create mode 100644 file1.txt Notice how after adding the file, git status says Changes to be commited: . What it means is whatever is listed there, will be included in the next commit. Then we go ahead and create a commit, with an attached messaged via -m . More About a Commit Commit is a snapshot of the repo. Whenever a commit is made, a snapshot of the current state of repo (the folder) is taken and saved. Each commit has a unique ID. ( df2fb7a for the commit we made in the previous step). As we keep adding/changing more and more contents and keep making commits, all those snapshots are stored by git. Again, all this magic happens inside the .git folder. This is where all this snapshot or versions are stored. In an efficient manner. Adding More Changes Let us create one more file and commit the change. It would look the same as the previous commit we made. spatel1-mn1:school-of-sre spatel1$ echo I am file 2 file2.txt spatel1-mn1:school-of-sre spatel1$ git add file2.txt spatel1-mn1:school-of-sre spatel1$ git commit -m adding file 2 [master 7f3b00e] adding file 2 1 file changed, 1 insertion(+) create mode 100644 file2.txt A new commit with ID 7f3b00e has been created. You can issue git status at any time to see the state of the repository. **IMPORTANT: Note that commit IDs are long string (SHA) but we can refer to a commit by its initial few (8 or more) characters too. We will interchangeably using shorter and longer commit IDs.** Now that we have two commits, let's visualize them: spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 7f3b00e (HEAD - master) adding file 2 * df2fb7a adding file 1 git log , as the name suggests, prints the log of all the git commits. Here you see two additional arguments, --oneline prints the shorter version of the log, ie: the commit message only and not the person who made the commit and when. --graph prints it in graph format. Now at this moment the commits might look like just one in each line but all commits are stored as a tree like data structure internally by git. That means there can be two or more children commits of a given commit. And not just a single line of commits. We will look more into this part when we get to the Branches section. For now this is our commit history: df2fb7a === 7f3b00e Are commits really linked? As I just said, the two commits we just made are linked via tree like data structure and we saw how they are linked. But let's actually verify it. Everything in git is an object. Newly created files are stored as an object. Changes to file are stored as an objects and even commits are objects. To view contents of an object we can use the following command with the object's ID. We will take a look at content of the contents of the second commit spatel1-mn1:school-of-sre spatel1$ git cat-file -p 7f3b00e tree ebf3af44d253e5328340026e45a9fa9ae3ea1982 parent df2fb7a61f5d40c1191e0fdeb0fc5d6e7969685a author Sanket Patel spatel1@linkedin.com 1603273316 -0700 committer Sanket Patel spatel1@linkedin.com 1603273316 -0700 adding file 2 Take a note of parent attribute in the above output. It points to the commit id of the first commit we made. So this proves that they are linked! Additionally you can see the second commit's message in this object. As I said all this magic is enabled by .git folder and the object to which we are looking at also is in that folder. spatel1-mn1:school-of-sre spatel1$ ls .git/objects/7f/3b00eaa957815884198e2fdfec29361108d6a9 .git/objects/7f/3b00eaa957815884198e2fdfec29361108d6a9 It is stored in .git/objects/ folder. All the files and changes to them as well are stored in this folder. The Version Control part of Git We already can see two commits (versions) in our git log. One thing a version control tool gives you is ability to browse back and forth in history. For example: some of your users are running an old version of code and they are reporting an issue. In order to debug the issue, you need access to the old code. The one in your current repo is the latest code. In this example, you are working on the second commit (7f3b00e) and someone reported an issue with the code snapshot at commit (df2fb7a). This is how you would get access to the code at any older commit # Current contents, two files present patel1-mn1:school-of-sre spatel1$ ls file1.txt file2.txt # checking out to (an older) commit spatel1-mn1:school-of-sre spatel1$ git checkout df2fb7a Note: checking out 'df2fb7a'. You are in 'detached HEAD' state. You can look around, make experimental changes and commit them, and you can discard any commits you make in this state without impacting any branches by performing another checkout. If you want to create a new branch to retain commits you create, you may do so (now or later) by using -b with the checkout command again. Example: git checkout -b new-branch-name HEAD is now at df2fb7a adding file 1 # checking contents, can verify it has old contents spatel1-mn1:school-of-sre spatel1$ ls file1.txt So this is how we would get access to old versions/snapshots. All we need is a reference to that snapshot. Upon executing git checkout ... , what git does for you is use the .git folder, see what was the state of things (files and folders) at that version/reference and replace the contents of current directory with those contents. The then-existing content will no longer be present in the local dir (repo) but we can and will still get access to them because they are tracked via git commit and .git folder has them stored/tracked. Reference I mention in the previous section that we need a reference to the version. By default, git repo is made of tree of commits. And each commit has a unique IDs. But the unique ID is not the only thing we can reference commits via. There are multiple ways to reference commits. For example: HEAD is a reference to current commit. Whatever commit your repo is checked out at, HEAD will point to that. HEAD~1 is reference to previous commit. So while checking out previous version in section above, we could have done git checkout HEAD~1 . Similarly, master is also a reference (to a branch). Since git uses tree like structure to store commits, there of course will be branches. And the default branch is called master . Master (or any branch reference) will point to the latest commit in the branch. Even though we have checked out to the previous commit in out repo, master still points to the latest commit. And we can get back to the latest version by checkout at master reference spatel1-mn1:school-of-sre spatel1$ git checkout master Previous HEAD position was df2fb7a adding file 1 Switched to branch 'master' # now we will see latest code, with two files spatel1-mn1:school-of-sre spatel1$ ls file1.txt file2.txt Note, instead of master in above command, we could have used commit's ID as well. References and The Magic Let's look at the state of things. Two commits, master and HEAD references are pointing to the latest commit spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 7f3b00e (HEAD - master) adding file 2 * df2fb7a adding file 1 The magic? Let's examine these files: spatel1-mn1:school-of-sre spatel1$ cat .git/refs/heads/master 7f3b00eaa957815884198e2fdfec29361108d6a9 Viola! Where master is pointing to is stored in a file. Whenever git needs to know where master reference is pointing to, or if git needs to update where master points, it just needs to update the file above. So when you create a new commit, a new commit is created on top of the current commit and the master file is updated with the new commit's ID. Similary, for HEAD reference: spatel1-mn1:school-of-sre spatel1$ cat .git/HEAD ref: refs/heads/master We can see HEAD is pointing to a reference called refs/heads/master . So HEAD will point where ever the master points. Little Adventure We discussed how git will update the files as we execute commands. But let's try to do it ourselves, by hand, and see what happens. spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 7f3b00e (HEAD - master) adding file 2 * df2fb7a adding file 1 Now let's change master to point to the previous/first commit. spatel1-mn1:school-of-sre spatel1$ echo df2fb7a61f5d40c1191e0fdeb0fc5d6e7969685a .git/refs/heads/master spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * df2fb7a (HEAD - master) adding file 1 # RESETTING TO ORIGINAL spatel1-mn1:school-of-sre spatel1$ echo 7f3b00eaa957815884198e2fdfec29361108d6a9 .git/refs/heads/master spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 7f3b00e (HEAD - master) adding file 2 * df2fb7a adding file 1 We just edited the master reference file and now we can see only the first commit in git log. Undoing the change to the file brings the state back to original. Not so much of magic, isn't it?","title":"Git Basics"},{"location":"git/git-basics/#school-of-sre-git","text":"","title":"School Of SRE: Git"},{"location":"git/git-basics/#pre-reads","text":"Have Git installed https://git-scm.com/downloads Have taken any git high level tutorial or following LinkedIn learning courses https://www.linkedin.com/learning/git-essential-training-the-basics/ https://www.linkedin.com/learning/git-branches-merges-and-remotes/ The Official Git Docs","title":"Pre - Reads"},{"location":"git/git-basics/#what-to-expect-from-this-training","text":"As an engineer in the field of computer science, having knowledge of version control tools becomes almost a requirement. While there are a lot of version control tools that exist today, Git perhaps is the most used one and this course we will be working with Git. While this course does not start with Git 101 and expects basic knowledge of git as a prerequisite, it will reintroduce the git concepts known by you with details covering what is happening under the hood as you execute various git commands. So that next time you run a git command, you will be able to press enter more confidently!","title":"What to expect from this training"},{"location":"git/git-basics/#what-is-not-covered-under-this-training","text":"Advanced usage and specifics of internal implementation details of Git.","title":"What is not covered under this training"},{"location":"git/git-basics/#training-content","text":"","title":"Training Content"},{"location":"git/git-basics/#table-of-contents","text":"Git Basics Working with Branches Git with Github Hooks","title":"Table of Contents"},{"location":"git/git-basics/#git-basics","text":"Though you might be aware already, let's revisit why we need a version control system. As the project grows and multiple developers start working on it, an efficient method for collaboration is warranted. Git helps the team collaborate easily and also maintains history of the changes happened with the codebase.","title":"Git Basics"},{"location":"git/git-basics/#creating-a-git-repo","text":"Any folder can be converted into a git repository. After executing the following command, we will see a .git folder within the folder, which makes our folder a git repository. All the magic that git does, .git folder is the enabler for the same. # creating an empty folder and changing current dir to it spatel1-mn1:~ spatel1$ cd /tmp spatel1-mn1:tmp spatel1$ mkdir school-of-sre spatel1-mn1:tmp spatel1$ cd school-of-sre/ # initialize a git repo spatel1-mn1:school-of-sre spatel1$ git init Initialized empty Git repository in /private/tmp/school-of-sre/.git/ As the output says, an empty git repo has been initialized in our folder. Let's take a look at what is there. spatel1-mn1:school-of-sre spatel1$ ls .git/ HEAD config description hooks info objects refs There are a bunch of folders and files in the .git folder. As I said, all these enables git to do its magic. We will look into some of these folders and files. But for now, what we have is an empty git repository.","title":"Creating a Git Repo"},{"location":"git/git-basics/#tracking-a-file","text":"Now as you might already know, let us create a new file in our repo (we will refer to the folder as repo now.) And see git status spatel1-mn1:school-of-sre spatel1$ echo I am file 1 file1.txt spatel1-mn1:school-of-sre spatel1$ git status On branch master No commits yet Untracked files: (use git add file ... to include in what will be committed) file1.txt nothing added to commit but untracked files present (use git add to track) The current git status says No commits yet and there is one untracked file. Since we just created the file, git is not tracking that file. We explicitly need to ask git to track files and folders. (also checkout gitignore ) And how we do that is via git add command as suggested in the above output. Then we go ahead and create a commit. spatel1-mn1:school-of-sre spatel1$ git add file1.txt spatel1-mn1:school-of-sre spatel1$ git status On branch master No commits yet Changes to be committed: (use git rm --cached file ... to unstage) new file: file1.txt spatel1-mn1:school-of-sre spatel1$ git commit -m adding file 1 [master (root-commit) df2fb7a] adding file 1 1 file changed, 1 insertion(+) create mode 100644 file1.txt Notice how after adding the file, git status says Changes to be commited: . What it means is whatever is listed there, will be included in the next commit. Then we go ahead and create a commit, with an attached messaged via -m .","title":"Tracking a File"},{"location":"git/git-basics/#more-about-a-commit","text":"Commit is a snapshot of the repo. Whenever a commit is made, a snapshot of the current state of repo (the folder) is taken and saved. Each commit has a unique ID. ( df2fb7a for the commit we made in the previous step). As we keep adding/changing more and more contents and keep making commits, all those snapshots are stored by git. Again, all this magic happens inside the .git folder. This is where all this snapshot or versions are stored. In an efficient manner.","title":"More About a Commit"},{"location":"git/git-basics/#adding-more-changes","text":"Let us create one more file and commit the change. It would look the same as the previous commit we made. spatel1-mn1:school-of-sre spatel1$ echo I am file 2 file2.txt spatel1-mn1:school-of-sre spatel1$ git add file2.txt spatel1-mn1:school-of-sre spatel1$ git commit -m adding file 2 [master 7f3b00e] adding file 2 1 file changed, 1 insertion(+) create mode 100644 file2.txt A new commit with ID 7f3b00e has been created. You can issue git status at any time to see the state of the repository. **IMPORTANT: Note that commit IDs are long string (SHA) but we can refer to a commit by its initial few (8 or more) characters too. We will interchangeably using shorter and longer commit IDs.** Now that we have two commits, let's visualize them: spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 7f3b00e (HEAD - master) adding file 2 * df2fb7a adding file 1 git log , as the name suggests, prints the log of all the git commits. Here you see two additional arguments, --oneline prints the shorter version of the log, ie: the commit message only and not the person who made the commit and when. --graph prints it in graph format. Now at this moment the commits might look like just one in each line but all commits are stored as a tree like data structure internally by git. That means there can be two or more children commits of a given commit. And not just a single line of commits. We will look more into this part when we get to the Branches section. For now this is our commit history: df2fb7a === 7f3b00e","title":"Adding More Changes"},{"location":"git/git-basics/#are-commits-really-linked","text":"As I just said, the two commits we just made are linked via tree like data structure and we saw how they are linked. But let's actually verify it. Everything in git is an object. Newly created files are stored as an object. Changes to file are stored as an objects and even commits are objects. To view contents of an object we can use the following command with the object's ID. We will take a look at content of the contents of the second commit spatel1-mn1:school-of-sre spatel1$ git cat-file -p 7f3b00e tree ebf3af44d253e5328340026e45a9fa9ae3ea1982 parent df2fb7a61f5d40c1191e0fdeb0fc5d6e7969685a author Sanket Patel spatel1@linkedin.com 1603273316 -0700 committer Sanket Patel spatel1@linkedin.com 1603273316 -0700 adding file 2 Take a note of parent attribute in the above output. It points to the commit id of the first commit we made. So this proves that they are linked! Additionally you can see the second commit's message in this object. As I said all this magic is enabled by .git folder and the object to which we are looking at also is in that folder. spatel1-mn1:school-of-sre spatel1$ ls .git/objects/7f/3b00eaa957815884198e2fdfec29361108d6a9 .git/objects/7f/3b00eaa957815884198e2fdfec29361108d6a9 It is stored in .git/objects/ folder. All the files and changes to them as well are stored in this folder.","title":"Are commits really linked?"},{"location":"git/git-basics/#the-version-control-part-of-git","text":"We already can see two commits (versions) in our git log. One thing a version control tool gives you is ability to browse back and forth in history. For example: some of your users are running an old version of code and they are reporting an issue. In order to debug the issue, you need access to the old code. The one in your current repo is the latest code. In this example, you are working on the second commit (7f3b00e) and someone reported an issue with the code snapshot at commit (df2fb7a). This is how you would get access to the code at any older commit # Current contents, two files present patel1-mn1:school-of-sre spatel1$ ls file1.txt file2.txt # checking out to (an older) commit spatel1-mn1:school-of-sre spatel1$ git checkout df2fb7a Note: checking out 'df2fb7a'. You are in 'detached HEAD' state. You can look around, make experimental changes and commit them, and you can discard any commits you make in this state without impacting any branches by performing another checkout. If you want to create a new branch to retain commits you create, you may do so (now or later) by using -b with the checkout command again. Example: git checkout -b new-branch-name HEAD is now at df2fb7a adding file 1 # checking contents, can verify it has old contents spatel1-mn1:school-of-sre spatel1$ ls file1.txt So this is how we would get access to old versions/snapshots. All we need is a reference to that snapshot. Upon executing git checkout ... , what git does for you is use the .git folder, see what was the state of things (files and folders) at that version/reference and replace the contents of current directory with those contents. The then-existing content will no longer be present in the local dir (repo) but we can and will still get access to them because they are tracked via git commit and .git folder has them stored/tracked.","title":"The Version Control part of Git"},{"location":"git/git-basics/#reference","text":"I mention in the previous section that we need a reference to the version. By default, git repo is made of tree of commits. And each commit has a unique IDs. But the unique ID is not the only thing we can reference commits via. There are multiple ways to reference commits. For example: HEAD is a reference to current commit. Whatever commit your repo is checked out at, HEAD will point to that. HEAD~1 is reference to previous commit. So while checking out previous version in section above, we could have done git checkout HEAD~1 . Similarly, master is also a reference (to a branch). Since git uses tree like structure to store commits, there of course will be branches. And the default branch is called master . Master (or any branch reference) will point to the latest commit in the branch. Even though we have checked out to the previous commit in out repo, master still points to the latest commit. And we can get back to the latest version by checkout at master reference spatel1-mn1:school-of-sre spatel1$ git checkout master Previous HEAD position was df2fb7a adding file 1 Switched to branch 'master' # now we will see latest code, with two files spatel1-mn1:school-of-sre spatel1$ ls file1.txt file2.txt Note, instead of master in above command, we could have used commit's ID as well.","title":"Reference"},{"location":"git/git-basics/#references-and-the-magic","text":"Let's look at the state of things. Two commits, master and HEAD references are pointing to the latest commit spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 7f3b00e (HEAD - master) adding file 2 * df2fb7a adding file 1 The magic? Let's examine these files: spatel1-mn1:school-of-sre spatel1$ cat .git/refs/heads/master 7f3b00eaa957815884198e2fdfec29361108d6a9 Viola! Where master is pointing to is stored in a file. Whenever git needs to know where master reference is pointing to, or if git needs to update where master points, it just needs to update the file above. So when you create a new commit, a new commit is created on top of the current commit and the master file is updated with the new commit's ID. Similary, for HEAD reference: spatel1-mn1:school-of-sre spatel1$ cat .git/HEAD ref: refs/heads/master We can see HEAD is pointing to a reference called refs/heads/master . So HEAD will point where ever the master points.","title":"References and The Magic"},{"location":"git/git-basics/#little-adventure","text":"We discussed how git will update the files as we execute commands. But let's try to do it ourselves, by hand, and see what happens. spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 7f3b00e (HEAD - master) adding file 2 * df2fb7a adding file 1 Now let's change master to point to the previous/first commit. spatel1-mn1:school-of-sre spatel1$ echo df2fb7a61f5d40c1191e0fdeb0fc5d6e7969685a .git/refs/heads/master spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * df2fb7a (HEAD - master) adding file 1 # RESETTING TO ORIGINAL spatel1-mn1:school-of-sre spatel1$ echo 7f3b00eaa957815884198e2fdfec29361108d6a9 .git/refs/heads/master spatel1-mn1:school-of-sre spatel1$ git log --oneline --graph * 7f3b00e (HEAD - master) adding file 2 * df2fb7a adding file 1 We just edited the master reference file and now we can see only the first commit in git log. Undoing the change to the file brings the state back to original. Not so much of magic, isn't it?","title":"Little Adventure"},{"location":"git/github-hooks/","text":"Git with Github Till now all the operations we did were in our local repo while git also helps us in a collaborative environment. GitHub is one place on the internet where you can centrally host your git repos and collaborate with other developers. Most of the workflow will remain the same as we discussed, with addition of couple of things: Pull: to pull latest changes from github (the central) repo Push: to push your changes to github repo so that it's available to all people GitHub has written nice guides and tutorials about this and you can refer them here: GitHub Hello World Git Handbook Hooks Git has another nice feature called hooks. Hooks are basically scripts which will be called when a certain event happens. Here is where hooks are located: spatel1-mn1:school-of-sre spatel1$ ls .git/hooks/ applypatch-msg.sample fsmonitor-watchman.sample pre-applypatch.sample pre-push.sample pre-receive.sample update.sample commit-msg.sample post-update.sample pre-commit.sample pre-rebase.sample prepare-commit-msg.sample Names are self explanatory. These hooks are useful when you want to do certain things when a certain event happens. Ie: if you want to run tests before pushing code, you would want to setup pre-push hooks. Let's try to create a pre commit hook. spatel1-mn1:school-of-sre spatel1$ echo echo this is from pre commit hook .git/hooks/pre-commit spatel1-mn1:school-of-sre spatel1$ chmod +x .git/hooks/pre-commit We basically create a file called pre-commit in hooks folder and make it executable. Now if we make a commit, we should see the message getting printed. spatel1-mn1:school-of-sre spatel1$ echo sample file sample.txt spatel1-mn1:school-of-sre spatel1$ git add sample.txt spatel1-mn1:school-of-sre spatel1$ git commit -m adding sample file this is from pre commit hook # ===== THE MESSAGE FROM HOOK EXECUTION [master 9894e05] adding sample file 1 file changed, 1 insertion(+) create mode 100644 sample.txt What next from here? There are a lot of git commands and features which we have not explored here. But with the base built-up, be sure to explore concepts like Cherrypick Squash Amend Stash Reset","title":"Github and Hooks"},{"location":"git/github-hooks/#git-with-github","text":"Till now all the operations we did were in our local repo while git also helps us in a collaborative environment. GitHub is one place on the internet where you can centrally host your git repos and collaborate with other developers. Most of the workflow will remain the same as we discussed, with addition of couple of things: Pull: to pull latest changes from github (the central) repo Push: to push your changes to github repo so that it's available to all people GitHub has written nice guides and tutorials about this and you can refer them here: GitHub Hello World Git Handbook","title":"Git with Github"},{"location":"git/github-hooks/#hooks","text":"Git has another nice feature called hooks. Hooks are basically scripts which will be called when a certain event happens. Here is where hooks are located: spatel1-mn1:school-of-sre spatel1$ ls .git/hooks/ applypatch-msg.sample fsmonitor-watchman.sample pre-applypatch.sample pre-push.sample pre-receive.sample update.sample commit-msg.sample post-update.sample pre-commit.sample pre-rebase.sample prepare-commit-msg.sample Names are self explanatory. These hooks are useful when you want to do certain things when a certain event happens. Ie: if you want to run tests before pushing code, you would want to setup pre-push hooks. Let's try to create a pre commit hook. spatel1-mn1:school-of-sre spatel1$ echo echo this is from pre commit hook .git/hooks/pre-commit spatel1-mn1:school-of-sre spatel1$ chmod +x .git/hooks/pre-commit We basically create a file called pre-commit in hooks folder and make it executable. Now if we make a commit, we should see the message getting printed. spatel1-mn1:school-of-sre spatel1$ echo sample file sample.txt spatel1-mn1:school-of-sre spatel1$ git add sample.txt spatel1-mn1:school-of-sre spatel1$ git commit -m adding sample file this is from pre commit hook # ===== THE MESSAGE FROM HOOK EXECUTION [master 9894e05] adding sample file 1 file changed, 1 insertion(+) create mode 100644 sample.txt","title":"Hooks"},{"location":"git/github-hooks/#what-next-from-here","text":"There are a lot of git commands and features which we have not explored here. But with the base built-up, be sure to explore concepts like Cherrypick Squash Amend Stash Reset","title":"What next from here?"},{"location":"python_web/intro/","text":"School of SRE: Python and The Web Pre - Reads Basic understanding of python language. Basic familiarity with flask framework. What to expect from this training This course is divided into two high level parts. In the first part, assuming familiarity with python language\u2019s basic operations and syntax usage, we will dive a little deeper into understanding python as a language. We will compare python with other programming languages that you might already know like Java and C. We will also explore concepts of Python objects and with help of that, explore python features like decorators. In the second part which will revolve around the web, and also assume familiarity with the Flask framework, we will start from the socket module and work with HTTP requests. This will demystify how frameworks like flask work internally. And to introduce SRE flavour to the course, we will design, develop and deploy (in theory) a URL shortening application. We will emphasize parts of the whole process that are more important as an SRE of the said app/service. What is not covered under this training Extensive knowledge of python internals and advanced python. Training Content Lab Environment Setup Have latest version of python installed TOC The Python Language Some Python Concepts Python Gotchas Python and Web Sockets Flask The URL Shortening App Design Scaling The App Monitoring The App The Python Language Assuming you know a little bit of C/C++ and Java, let's try to discuss the following questions in context of those two languages and python. You might have heard that C/C++ is a compiled language while python is an interpreted language. Generally, with compiled language we first compile the program and then run the executable while in case of python we run the source code directly like python hello_world.py . While Java, being an interpreted language, still has a separate compilation step and then its run. So what's really the difference? Compiled vs. Interpreted This might sound a little weird to you: python, in a way is a compiled language! Python has a compiler built-in! It is obvious in the case of java since we compile it using a separate command ie: javac helloWorld.java and it will produce a .class file which we know as a bytecode . Well, python is very similar to that. One difference here is that there is no separate compile command/binary needed to run a python program. What is the difference then, between java and python? Well, Java's compiler is more strict and sophisticated. As you might know Java is a statically typed language. So the compiler is written in a way that it can verify types related errors during compile time. While python being a dynamic language, types are not known until a program is run. So in a way, python compiler is dumb (or, less strict). But there indeed is a compile step involved when a python program is run. You might have seen python bytecode files with .pyc extension. Here is how you can see bytecode for a given python program. # Create a Hello World spatel1-mn1:tmp spatel1$ echo print('hello world') hello_world.py # Making sure it runs spatel1-mn1:tmp spatel1$ python3 hello_world.py hello world # The bytecode of the given program spatel1-mn1:tmp spatel1$ python -m dis hello_world.py 1 0 LOAD_NAME 0 (print) 2 LOAD_CONST 0 ('hello world') 4 CALL_FUNCTION 1 6 POP_TOP 8 LOAD_CONST 1 (None) 10 RETURN_VALUE Read more about dis module here Now coming to C/C++, there of course is a compiler. But the output is different than what java/python compiler would produce. Compiling a C program would produce what we also know as machine code . As opposed to bytecode. Running The Programs We know compilation is involved in all 3 languages we are discussing. Just that the compilers are different in nature and they output different types of content. In case of C/C++, the output is machine code which can be directly read by your operating system. When you execute that program, your OS will know how exactly to run it. But this is not the case with bytecode. Those bytecodes are language specific. Python has its own set of bytecode defined (more in dis module) and so does java. So naturally, your operating system will not know how to run it. To run this bytecode, we have something called Virtual Machines. Ie: The JVM or the Python VM (CPython, Jython). These so called Virtual Machines are the programs which can read the bytecode and run it on a given operating system. Python has multiple VMs available. Cpython is a python VM implemented in C language, similarly Jython is a Java implementation of python VM. At the end of the day, what they should be capable of is to understand python language syntax, be able to compile it to bytecode and be able to run that bytecode. You can implement a python VM in any language! (And people do so, just because it can be done) The Operating System +------------------------------------+ | | | | | | hello_world.py Python bytecode | Python VM Process | | | +----------------+ +----------------+ | +----------------+ | |print(... | COMPILE |LOAD_CONST... | | |Reads bytecode | | | +--------------- + +------------------- +line by line | | | | | | | |and executes. | | | | | | | | | | +----------------+ +----------------+ | +----------------+ | | | | | | | hello_world.c OS Specific machinecode | A New Process | | | +----------------+ +----------------+ | +----------------+ | |void main() { | COMPILE | binary contents| | | binary contents| | | +--------------- + +------------------- + | | | | | | | | | | | | | | | | | | +----------------+ +----------------+ | +----------------+ | | (binary contents | | runs as is) | | | | | +------------------------------------+ Two things to note for above diagram: Generally, when we run a python program, a python VM process is started which reads the python source code, compiles it to byte code and run it in a single step. Compiling is not a separate step. Shown only for illustration purpose. Binaries generated for C like languages are not exactly run as is. Since there are multiple types of binaries (eg: ELF), there are more complicated steps involved in order to run a binary but we will not go into that since all that is done at OS level.","title":"Intro"},{"location":"python_web/intro/#school-of-sre-python-and-the-web","text":"","title":"School of SRE: Python and The Web"},{"location":"python_web/intro/#pre-reads","text":"Basic understanding of python language. Basic familiarity with flask framework.","title":"Pre - Reads"},{"location":"python_web/intro/#what-to-expect-from-this-training","text":"This course is divided into two high level parts. In the first part, assuming familiarity with python language\u2019s basic operations and syntax usage, we will dive a little deeper into understanding python as a language. We will compare python with other programming languages that you might already know like Java and C. We will also explore concepts of Python objects and with help of that, explore python features like decorators. In the second part which will revolve around the web, and also assume familiarity with the Flask framework, we will start from the socket module and work with HTTP requests. This will demystify how frameworks like flask work internally. And to introduce SRE flavour to the course, we will design, develop and deploy (in theory) a URL shortening application. We will emphasize parts of the whole process that are more important as an SRE of the said app/service.","title":"What to expect from this training"},{"location":"python_web/intro/#what-is-not-covered-under-this-training","text":"Extensive knowledge of python internals and advanced python.","title":"What is not covered under this training"},{"location":"python_web/intro/#training-content","text":"","title":"Training Content"},{"location":"python_web/intro/#lab-environment-setup","text":"Have latest version of python installed","title":"Lab Environment Setup"},{"location":"python_web/intro/#toc","text":"The Python Language Some Python Concepts Python Gotchas Python and Web Sockets Flask The URL Shortening App Design Scaling The App Monitoring The App","title":"TOC"},{"location":"python_web/intro/#the-python-language","text":"Assuming you know a little bit of C/C++ and Java, let's try to discuss the following questions in context of those two languages and python. You might have heard that C/C++ is a compiled language while python is an interpreted language. Generally, with compiled language we first compile the program and then run the executable while in case of python we run the source code directly like python hello_world.py . While Java, being an interpreted language, still has a separate compilation step and then its run. So what's really the difference?","title":"The Python Language"},{"location":"python_web/intro/#compiled-vs-interpreted","text":"This might sound a little weird to you: python, in a way is a compiled language! Python has a compiler built-in! It is obvious in the case of java since we compile it using a separate command ie: javac helloWorld.java and it will produce a .class file which we know as a bytecode . Well, python is very similar to that. One difference here is that there is no separate compile command/binary needed to run a python program. What is the difference then, between java and python? Well, Java's compiler is more strict and sophisticated. As you might know Java is a statically typed language. So the compiler is written in a way that it can verify types related errors during compile time. While python being a dynamic language, types are not known until a program is run. So in a way, python compiler is dumb (or, less strict). But there indeed is a compile step involved when a python program is run. You might have seen python bytecode files with .pyc extension. Here is how you can see bytecode for a given python program. # Create a Hello World spatel1-mn1:tmp spatel1$ echo print('hello world') hello_world.py # Making sure it runs spatel1-mn1:tmp spatel1$ python3 hello_world.py hello world # The bytecode of the given program spatel1-mn1:tmp spatel1$ python -m dis hello_world.py 1 0 LOAD_NAME 0 (print) 2 LOAD_CONST 0 ('hello world') 4 CALL_FUNCTION 1 6 POP_TOP 8 LOAD_CONST 1 (None) 10 RETURN_VALUE Read more about dis module here Now coming to C/C++, there of course is a compiler. But the output is different than what java/python compiler would produce. Compiling a C program would produce what we also know as machine code . As opposed to bytecode.","title":"Compiled vs. Interpreted"},{"location":"python_web/intro/#running-the-programs","text":"We know compilation is involved in all 3 languages we are discussing. Just that the compilers are different in nature and they output different types of content. In case of C/C++, the output is machine code which can be directly read by your operating system. When you execute that program, your OS will know how exactly to run it. But this is not the case with bytecode. Those bytecodes are language specific. Python has its own set of bytecode defined (more in dis module) and so does java. So naturally, your operating system will not know how to run it. To run this bytecode, we have something called Virtual Machines. Ie: The JVM or the Python VM (CPython, Jython). These so called Virtual Machines are the programs which can read the bytecode and run it on a given operating system. Python has multiple VMs available. Cpython is a python VM implemented in C language, similarly Jython is a Java implementation of python VM. At the end of the day, what they should be capable of is to understand python language syntax, be able to compile it to bytecode and be able to run that bytecode. You can implement a python VM in any language! (And people do so, just because it can be done) The Operating System +------------------------------------+ | | | | | | hello_world.py Python bytecode | Python VM Process | | | +----------------+ +----------------+ | +----------------+ | |print(... | COMPILE |LOAD_CONST... | | |Reads bytecode | | | +--------------- + +------------------- +line by line | | | | | | | |and executes. | | | | | | | | | | +----------------+ +----------------+ | +----------------+ | | | | | | | hello_world.c OS Specific machinecode | A New Process | | | +----------------+ +----------------+ | +----------------+ | |void main() { | COMPILE | binary contents| | | binary contents| | | +--------------- + +------------------- + | | | | | | | | | | | | | | | | | | +----------------+ +----------------+ | +----------------+ | | (binary contents | | runs as is) | | | | | +------------------------------------+ Two things to note for above diagram: Generally, when we run a python program, a python VM process is started which reads the python source code, compiles it to byte code and run it in a single step. Compiling is not a separate step. Shown only for illustration purpose. Binaries generated for C like languages are not exactly run as is. Since there are multiple types of binaries (eg: ELF), there are more complicated steps involved in order to run a binary but we will not go into that since all that is done at OS level.","title":"Running The Programs"},{"location":"python_web/python-concepts/","text":"Some Python Concepts Though you are expected to know python and its syntax at basic level, let us discuss some fundamental concepts that will help you understand the python language better. Everything in Python is an object. That includes the functions, lists, dicts, classes, modules, a running function (instance of function definition), everything. In the CPython, it would mean there is an underlying struct variable for each object. In python's current execution context, all the variables are stored in a dict. It'd be a string to object mapping. If you have a function and a float variable defined in the current context, here is how it is handled internally. float_number=42.0 def foo_func(): ... pass ... # NOTICE HOW VARIABLE NAMES ARE STRINGS, stored in a dict locals() {'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': class '_frozen_importlib.BuiltinImporter' , '__spec__': None, '__annotations__': {}, '__builtins__': module 'builtins' (built-in) , 'float_number': 42.0, 'foo_func': function foo_func at 0x1055847a0 } Python Functions Since functions too are objects, we can see what all attributes a function contains as following def hello(name): ... print(f Hello, {name}! ) ... dir(hello) ['__annotations__', '__call__', '__class__', '__closure__', '__code__', '__defaults__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__get__', '__getattribute__', '__globals__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__kwdefaults__', '__le__', '__lt__', '__module__', '__name__', '__ne__', '__new__', '__qualname__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__'] While there are a lot of them, let's look at some interesting ones globals This attribute, as the name suggests, has references of global variables. If you ever need to know what all global variables are in the scope of this function, this will tell you. See how the function start seeing the new variable in globals hello.__globals__ {'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': class '_frozen_importlib.BuiltinImporter' , '__spec__': None, '__annotations__': {}, '__builtins__': module 'builtins' (built-in) , 'hello': function hello at 0x7fe4e82554c0 } # adding new global variable GLOBAL= g_val hello.__globals__ {'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': class '_frozen_importlib.BuiltinImporter' , '__spec__': None, '__annotations__': {}, '__builtins__': module 'builtins' (built-in) , 'hello': function hello at 0x7fe4e82554c0 , 'GLOBAL': 'g_val'} code This is an interesting one! As everything in python is an object, this includes the bytecode too. The compiled python bytecode is a python code object. Which is accessible via __code__ attribute here. A function has an associated code object which carries some interesting information. # the file in which function is defined # stdin here since this is run in an interpreter hello.__code__.co_filename ' stdin ' # number of arguments the function takes hello.__code__.co_argcount 1 # local variable names hello.__code__.co_varnames ('name',) # the function code's compiled bytecode hello.__code__.co_code b't\\x00d\\x01|\\x00\\x9b\\x00d\\x02\\x9d\\x03\\x83\\x01\\x01\\x00d\\x00S\\x00' There are more code attributes which you can enlist by dir(hello.__code__) Decorators Related to functions, python has another feature called decorators. Let's see how that works, keeping everything is an object in mind. Here is a sample decorator: def deco(func): ... def inner(): ... print( before ) ... func() ... print( after ) ... return inner ... @deco ... def hello_world(): ... print( hello world ) ... hello_world() before hello world after Here @deco syntax is used to decorate the hello_world function. It is essentially same as doing def hello_world(): ... print( hello world ) ... hello_world = deco(hello_world) What goes inside the deco function might seem complex. Let's try to uncover it. Function hello_world is created It is passed to deco function deco create a new function This new function is calls hello_world function And does a couple other things deco returns the newly created function hello_world is replaced with above function Let's visualize it for better understanding BEFORE function_object (ID: 100) hello_world +--------------------+ + |print( hello_world )| | | | +-------------- | | | | +--------------------+ WHAT DECORATOR DOES creates a new function (ID: 101) +---------------------------------+ |input arg: function with id: 100 | | | |print( before ) | |call function object with id 100 | |print( after ) | | | +---------------------------^-----+ | | AFTER | | | hello_world +-------------+ Note how the hello_world name points to a new function object but that new function object knows the reference (ID) of the original function. Some Gotchas While it is very quick to build prototypes in python and there are tons of libraries available, as the codebase complexity increases, type errors become more common and will get hard to deal with. (There are solutions to that problem like type annotations in python. Checkout mypy .) Because python is dynamically typed language, that means all types are determined at runtime. And that makes python run very slow compared to other statically typed languages. Python has something called GIL (global interpreter lock) which is a limiting factor for utilizing multiple CPI cores for parallel computation. Some weird things that python does: https://github.com/satwikkansal/wtfpython","title":"Some Python Concepts"},{"location":"python_web/python-concepts/#some-python-concepts","text":"Though you are expected to know python and its syntax at basic level, let us discuss some fundamental concepts that will help you understand the python language better. Everything in Python is an object. That includes the functions, lists, dicts, classes, modules, a running function (instance of function definition), everything. In the CPython, it would mean there is an underlying struct variable for each object. In python's current execution context, all the variables are stored in a dict. It'd be a string to object mapping. If you have a function and a float variable defined in the current context, here is how it is handled internally. float_number=42.0 def foo_func(): ... pass ... # NOTICE HOW VARIABLE NAMES ARE STRINGS, stored in a dict locals() {'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': class '_frozen_importlib.BuiltinImporter' , '__spec__': None, '__annotations__': {}, '__builtins__': module 'builtins' (built-in) , 'float_number': 42.0, 'foo_func': function foo_func at 0x1055847a0 }","title":"Some Python Concepts"},{"location":"python_web/python-concepts/#python-functions","text":"Since functions too are objects, we can see what all attributes a function contains as following def hello(name): ... print(f Hello, {name}! ) ... dir(hello) ['__annotations__', '__call__', '__class__', '__closure__', '__code__', '__defaults__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__get__', '__getattribute__', '__globals__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__kwdefaults__', '__le__', '__lt__', '__module__', '__name__', '__ne__', '__new__', '__qualname__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__'] While there are a lot of them, let's look at some interesting ones","title":"Python Functions"},{"location":"python_web/python-concepts/#globals","text":"This attribute, as the name suggests, has references of global variables. If you ever need to know what all global variables are in the scope of this function, this will tell you. See how the function start seeing the new variable in globals hello.__globals__ {'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': class '_frozen_importlib.BuiltinImporter' , '__spec__': None, '__annotations__': {}, '__builtins__': module 'builtins' (built-in) , 'hello': function hello at 0x7fe4e82554c0 } # adding new global variable GLOBAL= g_val hello.__globals__ {'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': class '_frozen_importlib.BuiltinImporter' , '__spec__': None, '__annotations__': {}, '__builtins__': module 'builtins' (built-in) , 'hello': function hello at 0x7fe4e82554c0 , 'GLOBAL': 'g_val'}","title":"globals"},{"location":"python_web/python-concepts/#code","text":"This is an interesting one! As everything in python is an object, this includes the bytecode too. The compiled python bytecode is a python code object. Which is accessible via __code__ attribute here. A function has an associated code object which carries some interesting information. # the file in which function is defined # stdin here since this is run in an interpreter hello.__code__.co_filename ' stdin ' # number of arguments the function takes hello.__code__.co_argcount 1 # local variable names hello.__code__.co_varnames ('name',) # the function code's compiled bytecode hello.__code__.co_code b't\\x00d\\x01|\\x00\\x9b\\x00d\\x02\\x9d\\x03\\x83\\x01\\x01\\x00d\\x00S\\x00' There are more code attributes which you can enlist by dir(hello.__code__)","title":"code"},{"location":"python_web/python-concepts/#decorators","text":"Related to functions, python has another feature called decorators. Let's see how that works, keeping everything is an object in mind. Here is a sample decorator: def deco(func): ... def inner(): ... print( before ) ... func() ... print( after ) ... return inner ... @deco ... def hello_world(): ... print( hello world ) ... hello_world() before hello world after Here @deco syntax is used to decorate the hello_world function. It is essentially same as doing def hello_world(): ... print( hello world ) ... hello_world = deco(hello_world) What goes inside the deco function might seem complex. Let's try to uncover it. Function hello_world is created It is passed to deco function deco create a new function This new function is calls hello_world function And does a couple other things deco returns the newly created function hello_world is replaced with above function Let's visualize it for better understanding BEFORE function_object (ID: 100) hello_world +--------------------+ + |print( hello_world )| | | | +-------------- | | | | +--------------------+ WHAT DECORATOR DOES creates a new function (ID: 101) +---------------------------------+ |input arg: function with id: 100 | | | |print( before ) | |call function object with id 100 | |print( after ) | | | +---------------------------^-----+ | | AFTER | | | hello_world +-------------+ Note how the hello_world name points to a new function object but that new function object knows the reference (ID) of the original function.","title":"Decorators"},{"location":"python_web/python-concepts/#some-gotchas","text":"While it is very quick to build prototypes in python and there are tons of libraries available, as the codebase complexity increases, type errors become more common and will get hard to deal with. (There are solutions to that problem like type annotations in python. Checkout mypy .) Because python is dynamically typed language, that means all types are determined at runtime. And that makes python run very slow compared to other statically typed languages. Python has something called GIL (global interpreter lock) which is a limiting factor for utilizing multiple CPI cores for parallel computation. Some weird things that python does: https://github.com/satwikkansal/wtfpython","title":"Some Gotchas"},{"location":"python_web/python-web-flask/","text":"Python, Web amd Flask Back in the old days, websites were simple. They were simple static html contents. A webserver would be listening on a defined port and according to the HTTP request received, it would read files from disk and return them in response. But since then, complexity has evolved and websites are now dynamic. Depending on the request, multiple operations need to be performed like reading from database or calling other API and finally returning some response (HTML data, JSON content etc.) Since serving web requests is no longer a simple task like reading files from disk and return contents, we need to process each http request, perform some operations programmatically and construct a response. Sockets Though we have frameworks like flask, HTTP is still a protocol that works over TCP protocol. So let us setup a TCP server and send an HTTP request and inspect the request's payload. Note that this is not a tutorial on socket programming but what we are doing here is inspecting HTTP protocol at its ground level and look at what its contents look like. (Ref: Socket Programming in Python (Guide) on RealPython ) import socket HOST = '127.0.0.1' # Standard loopback interface address (localhost) PORT = 65432 # Port to listen on (non-privileged ports are 1023) with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((HOST, PORT)) s.listen() conn, addr = s.accept() with conn: print('Connected by', addr) while True: data = conn.recv(1024) if not data: break print(data) Then we open localhost:65432 in our web browser and following would be the output: Connected by ('127.0.0.1', 54719) b'GET / HTTP/1.1\\r\\nHost: localhost:65432\\r\\nConnection: keep-alive\\r\\nDNT: 1\\r\\nUpgrade-Insecure-Requests: 1\\r\\nUser-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/85.0.4183.83 Safari/537.36 Edg/85.0.564.44\\r\\nAccept: text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9\\r\\nSec-Fetch-Site: none\\r\\nSec-Fetch-Mode: navigate\\r\\nSec-Fetch-User: ?1\\r\\nSec-Fetch-Dest: document\\r\\nAccept-Encoding: gzip, deflate, br\\r\\nAccept-Language: en-US,en;q=0.9\\r\\n\\r\\n' Examine closely and the content will look like the HTTP protocol's format. ie: HTTP_METHOD URI_PATH HTTP_VERSION HEADERS_SEPARATED_BY_SEPARATOR So though it's a blob of bytes, knowing http protocol specification , you can parse that string (ie: split by \\r\\n ) and get meaningful information out of it. Flask Flask, and other such frameworks does pretty much what we just discussed in the last section (with added more sophistication). They listen on a port on a TCP socket, receive an HTTP request, parse the data according to protocol format and make it available to you in a convenient manner. ie: you can access headers in flask by request.headers which is made available to you by splitting above payload by /r/n , as defined in http protocol. Another example: we register routes in flask by @app.route(\"/hello\") . What flask will do is maintain a registry internally which will map /hello with the function you decorated with. Now whenever a request comes with the /hello route (second component in the first line, split by space), flask calls the registered function and returns whatever the function returned. Same with all other web frameworks in other languages too. They all work on similar principles. What they basically do is understand the HTTP protocol, parses the HTTP request data and gives us programmers a nice interface to work with HTTP requests. Not so much of magic, innit?","title":"Python, Web and Flask"},{"location":"python_web/python-web-flask/#python-web-amd-flask","text":"Back in the old days, websites were simple. They were simple static html contents. A webserver would be listening on a defined port and according to the HTTP request received, it would read files from disk and return them in response. But since then, complexity has evolved and websites are now dynamic. Depending on the request, multiple operations need to be performed like reading from database or calling other API and finally returning some response (HTML data, JSON content etc.) Since serving web requests is no longer a simple task like reading files from disk and return contents, we need to process each http request, perform some operations programmatically and construct a response.","title":"Python, Web amd Flask"},{"location":"python_web/python-web-flask/#sockets","text":"Though we have frameworks like flask, HTTP is still a protocol that works over TCP protocol. So let us setup a TCP server and send an HTTP request and inspect the request's payload. Note that this is not a tutorial on socket programming but what we are doing here is inspecting HTTP protocol at its ground level and look at what its contents look like. (Ref: Socket Programming in Python (Guide) on RealPython ) import socket HOST = '127.0.0.1' # Standard loopback interface address (localhost) PORT = 65432 # Port to listen on (non-privileged ports are 1023) with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((HOST, PORT)) s.listen() conn, addr = s.accept() with conn: print('Connected by', addr) while True: data = conn.recv(1024) if not data: break print(data) Then we open localhost:65432 in our web browser and following would be the output: Connected by ('127.0.0.1', 54719) b'GET / HTTP/1.1\\r\\nHost: localhost:65432\\r\\nConnection: keep-alive\\r\\nDNT: 1\\r\\nUpgrade-Insecure-Requests: 1\\r\\nUser-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/85.0.4183.83 Safari/537.36 Edg/85.0.564.44\\r\\nAccept: text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9\\r\\nSec-Fetch-Site: none\\r\\nSec-Fetch-Mode: navigate\\r\\nSec-Fetch-User: ?1\\r\\nSec-Fetch-Dest: document\\r\\nAccept-Encoding: gzip, deflate, br\\r\\nAccept-Language: en-US,en;q=0.9\\r\\n\\r\\n' Examine closely and the content will look like the HTTP protocol's format. ie: HTTP_METHOD URI_PATH HTTP_VERSION HEADERS_SEPARATED_BY_SEPARATOR So though it's a blob of bytes, knowing http protocol specification , you can parse that string (ie: split by \\r\\n ) and get meaningful information out of it.","title":"Sockets"},{"location":"python_web/python-web-flask/#flask","text":"Flask, and other such frameworks does pretty much what we just discussed in the last section (with added more sophistication). They listen on a port on a TCP socket, receive an HTTP request, parse the data according to protocol format and make it available to you in a convenient manner. ie: you can access headers in flask by request.headers which is made available to you by splitting above payload by /r/n , as defined in http protocol. Another example: we register routes in flask by @app.route(\"/hello\") . What flask will do is maintain a registry internally which will map /hello with the function you decorated with. Now whenever a request comes with the /hello route (second component in the first line, split by space), flask calls the registered function and returns whatever the function returned. Same with all other web frameworks in other languages too. They all work on similar principles. What they basically do is understand the HTTP protocol, parses the HTTP request data and gives us programmers a nice interface to work with HTTP requests. Not so much of magic, innit?","title":"Flask"},{"location":"python_web/sre-conclusion/","text":"SRE Parts of The App and Conclusion Scaling The App The design and development is just a part of the journey. We will need to setup continuous integration and continuous delivery pipelines sooner or later. And we have to deploy this app somewhere. Initially we can start with deploying this app on one virtual machine on any cloud provider. But this is a Single point of failure which is something we never allow as an SRE (or even as an engineer). So an improvement here can be having multiple instances of applications deployed behind a load balancer. This certainly prevents problems of one machine going down. Scaling here would mean adding more instances behind the load balancer. But this is scalable upto only a certain point. After that, other bottlenecks in the system will start appearing. ie: DB will become the bottleneck, or perhaps the load balancer itself. How do you know what is the bottleneck? You need to have observability into each aspects of the application architecture. Only after you have metrics, you will be able to know what is going wrong where. What gets measured, gets fixed! Get deeper insights into scaling from School Of SRE's Scalability module and post going through it, apply your learnings and takeaways to this app. Think how will we make this app geographically distributed and highly available and scalable. Monitoring Strategy Once we have our application deployed. It will be working ok. But not forever. Reliability is in the title of our job and we make systems reliable by making the design in a certain way. But things still will go down. Machines will fail. Disks will behave weirdly. Buggy code will get pushed to production. And all these possible scenarios will make the system less reliable. So what do we do? We monitor! We keep an eye on the system's health and if anything is not going as expected, we want ourselves to get alerted. Now let's think in terms of the given url shortening app. We need to monitor it. And we would want to get notified in case something goes wrong. But we first need to decide what is that something that we want to keep an eye on. Since it's a web app serving HTTP requests, we want to keep an eye on HTTP Status codes and latencies Request volume again is a good candidate, if the app is receiving an unusual amount of traffic, something might be off. We also want to keep an eye on the database so depending on the database solution chosen. Query times, volumes, disk usage etc. Finally, there also needs to be some external monitoring which runs periodic tests from devices outside of your data centers. This emulates customers and ensures that from customer point of view, the system is working as expected. SRE Use-cases In the world of SRE, python is a widely used language. For small scripts and tooling developed for various purposes. Since tooling developed by SRE works with critical pieces of infrastructure and has great power (to bring things down), it is important to know what you are doing while using a programming language and its features. Also it is equally important to know the language and its characteristics while debugging the issues. As an SRE having a deeper understanding of python language, it has helped me a lot to debug very sneaky bugs and be generally more aware and informed while making certain design decisions. While developing tools may or may not be part of SRE job, supporting tools or services is more likely to be a daily duty. Building an application or tool is just a small part of productionization. While there is certainly that goes in the design of the application itself to make it more robust, as an SRE you are responsible for its reliability and stability once it is deployed and running. And to ensure that, you\u2019d need to understand the application first and then come up with a strategy to monitor it properly and be prepared for various failure scenarios. Optional Exercises Make a decorator that will cache function return values depending on input parameters. Host the URL shortening app on any cloud provider. Setup monitoring using many of the tools available like catchpoint, datadog etc. Create a minimal flask-like framework on top of TCP sockets. Conclusion This module, in the first part, aims to make you more aware of the things that will happen when you choose python as your programming language and what happens when you run a python program. With the knowledge of how python handles things internally as objects, lot of seemingly magic things in python will start to make more sense. The second part will first explain how a framework like flask works using the existing knowledge of protocols like TCP and HTTP. It then touches the whole lifecycle of an application development lifecycle including the SRE parts of it. While the design and areas in architecture considered will not be exhaustive, it will give a good overview of things that are also important being an SRE and why they are important.","title":"SRE Aspects of The App and Conclusion"},{"location":"python_web/sre-conclusion/#sre-parts-of-the-app-and-conclusion","text":"","title":"SRE Parts of The App and Conclusion"},{"location":"python_web/sre-conclusion/#scaling-the-app","text":"The design and development is just a part of the journey. We will need to setup continuous integration and continuous delivery pipelines sooner or later. And we have to deploy this app somewhere. Initially we can start with deploying this app on one virtual machine on any cloud provider. But this is a Single point of failure which is something we never allow as an SRE (or even as an engineer). So an improvement here can be having multiple instances of applications deployed behind a load balancer. This certainly prevents problems of one machine going down. Scaling here would mean adding more instances behind the load balancer. But this is scalable upto only a certain point. After that, other bottlenecks in the system will start appearing. ie: DB will become the bottleneck, or perhaps the load balancer itself. How do you know what is the bottleneck? You need to have observability into each aspects of the application architecture. Only after you have metrics, you will be able to know what is going wrong where. What gets measured, gets fixed! Get deeper insights into scaling from School Of SRE's Scalability module and post going through it, apply your learnings and takeaways to this app. Think how will we make this app geographically distributed and highly available and scalable.","title":"Scaling The App"},{"location":"python_web/sre-conclusion/#monitoring-strategy","text":"Once we have our application deployed. It will be working ok. But not forever. Reliability is in the title of our job and we make systems reliable by making the design in a certain way. But things still will go down. Machines will fail. Disks will behave weirdly. Buggy code will get pushed to production. And all these possible scenarios will make the system less reliable. So what do we do? We monitor! We keep an eye on the system's health and if anything is not going as expected, we want ourselves to get alerted. Now let's think in terms of the given url shortening app. We need to monitor it. And we would want to get notified in case something goes wrong. But we first need to decide what is that something that we want to keep an eye on. Since it's a web app serving HTTP requests, we want to keep an eye on HTTP Status codes and latencies Request volume again is a good candidate, if the app is receiving an unusual amount of traffic, something might be off. We also want to keep an eye on the database so depending on the database solution chosen. Query times, volumes, disk usage etc. Finally, there also needs to be some external monitoring which runs periodic tests from devices outside of your data centers. This emulates customers and ensures that from customer point of view, the system is working as expected.","title":"Monitoring Strategy"},{"location":"python_web/sre-conclusion/#sre-use-cases","text":"In the world of SRE, python is a widely used language. For small scripts and tooling developed for various purposes. Since tooling developed by SRE works with critical pieces of infrastructure and has great power (to bring things down), it is important to know what you are doing while using a programming language and its features. Also it is equally important to know the language and its characteristics while debugging the issues. As an SRE having a deeper understanding of python language, it has helped me a lot to debug very sneaky bugs and be generally more aware and informed while making certain design decisions. While developing tools may or may not be part of SRE job, supporting tools or services is more likely to be a daily duty. Building an application or tool is just a small part of productionization. While there is certainly that goes in the design of the application itself to make it more robust, as an SRE you are responsible for its reliability and stability once it is deployed and running. And to ensure that, you\u2019d need to understand the application first and then come up with a strategy to monitor it properly and be prepared for various failure scenarios.","title":"SRE Use-cases"},{"location":"python_web/sre-conclusion/#optional-exercises","text":"Make a decorator that will cache function return values depending on input parameters. Host the URL shortening app on any cloud provider. Setup monitoring using many of the tools available like catchpoint, datadog etc. Create a minimal flask-like framework on top of TCP sockets.","title":"Optional Exercises"},{"location":"python_web/sre-conclusion/#conclusion","text":"This module, in the first part, aims to make you more aware of the things that will happen when you choose python as your programming language and what happens when you run a python program. With the knowledge of how python handles things internally as objects, lot of seemingly magic things in python will start to make more sense. The second part will first explain how a framework like flask works using the existing knowledge of protocols like TCP and HTTP. It then touches the whole lifecycle of an application development lifecycle including the SRE parts of it. While the design and areas in architecture considered will not be exhaustive, it will give a good overview of things that are also important being an SRE and why they are important.","title":"Conclusion"},{"location":"python_web/url-shorten-app/","text":"The URL Shortening App Let's build a very simple URL shortening app using flask and try to incorporate all aspects of the development process including the reliability aspects. We will not be building the UI and we will come up with a minimal set of API that will be enough for the app to function well. Design We don't jump directly to coding. First thing we do is gather requirements. Come up with an approach. Have the approach/design reviewed by peers. Evolve, iterate, document the decisions and tradeoffs. And then finally implement. While we will not do the full blown design document here, we will raise certain questions here that are important to the design. 1. High Level Operations and API Endpoints Since it's a URL shortening app, we will need an API for generating the shorten link given an original link. And an API/Endpoint which will accept the shorten link and redirect to original URL. We are not including the user aspect of the app to keep things minimal. These two API should make app functional and usable by anyone. 2. How to shorten? Given a url, we will need to generate a shortened version of it. One approach could be using random characters for each link. Another thing that can be done is to use some sort of hashing algorithm. The benefit here is we will reuse the same hash for the same link. ie: if lot of people are shortening https://www.linkedin.com they all will have the same value, compared to multiple entries in DB if chosen random characters. What about hash collisions? Even in random characters approach, though there is a less probability, hash collisions can happen. And we need to be mindful of them. In that case we might want to prepend/append the string with some random value to avoid conflict. Also, choice of hash algorithm matters. We will need to analyze algorithms. Their CPU requirements and their characteristics. Choose one that suits the most. 3. Is URL Valid? Given a URL to shorten, how do we verify if the URL is valid? Do we even verify or validate? One basic check that can be done is see if the URL matches a regex of a URL. To go even further we can try opening/visiting the URL. But there are certain gotchas here. We need to define success criteria. ie: HTTP 200 means it is valid. What is the URL is in private network? What if URL is temporarily down? 4. Storage Finally, storage. Where will we store the data that we will generate over time? There are multiple database solutions available and we will need to choose the one that suits this app the most. Relational database like MySQL would be a fair choice but be sure to checkout School of SRE's database section for deeper insights into making a more informed decision. 5. Other We are not accounting for users into our app and other possible features like rate limiting, customized links etc but it will eventually come up with time. Depending on the requirements, they too might need to get incorporated. The minimal working code is given below for reference but I'd encourage you to come up with your own. from flask import Flask, redirect, request from hashlib import md5 app = Flask( url_shortener ) mapping = {} @app.route( /shorten , methods=[ POST ]) def shorten(): global mapping payload = request.json if url not in payload: return Missing URL Parameter , 400 # TODO: check if URL is valid hash_ = md5() hash_.update(payload[ url ].encode()) digest = hash_.hexdigest()[:5] # limiting to 5 chars. Less the limit more the chances of collission if digest not in mapping: mapping[digest] = payload[ url ] return f Shortened: r/{digest}\\n else: # TODO: check for hash collission return f Already exists: r/{digest}\\n @app.route( /r/ hash_ ) def redirect_(hash_): if hash_ not in mapping: return URL Not Found , 404 return redirect(mapping[hash_]) if __name__ == __main__ : app.run(debug=True) OUTPUT: === SHORTENING spatel1-mn1:tmp spatel1$ curl localhost:5000/shorten -H content-type: application/json --data '{ url : https://linkedin.com }' Shortened: r/a62a4 === REDIRECTING, notice the response code 302 and the location header spatel1-mn1:tmp spatel1$ curl localhost:5000/r/a62a4 -v * Uses proxy env variable NO_PROXY == '127.0.0.1' * Trying ::1... * TCP_NODELAY set * Connection failed * connect to ::1 port 5000 failed: Connection refused * Trying 127.0.0.1... * TCP_NODELAY set * Connected to localhost (127.0.0.1) port 5000 (#0) GET /r/a62a4 HTTP/1.1 Host: localhost:5000 User-Agent: curl/7.64.1 Accept: */* * HTTP 1.0, assume close after body HTTP/1.0 302 FOUND Content-Type: text/html; charset=utf-8 Content-Length: 247 Location: https://linkedin.com Server: Werkzeug/0.15.4 Python/3.7.7 Date: Tue, 27 Oct 2020 09:37:12 GMT !DOCTYPE HTML PUBLIC -//W3C//DTD HTML 3.2 Final//EN title Redirecting... /title h1 Redirecting... /h1 * Closing connection 0 p You should be redirected automatically to target URL: a href= https://linkedin.com https://linkedin.com /a . If not click the link.","title":"The URL Shortening App"},{"location":"python_web/url-shorten-app/#the-url-shortening-app","text":"Let's build a very simple URL shortening app using flask and try to incorporate all aspects of the development process including the reliability aspects. We will not be building the UI and we will come up with a minimal set of API that will be enough for the app to function well.","title":"The URL Shortening App"},{"location":"python_web/url-shorten-app/#design","text":"We don't jump directly to coding. First thing we do is gather requirements. Come up with an approach. Have the approach/design reviewed by peers. Evolve, iterate, document the decisions and tradeoffs. And then finally implement. While we will not do the full blown design document here, we will raise certain questions here that are important to the design.","title":"Design"},{"location":"python_web/url-shorten-app/#1-high-level-operations-and-api-endpoints","text":"Since it's a URL shortening app, we will need an API for generating the shorten link given an original link. And an API/Endpoint which will accept the shorten link and redirect to original URL. We are not including the user aspect of the app to keep things minimal. These two API should make app functional and usable by anyone.","title":"1. High Level Operations and API Endpoints"},{"location":"python_web/url-shorten-app/#2-how-to-shorten","text":"Given a url, we will need to generate a shortened version of it. One approach could be using random characters for each link. Another thing that can be done is to use some sort of hashing algorithm. The benefit here is we will reuse the same hash for the same link. ie: if lot of people are shortening https://www.linkedin.com they all will have the same value, compared to multiple entries in DB if chosen random characters. What about hash collisions? Even in random characters approach, though there is a less probability, hash collisions can happen. And we need to be mindful of them. In that case we might want to prepend/append the string with some random value to avoid conflict. Also, choice of hash algorithm matters. We will need to analyze algorithms. Their CPU requirements and their characteristics. Choose one that suits the most.","title":"2. How to shorten?"},{"location":"python_web/url-shorten-app/#3-is-url-valid","text":"Given a URL to shorten, how do we verify if the URL is valid? Do we even verify or validate? One basic check that can be done is see if the URL matches a regex of a URL. To go even further we can try opening/visiting the URL. But there are certain gotchas here. We need to define success criteria. ie: HTTP 200 means it is valid. What is the URL is in private network? What if URL is temporarily down?","title":"3. Is URL Valid?"},{"location":"python_web/url-shorten-app/#4-storage","text":"Finally, storage. Where will we store the data that we will generate over time? There are multiple database solutions available and we will need to choose the one that suits this app the most. Relational database like MySQL would be a fair choice but be sure to checkout School of SRE's database section for deeper insights into making a more informed decision.","title":"4. Storage"},{"location":"python_web/url-shorten-app/#5-other","text":"We are not accounting for users into our app and other possible features like rate limiting, customized links etc but it will eventually come up with time. Depending on the requirements, they too might need to get incorporated. The minimal working code is given below for reference but I'd encourage you to come up with your own. from flask import Flask, redirect, request from hashlib import md5 app = Flask( url_shortener ) mapping = {} @app.route( /shorten , methods=[ POST ]) def shorten(): global mapping payload = request.json if url not in payload: return Missing URL Parameter , 400 # TODO: check if URL is valid hash_ = md5() hash_.update(payload[ url ].encode()) digest = hash_.hexdigest()[:5] # limiting to 5 chars. Less the limit more the chances of collission if digest not in mapping: mapping[digest] = payload[ url ] return f Shortened: r/{digest}\\n else: # TODO: check for hash collission return f Already exists: r/{digest}\\n @app.route( /r/ hash_ ) def redirect_(hash_): if hash_ not in mapping: return URL Not Found , 404 return redirect(mapping[hash_]) if __name__ == __main__ : app.run(debug=True) OUTPUT: === SHORTENING spatel1-mn1:tmp spatel1$ curl localhost:5000/shorten -H content-type: application/json --data '{ url : https://linkedin.com }' Shortened: r/a62a4 === REDIRECTING, notice the response code 302 and the location header spatel1-mn1:tmp spatel1$ curl localhost:5000/r/a62a4 -v * Uses proxy env variable NO_PROXY == '127.0.0.1' * Trying ::1... * TCP_NODELAY set * Connection failed * connect to ::1 port 5000 failed: Connection refused * Trying 127.0.0.1... * TCP_NODELAY set * Connected to localhost (127.0.0.1) port 5000 (#0) GET /r/a62a4 HTTP/1.1 Host: localhost:5000 User-Agent: curl/7.64.1 Accept: */* * HTTP 1.0, assume close after body HTTP/1.0 302 FOUND Content-Type: text/html; charset=utf-8 Content-Length: 247 Location: https://linkedin.com Server: Werkzeug/0.15.4 Python/3.7.7 Date: Tue, 27 Oct 2020 09:37:12 GMT !DOCTYPE HTML PUBLIC -//W3C//DTD HTML 3.2 Final//EN title Redirecting... /title h1 Redirecting... /h1 * Closing connection 0 p You should be redirected automatically to target URL: a href= https://linkedin.com https://linkedin.com /a . If not click the link.","title":"5. Other"},{"location":"security/fundamentals/","text":"Part I: Fundamentals Introduction to Security Overview for SRE If you look closely, both Site Reliability Engineering and Security Engineering are concerned with keeping a system usable. Issues like broken releases, capacity shortages, and misconfigurations can make a system unusable (at least temporarily). Security or privacy incidents that break the trust of users also undermine the usefulness of a system. Consequently, system security should be top of mind for SREs. SREs should be involved in both significant design discussions and actual system changes. They have quite a big role in System design hence are quite sometimes the first line of defense. SRE\u2019s help in preventing bad design implementations which can affect the overall security of the infrastructure. Successfully designing, implementing, and maintaining systems requires a commitment to the full system lifecycle . This commitment is possible only when security and reliability are central elements in the architecture of systems. Core Pillars of Information Security : Confidentiality \u2013 only allow access to data for which the user is permitted Integrity \u2013 ensure data is not tampered or altered by unauthorized users Availability \u2013 ensure systems and data are available to authorized users when they need it Thinking like a Security Engineer When starting a new application or re-factoring an existing application, you should consider each functional feature, and consider: Is the process surrounding this feature as safe as possible? In other words, is this a flawed process? If I were evil, how would I abuse this feature? Or more specifically failing to address how a feature can be abused can cause design flaws. Is the feature required to be on by default? If so, are there limits or options that could help reduce the risk from this feature? Security Principles By OWASP (Open Web Application Security Project) Minimize attack surface area : Every feature that is added to an application adds a certain amount of risk to the overall application. The aim for secure development is to reduce the overall risk by reducing the attack surface area. For example, a web application implements online help with a search function. The search function may be vulnerable to SQL injection attacks. If the help feature was limited to authorized users, the attack likelihood is reduced. If the help feature\u2019s search function was gated through centralized data validation routines, the ability to perform SQL injection is dramatically reduced. However, if the help feature was re-written to eliminate the search function (through better user interface, for example), this almost eliminates the attack surface area, even if the help feature was available to the Internet at large. Establish secure defaults: There are many ways to deliver an \u201cout of the box\u201d experience for users. However, by default, the experience should be secure, and it should be up to the user to reduce their security \u2013 if they are allowed. For example, by default, password aging and complexity should be enabled. Users might be allowed to turn these two features off to simplify their use of the application and increase their risk. Default Passwords of routers, IOT devices should be changed Principle of Least privilege The principle of least privilege recommends that accounts have the least amount of privilege required to perform their business processes. This encompasses user rights, resource permissions such as CPU limits, memory, network, and file system permissions. For example, if a middleware server only requires access to the network, read access to a database table, and the ability to write to a log, this describes all the permissions that should be granted. Under no circumstances should the middleware be granted administrative privileges. Principle of Defense in depth The principle of defense in depth suggests that where one control would be reasonable, more controls that approach risks in different fashions are better. Controls, when used in-depth, can make severe vulnerabilities extraordinarily difficult to exploit and thus unlikely to occur. With secure coding, this may take the form of tier-based validation, centralized auditing controls, and requiring users to be logged on all pages. For example, a flawed administrative interface is unlikely to be vulnerable to an anonymous attack if it correctly gates access to production management networks, checks for administrative user authorization, and logs all access. Fail securely Applications regularly fail to process transactions for many reasons. How they fail can determine if an application is secure or not. - If either codeWhichMayFail() or isUserInRole fails or throws an exception, the user is an admin by default. This is obviously a security risk. Don\u2019t trust services Many organizations utilize the processing capabilities of third-party partners, who more than likely have different security policies and posture than you. It is unlikely that you can influence or control any external third party, whether they are home users or major suppliers or partners. Therefore, the implicit trust of externally run systems is not warranted. All external systems should be treated in a similar fashion. For example, a loyalty program provider provides data that is used by Internet Banking, providing the number of reward points and a small list of potential redemption items. However, the data should be checked to ensure that it is safe to display to end-users, and that the reward points are a positive number, and not improbably large. Separation of duties The key to fraud control is the separation of duties. For example, someone who requests a computer cannot also sign for it, nor should they directly receive the computer. This prevents the user from requesting many computers and claiming they never arrived. Certain roles have different levels of trust than normal users. In particular, administrators are different from normal users. In general, administrators should not be users of the application. For example, an administrator should be able to turn the system on or off, set password policy but shouldn\u2019t be able to log on to the storefront as a super privileged user, such as being able to \u201cbuy\u201d goods on behalf of other users. Avoid security by obscurity Security through obscurity is a weak security control, and nearly always fails when it is the only control. This is not to say that keeping secrets is a bad idea, it simply means that the security of systems should not be reliant upon keeping details hidden. For example, the security of an application should not rely upon knowledge of the source code being kept secret. The security should rely upon many other factors, including reasonable password policies, defense in depth, business transaction limits, solid network architecture, and fraud, and audit controls. A practical example is Linux. Linux\u2019s source code is widely available, and yet when properly secured, Linux is a secure and robust operating system. Keep security simple Attack surface area and simplicity go hand in hand. Certain software engineering practices prefer overly complex approaches to what would otherwise be a relatively straightforward and simple design. Developers should avoid the use of double negatives and complex architectures when a simpler approach would be faster and simpler. For example, although it might be fashionable to have a slew of singleton entity beans running on a separate middleware server, it is more secure and faster to simply use global variables with an appropriate mutex mechanism to protect against race conditions. Fix security issues correctly Once a security issue has been identified, it is important to develop a test for it and to understand the root cause of the issue. When design patterns are used, it is likely that the security issue is widespread amongst all codebases, so developing the right fix without introducing regressions is essential. For example, a user has found that they can see another user\u2019s balance by adjusting their cookie. The fix seems to be relatively straightforward, but as the cookie handling code is shared among all applications, a change to just one application will trickle through to all other applications. The fix must, therefore, be tested on all affected applications. Reliability Security Reliability and security are both crucial components of a truly trustworthy system,but building systems that are both reliable and secure is difficult. While the requirements for reliability and security share many common properties, they also require different design considerations. It is easy to miss the subtle interplay between reliability and security that can cause unexpected outcomes Ex: A password management application failure was triggered by a reliability problem i.e poor load-balancing and load-shedding strategies and its recovery was later complicated by multiple measures (HSM mechanism which needs to be plugged into server racks , which works as an authentication the HSM token supposedly locked inside a case.. the problem can be further elongated ) designed to increase the security of the system. Authentication vs Authorization Authentication is the act of validating that users are who they claim to be. Passwords are the most common authentication factor\u2014if a user enters the correct password, the system assumes the identity is valid and grants access. Other technologies such as One-Time Pins, authentication apps, and even biometrics can also be used to authenticate identity. In some instances, systems require the successful verification of more than one factor before granting access. This multi-factor authentication (MFA) requirement is often deployed to increase security beyond what passwords alone can provide. Authorization in system security is the process of giving the user permission to access a specific resource or function. This term is often used interchangeably with access control or client privilege. Giving someone permission to download a particular file on a server or providing individual users with administrative access to an application are good examples. In secure environments, authorization must always follow authentication, users should first prove that their identities are genuine before an organization\u2019s administrators grant them access to the requested resources. Common authentication flow (local authentication) The user registers using an identifier like username/email/mobile The application stores user credentials in the database The application sends a verification email/message to validate the registration Post successful registration, the user enters credentials for logging in On successful authentication, the user is allowed access to specific resources OpenID/OAuth OpenID is an authentication protocol that allows us to authenticate users without using a local auth system. In such a scenario, a user has to be registered with an OpenID Provider and the same provider should be integrated with the authentication flow of your application. To verify the details, we have to forward the authentication requests to the provider. On successful authentication, we receive a success message and/or profile details with which we can execute the necessary flow. OAuth is an authorization mechanism that allows your application user access to a provider(Gmail/Facebook/Instagram/etc). On successful response, we (your application) receive a token with which the application can access certain APIs on behalf of a user. OAuth is convenient in case your business use case requires some certain user-facing APIs like access to Google Drive or sending tweets on your behalf. Most OAuth 2.0 providers can be used for pseudo authentication. Having said that, it can get pretty complicated if you are using multiple OAuth providers to authenticate users on top of the local authentication system. Cryptography It is the science and study of hiding any text in such a way that only the intended recipients or authorized persons can read it and that any text can even use things such as invisible ink or the mechanical cryptography machines of the past. Cryptography is necessary for securing critical or proprietary information and is used to encode private data messages by converting some plain text into ciphertext. At its core, there are two ways of doing this, more advanced methods are all built upon. Ciphers Ciphers are the cornerstone of cryptography. A cipher is a set of algorithms that performs encryption or decryption on a message. An encryption algorithm (E) takes a secret key (k) and a message (m), and produces a ciphertext (c). Similarly, a Decryption algorithm (D) takes a secret key (K) and the previous resulting Ciphertext (C). They are represented as follows: This also means that in order for it to be a cipher, it must satisfy the consistency equation as follows, making it possible to decrypt. Stream Ciphers: The message is broken into characters or bits and enciphered with a key or keystream(should be random and generated independently of the message stream) that is as long as the plaintext bitstream. sIf the keystream is random, this scheme would be unbreakable unless the keystream was acquired, making it unconditionally secure. The keystream must be provided to both parties in a secure way to prevent its release. Block Ciphers: Block ciphers \u2014 process messages in blocks, each of which is then encrypted or decrypted. A block cipher is a symmetric cipher in which blocks of plaintext are treated as a whole and used to produce ciphertext blocks. The block cipher takes blocks that are b bits long and encrypts them to blocks that are also b bits long. Block sizes are typically 64 or 128 bits long. Encryption Secret Key (Symmetric Key) : the same key is used for encryption and decryption Public Key (Asymmetric Key) in an asymmetric, the encryption and decryption keys are different but related. The encryption key is known as the public key and the decryption key is known as the private key. The public and private keys are known as a key pair. Symmetric Key Encryption DES The Data Encryption Standard (DES) has been the worldwide encryption standard for a long time. IBM developed DES in 1975, and it has held up remarkably well against years of cryptanalysis. DES is a symmetric encryption algorithm with a fixed key length of 56 bits. The algorithm is still good, but because of the short key length, it is susceptible to brute-force attacks that have sufficient resources. DES usually operates in block mode, whereby it encrypts data in 64-bit blocks. The same algorithm and key are used for both encryption and decryption. Because DES is based on simple mathematical functions, it can be easily implemented and accelerated in hardware. Triple DES With advances in computer processing power, the original 56-bit DES key became too short to withstand an attacker with even a limited budget. One way of increasing the effective key length of DES without changing the well-analyzed algorithm itself is to use the same algorithm with different keys several times in a row. The technique of applying DES three times in a row to a plain text block is called Triple DES (3DES). The 3DES technique is shown in Figure. Brute-force attacks on 3DES are considered unfeasible today. Because the basic algorithm has been tested in the field for more than 25 years, it is considered to be more trustworthy than its predecessor. AES On October 2, 2000, The U.S. National Institute of Standards and Technology (NIST) announced the selection of the Rijndael cipher as the AES algorithm. This cipher, developed by Joan Daemen and Vincent Rijmen, has a variable block length and key length. The algorithm currently specifies how to use keys with a length of 128, 192, or 256 bits to encrypt blocks with a length of 128, 192, or 256 bits (all nine combinations of key length and block length are possible). Both block and key lengths can be extended easily to multiples of 32 bits. AES was chosen to replace DES and 3DES because they are either too weak (DES, in terms of key length) or too slow (3DES) to run on modern, efficient hardware. AES is more efficient and much faster, usually by a factor of 5 compared to DES on the same hardware. AES is also more suitable for high throughput, especially if pure software encryption is used. However, AES is a relatively young algorithm, and as the golden rule of cryptography states, \u201cA more mature algorithm is always more trusted.\u201d Asymmetric Key Algorithm In a symmetric key system, Alice first puts the secret message in a box and then padlocks the box using a lock to which she has a key. She then sends the box to Bob through regular mail. When Bob receives the box, he uses an identical copy of Alice's key (which he has obtained previously) to open the box and read the message. In an asymmetric key system, instead of opening the box when he receives it, Bob simply adds his own personal lock to the box and returns the box through public mail to Alice. Alice uses her key to remove her lock and returns the box to Bob, with Bob's lock still in place. Finally, Bob uses his key to remove his lock and reads the message from Alice. The critical advantage in an asymmetric system is that Alice never needs to send a copy of her key to Bob. This reduces the possibility that a third party (for example, an unscrupulous postmaster) can copy the key while it is in transit to Bob, allowing that third party to spy on all future messages sent by Alice. In addition, if Bob is careless and allows someone else to copy his key, Alice's messages to Bob are compromised, but Alice's messages to other people remain secret NOTE : In terms of TLS key exchange, this is the common approach. Diffie-Hellman The protocol has two system parameters, p and g. They are both public and may be used by everybody. Parameter p is a prime number, and parameter g (usually called a generator) is an integer that is smaller than p, but with the following property: For every number n between 1 and p \u2013 1 inclusive, there is a power k of g such that n = gk mod p. Diffie Hellman algorithm is an asymmetric algorithm used to establish a shared secret for a symmetric key algorithm. Nowadays most of the people use hybrid cryptosystem i.e, combination of symmetric and asymmetric encryption. Asymmetric Encryption is used as a technique in key exchange mechanism to share secret key and after the key is shared between sender and receiver, the communication will take place using symmetric encryption. The shared secret key will be used to encrypt the communication. Refer: https://medium.com/@akhigbemmanuel/what-is-the-diffie-hellman-key-exchange-algorithm-84d60025a30d RSA The RSA algorithm is very flexible and has a variable key length where, if necessary, speed can be traded for the level of security of the algorithm. The RSA keys are usually 512 to 2048 bits long. RSA has withstood years of extensive cryptanalysis. Although those years neither proved nor disproved RSA's security, they attest to a confidence level in the algorithm. RSA security is based on the difficulty of factoring very large numbers. If an easy method of factoring these large numbers were discovered, the effectiveness of RSA would be destroyed. Refer : https://medium.com/curiositypapers/a-complete-explanation-of-rsa-asymmetric-encryption-742c5971e0f NOTE : RSA Keys can be used for key exchange just like Deffie Hellman Hashing Algorithms Hashing is one of the mechanisms used for data integrity assurance. Hashing is based on a one-way mathematical function, which is relatively easy to compute but significantly harder to reverse. A hash function, which is a one-way function to input data to produce a fixed-length digest (fingerprint) of output data. The digest is cryptographically strong; that is, it is impossible to recover input data from its digest. If the input data changes just a little, the digest (fingerprint) changes substantially in what is called an avalanche effect. More: https://medium.com/@rauljordan/the-state-of-hashing-algorithms-the-why-the-how-and-the-future-b21d5c0440de https://medium.com/@StevieCEllis/the-beautiful-hash-algorithm-f18d9d2b84fb MD5 MD5 is a one-way function with which it is easy to compute the hash from the given input data, but it is unfeasible to compute input data given only a hash. SHA-1 MD5 is considered less secure than SHA-1 because MD5 has some weaknesses. HA-1 also uses a stronger, 160-bit digest, which makes MD5 the second choice as hash methods are concerned. The algorithm takes a message of less than 264 bits in length and produces a 160-bit message digest. This algorithm is slightly slower than MD5. NOTE : SHA-1 is also recently demonstrated to be broken, Minimum current recommendation is SHA-256 Digital Certificates Digital signatures, provide a means to digitally authenticate devices and individual users. In public-key cryptography, such as the RSA encryption system, each user has a key-pair containing both a public key and a private key. The keys act as complements, and anything encrypted with one of the keys can be decrypted with the other. In simple terms, a signature is formed when data is encrypted with a user's private key. The receiver verifies the signature by decrypting the message with the sender's public key. Key management is often considered the most difficult task in designing and implementing cryptographic systems. Businesses can simplify some of the deployment and management issues that are encountered with secured data communications by employing a Public Key Infrastructure (PKI). Because corporations often move security-sensitive communications across the Internet, an effective mechanism must be implemented to protect sensitive information from the threats presented on the Internet. PKI provides a hierarchical framework for managing digital security attributes. Each PKI participant holds a digital certificate that has been issued by a CA (either public or private). The certificate contains a number of attributes that are used when parties negotiate a secure connection. These attributes must include the certificate validity period, end-host identity information, encryption keys that will be used for secure communications, and the signature of the issuing CA. Optional attributes may be included, depending on the requirements and capability of the PKI. A CA can be a trusted third party, such as VeriSign or Entrust, or a private (in-house) CA that you establish within your organization. The fact that the message could be decrypted using the sender's public key means that the holder of the private key created the message. This process relies on the receiver having a copy of the sender's public key and knowing with a high degree of certainty that it really does belong to the sender and not to someone pretending to be the sender. To validate the CA's signature, the receiver must know the CA's public key. Normally, this is handled out-of-band or through an operation performed during installation of the certificate. For instance, most web browsers are configured with the root certificates of several CAs by default. CA Enrollment process The end host generates a private-public key pair. The end host generates a certificate request, which it forwards to the CA. Manual human intervention is required to approve the enrollment request, which is received by the CA. After the CA operator approves the request, the CA signs the certificate request with its private key and returns the completed certificate to the end host. The end host writes the certificate into a nonvolatile storage area (PC hard disk or NVRAM on Cisco routers). Refer : https://www.ssh.com/manuals/server-zos-product/55/ch06s03s01.html Login Security SSH SSH, the Secure Shell, is a popular, powerful, software-based approach to network security. Whenever data is sent by a computer to the network, SSH automatically encrypts (scrambles) it. Then, when the data reaches its intended recipient, SSH automatically decrypts (unscrambles) it. The result is transparent encryption: users can work normally, unaware that their communications are safely encrypted on the network. In addition, SSH can use modern, secure encryption algorithms based on how it's being configured and is effective enough to be found within mission-critical applications at major corporations. SSH has a client/server architecture An SSH server program, typically installed and run by a system administrator, accepts or rejects incoming connections to its host computer. Users then run SSH client programs, typically on other computers, to make requests of the SSH server, such as \u201cPlease log me in,\u201d \u201cPlease send me a file,\u201d or \u201cPlease execute this command.\u201d All communications between clients and servers are securely encrypted and protected from modification. What SSH is not: Although SSH stands for Secure Shell, it is not a true shell in the sense of the Unix Bourne shell and C shell. It is not a command interpreter, nor does it provide wildcard expansion, command history, and so forth. Rather, SSH creates a channel for running a shell on a remote computer, with end-to-end encryption between the two systems. The major features and guarantees of the SSH protocol are: Privacy of your data, via strong encryption Integrity of communications, guaranteeing they haven\u2019t been altered Authentication, i.e., proof of identity of senders and receivers Authorization, i.e., access control to accounts Forwarding or tunneling to encrypt other TCP/IP-based sessions Kerberos According to Greek mythology Kerberos (Cerberus) was the gigantic, three-headed dog that guards the gates of the underworld to prevent the dead from leaving. So when it comes to Computer Science, Kerberos is a network authentication protocol, and is currently the default authentication technology used by Microsoft Active Directory to authenticate users to services within a local area network. Kerberos uses symmetric key cryptography and requires trusted third-party authentication service to verify user identities. So they used the name of Kerberos for their computer network authentication protocol as the three heads of the Kerberos represent: a client : A user/ a service a server : Kerberos protected hosts reside - a Key Distribution Center (KDC), which acts as the trusted third-party authentication service. The KDC includes following two servers: Authentication Server (AS) that performs the initial authentication and issues ticket-granting tickets (TGT) for users. Ticket-Granting Server (TGS) that issues service tickets that are based on the initial ticket-granting tickets (TGT). Certificate Chain The first part of the output of the OpenSSL command shows three certificates numbered 0, 1, and 2(not 2 anymore). Each certificate has a subject, s, and an issuer, i. The first certificate, number 0, is called the end-entity certificate. The subject line tells us it\u2019s valid for any subdomain of google.com because its subject is set to *.google.com. $ openssl s_client -connect www.google.com:443 -CApath /etc/ssl/certs CONNECTED(00000005) depth=2 OU = GlobalSign Root CA - R2, O = GlobalSign, CN = GlobalSign verify return:1 depth=1 C = US, O = Google Trust Services, CN = GTS CA 1O1 verify return:1 depth=0 C = US, ST = California, L = Mountain View, O = Google LLC, CN = www.google.com verify return:1 --- Certificate chain 0 s:/C=US/ST=California/L=Mountain View/O=Google LLC/CN=www.google.com i:/C=US/O=Google Trust Services/CN=GTS CA 1O1 1 s:/C=US/O=Google Trust Services/CN=GTS CA 1O1 i:/OU=GlobalSign Root CA - R2/O=GlobalSign/CN=GlobalSign --- Server certificate The issuer line indicates it\u2019s issued by Google Internet Authority G2, which also happens to be the subject of the second certificate, number 1 What the OpenSSL command line doesn\u2019t show here is the trust store that contains the list of CA certificates trusted by the system OpenSSL runs on. The public certificate of GlobalSign Authority must be present in the system\u2019s trust store to close the verification chain. This is called a chain of trust, and figure below summarizes its behavior at a high level. High-level view of the concept of chain of trust applied to verifying the authenticity of a website. The Root CA in the Firefox trust store provides the initial trust to verify the entire chain and trust the end-entity certificate. TLS Handshake The client sends a HELLO message to the server with a list of protocols and algorithms it supports. The server says HELLO back and sends its chain of certificates. Based on the capabilities of the client, the server picks a cipher suite. If the cipher suite supports ephemeral key exchange, like ECDHE does(ECDHE is an algorithm known as the Elliptic Curve Diffie-Hellman Exchange), the server and the client negotiate a pre master key with the Diffie-Hellman algorithm. The pre master key is never sent over the wire. The client and server create a session key that will be used to encrypt the data transiting through the connection. At the end of the handshake, both parties possess a secret session key used to encrypt data for the rest of the connection. This is what OpenSSL refers to as Master-Key NOTE There are 3 versions of TLS , TLS 1.0, 1.1 1.2 TLS 1.0 was released in 1999, making it a nearly two-decade-old protocol. It has been known to be vulnerable to attacks\u2014such as BEAST and POODLE\u2014for years, in addition to supporting weak cryptography, which doesn\u2019t keep modern-day connections sufficiently secure. TLS 1.1 is the forgotten \u201cmiddle child.\u201d It also has bad cryptography like its younger sibling. In most software it was leapfrogged by TLS 1.2 and it\u2019s rare to see TLS 1.1 used. \u201cPerfect\u201d Forward Secrecy The term \u201cephemeral\u201d in the key exchange provides an important security feature mis-named perfect forward secrecy (PFS) or just \u201cForward Secrecy\u201d. In a non-ephemeral key exchange, the client sends the pre-master key to the server by encrypting it with the server\u2019s public key. The server then decrypts the pre-master key with its private key. If, at a later point in time, the private key of the server is compromised, an attacker can go back to this handshake, decrypt the pre-master key, obtain the session key, and decrypt the entire traffic. Non-ephemeral key exchanges are vulnerable to attacks that may happen in the future on recorded traffic. And because people seldom change their password, decrypting data from the past may still be valuable for an attacker. An ephemeral key exchange like DHE, or its variant on elliptic curve, ECDHE, solves this problem by not transmitting the pre-master key over the wire. Instead, the pre-master key is computed by both the client and the server in isolation, using nonsensitive information exchanged publicly. Because the pre-master key can\u2019t be decrypted later by an attacker, the session key is safe from future attacks: hence, the term perfect forward secrecy. Keys are changed every X blocks along the stream. That prevents an attacker from simply sniffing the stream and applying brute force to crack the whole thing. \"Forward secrecy\" means that just because I can decrypt block M, does not mean that I can decrypt block Q Downside: The downside to PFS is that all those extra computational steps induce latency on the handshake and slow the user down. To avoid repeating this expensive work at every connection, both sides cache the session key for future use via a technique called session resumption. This is what the session-ID and TLS ticket are for: they allow a client and server that share a session ID to skip over the negotiation of a session key, because they already agreed on one previously, and go directly to exchanging data securely.","title":"Fundamentals of Security"},{"location":"security/fundamentals/#part-i-fundamentals","text":"","title":"Part I: Fundamentals"},{"location":"security/fundamentals/#introduction-to-security-overview-for-sre","text":"If you look closely, both Site Reliability Engineering and Security Engineering are concerned with keeping a system usable. Issues like broken releases, capacity shortages, and misconfigurations can make a system unusable (at least temporarily). Security or privacy incidents that break the trust of users also undermine the usefulness of a system. Consequently, system security should be top of mind for SREs. SREs should be involved in both significant design discussions and actual system changes. They have quite a big role in System design hence are quite sometimes the first line of defense. SRE\u2019s help in preventing bad design implementations which can affect the overall security of the infrastructure. Successfully designing, implementing, and maintaining systems requires a commitment to the full system lifecycle . This commitment is possible only when security and reliability are central elements in the architecture of systems. Core Pillars of Information Security : Confidentiality \u2013 only allow access to data for which the user is permitted Integrity \u2013 ensure data is not tampered or altered by unauthorized users Availability \u2013 ensure systems and data are available to authorized users when they need it Thinking like a Security Engineer When starting a new application or re-factoring an existing application, you should consider each functional feature, and consider: Is the process surrounding this feature as safe as possible? In other words, is this a flawed process? If I were evil, how would I abuse this feature? Or more specifically failing to address how a feature can be abused can cause design flaws. Is the feature required to be on by default? If so, are there limits or options that could help reduce the risk from this feature? Security Principles By OWASP (Open Web Application Security Project) Minimize attack surface area : Every feature that is added to an application adds a certain amount of risk to the overall application. The aim for secure development is to reduce the overall risk by reducing the attack surface area. For example, a web application implements online help with a search function. The search function may be vulnerable to SQL injection attacks. If the help feature was limited to authorized users, the attack likelihood is reduced. If the help feature\u2019s search function was gated through centralized data validation routines, the ability to perform SQL injection is dramatically reduced. However, if the help feature was re-written to eliminate the search function (through better user interface, for example), this almost eliminates the attack surface area, even if the help feature was available to the Internet at large. Establish secure defaults: There are many ways to deliver an \u201cout of the box\u201d experience for users. However, by default, the experience should be secure, and it should be up to the user to reduce their security \u2013 if they are allowed. For example, by default, password aging and complexity should be enabled. Users might be allowed to turn these two features off to simplify their use of the application and increase their risk. Default Passwords of routers, IOT devices should be changed Principle of Least privilege The principle of least privilege recommends that accounts have the least amount of privilege required to perform their business processes. This encompasses user rights, resource permissions such as CPU limits, memory, network, and file system permissions. For example, if a middleware server only requires access to the network, read access to a database table, and the ability to write to a log, this describes all the permissions that should be granted. Under no circumstances should the middleware be granted administrative privileges. Principle of Defense in depth The principle of defense in depth suggests that where one control would be reasonable, more controls that approach risks in different fashions are better. Controls, when used in-depth, can make severe vulnerabilities extraordinarily difficult to exploit and thus unlikely to occur. With secure coding, this may take the form of tier-based validation, centralized auditing controls, and requiring users to be logged on all pages. For example, a flawed administrative interface is unlikely to be vulnerable to an anonymous attack if it correctly gates access to production management networks, checks for administrative user authorization, and logs all access. Fail securely Applications regularly fail to process transactions for many reasons. How they fail can determine if an application is secure or not. - If either codeWhichMayFail() or isUserInRole fails or throws an exception, the user is an admin by default. This is obviously a security risk. Don\u2019t trust services Many organizations utilize the processing capabilities of third-party partners, who more than likely have different security policies and posture than you. It is unlikely that you can influence or control any external third party, whether they are home users or major suppliers or partners. Therefore, the implicit trust of externally run systems is not warranted. All external systems should be treated in a similar fashion. For example, a loyalty program provider provides data that is used by Internet Banking, providing the number of reward points and a small list of potential redemption items. However, the data should be checked to ensure that it is safe to display to end-users, and that the reward points are a positive number, and not improbably large. Separation of duties The key to fraud control is the separation of duties. For example, someone who requests a computer cannot also sign for it, nor should they directly receive the computer. This prevents the user from requesting many computers and claiming they never arrived. Certain roles have different levels of trust than normal users. In particular, administrators are different from normal users. In general, administrators should not be users of the application. For example, an administrator should be able to turn the system on or off, set password policy but shouldn\u2019t be able to log on to the storefront as a super privileged user, such as being able to \u201cbuy\u201d goods on behalf of other users. Avoid security by obscurity Security through obscurity is a weak security control, and nearly always fails when it is the only control. This is not to say that keeping secrets is a bad idea, it simply means that the security of systems should not be reliant upon keeping details hidden. For example, the security of an application should not rely upon knowledge of the source code being kept secret. The security should rely upon many other factors, including reasonable password policies, defense in depth, business transaction limits, solid network architecture, and fraud, and audit controls. A practical example is Linux. Linux\u2019s source code is widely available, and yet when properly secured, Linux is a secure and robust operating system. Keep security simple Attack surface area and simplicity go hand in hand. Certain software engineering practices prefer overly complex approaches to what would otherwise be a relatively straightforward and simple design. Developers should avoid the use of double negatives and complex architectures when a simpler approach would be faster and simpler. For example, although it might be fashionable to have a slew of singleton entity beans running on a separate middleware server, it is more secure and faster to simply use global variables with an appropriate mutex mechanism to protect against race conditions. Fix security issues correctly Once a security issue has been identified, it is important to develop a test for it and to understand the root cause of the issue. When design patterns are used, it is likely that the security issue is widespread amongst all codebases, so developing the right fix without introducing regressions is essential. For example, a user has found that they can see another user\u2019s balance by adjusting their cookie. The fix seems to be relatively straightforward, but as the cookie handling code is shared among all applications, a change to just one application will trickle through to all other applications. The fix must, therefore, be tested on all affected applications. Reliability Security Reliability and security are both crucial components of a truly trustworthy system,but building systems that are both reliable and secure is difficult. While the requirements for reliability and security share many common properties, they also require different design considerations. It is easy to miss the subtle interplay between reliability and security that can cause unexpected outcomes Ex: A password management application failure was triggered by a reliability problem i.e poor load-balancing and load-shedding strategies and its recovery was later complicated by multiple measures (HSM mechanism which needs to be plugged into server racks , which works as an authentication the HSM token supposedly locked inside a case.. the problem can be further elongated ) designed to increase the security of the system.","title":"Introduction to Security Overview for SRE"},{"location":"security/fundamentals/#authentication-vs-authorization","text":"Authentication is the act of validating that users are who they claim to be. Passwords are the most common authentication factor\u2014if a user enters the correct password, the system assumes the identity is valid and grants access. Other technologies such as One-Time Pins, authentication apps, and even biometrics can also be used to authenticate identity. In some instances, systems require the successful verification of more than one factor before granting access. This multi-factor authentication (MFA) requirement is often deployed to increase security beyond what passwords alone can provide. Authorization in system security is the process of giving the user permission to access a specific resource or function. This term is often used interchangeably with access control or client privilege. Giving someone permission to download a particular file on a server or providing individual users with administrative access to an application are good examples. In secure environments, authorization must always follow authentication, users should first prove that their identities are genuine before an organization\u2019s administrators grant them access to the requested resources.","title":"Authentication vs Authorization"},{"location":"security/fundamentals/#common-authentication-flow-local-authentication","text":"The user registers using an identifier like username/email/mobile The application stores user credentials in the database The application sends a verification email/message to validate the registration Post successful registration, the user enters credentials for logging in On successful authentication, the user is allowed access to specific resources","title":"Common authentication flow (local authentication)"},{"location":"security/fundamentals/#openidoauth","text":"OpenID is an authentication protocol that allows us to authenticate users without using a local auth system. In such a scenario, a user has to be registered with an OpenID Provider and the same provider should be integrated with the authentication flow of your application. To verify the details, we have to forward the authentication requests to the provider. On successful authentication, we receive a success message and/or profile details with which we can execute the necessary flow. OAuth is an authorization mechanism that allows your application user access to a provider(Gmail/Facebook/Instagram/etc). On successful response, we (your application) receive a token with which the application can access certain APIs on behalf of a user. OAuth is convenient in case your business use case requires some certain user-facing APIs like access to Google Drive or sending tweets on your behalf. Most OAuth 2.0 providers can be used for pseudo authentication. Having said that, it can get pretty complicated if you are using multiple OAuth providers to authenticate users on top of the local authentication system.","title":"OpenID/OAuth"},{"location":"security/fundamentals/#cryptography","text":"It is the science and study of hiding any text in such a way that only the intended recipients or authorized persons can read it and that any text can even use things such as invisible ink or the mechanical cryptography machines of the past. Cryptography is necessary for securing critical or proprietary information and is used to encode private data messages by converting some plain text into ciphertext. At its core, there are two ways of doing this, more advanced methods are all built upon.","title":"Cryptography"},{"location":"security/fundamentals/#ciphers","text":"Ciphers are the cornerstone of cryptography. A cipher is a set of algorithms that performs encryption or decryption on a message. An encryption algorithm (E) takes a secret key (k) and a message (m), and produces a ciphertext (c). Similarly, a Decryption algorithm (D) takes a secret key (K) and the previous resulting Ciphertext (C). They are represented as follows: This also means that in order for it to be a cipher, it must satisfy the consistency equation as follows, making it possible to decrypt. Stream Ciphers: The message is broken into characters or bits and enciphered with a key or keystream(should be random and generated independently of the message stream) that is as long as the plaintext bitstream. sIf the keystream is random, this scheme would be unbreakable unless the keystream was acquired, making it unconditionally secure. The keystream must be provided to both parties in a secure way to prevent its release. Block Ciphers: Block ciphers \u2014 process messages in blocks, each of which is then encrypted or decrypted. A block cipher is a symmetric cipher in which blocks of plaintext are treated as a whole and used to produce ciphertext blocks. The block cipher takes blocks that are b bits long and encrypts them to blocks that are also b bits long. Block sizes are typically 64 or 128 bits long. Encryption Secret Key (Symmetric Key) : the same key is used for encryption and decryption Public Key (Asymmetric Key) in an asymmetric, the encryption and decryption keys are different but related. The encryption key is known as the public key and the decryption key is known as the private key. The public and private keys are known as a key pair. Symmetric Key Encryption DES The Data Encryption Standard (DES) has been the worldwide encryption standard for a long time. IBM developed DES in 1975, and it has held up remarkably well against years of cryptanalysis. DES is a symmetric encryption algorithm with a fixed key length of 56 bits. The algorithm is still good, but because of the short key length, it is susceptible to brute-force attacks that have sufficient resources. DES usually operates in block mode, whereby it encrypts data in 64-bit blocks. The same algorithm and key are used for both encryption and decryption. Because DES is based on simple mathematical functions, it can be easily implemented and accelerated in hardware. Triple DES With advances in computer processing power, the original 56-bit DES key became too short to withstand an attacker with even a limited budget. One way of increasing the effective key length of DES without changing the well-analyzed algorithm itself is to use the same algorithm with different keys several times in a row. The technique of applying DES three times in a row to a plain text block is called Triple DES (3DES). The 3DES technique is shown in Figure. Brute-force attacks on 3DES are considered unfeasible today. Because the basic algorithm has been tested in the field for more than 25 years, it is considered to be more trustworthy than its predecessor. AES On October 2, 2000, The U.S. National Institute of Standards and Technology (NIST) announced the selection of the Rijndael cipher as the AES algorithm. This cipher, developed by Joan Daemen and Vincent Rijmen, has a variable block length and key length. The algorithm currently specifies how to use keys with a length of 128, 192, or 256 bits to encrypt blocks with a length of 128, 192, or 256 bits (all nine combinations of key length and block length are possible). Both block and key lengths can be extended easily to multiples of 32 bits. AES was chosen to replace DES and 3DES because they are either too weak (DES, in terms of key length) or too slow (3DES) to run on modern, efficient hardware. AES is more efficient and much faster, usually by a factor of 5 compared to DES on the same hardware. AES is also more suitable for high throughput, especially if pure software encryption is used. However, AES is a relatively young algorithm, and as the golden rule of cryptography states, \u201cA more mature algorithm is always more trusted.\u201d Asymmetric Key Algorithm In a symmetric key system, Alice first puts the secret message in a box and then padlocks the box using a lock to which she has a key. She then sends the box to Bob through regular mail. When Bob receives the box, he uses an identical copy of Alice's key (which he has obtained previously) to open the box and read the message. In an asymmetric key system, instead of opening the box when he receives it, Bob simply adds his own personal lock to the box and returns the box through public mail to Alice. Alice uses her key to remove her lock and returns the box to Bob, with Bob's lock still in place. Finally, Bob uses his key to remove his lock and reads the message from Alice. The critical advantage in an asymmetric system is that Alice never needs to send a copy of her key to Bob. This reduces the possibility that a third party (for example, an unscrupulous postmaster) can copy the key while it is in transit to Bob, allowing that third party to spy on all future messages sent by Alice. In addition, if Bob is careless and allows someone else to copy his key, Alice's messages to Bob are compromised, but Alice's messages to other people remain secret NOTE : In terms of TLS key exchange, this is the common approach. Diffie-Hellman The protocol has two system parameters, p and g. They are both public and may be used by everybody. Parameter p is a prime number, and parameter g (usually called a generator) is an integer that is smaller than p, but with the following property: For every number n between 1 and p \u2013 1 inclusive, there is a power k of g such that n = gk mod p. Diffie Hellman algorithm is an asymmetric algorithm used to establish a shared secret for a symmetric key algorithm. Nowadays most of the people use hybrid cryptosystem i.e, combination of symmetric and asymmetric encryption. Asymmetric Encryption is used as a technique in key exchange mechanism to share secret key and after the key is shared between sender and receiver, the communication will take place using symmetric encryption. The shared secret key will be used to encrypt the communication. Refer: https://medium.com/@akhigbemmanuel/what-is-the-diffie-hellman-key-exchange-algorithm-84d60025a30d RSA The RSA algorithm is very flexible and has a variable key length where, if necessary, speed can be traded for the level of security of the algorithm. The RSA keys are usually 512 to 2048 bits long. RSA has withstood years of extensive cryptanalysis. Although those years neither proved nor disproved RSA's security, they attest to a confidence level in the algorithm. RSA security is based on the difficulty of factoring very large numbers. If an easy method of factoring these large numbers were discovered, the effectiveness of RSA would be destroyed. Refer : https://medium.com/curiositypapers/a-complete-explanation-of-rsa-asymmetric-encryption-742c5971e0f NOTE : RSA Keys can be used for key exchange just like Deffie Hellman Hashing Algorithms Hashing is one of the mechanisms used for data integrity assurance. Hashing is based on a one-way mathematical function, which is relatively easy to compute but significantly harder to reverse. A hash function, which is a one-way function to input data to produce a fixed-length digest (fingerprint) of output data. The digest is cryptographically strong; that is, it is impossible to recover input data from its digest. If the input data changes just a little, the digest (fingerprint) changes substantially in what is called an avalanche effect. More: https://medium.com/@rauljordan/the-state-of-hashing-algorithms-the-why-the-how-and-the-future-b21d5c0440de https://medium.com/@StevieCEllis/the-beautiful-hash-algorithm-f18d9d2b84fb MD5 MD5 is a one-way function with which it is easy to compute the hash from the given input data, but it is unfeasible to compute input data given only a hash. SHA-1 MD5 is considered less secure than SHA-1 because MD5 has some weaknesses. HA-1 also uses a stronger, 160-bit digest, which makes MD5 the second choice as hash methods are concerned. The algorithm takes a message of less than 264 bits in length and produces a 160-bit message digest. This algorithm is slightly slower than MD5. NOTE : SHA-1 is also recently demonstrated to be broken, Minimum current recommendation is SHA-256 Digital Certificates Digital signatures, provide a means to digitally authenticate devices and individual users. In public-key cryptography, such as the RSA encryption system, each user has a key-pair containing both a public key and a private key. The keys act as complements, and anything encrypted with one of the keys can be decrypted with the other. In simple terms, a signature is formed when data is encrypted with a user's private key. The receiver verifies the signature by decrypting the message with the sender's public key. Key management is often considered the most difficult task in designing and implementing cryptographic systems. Businesses can simplify some of the deployment and management issues that are encountered with secured data communications by employing a Public Key Infrastructure (PKI). Because corporations often move security-sensitive communications across the Internet, an effective mechanism must be implemented to protect sensitive information from the threats presented on the Internet. PKI provides a hierarchical framework for managing digital security attributes. Each PKI participant holds a digital certificate that has been issued by a CA (either public or private). The certificate contains a number of attributes that are used when parties negotiate a secure connection. These attributes must include the certificate validity period, end-host identity information, encryption keys that will be used for secure communications, and the signature of the issuing CA. Optional attributes may be included, depending on the requirements and capability of the PKI. A CA can be a trusted third party, such as VeriSign or Entrust, or a private (in-house) CA that you establish within your organization. The fact that the message could be decrypted using the sender's public key means that the holder of the private key created the message. This process relies on the receiver having a copy of the sender's public key and knowing with a high degree of certainty that it really does belong to the sender and not to someone pretending to be the sender. To validate the CA's signature, the receiver must know the CA's public key. Normally, this is handled out-of-band or through an operation performed during installation of the certificate. For instance, most web browsers are configured with the root certificates of several CAs by default. CA Enrollment process The end host generates a private-public key pair. The end host generates a certificate request, which it forwards to the CA. Manual human intervention is required to approve the enrollment request, which is received by the CA. After the CA operator approves the request, the CA signs the certificate request with its private key and returns the completed certificate to the end host. The end host writes the certificate into a nonvolatile storage area (PC hard disk or NVRAM on Cisco routers). Refer : https://www.ssh.com/manuals/server-zos-product/55/ch06s03s01.html","title":"Ciphers"},{"location":"security/fundamentals/#login-security","text":"","title":"Login Security"},{"location":"security/fundamentals/#ssh","text":"SSH, the Secure Shell, is a popular, powerful, software-based approach to network security. Whenever data is sent by a computer to the network, SSH automatically encrypts (scrambles) it. Then, when the data reaches its intended recipient, SSH automatically decrypts (unscrambles) it. The result is transparent encryption: users can work normally, unaware that their communications are safely encrypted on the network. In addition, SSH can use modern, secure encryption algorithms based on how it's being configured and is effective enough to be found within mission-critical applications at major corporations. SSH has a client/server architecture An SSH server program, typically installed and run by a system administrator, accepts or rejects incoming connections to its host computer. Users then run SSH client programs, typically on other computers, to make requests of the SSH server, such as \u201cPlease log me in,\u201d \u201cPlease send me a file,\u201d or \u201cPlease execute this command.\u201d All communications between clients and servers are securely encrypted and protected from modification. What SSH is not: Although SSH stands for Secure Shell, it is not a true shell in the sense of the Unix Bourne shell and C shell. It is not a command interpreter, nor does it provide wildcard expansion, command history, and so forth. Rather, SSH creates a channel for running a shell on a remote computer, with end-to-end encryption between the two systems. The major features and guarantees of the SSH protocol are: Privacy of your data, via strong encryption Integrity of communications, guaranteeing they haven\u2019t been altered Authentication, i.e., proof of identity of senders and receivers Authorization, i.e., access control to accounts Forwarding or tunneling to encrypt other TCP/IP-based sessions","title":"SSH"},{"location":"security/fundamentals/#kerberos","text":"According to Greek mythology Kerberos (Cerberus) was the gigantic, three-headed dog that guards the gates of the underworld to prevent the dead from leaving. So when it comes to Computer Science, Kerberos is a network authentication protocol, and is currently the default authentication technology used by Microsoft Active Directory to authenticate users to services within a local area network. Kerberos uses symmetric key cryptography and requires trusted third-party authentication service to verify user identities. So they used the name of Kerberos for their computer network authentication protocol as the three heads of the Kerberos represent: a client : A user/ a service a server : Kerberos protected hosts reside - a Key Distribution Center (KDC), which acts as the trusted third-party authentication service. The KDC includes following two servers: Authentication Server (AS) that performs the initial authentication and issues ticket-granting tickets (TGT) for users. Ticket-Granting Server (TGS) that issues service tickets that are based on the initial ticket-granting tickets (TGT).","title":"Kerberos"},{"location":"security/fundamentals/#certificate-chain","text":"The first part of the output of the OpenSSL command shows three certificates numbered 0, 1, and 2(not 2 anymore). Each certificate has a subject, s, and an issuer, i. The first certificate, number 0, is called the end-entity certificate. The subject line tells us it\u2019s valid for any subdomain of google.com because its subject is set to *.google.com. $ openssl s_client -connect www.google.com:443 -CApath /etc/ssl/certs CONNECTED(00000005) depth=2 OU = GlobalSign Root CA - R2, O = GlobalSign, CN = GlobalSign verify return:1 depth=1 C = US, O = Google Trust Services, CN = GTS CA 1O1 verify return:1 depth=0 C = US, ST = California, L = Mountain View, O = Google LLC, CN = www.google.com verify return:1 --- Certificate chain 0 s:/C=US/ST=California/L=Mountain View/O=Google LLC/CN=www.google.com i:/C=US/O=Google Trust Services/CN=GTS CA 1O1 1 s:/C=US/O=Google Trust Services/CN=GTS CA 1O1 i:/OU=GlobalSign Root CA - R2/O=GlobalSign/CN=GlobalSign --- Server certificate The issuer line indicates it\u2019s issued by Google Internet Authority G2, which also happens to be the subject of the second certificate, number 1 What the OpenSSL command line doesn\u2019t show here is the trust store that contains the list of CA certificates trusted by the system OpenSSL runs on. The public certificate of GlobalSign Authority must be present in the system\u2019s trust store to close the verification chain. This is called a chain of trust, and figure below summarizes its behavior at a high level. High-level view of the concept of chain of trust applied to verifying the authenticity of a website. The Root CA in the Firefox trust store provides the initial trust to verify the entire chain and trust the end-entity certificate.","title":"Certificate Chain"},{"location":"security/fundamentals/#tls-handshake","text":"The client sends a HELLO message to the server with a list of protocols and algorithms it supports. The server says HELLO back and sends its chain of certificates. Based on the capabilities of the client, the server picks a cipher suite. If the cipher suite supports ephemeral key exchange, like ECDHE does(ECDHE is an algorithm known as the Elliptic Curve Diffie-Hellman Exchange), the server and the client negotiate a pre master key with the Diffie-Hellman algorithm. The pre master key is never sent over the wire. The client and server create a session key that will be used to encrypt the data transiting through the connection. At the end of the handshake, both parties possess a secret session key used to encrypt data for the rest of the connection. This is what OpenSSL refers to as Master-Key NOTE There are 3 versions of TLS , TLS 1.0, 1.1 1.2 TLS 1.0 was released in 1999, making it a nearly two-decade-old protocol. It has been known to be vulnerable to attacks\u2014such as BEAST and POODLE\u2014for years, in addition to supporting weak cryptography, which doesn\u2019t keep modern-day connections sufficiently secure. TLS 1.1 is the forgotten \u201cmiddle child.\u201d It also has bad cryptography like its younger sibling. In most software it was leapfrogged by TLS 1.2 and it\u2019s rare to see TLS 1.1 used.","title":"TLS Handshake"},{"location":"security/fundamentals/#perfect-forward-secrecy","text":"The term \u201cephemeral\u201d in the key exchange provides an important security feature mis-named perfect forward secrecy (PFS) or just \u201cForward Secrecy\u201d. In a non-ephemeral key exchange, the client sends the pre-master key to the server by encrypting it with the server\u2019s public key. The server then decrypts the pre-master key with its private key. If, at a later point in time, the private key of the server is compromised, an attacker can go back to this handshake, decrypt the pre-master key, obtain the session key, and decrypt the entire traffic. Non-ephemeral key exchanges are vulnerable to attacks that may happen in the future on recorded traffic. And because people seldom change their password, decrypting data from the past may still be valuable for an attacker. An ephemeral key exchange like DHE, or its variant on elliptic curve, ECDHE, solves this problem by not transmitting the pre-master key over the wire. Instead, the pre-master key is computed by both the client and the server in isolation, using nonsensitive information exchanged publicly. Because the pre-master key can\u2019t be decrypted later by an attacker, the session key is safe from future attacks: hence, the term perfect forward secrecy. Keys are changed every X blocks along the stream. That prevents an attacker from simply sniffing the stream and applying brute force to crack the whole thing. \"Forward secrecy\" means that just because I can decrypt block M, does not mean that I can decrypt block Q Downside: The downside to PFS is that all those extra computational steps induce latency on the handshake and slow the user down. To avoid repeating this expensive work at every connection, both sides cache the session key for future use via a technique called session resumption. This is what the session-ID and TLS ticket are for: they allow a client and server that share a session ID to skip over the negotiation of a session key, because they already agreed on one previously, and go directly to exchanging data securely.","title":"\u201cPerfect\u201d Forward Secrecy"},{"location":"security/intro/","text":"Security Fundamental classroom courseware for people getting started with SRE developing an understanding of the need for security in day to day operations Target Audience The material is suitable for new SRE hires or graduate computer science majors straight out of college, anyone who has a basic technical background, or readers who have a basic understanding of IT security and want to expand their knowledge. The approach being covered here deals with the fundamentals of computer security in the modern IT landscape moreover it sheds light on most of the dangerous \"things\" out there on public internet which are potentially a gateway to compromising systems. As an SRE, you are expected to design, build and develop products, this course will give you that \u2018security knob\u2019 into your thinking and problem-solving approach which is expected to be turned on as a critical area that always takes precedence over anything else. Pre Requirements Basics of Linux fundamentals command line usage Networking Module What to expect from this training The course covers fundamentals of information security along with touching on subjects of system security, network web security. The aim of this course is to get familiar with the basics of information security in day to day operations then as an SRE develop the mindset of ensuring that security takes a front-seat while developing solutions. The course also serves as an introduction to common risks and best practices along with practical ways to find out vulnerable systems and loopholes which might become compromised if not secured. What is not covered under this training The courseware is not an ethical hacking workshop or a very deep dive into the fundamentals of the problems. The course does not deal with hacking or breaking into systems but rather an approach on how to ensure you don\u2019t get into those situations and also to make you aware of different ways a system can be compromised. Training Content Part I: Fundamentals Part II: Network Security Part III: Threats, Attacks Defense PART IV: Writing Secure Code More Post Training asks/ Further Reading CTF Events like : https://github.com/apsdehal/awesome-ctf Penetration Testing : https://github.com/enaqx/awesome-pentest Threat Intelligence : https://github.com/hslatman/awesome-threat-intelligence Threat Detection Hunting : https://github.com/0x4D31/awesome-threat-detection Web Security: https://github.com/qazbnm456/awesome-web-security Building Secure and Reliable Systems : https://landing.google.com/sre/resources/foundationsandprinciples/srs-book/","title":"Inro"},{"location":"security/intro/#security","text":"","title":"Security"},{"location":"security/intro/#fundamental-classroom-courseware-for-people-getting-started-with-sre-developing-an-understanding-of-the-need-for-security-in-day-to-day-operations","text":"","title":"Fundamental classroom courseware for people getting started with SRE & developing an understanding of the need for security in day to day operations"},{"location":"security/intro/#target-audience","text":"The material is suitable for new SRE hires or graduate computer science majors straight out of college, anyone who has a basic technical background, or readers who have a basic understanding of IT security and want to expand their knowledge. The approach being covered here deals with the fundamentals of computer security in the modern IT landscape moreover it sheds light on most of the dangerous \"things\" out there on public internet which are potentially a gateway to compromising systems. As an SRE, you are expected to design, build and develop products, this course will give you that \u2018security knob\u2019 into your thinking and problem-solving approach which is expected to be turned on as a critical area that always takes precedence over anything else.","title":"Target Audience"},{"location":"security/intro/#pre-requirements","text":"Basics of Linux fundamentals command line usage Networking Module","title":"Pre Requirements"},{"location":"security/intro/#what-to-expect-from-this-training","text":"The course covers fundamentals of information security along with touching on subjects of system security, network web security. The aim of this course is to get familiar with the basics of information security in day to day operations then as an SRE develop the mindset of ensuring that security takes a front-seat while developing solutions. The course also serves as an introduction to common risks and best practices along with practical ways to find out vulnerable systems and loopholes which might become compromised if not secured.","title":"What to expect from this training"},{"location":"security/intro/#what-is-not-covered-under-this-training","text":"The courseware is not an ethical hacking workshop or a very deep dive into the fundamentals of the problems. The course does not deal with hacking or breaking into systems but rather an approach on how to ensure you don\u2019t get into those situations and also to make you aware of different ways a system can be compromised.","title":"What is not covered under this training"},{"location":"security/intro/#training-content","text":"Part I: Fundamentals Part II: Network Security Part III: Threats, Attacks Defense PART IV: Writing Secure Code More","title":"Training Content"},{"location":"security/intro/#post-training-asks-further-reading","text":"CTF Events like : https://github.com/apsdehal/awesome-ctf Penetration Testing : https://github.com/enaqx/awesome-pentest Threat Intelligence : https://github.com/hslatman/awesome-threat-intelligence Threat Detection Hunting : https://github.com/0x4D31/awesome-threat-detection Web Security: https://github.com/qazbnm456/awesome-web-security Building Secure and Reliable Systems : https://landing.google.com/sre/resources/foundationsandprinciples/srs-book/","title":"Post Training asks/ Further Reading"},{"location":"security/network_security/","text":"Part II : Network Security Introduction TCP/IP is the dominant networking technology today. It is a five-layer architecture. These layers are, from top to bottom, the application layer, the transport layer (TCP), the network layer (IP), the data-link layer, and the physical layer. In addition to TCP/IP, there also are other networking technologies. For convenience, we use the OSI network model to represent non-TCP/IP network technologies. Different networks are interconnected using gateways. A gateway can be placed at any layer. The OSI model is a seven-layer architecture. The OSI architecture is similar to the TCP/IP architecture, except that the OSI model specifies two additional layers between the application layer and the transport layer in the TCP/IP architecture. These two layers are the presentation layer and the session layer. Figure 5.1 shows the relation between the TCP/IP layers and the OSI layers. The application layer in TCP/IP corresponds to the application layer and the presentation layer in OSI. The transport layer in TCP/IP corresponds to the session layer and the transport layer in OSI. The remaining three layers in the TCP/IP architecture are one-to-one correspondent to the remaining three layers in the OSI model. Correspondence between layers of the TCP/IP architecture and the OSI model. Also shown are placements of cryptographic algorithms in network layers, where the dotted arrows indicate actual communications of cryptographic algorithms The functionalities of OSI layers are briefly described as follows: The application layer serves as an interface between applications and network programs. It supports application programs and end-user processing. Common application-layer programs include remote logins, file transfer, email, and Web browsing. The presentation layer is responsible for dealing with data that is formed differently. This protocol layer allows application-layer programs residing on different sides of a communication channel with different platforms to understand each other's data formats regardless of how they are presented. The session layer is responsible for creating, managing, and closing a communication connection. The transport layer is responsible for providing reliable connections, such as packet sequencing, traffic control, and congestion control. The network layer is responsible for routing device-independent data packets from the current hop to the next hop. The data-link layer is responsible for encapsulating device-independent data packets into device-dependent data frames. It has two sublayers: logical link control and media access control. The physical layer is responsible for transmitting device-dependent frames through some physical media. Starting from the application layer, data generated from an application program is passed down layer-by-layer to the physical layer. Data from the previous layer is enclosed in a new envelope at the current layer, where the data from the previous layer is also just an envelope containing the data from the layer before it. This is similar to enclosing a smaller envelope in a larger one. The envelope added at each layer contains sufficient information for handling the packet. Application-layer data are divided into blocks small enough to be encapsulated in an envelope at the next layer. Application data blocks are \u201cdressed up\u201d in the TCP/IP architecture according to the following basic steps. At the sending side, an application data block is encapsulated in a TCP packet when it is passed down to the TCP layer. In other words, a TCP packet consists of a header and a payload, where the header corresponds to the TCP envelope and the payload is the application data block. Likewise, the TCP packet will be encapsulated in an IP packet when it is passed down to the IP layer. An IP packet consists of a header and a payload, which is the TCP packet passed down from the TCP layer. The IP packet will be encapsulated in a device-dependent frame (e.g., an Ethernet frame) when it is passed down to the data-link layer. A frame has a header, and it may also have a trailer. For example, in addition to having a header, an Ethernet frame also has a 32-bit cyclic redundancy check (CRC) trailer. When it is passed down to the physical layer, a frame will be transformed to a sequence of media signals for transmission Flow Diagram of a Packet Generation At the destination side, the medium signals are converted by the physical layer into a frame, which is passed up to the data-link layer. The data-link layer passes the frame payload (i.e., the IP packet encapsulated in the frame) up to the IP layer. The IP layer passes the IP payload, namely, the TCP packet encapsulated in the IP packet, up to the TCP layer. The TCP layer passes the TCP payload, namely, the application data block, up to the application layer. When a packet arrives at a router, it only goes up to the IP layer, where certain fields in the IP header are modified (e.g., the value of TTL is decreased by 1). This modified packet is then passed back down layer-by-layer to the physical layer for further transmission. Public Key Infrastructure To deploy cryptographic algorithms in network applications, we need a way to distribute secret keys using open networks. Public-key cryptography is the best way to distribute these secret keys. In order to use public-key cryptography, we need to build a public-key infrastructure (PKI) to support and manage public-key certificates and certificate authority (CA) networks. In particular, PKIs are set up to perform the following functions: Determine the legitimacy of users before issuing public-key certificates to them. Issue public-key certificates upon user requests. Extend public-key certificates valid time upon user requests. Revoke public-key certificates upon users' requests or when the corresponding private keys are compromised. Store and manage public-key certificates. Prevent digital signature signers from denying their signatures. Support CA networks to allow different CAs to authenticate public-key certificates issued by other CAs. X.509: https://certificatedecoder.dev/?gclid=EAIaIQobChMI0M731O6G6gIVVSQrCh04bQaAEAAYASAAEgKRkPD_BwE IPsec: A Security Protocol at the Network Layer IPsec is a major security protocol at the network layer IPsec provides a potent platform for constructing virtual private networks (VPN). VPNs are private networks overlayed on public networks. The purpose of deploying cryptographic algorithms at the network layer is to encrypt or authenticate IP packets (either just the payloads or the whole packets). IPsec also specifies how to exchange keys. Thus, IPsec consists of authentication protocols, encryption protocols, and key exchange protocols. They are referred to, respectively, as authentication header (AH), encapsulating security payload (ESP), and Internet key exchange (IKE). PGP S/MIME : Email Security There are a number of security protocols at the application layer. The most used of these protocols are email security protocols namely PGP and S/MIME. SMTP (\u201cSimple Mail Transfer Protocol\u201d) is used for sending and delivering from a client to a server via port 25: it\u2019s the outgoing server. On the contrary, POP (\u201cPost Office Protocol\u201d) allows the user to pick up the message and download it into his own inbox: it\u2019s the incoming server. The latest version of the Post Office Protocol is named POP3, and it\u2019s been used since 1996; it uses port 110 PGP PGP implements all major cryptographic algorithms, the ZIP compression algorithm, and the Base64 encoding algorithm. It can be used to authenticate a message, encrypt a message, or both. PGP follows the following general process: authentication, ZIP compression, encryption, and Base64 encoding. The Base64 encoding procedure makes the message ready for SMTP transmission GPG (GnuPG) GnuPG is another free encryption standard that companies may use that is based on OpenPGP. GnuPG serves as a replacement for Symantec\u2019s PGP. The main difference is the supported algorithms. However, GnuPG plays nice with PGP by design. Because GnuPG is open, some businesses would prefer the technical support and the user interface that comes with Symantec\u2019s PGP. It is important to note that there are some nuances between compatibility of GnuPG and PGP, such as the compatibility between certain algorithms, but in most applications such as email, there are workarounds. One such algorithm is the IDEA Module which isn\u2019t included in GnuPG out of the box due to patent issues. S/MIME SMTP can only handle 7-bit ASCII text (You can use UTF-8 extensions to alleviate this limitations, ) messages. While POP can handle other content types besides 7-bit ASCII, POP may, under a common default setting, download all the messages stored in the mail server to the user's local computer. After that, if POP removes these messages from the mail server. This makes it difficult for the user to read his messages from multiple computers. The Multipurpose Internet Mail Extension protocol (MIME) was designed to support sending and receiving email messages in various formats, including nontext files generated by word processors, graphics files, sound files, and video clips. Moreover, MIME allows a single message to include mixed types of data in any combination of these formats. The Internet Mail Access Protocol (IMAP), operated on TCP port 143(only for non-encrypted), stores (Configurable on both server client just like PoP) incoming email messages in the mail server until the user deletes them deliberately. This allows the user to access his mailbox from multiple machines and download messages to a local machine without deleting it from the mailbox in the mail server. SSL/TLS SSL uses a PKI to decide if a server\u2019s public key is trustworthy by requiring servers to use a security certificate signed by a trusted CA. When Netscape Navigator 1.0 was released, it trusted a single CA operated by the RSA Data Security corporation. The server\u2019s public RSA keys were used to be stored in the security certificate, which can then be used by the browser to establish a secure communication channel. The security certificates we use today still rely on the same standard (named X.509) that Netscape Navigator 1.0 used back then. Netscape\u2019s intent was to train users(though this didn\u2019t work out later) to differentiate secure communications from insecure ones, so they put a lock icon next to the address bar. When the lock is open, the communication is insecure. A closed lock means communication has been secured with SSL, which required the server to provide a signed certificate. You\u2019re obviously familiar with this icon as it\u2019s been in every browser ever since. The engineers at Netscape truly created a standard for secure internet communications. A year after releasing SSL 2.0, Netscape fixed several security issues and released SSL 3.0, a protocol that, albeit being officially deprecated since June 2015, remains in use in certain parts of the world more than 20 years after its introduction. In an effort to standardize SSL, the Internet Engineering Task Force (IETF) created a slightly modified SSL 3.0 and, in 1999, unveiled it as Transport Layer Security (TLS) 1.0. The name change between SSL and TLS continues to confuse people today. Officially, TLS is the new SSL, but in practice, people use SSL and TLS interchangeably to talk about any version of the protocol. Must See: https://tls.ulfheim.net/ https://davidwong.fr/tls13/ Network Perimeter Security Let us see how we keep a check on the perimeter i.e the edges, the first layer of protection General Firewall Framework Firewalls are needed because encryption algorithms cannot effectively stop malicious packets from getting into an edge network. This is because IP packets, regardless of whether they are encrypted, can always be forwarded into an edge network. Firewalls that were developed in the 1990s are important instruments to help restrict network access. A firewall may be a hardware device, a software package, or a combination of both. Packets flowing into the internal network from the outside should be evaluated before they are allowed to enter. One of the critical elements of a firewall is its ability to examine packets without imposing a negative impact on communication speed while providing security protections for the internal network. The packet inspection that is carried out by firewalls can be done using several different methods. On the basis of the particular method used by the firewall, it can be characterized as either a packet filter, circuit gateway, application gateway, or dynamic packet filter. Packet Filters It inspects ingress packets coming to an internal network from outside and inspects egress packets going outside from an internal network Packing filtering only inspects IP headers and TCP headers, not the payloads generated at the application layer A packet filtering firewall uses a set of rules to determine whether a packet should be allowed or denied to pass through. 2 types: Stateless It treats each packet as an independent object, and it does not keep track of any previously processed packets. In other words, stateless filtering inspects a packet when it arrives and makes a decision without leaving any record of the packet being inspected. Stateful Stateful filtering, also referred to as connection-state filtering, keeps track of connections between an internal host and an external host. A connection state (or state, for short) indicates whether it is a TCP connection or a UDP connection and whether the connection is established. Circuit Gateways Circuit gateways, also referred to as circuit-level gateways, are typically operated at the transportation layer They evaluate the information of the IP addresses and the port numbers contained in TCP (or UDP) headers and use it to determine whether to allow or to disallow an internal host and an external host to establish a connection. It is common practice to combine packet filters and circuit gateways to form a dynamic packet filter (DPF). Application Gateways(ALG) Aka PROXY Servers An Application Level Gateway (ALG) acts like a proxy for internal hosts, processing service requests from external clients. An ALG performs deep inspections on each IP packet (ingress or egress). In particular, an ALG inspects application program formats contained in the packet (e.g., MIME format or SQL format) and examines whether its payload is permitted. Thus, an ALG may be able to detect a computer virus contained in the payload. Because an ALG inspects packet payloads, it may be able to detect malicious code and quarantine suspicious packets, in addition to blocking packets with suspicious IP addresses and TCP ports. On the other hand, an ALG also incurs substantial computation and space overheads. Trusted Systems Bastion Hosts A Trusted Operating System (TOS) is an operating system that meets a particular set of security requirements. Whether an operating system can be trusted or not depends on a number of elements. For example, for an operating system on a particular computer to be certified trusted, one needs to validate that, among other things, the following four requirements are satisfied: Its system design contains no defects; Its system software contains no loopholes; Its system is configured properly; and Its system management is appropriate. Bastion Hosts Bastion hosts are computers with strong defense mechanisms. They often serve as host computers for implementing application gateways, circuit gateways, and other types of firewalls. A bastion host is operated on a trusted operating system that must not contain unnecessary functionalities or programs. This measure helps to reduce error probabilities and makes it easier to conduct security checks. Only those network application programs that are absolutely necessary, for example, SSH, DNS, SMTP, and authentication programs, are installed on a bastion host. Bastion hosts are also primarily used as controlled ingress points so that the security monitoring can focus more narrowly on actions happening at a single point closely. Common Techniques Scannings, Packet Capturing Scanning Ports with Nmap Nmap (\"Network Mapper\") is a free and open source (license) utility for network discovery and security auditing. Many systems and network administrators also find it useful for tasks such as network inventory, managing service upgrade schedules, and monitoring host or service uptime. The best thing about Nmap is it\u2019s free and open source and is very flexible and versatile Nmap is often used to determine alive hosts in a network, open ports on those hosts, services running on those open ports, and version identification of that service on that port. More at http://scanme.nmap.org/ Nmap uses 6 different port states: Open \u2014 An open port is one that is actively accepting TCP, UDP or SCTP connections. Open ports are what interests us the most because they are the ones that are vulnerable to attacks. Open ports also show the available services on a network. Closed \u2014 A port that receives and responds to Nmap probe packets but there is no application listening on that port. Useful for identifying that the host exists and for OS detection. Filtered \u2014 Nmap can\u2019t determine whether the port is open because packet filtering prevents its probes from reaching the port. Filtering could come from firewalls or router rules. Often little information is given from filtered ports during scans as the filters can drop the probes without responding or respond with useless error messages e.g. destination unreachable. Unfiltered \u2014 Port is accessible but Nmap doesn\u2019t know if its open or closed. Only used in ACK scan which is used to map firewall rulesets. Other scan types can be used to identify whether the port is open. Open/filtered \u2014 Nmap is unable to determine between open and filtered. This happens when an open port gives no response. No response could mean that the probe was dropped by a packet filter or any response is blocked. Closed/filtered \u2014 Nmap is unable to determine whether a port is closed or filtered. Only used in the IP ID idle scan. Types of Nmap Scan: TCP Connect TCP Connect scan completes the 3-way handshake. If a port is open, the operating system completes the TCP three-way handshake and the port scanner immediately closes the connection to avoid DOS. This is \u201cnoisy\u201d because the services can log the sender IP address and might trigger Intrusion Detection Systems. UDP Scan This scan checks to see if there are any UDP ports listening. Since UDP does not respond with a positive acknowledgment like TCP and only responds to an incoming UDP packet when the port is closed, SYN Scan SYN scan is another form of TCP scanning. This scan type is also known as \u201chalf-open scanning\u201d because it never actually opens a full TCP connection. The port scanner generates a SYN packet. If the target port is open, it will respond with an SYN-ACK packet. The scanner host responds with an RST packet, closing the connection before the handshake is completed. If the port is closed but unfiltered, the target will instantly respond with an RST packet. SYN scan has the advantage that the individual services never actually receive a connection. FIN Scan This is a stealthy scan, like the SYN scan, but sends a TCP FIN packet instead. ACK Scan Ack scanning determines whether the port is filtered or not. Null Scan Another very stealthy scan that sets all the TCP header flags to off or null. This is not normally a valid packet and some hosts will not know what to do with this. XMAS Scan Similar to the NULL scan except for all the flags in the TCP header is set to on RPC Scan This special type of scan looks for machine answering to RPC (Remote Procedure Call) services IDLE Scan It is a super stealthy method whereby the scan packets are bounced off an external host. You don\u2019t need to have control over the other host but it does have to set up and meet certain requirements. You must input the IP address of our \u201czombie\u201d host and what port number to use. It is one of the more controversial options in Nmap since it really only has a use for malicious attacks. Scan Techniques A couple of scan techniques which can be used to gain more information about a system and its ports. You can read more at https://medium.com/infosec-adventures/nmap-cheatsheet-a423fcdda0ca OpenVAS OpenVAS is a full-featured vulnerability scanner. OpenVAS is a framework of services and tools that provides a comprehensive and powerful vulnerability scanning and management package OpenVAS, which is an open-source program, began as a fork of the once-more-popular scanning program, Nessus. OpenVAS is made up of three main parts. These are: a regularly updated feed of Network Vulnerability Tests (NVTs); a scanner, which runs the NVTs; and a SQLite 3 database for storing both your test configurations and the NVTs\u2019 results and configurations. https://www.greenbone.net/en/install_use_gce/ WireShark Wireshark is a protocol analyzer. This means Wireshark is designed to decode not only packet bits and bytes but also the relations between packets and protocols. Wireshark understands protocol sequences. A simple demo of wireshark Capture only udp packets: Capture filter = \u201cudp\u201d Capture only tcp packets Capture filter = \u201ctcp\u201d TCP/IP 3 way Handshake Filter by IP address: displays all traffic from IP, be it source or destination ip.addr == 192.168.1.1 Filter by source address: display traffic only from IP source ip.src == 192.168.0.1 Filter by destination: display traffic only form IP destination ip.dst == 192.168.0.1 Filter by IP subnet: display traffic from subnet, be it source or destination ip.addr = 192.168.0.1/24 Filter by protocol: filter traffic by protocol name dns http ftp arp ssh telnet icmp Exclude IP address: remove traffic from and to IP address !ip.addr ==192.168.0.1 Display traffic between two specific subnet ip.addr == 192.168.0.1/24 and ip.addr == 192.168.1.1/24 Display traffic between two specific workstations ip.addr == 192.168.0.1 and ip.addr == 192.168.0.2 Filter by MAC eth.addr = 00:50:7f:c5:b6:78 Filter TCP port tcp.port == 80 Filter TCP port source tcp.srcport == 80 Filter TCP port destination tcp.dstport == 80 Find user agents http.user_agent contains Firefox !http.user_agent contains || !http.user_agent contains Chrome Filter broadcast traffic !(arp or icmp or dns) Filter IP address and port tcp.port == 80 ip.addr == 192.168.0.1 Filter all http get requests http.request Filter all http get requests and responses http.request or http.response Filter three way handshake tcp.flags.syn==1 or (tcp.seq==1 and tcp.ack==1 and tcp.len==0 and tcp.analysis.initial_rtt) Find files by type frame contains \u201c(attachment|tar|exe|zip|pdf)\u201d Find traffic based on keyword tcp contains facebook frame contains facebook Detecting SYN Floods tcp.flags.syn == 1 and tcp.flags.ack == 0 Wireshark Promiscuous Mode - By default, Wireshark only captures packets going to and from the computer where it runs. By checking the box to run Wireshark in Promiscuous Mode in the Capture Settings, you can capture most of the traffic on the LAN. DumpCap Dumpcap is a network traffic dump tool. It captures packet data from a live network and writes the packets to a file. Dumpcap\u2019s native capture file format is pcapng, which is also the format used by Wireshark. By default, Dumpcap uses the pcap library to capture traffic from the first available network interface and writes the received raw packet data, along with the packets\u2019 time stamps into a pcapng file. The capture filter syntax follows the rules of the pcap library. The Wireshark command line utility called 'dumpcap.exe' can be used to capture LAN traffic over an extended period of time. Wireshark itself can also be used, but dumpcap does not significantly utilize the computer's memory while capturing for long periods of time. DaemonLogger Daemonlogger is a packet logging application designed specifically for use in Network and Systems Management (NSM) environments. The biggest benefit Daemonlogger provides is that, like Dumpcap, it is simple to use for capturing packets. In order to begin capturing, you need only to invoke the command and specify an interface. daemonlogger \u2013i eth1 This option, by default, will begin capturing packets and logging them to the current working directory. Packets will be collected until the capture file size reaches 2 GB, and then a new file will be created. This will continue indefinitely until the process is halted. NetSniff-NG Netsniff-NG is a high-performance packet capture utility While the utilities we\u2019ve discussed to this point rely on Libpcap for capture, Netsniff-NG utilizes zero-copy mechanisms to capture packets. This is done with the intent to support full packet capture over high throughput links. In order to begin capturing packets with Netsniff-NG, we have to specify an input and output. In most cases, the input will be a network interface, and the output will be a file or folder on disk. netsniff-ng \u2013i eth1 \u2013o data.pcap Netflow NetFlow is a feature that was introduced on Cisco routers around 1996 that provides the ability to collect IP network traffic as it enters or exits an interface. By analyzing the data provided by NetFlow, a network administrator can determine things such as the source and destination of traffic, class of service, and the causes of congestion. A typical flow monitoring setup (using NetFlow) consists of three main components:[1] Flow exporter: aggregates packets into flows and exports flow records towards one or more flow collectors. Flow collector: responsible for reception, storage and pre-processing of flow data received from a flow exporter. Analysis application: analyzes received flow data in the context of intrusion detection or traffic profiling, for example. Routers and switches that support NetFlow can collect IP traffic statistics on all interfaces where NetFlow is enabled, and later export those statistics as NetFlow records toward at least one NetFlow collector\u2014typically a server that does the actual traffic analysis. IDS A security solution that detects security-related events in your environment but does not block them. IDS sensors can be software and hardware based used to collect and analyze the network traffic. These sensors are available in two varieties, network IDS and host IDS. A host IDS is a server-specific agent running on a server with a minimum of overhead to monitor the operating system. A network IDS can be embedded in a networking device, a standalone appliance, or a module monitoring the network traffic. Signature Based IDS The signature-based IDS monitors the network traffic or observes the system and sends an alarm if a known malicious event is happening. It does so by comparing the data flow against a database of known attack patterns These signatures explicitly define what traffic or activity should be considered as malicious. Signature-based detection has been the bread and butter of network-based defensive security for over a decade, partially because it is very similar to how malicious activity is detected at the host level with antivirus utilities The formula is fairly simple: an analyst observes a malicious activity, derives indicators from the activity and develops them into signatures, and then those signatures will alert whenever the activity occurs again. ex: SNORT SURICATA Policy Based IDS The policy-based IDSs (mainly host IDSs) trigger an alarm whenever a violation occurs against the configured policy. This configured policy is or should be a representation of the security policies. This type of IDS is flexible and can be customized to a company's network requirements because it knows exactly what is permitted and what is not. On the other hand, the signature-based systems rely on vendor specifics and default settings. Anomaly Based IDS The anomaly-based IDS looks for traffic that deviates from the normal, but the definition of what is a normal network traffic pattern is the tricky part Two types of anomaly-based IDS exist: statistical and nonstatistical anomaly detection Statistical anomaly detection learns the traffic patterns interactively over a period of time. In the nonstatistical approach, the IDS has a predefined configuration of the supposedly acceptable and valid traffic patterns. Host Based IDS Network Based IDS A host IDS can be described as a distributed agent residing on each server of the network that needs protection. These distributed agents are tied very closely to the underlying operating system. Network IDSs, on the other hand, can be described as intelligent sniffing devices. Data (raw packets) is captured from the network by a network IDS, whereas host IDSs capture the data from the host on which they are installed. Honeypots The use of decoy machines to direct intruders' attention away from the machines under protection is a major technique to preclude intrusion attacks. Any device, system, directory, or file used as a decoy to lure attackers away from important assets and to collect intrusion or abusive behaviors is referred to as a honeypot. A honeypot may be implemented as a physical device or as an emulation system. The idea is to set up decoy machines in a LAN, or decoy directories/files in a file system and make them appear important, but with several exploitable loopholes, to lure attackers to attack these machines or directories/files, so that other machines, directories, and files can evade intruders' attentions. A decoy machine may be a host computer or a server computer. Likewise, we may also set up decoy routers or even decoy LANs. Chinks In The Armour (TCP/IP Security Issues) IP Spoofing In this type of attack, the attacker replaces the IP address of the sender, or in some rare cases the destination, with a different address. IP spoofing is normally used to exploit a target host. In other cases, it is used to start a denial-of-service (DoS) attack. In a DoS attack, an attacker modifies the IP packet to mislead the target host into accepting the original packet as a packet sourced at a trusted host. The attacker must know the IP address of the trusted host to modify the packet headers (source IP address) so that it appears that the packets are coming from that host. IP Spoofing Detection Techniques Direct TTL Probes In this technique we send a packet to a host of suspect spoofed IP that triggers reply and compare TTL with suspect packet; if the TTL in the reply is not the same as the packet being checked; it is a spoofed packet. This Technique is successful when the attacker is in a different subnet from the victim. IP Identification Number. Send a probe to the host of suspect spoofed traffic that triggers a reply and compare IP ID with suspect traffic. If IP IDs are not in the near value of packet being checked, suspect traffic is spoofed TCP Flow Control Method Attackers sending spoofed TCP packets will not receive the target\u2019s SYN-ACK packets. Attackers cannot therefore be responsive to change in the congestion window size When the receiver still receives traffic even after a windows size is exhausted, most probably the packets are spoofed. Covert Channel A covert or clandestine channel can be best described as a pipe or communication channel between two entities that can be exploited by a process or application transferring information in a manner that violates the system's security specifications. More specifically for TCP/IP, in some instances, covert channels are established, and data can be secretly passed between two end systems. Ex: ICMP resides at the Internet layer of the TCP/IP protocol suite and is implemented in all TCP/IP hosts. Based on the specifications of the ICMP Protocol, an ICMP Echo Request message should have an 8-byte header and a 56-byte payload. The ICMP Echo Request packet should not carry any data in the payload. However, these packets are often used to carry secret information. The ICMP packets are altered slightly to carry secret data in the payload. This makes the size of the packet larger, but no control exists in the protocol stack to defeat this behavior. The alteration of ICMP packets gives intruders the opportunity to program specialized client-server pairs. These small pieces of code export confidential information without alerting the network administrator. ICMP can be leveraged for more than data exfiltration. For eg. some C C tools such as Loki used ICMP channel to establish encrypted interactive session back in 1996. Deep packet inspection has since come a long way. A lot of IDS/IPS detect ICMP tunneling. Check for echo responses that do not contain the same payload as request Check for volume of ICMP traffic specially for volumes beyond an acceptable threshold IP Fragmentation Attack The TCP/IP protocol suite, or more specifically IP, allows the fragmentation of packets.(this is a feature not a bug) IP fragmentation offset is used to keep track of the different parts of a datagram. The information or content in this field is used at the destination to reassemble the datagrams All such fragments have the same Identification field value, and the fragmentation offset indicates the position of the current fragment in the context of the original packet. Many access routers and firewalls do not perform packet reassembly. In normal operation, IP fragments do not overlap, but attackers can create artificially fragmented packets to mislead the routers or firewalls. Usually, these packets are small and almost impractical for end systems because of data and computational overhead. A good example of an IP fragmentation attack is the Ping of Death attack. The Ping of Death attack sends fragments that, when reassembled at the end station, create a larger packet than the maximum permissible length. TCP Flags Data exchange using TCP does not happen until a three-way handshake has been successfully completed. This handshake uses different flags to influence the way TCP segments are processed. There are 6 bits in the TCP header that are often called flags. Namely: 6 different flags are part of the TCP header: Urgent pointer field (URG), Acknowledgment field (ACK), Push function (PSH), Reset the connection (RST), Synchronize sequence numbers (SYN), and sender is finished with this connection (FIN). Abuse of the normal operation or settings of these flags can be used by attackers to launch DoS attacks. This causes network servers or web servers to crash or hang. The attacker's ultimate goal is to write special programs or pieces of code that are able to construct these illegal combinations resulting in an efficient DoS attack. SYN FLOOD The timers (or lack of certain timers) in 3 way handshake are often used and exploited by attackers to disable services or even to enter systems. After step 2 of the three-way handshake, no limit is set on the time to wait after receiving a SYN. The attacker initiates many connection requests to the web server of Company XYZ (almost certainly with a spoofed IP address). The SYN+ACK packets (Step 2) sent by the web server back to the originating source IP address are not replied to. This leaves a TCP session half-open on the web server. Multiple packets cause multiple TCP sessions to stay open. Based on the hardware limitations of the server, a limited number of TCP sessions can stay open, and as a result, the web server refuses further connection establishments attempts from any host as soon as a certain limit is reached. These half-open connections need to be completed or timed out before new connections can be established. FIN Attack In normal operation, the sender sets the TCP FIN flag indicating that no more data will be transmitted and the connection can be closed down. This is a four-way handshake mechanism, with both sender and receiver expected to send an acknowledgement on a received FIN packet. During an attack that is trying to kill connections, a spoofed FIN packet is constructed. This packet also has the correct sequence number, so the packets are seen as valid by the targeted host. These sequence numbers are easy to predict. This process is referred to as TCP sequence number prediction, whereby the attacker either sniffs the current Sequence and Acknowledgment (SEQ/ACK) numbers of the connection or can algorithmically predict these numbers. Connection Hijacking An authorized user (Employee X) sends HTTP requests over a TCP session with the web server. The web server accepts the packets from Employee X only when the packet has the correct SEQ/ACK numbers. As seen previously, these numbers are important for the web server to distinguish between different sessions and to make sure it is still talking to Employee X. Imagine that the cracker starts sending packets to the web server spoofing the IP address of Employee X, using the correct SEQ/ACK combination. The web server accepts the packet and increments the ACK number. In the meantime, Employee X continues to send packets but with incorrect SEQ/ACK numbers. As a result of sending unsynchronized packets, all data from Employee X is discarded when received by the web server. The attacker pretends to be Employee X using the correct numbers. This finally results in the cracker hijacking the connection, whereby Employee X is completely confused and the web server replies assuming the cracker is sending correct synchronized data. STEPS: The attacker examines the traffic flows with a network monitor and notices traffic from Employee X to a web server. The web server returns or echoes data back to the origination station (Employee X). Employee X acknowledges the packet. The cracker launches a spoofed packet to the server. The web server responds to the cracker. The cracker starts verifying SEQ/ACK numbers to double-check success. At this time, the cracker takes over the session from Employee X, which results in a session hanging for Employee X. The cracker can start sending traffic to the web server. The web server returns the requested data to confirm delivery with the correct ACK number. The cracker can continue to send data (keeping track of the correct SEQ/ACK numbers) until eventually setting the FIN flag to terminate the session. Buffer Overflow A buffer is a temporary data storage area used to store program code and data. When a program or process tries to store more data in a buffer than it was originally anticipated to hold, a buffer overflow occurs. Buffers are temporary storage locations in memory (memory or buffer sizes are often measured in bytes) that are able to store a fixed amount of data in bytes. When more data is retrieved than can be stored in a buffer location, the additional information must go into an adjacent buffer, resulting in overwriting the valid data held in them. Mechanism: Buffer overflow vulnerabilities exist in different types. But the overall goal for all buffer overflow attacks is to take over the control of a privileged program and, if possible, the host. The attacker has two tasks to achieve this goal. First, the dirty code needs to be available in the program's code address space. Second, the privileged program should jump to that particular part of the code, which ensures that the proper parameters are loaded into memory. The first task can be achieved in two ways: by injecting the code in the right address space or by using the existing code and modifying certain parameters slightly. The second task is a little more complex because the program's control flow needs to be modified to make the program jump to the dirty code. CounterMeasure: The most important approach is to have a concerted focus on writing correct code. A second method is to make the data buffers (memory locations) address space of the program code non executable. This type of address space makes it impossible to execute code, which might be infiltrated in the program's buffers during an attack. More Spoofing Address Resolution Protocol Spoofing The Address Resolution Protocol (ARP) provides a mechanism to resolve, or map, a known IP address to a MAC sublayer address. Using ARP spoofing, the cracker can exploit this hardware address authentication mechanism by spoofing the hardware address of Host B. Basically, the attacker can convince any host or network device on the local network that the cracker's workstation is the host to be trusted. This is a common method used in a switched environment. ARP spoofing can be prevented with the implementation of static ARP tables in all the hosts and routers of your network. Alternatively, you can implement an ARP server that responds to ARP requests on behalf of the target host. DNS Spoofing DNS spoofing is the method whereby the hacker convinces the target machine that the system it wants to connect to is the machine of the cracker. The cracker modifies some records so that name entries of hosts correspond to the attacker's IP address. There have been instances in which the complete DNS server was compromised by an attack. To counter DNS spoofing, the reverse lookup detects these attacks. The reverse lookup is a mechanism to verify the IP address against a name. The IP address and name files are usually kept on different servers to make compromise much more difficult","title":"Network Securuty"},{"location":"security/network_security/#part-ii-network-security","text":"","title":"Part II : Network Security"},{"location":"security/network_security/#introduction","text":"TCP/IP is the dominant networking technology today. It is a five-layer architecture. These layers are, from top to bottom, the application layer, the transport layer (TCP), the network layer (IP), the data-link layer, and the physical layer. In addition to TCP/IP, there also are other networking technologies. For convenience, we use the OSI network model to represent non-TCP/IP network technologies. Different networks are interconnected using gateways. A gateway can be placed at any layer. The OSI model is a seven-layer architecture. The OSI architecture is similar to the TCP/IP architecture, except that the OSI model specifies two additional layers between the application layer and the transport layer in the TCP/IP architecture. These two layers are the presentation layer and the session layer. Figure 5.1 shows the relation between the TCP/IP layers and the OSI layers. The application layer in TCP/IP corresponds to the application layer and the presentation layer in OSI. The transport layer in TCP/IP corresponds to the session layer and the transport layer in OSI. The remaining three layers in the TCP/IP architecture are one-to-one correspondent to the remaining three layers in the OSI model. Correspondence between layers of the TCP/IP architecture and the OSI model. Also shown are placements of cryptographic algorithms in network layers, where the dotted arrows indicate actual communications of cryptographic algorithms The functionalities of OSI layers are briefly described as follows: The application layer serves as an interface between applications and network programs. It supports application programs and end-user processing. Common application-layer programs include remote logins, file transfer, email, and Web browsing. The presentation layer is responsible for dealing with data that is formed differently. This protocol layer allows application-layer programs residing on different sides of a communication channel with different platforms to understand each other's data formats regardless of how they are presented. The session layer is responsible for creating, managing, and closing a communication connection. The transport layer is responsible for providing reliable connections, such as packet sequencing, traffic control, and congestion control. The network layer is responsible for routing device-independent data packets from the current hop to the next hop. The data-link layer is responsible for encapsulating device-independent data packets into device-dependent data frames. It has two sublayers: logical link control and media access control. The physical layer is responsible for transmitting device-dependent frames through some physical media. Starting from the application layer, data generated from an application program is passed down layer-by-layer to the physical layer. Data from the previous layer is enclosed in a new envelope at the current layer, where the data from the previous layer is also just an envelope containing the data from the layer before it. This is similar to enclosing a smaller envelope in a larger one. The envelope added at each layer contains sufficient information for handling the packet. Application-layer data are divided into blocks small enough to be encapsulated in an envelope at the next layer. Application data blocks are \u201cdressed up\u201d in the TCP/IP architecture according to the following basic steps. At the sending side, an application data block is encapsulated in a TCP packet when it is passed down to the TCP layer. In other words, a TCP packet consists of a header and a payload, where the header corresponds to the TCP envelope and the payload is the application data block. Likewise, the TCP packet will be encapsulated in an IP packet when it is passed down to the IP layer. An IP packet consists of a header and a payload, which is the TCP packet passed down from the TCP layer. The IP packet will be encapsulated in a device-dependent frame (e.g., an Ethernet frame) when it is passed down to the data-link layer. A frame has a header, and it may also have a trailer. For example, in addition to having a header, an Ethernet frame also has a 32-bit cyclic redundancy check (CRC) trailer. When it is passed down to the physical layer, a frame will be transformed to a sequence of media signals for transmission Flow Diagram of a Packet Generation At the destination side, the medium signals are converted by the physical layer into a frame, which is passed up to the data-link layer. The data-link layer passes the frame payload (i.e., the IP packet encapsulated in the frame) up to the IP layer. The IP layer passes the IP payload, namely, the TCP packet encapsulated in the IP packet, up to the TCP layer. The TCP layer passes the TCP payload, namely, the application data block, up to the application layer. When a packet arrives at a router, it only goes up to the IP layer, where certain fields in the IP header are modified (e.g., the value of TTL is decreased by 1). This modified packet is then passed back down layer-by-layer to the physical layer for further transmission.","title":"Introduction"},{"location":"security/network_security/#public-key-infrastructure","text":"To deploy cryptographic algorithms in network applications, we need a way to distribute secret keys using open networks. Public-key cryptography is the best way to distribute these secret keys. In order to use public-key cryptography, we need to build a public-key infrastructure (PKI) to support and manage public-key certificates and certificate authority (CA) networks. In particular, PKIs are set up to perform the following functions: Determine the legitimacy of users before issuing public-key certificates to them. Issue public-key certificates upon user requests. Extend public-key certificates valid time upon user requests. Revoke public-key certificates upon users' requests or when the corresponding private keys are compromised. Store and manage public-key certificates. Prevent digital signature signers from denying their signatures. Support CA networks to allow different CAs to authenticate public-key certificates issued by other CAs. X.509: https://certificatedecoder.dev/?gclid=EAIaIQobChMI0M731O6G6gIVVSQrCh04bQaAEAAYASAAEgKRkPD_BwE","title":"Public Key Infrastructure"},{"location":"security/network_security/#ipsec-a-security-protocol-at-the-network-layer","text":"IPsec is a major security protocol at the network layer IPsec provides a potent platform for constructing virtual private networks (VPN). VPNs are private networks overlayed on public networks. The purpose of deploying cryptographic algorithms at the network layer is to encrypt or authenticate IP packets (either just the payloads or the whole packets). IPsec also specifies how to exchange keys. Thus, IPsec consists of authentication protocols, encryption protocols, and key exchange protocols. They are referred to, respectively, as authentication header (AH), encapsulating security payload (ESP), and Internet key exchange (IKE).","title":"IPsec: A Security Protocol at the Network Layer"},{"location":"security/network_security/#pgp-smime-email-security","text":"There are a number of security protocols at the application layer. The most used of these protocols are email security protocols namely PGP and S/MIME. SMTP (\u201cSimple Mail Transfer Protocol\u201d) is used for sending and delivering from a client to a server via port 25: it\u2019s the outgoing server. On the contrary, POP (\u201cPost Office Protocol\u201d) allows the user to pick up the message and download it into his own inbox: it\u2019s the incoming server. The latest version of the Post Office Protocol is named POP3, and it\u2019s been used since 1996; it uses port 110 PGP PGP implements all major cryptographic algorithms, the ZIP compression algorithm, and the Base64 encoding algorithm. It can be used to authenticate a message, encrypt a message, or both. PGP follows the following general process: authentication, ZIP compression, encryption, and Base64 encoding. The Base64 encoding procedure makes the message ready for SMTP transmission GPG (GnuPG) GnuPG is another free encryption standard that companies may use that is based on OpenPGP. GnuPG serves as a replacement for Symantec\u2019s PGP. The main difference is the supported algorithms. However, GnuPG plays nice with PGP by design. Because GnuPG is open, some businesses would prefer the technical support and the user interface that comes with Symantec\u2019s PGP. It is important to note that there are some nuances between compatibility of GnuPG and PGP, such as the compatibility between certain algorithms, but in most applications such as email, there are workarounds. One such algorithm is the IDEA Module which isn\u2019t included in GnuPG out of the box due to patent issues. S/MIME SMTP can only handle 7-bit ASCII text (You can use UTF-8 extensions to alleviate this limitations, ) messages. While POP can handle other content types besides 7-bit ASCII, POP may, under a common default setting, download all the messages stored in the mail server to the user's local computer. After that, if POP removes these messages from the mail server. This makes it difficult for the user to read his messages from multiple computers. The Multipurpose Internet Mail Extension protocol (MIME) was designed to support sending and receiving email messages in various formats, including nontext files generated by word processors, graphics files, sound files, and video clips. Moreover, MIME allows a single message to include mixed types of data in any combination of these formats. The Internet Mail Access Protocol (IMAP), operated on TCP port 143(only for non-encrypted), stores (Configurable on both server client just like PoP) incoming email messages in the mail server until the user deletes them deliberately. This allows the user to access his mailbox from multiple machines and download messages to a local machine without deleting it from the mailbox in the mail server. SSL/TLS SSL uses a PKI to decide if a server\u2019s public key is trustworthy by requiring servers to use a security certificate signed by a trusted CA. When Netscape Navigator 1.0 was released, it trusted a single CA operated by the RSA Data Security corporation. The server\u2019s public RSA keys were used to be stored in the security certificate, which can then be used by the browser to establish a secure communication channel. The security certificates we use today still rely on the same standard (named X.509) that Netscape Navigator 1.0 used back then. Netscape\u2019s intent was to train users(though this didn\u2019t work out later) to differentiate secure communications from insecure ones, so they put a lock icon next to the address bar. When the lock is open, the communication is insecure. A closed lock means communication has been secured with SSL, which required the server to provide a signed certificate. You\u2019re obviously familiar with this icon as it\u2019s been in every browser ever since. The engineers at Netscape truly created a standard for secure internet communications. A year after releasing SSL 2.0, Netscape fixed several security issues and released SSL 3.0, a protocol that, albeit being officially deprecated since June 2015, remains in use in certain parts of the world more than 20 years after its introduction. In an effort to standardize SSL, the Internet Engineering Task Force (IETF) created a slightly modified SSL 3.0 and, in 1999, unveiled it as Transport Layer Security (TLS) 1.0. The name change between SSL and TLS continues to confuse people today. Officially, TLS is the new SSL, but in practice, people use SSL and TLS interchangeably to talk about any version of the protocol. Must See: https://tls.ulfheim.net/ https://davidwong.fr/tls13/","title":"PGP & S/MIME : Email Security"},{"location":"security/network_security/#network-perimeter-security","text":"Let us see how we keep a check on the perimeter i.e the edges, the first layer of protection","title":"Network Perimeter Security"},{"location":"security/network_security/#general-firewall-framework","text":"Firewalls are needed because encryption algorithms cannot effectively stop malicious packets from getting into an edge network. This is because IP packets, regardless of whether they are encrypted, can always be forwarded into an edge network. Firewalls that were developed in the 1990s are important instruments to help restrict network access. A firewall may be a hardware device, a software package, or a combination of both. Packets flowing into the internal network from the outside should be evaluated before they are allowed to enter. One of the critical elements of a firewall is its ability to examine packets without imposing a negative impact on communication speed while providing security protections for the internal network. The packet inspection that is carried out by firewalls can be done using several different methods. On the basis of the particular method used by the firewall, it can be characterized as either a packet filter, circuit gateway, application gateway, or dynamic packet filter.","title":"General Firewall Framework"},{"location":"security/network_security/#packet-filters","text":"It inspects ingress packets coming to an internal network from outside and inspects egress packets going outside from an internal network Packing filtering only inspects IP headers and TCP headers, not the payloads generated at the application layer A packet filtering firewall uses a set of rules to determine whether a packet should be allowed or denied to pass through. 2 types: Stateless It treats each packet as an independent object, and it does not keep track of any previously processed packets. In other words, stateless filtering inspects a packet when it arrives and makes a decision without leaving any record of the packet being inspected. Stateful Stateful filtering, also referred to as connection-state filtering, keeps track of connections between an internal host and an external host. A connection state (or state, for short) indicates whether it is a TCP connection or a UDP connection and whether the connection is established.","title":"Packet Filters"},{"location":"security/network_security/#circuit-gateways","text":"Circuit gateways, also referred to as circuit-level gateways, are typically operated at the transportation layer They evaluate the information of the IP addresses and the port numbers contained in TCP (or UDP) headers and use it to determine whether to allow or to disallow an internal host and an external host to establish a connection. It is common practice to combine packet filters and circuit gateways to form a dynamic packet filter (DPF).","title":"Circuit Gateways"},{"location":"security/network_security/#application-gatewaysalg","text":"Aka PROXY Servers An Application Level Gateway (ALG) acts like a proxy for internal hosts, processing service requests from external clients. An ALG performs deep inspections on each IP packet (ingress or egress). In particular, an ALG inspects application program formats contained in the packet (e.g., MIME format or SQL format) and examines whether its payload is permitted. Thus, an ALG may be able to detect a computer virus contained in the payload. Because an ALG inspects packet payloads, it may be able to detect malicious code and quarantine suspicious packets, in addition to blocking packets with suspicious IP addresses and TCP ports. On the other hand, an ALG also incurs substantial computation and space overheads.","title":"Application Gateways(ALG)"},{"location":"security/network_security/#trusted-systems-bastion-hosts","text":"A Trusted Operating System (TOS) is an operating system that meets a particular set of security requirements. Whether an operating system can be trusted or not depends on a number of elements. For example, for an operating system on a particular computer to be certified trusted, one needs to validate that, among other things, the following four requirements are satisfied: Its system design contains no defects; Its system software contains no loopholes; Its system is configured properly; and Its system management is appropriate. Bastion Hosts Bastion hosts are computers with strong defense mechanisms. They often serve as host computers for implementing application gateways, circuit gateways, and other types of firewalls. A bastion host is operated on a trusted operating system that must not contain unnecessary functionalities or programs. This measure helps to reduce error probabilities and makes it easier to conduct security checks. Only those network application programs that are absolutely necessary, for example, SSH, DNS, SMTP, and authentication programs, are installed on a bastion host. Bastion hosts are also primarily used as controlled ingress points so that the security monitoring can focus more narrowly on actions happening at a single point closely.","title":"Trusted Systems & Bastion Hosts"},{"location":"security/network_security/#common-techniques-scannings-packet-capturing","text":"","title":"Common Techniques & Scannings, Packet Capturing"},{"location":"security/network_security/#scanning-ports-with-nmap","text":"Nmap (\"Network Mapper\") is a free and open source (license) utility for network discovery and security auditing. Many systems and network administrators also find it useful for tasks such as network inventory, managing service upgrade schedules, and monitoring host or service uptime. The best thing about Nmap is it\u2019s free and open source and is very flexible and versatile Nmap is often used to determine alive hosts in a network, open ports on those hosts, services running on those open ports, and version identification of that service on that port. More at http://scanme.nmap.org/ Nmap uses 6 different port states: Open \u2014 An open port is one that is actively accepting TCP, UDP or SCTP connections. Open ports are what interests us the most because they are the ones that are vulnerable to attacks. Open ports also show the available services on a network. Closed \u2014 A port that receives and responds to Nmap probe packets but there is no application listening on that port. Useful for identifying that the host exists and for OS detection. Filtered \u2014 Nmap can\u2019t determine whether the port is open because packet filtering prevents its probes from reaching the port. Filtering could come from firewalls or router rules. Often little information is given from filtered ports during scans as the filters can drop the probes without responding or respond with useless error messages e.g. destination unreachable. Unfiltered \u2014 Port is accessible but Nmap doesn\u2019t know if its open or closed. Only used in ACK scan which is used to map firewall rulesets. Other scan types can be used to identify whether the port is open. Open/filtered \u2014 Nmap is unable to determine between open and filtered. This happens when an open port gives no response. No response could mean that the probe was dropped by a packet filter or any response is blocked. Closed/filtered \u2014 Nmap is unable to determine whether a port is closed or filtered. Only used in the IP ID idle scan.","title":"Scanning Ports with Nmap"},{"location":"security/network_security/#types-of-nmap-scan","text":"TCP Connect TCP Connect scan completes the 3-way handshake. If a port is open, the operating system completes the TCP three-way handshake and the port scanner immediately closes the connection to avoid DOS. This is \u201cnoisy\u201d because the services can log the sender IP address and might trigger Intrusion Detection Systems. UDP Scan This scan checks to see if there are any UDP ports listening. Since UDP does not respond with a positive acknowledgment like TCP and only responds to an incoming UDP packet when the port is closed, SYN Scan SYN scan is another form of TCP scanning. This scan type is also known as \u201chalf-open scanning\u201d because it never actually opens a full TCP connection. The port scanner generates a SYN packet. If the target port is open, it will respond with an SYN-ACK packet. The scanner host responds with an RST packet, closing the connection before the handshake is completed. If the port is closed but unfiltered, the target will instantly respond with an RST packet. SYN scan has the advantage that the individual services never actually receive a connection. FIN Scan This is a stealthy scan, like the SYN scan, but sends a TCP FIN packet instead. ACK Scan Ack scanning determines whether the port is filtered or not. Null Scan Another very stealthy scan that sets all the TCP header flags to off or null. This is not normally a valid packet and some hosts will not know what to do with this. XMAS Scan Similar to the NULL scan except for all the flags in the TCP header is set to on RPC Scan This special type of scan looks for machine answering to RPC (Remote Procedure Call) services IDLE Scan It is a super stealthy method whereby the scan packets are bounced off an external host. You don\u2019t need to have control over the other host but it does have to set up and meet certain requirements. You must input the IP address of our \u201czombie\u201d host and what port number to use. It is one of the more controversial options in Nmap since it really only has a use for malicious attacks. Scan Techniques A couple of scan techniques which can be used to gain more information about a system and its ports. You can read more at https://medium.com/infosec-adventures/nmap-cheatsheet-a423fcdda0ca","title":"Types of Nmap Scan:"},{"location":"security/network_security/#openvas","text":"OpenVAS is a full-featured vulnerability scanner. OpenVAS is a framework of services and tools that provides a comprehensive and powerful vulnerability scanning and management package OpenVAS, which is an open-source program, began as a fork of the once-more-popular scanning program, Nessus. OpenVAS is made up of three main parts. These are: a regularly updated feed of Network Vulnerability Tests (NVTs); a scanner, which runs the NVTs; and a SQLite 3 database for storing both your test configurations and the NVTs\u2019 results and configurations. https://www.greenbone.net/en/install_use_gce/","title":"OpenVAS"},{"location":"security/network_security/#wireshark","text":"Wireshark is a protocol analyzer. This means Wireshark is designed to decode not only packet bits and bytes but also the relations between packets and protocols. Wireshark understands protocol sequences. A simple demo of wireshark Capture only udp packets: Capture filter = \u201cudp\u201d Capture only tcp packets Capture filter = \u201ctcp\u201d TCP/IP 3 way Handshake Filter by IP address: displays all traffic from IP, be it source or destination ip.addr == 192.168.1.1 Filter by source address: display traffic only from IP source ip.src == 192.168.0.1 Filter by destination: display traffic only form IP destination ip.dst == 192.168.0.1 Filter by IP subnet: display traffic from subnet, be it source or destination ip.addr = 192.168.0.1/24 Filter by protocol: filter traffic by protocol name dns http ftp arp ssh telnet icmp Exclude IP address: remove traffic from and to IP address !ip.addr ==192.168.0.1 Display traffic between two specific subnet ip.addr == 192.168.0.1/24 and ip.addr == 192.168.1.1/24 Display traffic between two specific workstations ip.addr == 192.168.0.1 and ip.addr == 192.168.0.2 Filter by MAC eth.addr = 00:50:7f:c5:b6:78 Filter TCP port tcp.port == 80 Filter TCP port source tcp.srcport == 80 Filter TCP port destination tcp.dstport == 80 Find user agents http.user_agent contains Firefox !http.user_agent contains || !http.user_agent contains Chrome Filter broadcast traffic !(arp or icmp or dns) Filter IP address and port tcp.port == 80 ip.addr == 192.168.0.1 Filter all http get requests http.request Filter all http get requests and responses http.request or http.response Filter three way handshake tcp.flags.syn==1 or (tcp.seq==1 and tcp.ack==1 and tcp.len==0 and tcp.analysis.initial_rtt) Find files by type frame contains \u201c(attachment|tar|exe|zip|pdf)\u201d Find traffic based on keyword tcp contains facebook frame contains facebook Detecting SYN Floods tcp.flags.syn == 1 and tcp.flags.ack == 0 Wireshark Promiscuous Mode - By default, Wireshark only captures packets going to and from the computer where it runs. By checking the box to run Wireshark in Promiscuous Mode in the Capture Settings, you can capture most of the traffic on the LAN.","title":"WireShark"},{"location":"security/network_security/#dumpcap","text":"Dumpcap is a network traffic dump tool. It captures packet data from a live network and writes the packets to a file. Dumpcap\u2019s native capture file format is pcapng, which is also the format used by Wireshark. By default, Dumpcap uses the pcap library to capture traffic from the first available network interface and writes the received raw packet data, along with the packets\u2019 time stamps into a pcapng file. The capture filter syntax follows the rules of the pcap library. The Wireshark command line utility called 'dumpcap.exe' can be used to capture LAN traffic over an extended period of time. Wireshark itself can also be used, but dumpcap does not significantly utilize the computer's memory while capturing for long periods of time.","title":"DumpCap"},{"location":"security/network_security/#daemonlogger","text":"Daemonlogger is a packet logging application designed specifically for use in Network and Systems Management (NSM) environments. The biggest benefit Daemonlogger provides is that, like Dumpcap, it is simple to use for capturing packets. In order to begin capturing, you need only to invoke the command and specify an interface. daemonlogger \u2013i eth1 This option, by default, will begin capturing packets and logging them to the current working directory. Packets will be collected until the capture file size reaches 2 GB, and then a new file will be created. This will continue indefinitely until the process is halted.","title":"DaemonLogger"},{"location":"security/network_security/#netsniff-ng","text":"Netsniff-NG is a high-performance packet capture utility While the utilities we\u2019ve discussed to this point rely on Libpcap for capture, Netsniff-NG utilizes zero-copy mechanisms to capture packets. This is done with the intent to support full packet capture over high throughput links. In order to begin capturing packets with Netsniff-NG, we have to specify an input and output. In most cases, the input will be a network interface, and the output will be a file or folder on disk. netsniff-ng \u2013i eth1 \u2013o data.pcap","title":"NetSniff-NG"},{"location":"security/network_security/#netflow","text":"NetFlow is a feature that was introduced on Cisco routers around 1996 that provides the ability to collect IP network traffic as it enters or exits an interface. By analyzing the data provided by NetFlow, a network administrator can determine things such as the source and destination of traffic, class of service, and the causes of congestion. A typical flow monitoring setup (using NetFlow) consists of three main components:[1] Flow exporter: aggregates packets into flows and exports flow records towards one or more flow collectors. Flow collector: responsible for reception, storage and pre-processing of flow data received from a flow exporter. Analysis application: analyzes received flow data in the context of intrusion detection or traffic profiling, for example. Routers and switches that support NetFlow can collect IP traffic statistics on all interfaces where NetFlow is enabled, and later export those statistics as NetFlow records toward at least one NetFlow collector\u2014typically a server that does the actual traffic analysis.","title":"Netflow"},{"location":"security/network_security/#ids","text":"A security solution that detects security-related events in your environment but does not block them. IDS sensors can be software and hardware based used to collect and analyze the network traffic. These sensors are available in two varieties, network IDS and host IDS. A host IDS is a server-specific agent running on a server with a minimum of overhead to monitor the operating system. A network IDS can be embedded in a networking device, a standalone appliance, or a module monitoring the network traffic. Signature Based IDS The signature-based IDS monitors the network traffic or observes the system and sends an alarm if a known malicious event is happening. It does so by comparing the data flow against a database of known attack patterns These signatures explicitly define what traffic or activity should be considered as malicious. Signature-based detection has been the bread and butter of network-based defensive security for over a decade, partially because it is very similar to how malicious activity is detected at the host level with antivirus utilities The formula is fairly simple: an analyst observes a malicious activity, derives indicators from the activity and develops them into signatures, and then those signatures will alert whenever the activity occurs again. ex: SNORT SURICATA Policy Based IDS The policy-based IDSs (mainly host IDSs) trigger an alarm whenever a violation occurs against the configured policy. This configured policy is or should be a representation of the security policies. This type of IDS is flexible and can be customized to a company's network requirements because it knows exactly what is permitted and what is not. On the other hand, the signature-based systems rely on vendor specifics and default settings. Anomaly Based IDS The anomaly-based IDS looks for traffic that deviates from the normal, but the definition of what is a normal network traffic pattern is the tricky part Two types of anomaly-based IDS exist: statistical and nonstatistical anomaly detection Statistical anomaly detection learns the traffic patterns interactively over a period of time. In the nonstatistical approach, the IDS has a predefined configuration of the supposedly acceptable and valid traffic patterns. Host Based IDS Network Based IDS A host IDS can be described as a distributed agent residing on each server of the network that needs protection. These distributed agents are tied very closely to the underlying operating system. Network IDSs, on the other hand, can be described as intelligent sniffing devices. Data (raw packets) is captured from the network by a network IDS, whereas host IDSs capture the data from the host on which they are installed. Honeypots The use of decoy machines to direct intruders' attention away from the machines under protection is a major technique to preclude intrusion attacks. Any device, system, directory, or file used as a decoy to lure attackers away from important assets and to collect intrusion or abusive behaviors is referred to as a honeypot. A honeypot may be implemented as a physical device or as an emulation system. The idea is to set up decoy machines in a LAN, or decoy directories/files in a file system and make them appear important, but with several exploitable loopholes, to lure attackers to attack these machines or directories/files, so that other machines, directories, and files can evade intruders' attentions. A decoy machine may be a host computer or a server computer. Likewise, we may also set up decoy routers or even decoy LANs.","title":"IDS"},{"location":"security/network_security/#chinks-in-the-armour-tcpip-security-issues","text":"","title":"Chinks In The Armour (TCP/IP Security Issues)"},{"location":"security/network_security/#ip-spoofing","text":"In this type of attack, the attacker replaces the IP address of the sender, or in some rare cases the destination, with a different address. IP spoofing is normally used to exploit a target host. In other cases, it is used to start a denial-of-service (DoS) attack. In a DoS attack, an attacker modifies the IP packet to mislead the target host into accepting the original packet as a packet sourced at a trusted host. The attacker must know the IP address of the trusted host to modify the packet headers (source IP address) so that it appears that the packets are coming from that host. IP Spoofing Detection Techniques Direct TTL Probes In this technique we send a packet to a host of suspect spoofed IP that triggers reply and compare TTL with suspect packet; if the TTL in the reply is not the same as the packet being checked; it is a spoofed packet. This Technique is successful when the attacker is in a different subnet from the victim. IP Identification Number. Send a probe to the host of suspect spoofed traffic that triggers a reply and compare IP ID with suspect traffic. If IP IDs are not in the near value of packet being checked, suspect traffic is spoofed TCP Flow Control Method Attackers sending spoofed TCP packets will not receive the target\u2019s SYN-ACK packets. Attackers cannot therefore be responsive to change in the congestion window size When the receiver still receives traffic even after a windows size is exhausted, most probably the packets are spoofed.","title":"IP Spoofing"},{"location":"security/network_security/#covert-channel","text":"A covert or clandestine channel can be best described as a pipe or communication channel between two entities that can be exploited by a process or application transferring information in a manner that violates the system's security specifications. More specifically for TCP/IP, in some instances, covert channels are established, and data can be secretly passed between two end systems. Ex: ICMP resides at the Internet layer of the TCP/IP protocol suite and is implemented in all TCP/IP hosts. Based on the specifications of the ICMP Protocol, an ICMP Echo Request message should have an 8-byte header and a 56-byte payload. The ICMP Echo Request packet should not carry any data in the payload. However, these packets are often used to carry secret information. The ICMP packets are altered slightly to carry secret data in the payload. This makes the size of the packet larger, but no control exists in the protocol stack to defeat this behavior. The alteration of ICMP packets gives intruders the opportunity to program specialized client-server pairs. These small pieces of code export confidential information without alerting the network administrator. ICMP can be leveraged for more than data exfiltration. For eg. some C C tools such as Loki used ICMP channel to establish encrypted interactive session back in 1996. Deep packet inspection has since come a long way. A lot of IDS/IPS detect ICMP tunneling. Check for echo responses that do not contain the same payload as request Check for volume of ICMP traffic specially for volumes beyond an acceptable threshold","title":"Covert Channel"},{"location":"security/network_security/#ip-fragmentation-attack","text":"The TCP/IP protocol suite, or more specifically IP, allows the fragmentation of packets.(this is a feature not a bug) IP fragmentation offset is used to keep track of the different parts of a datagram. The information or content in this field is used at the destination to reassemble the datagrams All such fragments have the same Identification field value, and the fragmentation offset indicates the position of the current fragment in the context of the original packet. Many access routers and firewalls do not perform packet reassembly. In normal operation, IP fragments do not overlap, but attackers can create artificially fragmented packets to mislead the routers or firewalls. Usually, these packets are small and almost impractical for end systems because of data and computational overhead. A good example of an IP fragmentation attack is the Ping of Death attack. The Ping of Death attack sends fragments that, when reassembled at the end station, create a larger packet than the maximum permissible length. TCP Flags Data exchange using TCP does not happen until a three-way handshake has been successfully completed. This handshake uses different flags to influence the way TCP segments are processed. There are 6 bits in the TCP header that are often called flags. Namely: 6 different flags are part of the TCP header: Urgent pointer field (URG), Acknowledgment field (ACK), Push function (PSH), Reset the connection (RST), Synchronize sequence numbers (SYN), and sender is finished with this connection (FIN). Abuse of the normal operation or settings of these flags can be used by attackers to launch DoS attacks. This causes network servers or web servers to crash or hang. The attacker's ultimate goal is to write special programs or pieces of code that are able to construct these illegal combinations resulting in an efficient DoS attack. SYN FLOOD The timers (or lack of certain timers) in 3 way handshake are often used and exploited by attackers to disable services or even to enter systems. After step 2 of the three-way handshake, no limit is set on the time to wait after receiving a SYN. The attacker initiates many connection requests to the web server of Company XYZ (almost certainly with a spoofed IP address). The SYN+ACK packets (Step 2) sent by the web server back to the originating source IP address are not replied to. This leaves a TCP session half-open on the web server. Multiple packets cause multiple TCP sessions to stay open. Based on the hardware limitations of the server, a limited number of TCP sessions can stay open, and as a result, the web server refuses further connection establishments attempts from any host as soon as a certain limit is reached. These half-open connections need to be completed or timed out before new connections can be established. FIN Attack In normal operation, the sender sets the TCP FIN flag indicating that no more data will be transmitted and the connection can be closed down. This is a four-way handshake mechanism, with both sender and receiver expected to send an acknowledgement on a received FIN packet. During an attack that is trying to kill connections, a spoofed FIN packet is constructed. This packet also has the correct sequence number, so the packets are seen as valid by the targeted host. These sequence numbers are easy to predict. This process is referred to as TCP sequence number prediction, whereby the attacker either sniffs the current Sequence and Acknowledgment (SEQ/ACK) numbers of the connection or can algorithmically predict these numbers.","title":"IP Fragmentation Attack"},{"location":"security/network_security/#connection-hijacking","text":"An authorized user (Employee X) sends HTTP requests over a TCP session with the web server. The web server accepts the packets from Employee X only when the packet has the correct SEQ/ACK numbers. As seen previously, these numbers are important for the web server to distinguish between different sessions and to make sure it is still talking to Employee X. Imagine that the cracker starts sending packets to the web server spoofing the IP address of Employee X, using the correct SEQ/ACK combination. The web server accepts the packet and increments the ACK number. In the meantime, Employee X continues to send packets but with incorrect SEQ/ACK numbers. As a result of sending unsynchronized packets, all data from Employee X is discarded when received by the web server. The attacker pretends to be Employee X using the correct numbers. This finally results in the cracker hijacking the connection, whereby Employee X is completely confused and the web server replies assuming the cracker is sending correct synchronized data. STEPS: The attacker examines the traffic flows with a network monitor and notices traffic from Employee X to a web server. The web server returns or echoes data back to the origination station (Employee X). Employee X acknowledges the packet. The cracker launches a spoofed packet to the server. The web server responds to the cracker. The cracker starts verifying SEQ/ACK numbers to double-check success. At this time, the cracker takes over the session from Employee X, which results in a session hanging for Employee X. The cracker can start sending traffic to the web server. The web server returns the requested data to confirm delivery with the correct ACK number. The cracker can continue to send data (keeping track of the correct SEQ/ACK numbers) until eventually setting the FIN flag to terminate the session.","title":"Connection Hijacking"},{"location":"security/network_security/#buffer-overflow","text":"A buffer is a temporary data storage area used to store program code and data. When a program or process tries to store more data in a buffer than it was originally anticipated to hold, a buffer overflow occurs. Buffers are temporary storage locations in memory (memory or buffer sizes are often measured in bytes) that are able to store a fixed amount of data in bytes. When more data is retrieved than can be stored in a buffer location, the additional information must go into an adjacent buffer, resulting in overwriting the valid data held in them. Mechanism: Buffer overflow vulnerabilities exist in different types. But the overall goal for all buffer overflow attacks is to take over the control of a privileged program and, if possible, the host. The attacker has two tasks to achieve this goal. First, the dirty code needs to be available in the program's code address space. Second, the privileged program should jump to that particular part of the code, which ensures that the proper parameters are loaded into memory. The first task can be achieved in two ways: by injecting the code in the right address space or by using the existing code and modifying certain parameters slightly. The second task is a little more complex because the program's control flow needs to be modified to make the program jump to the dirty code. CounterMeasure: The most important approach is to have a concerted focus on writing correct code. A second method is to make the data buffers (memory locations) address space of the program code non executable. This type of address space makes it impossible to execute code, which might be infiltrated in the program's buffers during an attack.","title":"Buffer Overflow"},{"location":"security/network_security/#more-spoofing","text":"Address Resolution Protocol Spoofing The Address Resolution Protocol (ARP) provides a mechanism to resolve, or map, a known IP address to a MAC sublayer address. Using ARP spoofing, the cracker can exploit this hardware address authentication mechanism by spoofing the hardware address of Host B. Basically, the attacker can convince any host or network device on the local network that the cracker's workstation is the host to be trusted. This is a common method used in a switched environment. ARP spoofing can be prevented with the implementation of static ARP tables in all the hosts and routers of your network. Alternatively, you can implement an ARP server that responds to ARP requests on behalf of the target host. DNS Spoofing DNS spoofing is the method whereby the hacker convinces the target machine that the system it wants to connect to is the machine of the cracker. The cracker modifies some records so that name entries of hosts correspond to the attacker's IP address. There have been instances in which the complete DNS server was compromised by an attack. To counter DNS spoofing, the reverse lookup detects these attacks. The reverse lookup is a mechanism to verify the IP address against a name. The IP address and name files are usually kept on different servers to make compromise much more difficult","title":"More Spoofing"},{"location":"security/threats_attacks_defences/","text":"Part III: Threats, Attacks Defense DNS Protection Cache Poisoning Attack Since DNS responses are cached, a quick response can be provided for repeated translations. DNS negative queries are also cached, e.g., misspelled words, and all cached data periodically times out. Cache poisoning is an issue in what is known as pharming. This term is used to describe a hacker\u2019s attack in which a website\u2019s traffic is redirected to a bogus website by forging the DNS mapping. In this case, an attacker attempts to insert a fake address record for an Internet domain into the DNS. If the server accepts the fake record, the cache is poisoned and subsequent requests for the address of the domain are answered with the address of a server controlled by the attacker. As long as the fake entry is cached by the server, browsers or e-mail servers will automatically go to the address provided by the compromised DNS server. the typical time to live (TTL) for cached entries is a couple of hours, thereby permitting ample time for numerous users to be affected by the attack. DNSSEC (Security Extension) The long-term solution to these DNS problems is authentication. If a resolver cannot distinguish between valid and invalid data in a response, then add source authentication to verify that the data received in a response is equal to the data entered by the zone administrator DNS Security Extensions (DNSSEC) protects against data spoofing and corruption, and provides mechanisms to authenticate servers and requests, as well as mechanisms to establish authenticity and integrity. When authenticating DNS responses, each DNS zone signs its data using a private key. It is recommended that this signing be done offline and in advance. The query for a particular record returns the requested resource record set (RRset) and signature (RRSIG) of the requested resource record set. The resolver then authenticates the response using a public key, which is pre-configured or learned via a sequence of key records in the DNS hierarchy. The goals of DNSSEC are to provide authentication and integrity for DNS responses without confidentiality or DDoS protection. BGP BGP stands for border gateway protocol. It is a routing protocol that exchanges routing information among multiple Autonomous Systems (AS) An Autonomous system is a collection of routers or networks with the same network policy usually under a single administrative control. BGP tells routers which hop to use in order to reach the destination network. BGP is used for both communicating information among routers in an AS (interior) and between multiple ASes (exterior). How BGP Works BGP is responsible for finding a path to a destination router the path it chooses should be the shortest and most reliable one. This decision is done through a protocol known as Link state. With the link state protocol each router broadcasts to all other routers in the network the state of its links and IP subnets. Each router then receives information from the other routers and constructs a complete topology view of the entire network. The next hop routing table is based on this topology view. The link state protocol uses a famous algorithm in the field of computer science, Dijkstra\u2019s shortest path algorithm: We start from our router considering the path cost to all our direct neighbors. The shortest path is then taken We then re-look at all our neighbors that we can reach and update our link state table with the cost information. We then continue taking the shortest path until every router has been visited. BGP Vulnerabilities By corrupting the BGP routing table we are able to influence the direction traffic flows on the internet! This action is known as BGP hijacking. Injecting bogus route advertising information into the BGP-distributed routing database by malicious sources, accidentally or routers can disrupt Internet backbone operations. Blackholing traffic: Blackhole route is a network route, i.e., routing table entry, that goes nowhere and packets matching the route prefix are dropped or ignored. Blackhole routes can only be detected by monitoring the lost traffic. Blackhole routes are best defence against many common viral attacks where the traffic is dropped from infected machines to/from command control masters. Infamous BGP Injection attack on Youtube - EX: In 2008, Pakistan decided to block YouTube by creating a BGP route that led into a black hole. Instead this routing information got transmitted to a hong kong ISP and from there accidentally got propagated to the rest of the world meaning millions were routed through to this black hole and therefore unable to access YouTube. - Potentially, the greatest risk to BGP occurs in a denial of service attack in which a router is flooded with more packets than it can handle. Network overload and router resource exhaustion happen when the network begins carrying an excessive number of BGP messages, overloading the router control processors, memory, routing table and reducing the bandwidth available for data traffic. - Refer : https://medium.com/bugbountywriteup/bgp-the-weak-link-in-the-internet-what-is-bgp-and-how-do-hackers-exploit-it-d899a68ba5bb - Router flapping is another type of attack. Route flapping refers to repetitive changes to the BGP routing table, often several times a minute. Withdrawing and re-advertising at a high-rate can cause a serious problem for routers, since they propagate the announcements of routes. If these route flaps happen fast enough, e.g., 30 to 50 times per second, the router becomes overloaded, which eventually prevents convergence on valid routes. The potential impact for Internet users is a slowdown in message delivery, and in some cases packets may not be delivered at all. BGP Security Border Gateway Protocol Security recommends the use of BGP peer authentication, since it is one of the strongest mechanisms for preventing malicious activity. The authentication mechanisms are Internet Protocol Security (IPsec) or BGP MD5. Another method, known as prefix limits, can be used to avoid filling router tables. In this approach, routers should be configured to disable or terminate a BGP peering session, and issue warning messages to administrators, when a neighbor sends in excess of a preset number of prefixes. IETF is currently working on improving this space Web Based Attacks HTTP Response Splitting Attacks HTTP response splitting attack may happen where the server script embeds user data in HTTP response headers without appropriate sanitation. This typically happens when the script embeds user data in the redirection URL of a redirection response (HTTP status code 3xx), or when the script embeds user data in a cookie value or name when the response sets a cookie. HTTP response splitting attacks can be used to perform web cache poisoning and cross-site scripting attacks. HTTP response splitting is the attacker\u2019s ability to send a single HTTP request that forces the web server to form an output stream, which is then interpreted by the target as two HTTP responses instead of one response. Cross-Site Request Forgery (CSRF or XSRF) A Cross-Site Request Forgery attack tricks the victim\u2019s browser into issuing a command to a vulnerable web application. Vulnerability is caused by browsers automatically including user authentication data, session ID, IP address, Windows domain credentials, etc with each request. Attackers typically use CSRF to initiate transactions such as transfer funds, login/logout user, close account, access sensitive data, and change account details. The vulnerability is caused by web browsers that automatically include credentials with each request, even for requests caused by a form, script, or image on another site. CSRF can also be dynamically constructed as part of a payload for a cross-site scripting attack All sites relying on automatic credentials are vulnerable. Popular browsers cannot prevent cross-site request forgery. Logging out of high-value sites as soon as possible can mitigate CSRF risk. It is recommended that a high-value website must require a client to manually provide authentication data in the same HTTP request used to perform any operation with security implications. Limiting the lifetime of session cookies can also reduce the chance of being used by other malicious sites. OWASP recommends website developers include a required security token in HTTP requests associated with sensitive business functions in order to mitigate CSRF attacks Cross-Site Scripting (XSS) Attacks Cross-Site Scripting occurs when dynamically generated web pages display user input, such as login information, that is not properly validated, allowing an attacker to embed malicious scripts into the generated page and then execute the script on the machine of any user that views the site. If successful, Cross-Site Scripting vulnerabilities can be exploited to manipulate or steal cookies, create requests that can be mistaken for those of a valid user, compromise confidential information, or execute malicious code on end user systems. Cross-Site Scripting (XSS or CSS) attacks involve the execution of malicious scripts on the victim\u2019s browser. The victim is simply a user\u2019s host and not the server. XSS results from a failure to validate user input by a web-based application. Document Object Model (DOM) XSS Attacks The Document Object Model (DOM) based XSS does not require the web server to receive the XSS payload for a successful attack. The attacker abuses the runtime by embedding their data on the client side. An attacker can force the client (browser) to render the page with parts of the DOM controlled by the attacker. When the page is rendered and the data is processed by the page, typically by a client side HTML-embedded script such as JavaScript, the page\u2019s code may insecurely embed the data in the page itself, thus delivering the cross-site scripting payload. There are several DOM objects which can serve as an attack vehicle for delivering malicious script to victims browser. Clickjacking The technique works by hiding malicious link/scripts under the cover of the content of a legitimate site. Buttons on a website actually contain invisible links, placed there by the attacker. So, an individual who clicks on an object they can visually see, is actually being duped into visiting a malicious page or executing a malicious script. When mouseover is used together with clickjacking, the outcome is devastating. Facebook users have been hit by a clickjacking attack, which tricks people into \u201cliking\u201d a particular Facebook page, thus enabling the attack to spread since Memorial Day 2010. There is not yet effective defense against clickjacking, and disabling JavaScript is the only viable method DataBase Attacks Defenses SQL injection Attacks It exploits improper input validation in database queries. A successful exploit will allow attackers to access, modify, or delete information in the database. It permits attackers to steal sensitive information stored within the backend databases of affected websites, which may include such things as user credentials, email addresses, personal information, and credit card numbers SQL Injection Attack Defenses SQL injection can be protected by filtering the query to eliminate malicious syntax, which involves the employment of some tools in order to (a) scan the source code. In addition, the input fields should be restricted to the absolute minimum, typically anywhere from 7-12 characters, and validate any data, e.g., if a user inputs an age make sure the input is an integer with a maximum of 3 digits. VPN A virtual private network (VPN) is a service that offers a secure, reliable connection over a shared public infrastructure such as the Internet. Cisco defines a VPN as an encrypted connection between private networks over a public network. To date, there are three types of VPNs: Remote access Site-to-site Firewall-based Security Breach In spite of the most aggressive steps to protect computers from attacks, attackers sometimes get through. Any event that results in a violation of any of the confidentiality, integrity, or availability (CIA) security tenets is a security breach. Denial of Service Attacks Denial of service (DoS) attacks result in downtime or inability of a user to access a system. DoS attacks impact the availability tenet of information systems security. A DoS attack is a coordinated attempt to deny service by occupying a computer to perform large amounts of unnecessary tasks. This excessive activity makes the system unavailable to perform legitimate operations Two common types of DoS attacks are as follows: Logic attacks\u2014Logic attacks use software flaws to crash or seriously hinder the performance of remote servers. You can prevent many of these attacks by installing the latest patches to keep your software up to date. Flooding attacks\u2014Flooding attacks overwhelm the victim computer\u2019s CPU, memory, or network resources by sending large numbers of useless requests to the machine. Most DoS attacks target weaknesses in the overall system architecture rather than a software bug or security flaw One popular technique for launching a packet flood is a SYN flood. One of the best defenses against DoS attacks is to use intrusion prevention system (IPS) software or devices to detect and stop the attack. Distributed Denial of Service Attacks DDoS attacks differ from regular DoS attacks in their scope. In a DDoS attack, attackers hijack hundreds or even thousands of Internet computers, planting automated attack agents on those systems. The attacker then instructs the agents to bombard the target site with forged messages. This overloads the site and blocks legitimate traffic. The key here is strength in numbers. The attacker does more damage by distributing the attack across multiple computers. Wiretapping Although the term wiretapping is generally associated with voice telephone communications, attackers can also use wiretapping to intercept data communications. Attackers can tap telephone lines and data communication lines. Wiretapping can be active, where the attacker makes modifications to the line. It can also be passive, where an unauthorized user simply listens to the transmission without changing the contents. Passive intrusion can include the copying of data for a subsequent active attack. Two methods of active wiretapping are as follows: Between-the-lines wiretapping\u2014This type of wiretapping does not alter the messages sent by the legitimate user but inserts additional messages into the communication line when the legitimate user pauses. Piggyback-entry wiretapping\u2014This type of wiretapping intercepts and modifies the original message by breaking the communications line and routing the message to another computer that acts as a host. Backdoors Software developers sometimes include hidden access methods, called backdoors, in their programs. Backdoors give developers or support personnel easy access to a system without having to struggle with security controls. The problem is that backdoors don\u2019t always stay hidden. When an attacker discovers a backdoor, he or she can use it to bypass existing security controls such as passwords, encryption, and so on. Where legitimate users log on through front doors using a user ID and password, attackers use backdoors to bypass these normal access controls. Malicious Attacks Birthday Attack Once an attacker compromises a hashed password file, a birthday attack is performed. A birthday attack is a type of cryptographic attack that is used to make brute-force attack of one-way hashes easier. It is a mathematical exploit that is based on the birthday problem in probability theory. Further Reading: https://www.sciencedirect.com/topics/computer-science/birthday-attack https://www.internetsecurity.tips/birthday-attack/ Brute-Force Password Attacks In a brute-force password attack, the attacker tries different passwords on a system until one of them is successful. Usually the attacker employs a software program to try all possible combinations of a likely password, user ID, or security code until it locates a match. This occurs rapidly and in sequence. This type of attack is called a brute-force password attack because the attacker simply hammers away at the code. There is no skill or stealth involved\u2014just brute force that eventually breaks the code. Further Reading: https://owasp.org/www-community/attacks/Brute_force_attack https://owasp.org/www-community/controls/Blocking_Brute_Force_Attacks Dictionary Password Attacks A dictionary password attack is a simple attack that relies on users making poor password choices. In a dictionary password attack, a simple password-cracker program takes all the words from a dictionary file and attempts to log on by entering each dictionary entry as a password. Further Reading: https://capec.mitre.org/data/definitions/16.html Replay Attacks Replay attacks involve capturing data packets from a network and retransmitting them to produce an unauthorized effect. The receipt of duplicate, authenticated IP packets may disrupt service or have some other undesired consequence. Systems can be broken through replay attacks when attackers reuse old messages or parts of old messages to deceive system users. This helps intruders to gain information that allows unauthorized access into a system. Further reading: https://study.com/academy/lesson/replay-attack-definition-examples-prevention.html Man-in-the-Middle Attacks A man-in-the-middle attack takes advantage of the multihop process used by many types of networks. In this type of attack, an attacker intercepts messages between two parties before transferring them on to their intended destination. Web spoofing is a type of man-in-the-middle attack in which the user believes a secure session exists with a particular web server. In reality, the secure connection exists only with the attacker, not the web server. The attacker then establishes a secure connection with the web server, acting as an invisible go-between. The attacker passes traffic between the user and the web server. In this way, the attacker can trick the user into supplying passwords, credit card information, and other private data. Further Reading: https://owasp.org/www-community/attacks/Man-in-the-middle_attack Masquerading In a masquerade attack, one user or computer pretends to be another user or computer. Masquerade attacks usually include one of the other forms of active attacks, such as IP address spoofing or replaying. Attackers can capture authentication sequences and then replay them later to log on again to an application or operating system. For example, an attacker might monitor usernames and passwords sent to a weak web application. The attacker could then use the intercepted credentials to log on to the web application and impersonate the user. Further Reading: https://dl.acm.org/doi/book/10.5555/2521792 https://ieeexplore.ieee.org/document/1653228 Eavesdropping Eavesdropping, or sniffing, occurs when a host sets its network interface on promiscuous mode and copies packets that pass by for later analysis. Promiscuous mode enables a network device to intercept and read each network packet(ofcourse given some conditions) given sec, even if the packet\u2019s address doesn\u2019t match the network device. It is possible to attach hardware and software to monitor and analyze all packets on that segment of the transmission media without alerting any other users. Candidates for eavesdropping include satellite, wireless, mobile, and other transmission methods. Social Engineering Attackers often use a deception technique called social engineering to gain access to resources in an IT infrastructure. In nearly all cases, social engineering involves tricking authorized users into carrying out actions for unauthorized users. The success of social engineering attacks depends on the basic tendency of people to want to be helpful. Phreaking Phone phreaking, or simply phreaking, is a slang term that describes the activity of a subculture of people who study, experiment with, or explore telephone systems, telephone company equipment, and systems connected to public telephone networks. Phreaking is the art of exploiting bugs and glitches that exist in the telephone system. Phishing Phishing is a type of fraud in which an attacker attempts to trick the victim into providing private information such as credit card numbers, passwords, dates of birth, bank account numbers, automated teller machine (ATM) PINs, and Social Security numbers. Pharming Pharming is another type of attack that seeks to obtain personal or private financial information through domain spoofing. A pharming attack doesn\u2019t use messages to trick victims into visiting spoofed websites that appear legitimate, however. Instead, pharming \u201cpoisons\u201d a domain name on the domain name server (DNS), a process known as DNS poisoning. The result is that when a user enters the poisoned server\u2019s web address into his or her address bar, that user navigates to the attacker\u2019s site. The user\u2019s browser still shows the correct website, which makes pharming difficult to detect\u2014and therefore more serious. Where phishing attempts to scam people one at a time with an email or instant message, pharming enables scammers to target large groups of people at one time through domain spoofing.","title":"Threat, Attacks & Defences"},{"location":"security/threats_attacks_defences/#part-iii-threats-attacks-defense","text":"","title":"Part III: Threats, Attacks & Defense"},{"location":"security/threats_attacks_defences/#dns-protection","text":"","title":"DNS Protection"},{"location":"security/threats_attacks_defences/#cache-poisoning-attack","text":"Since DNS responses are cached, a quick response can be provided for repeated translations. DNS negative queries are also cached, e.g., misspelled words, and all cached data periodically times out. Cache poisoning is an issue in what is known as pharming. This term is used to describe a hacker\u2019s attack in which a website\u2019s traffic is redirected to a bogus website by forging the DNS mapping. In this case, an attacker attempts to insert a fake address record for an Internet domain into the DNS. If the server accepts the fake record, the cache is poisoned and subsequent requests for the address of the domain are answered with the address of a server controlled by the attacker. As long as the fake entry is cached by the server, browsers or e-mail servers will automatically go to the address provided by the compromised DNS server. the typical time to live (TTL) for cached entries is a couple of hours, thereby permitting ample time for numerous users to be affected by the attack.","title":"Cache Poisoning Attack"},{"location":"security/threats_attacks_defences/#dnssec-security-extension","text":"The long-term solution to these DNS problems is authentication. If a resolver cannot distinguish between valid and invalid data in a response, then add source authentication to verify that the data received in a response is equal to the data entered by the zone administrator DNS Security Extensions (DNSSEC) protects against data spoofing and corruption, and provides mechanisms to authenticate servers and requests, as well as mechanisms to establish authenticity and integrity. When authenticating DNS responses, each DNS zone signs its data using a private key. It is recommended that this signing be done offline and in advance. The query for a particular record returns the requested resource record set (RRset) and signature (RRSIG) of the requested resource record set. The resolver then authenticates the response using a public key, which is pre-configured or learned via a sequence of key records in the DNS hierarchy. The goals of DNSSEC are to provide authentication and integrity for DNS responses without confidentiality or DDoS protection.","title":"DNSSEC (Security Extension)"},{"location":"security/threats_attacks_defences/#bgp","text":"BGP stands for border gateway protocol. It is a routing protocol that exchanges routing information among multiple Autonomous Systems (AS) An Autonomous system is a collection of routers or networks with the same network policy usually under a single administrative control. BGP tells routers which hop to use in order to reach the destination network. BGP is used for both communicating information among routers in an AS (interior) and between multiple ASes (exterior).","title":"BGP"},{"location":"security/threats_attacks_defences/#how-bgp-works","text":"BGP is responsible for finding a path to a destination router the path it chooses should be the shortest and most reliable one. This decision is done through a protocol known as Link state. With the link state protocol each router broadcasts to all other routers in the network the state of its links and IP subnets. Each router then receives information from the other routers and constructs a complete topology view of the entire network. The next hop routing table is based on this topology view. The link state protocol uses a famous algorithm in the field of computer science, Dijkstra\u2019s shortest path algorithm: We start from our router considering the path cost to all our direct neighbors. The shortest path is then taken We then re-look at all our neighbors that we can reach and update our link state table with the cost information. We then continue taking the shortest path until every router has been visited.","title":"How BGP Works"},{"location":"security/threats_attacks_defences/#bgp-vulnerabilities","text":"By corrupting the BGP routing table we are able to influence the direction traffic flows on the internet! This action is known as BGP hijacking. Injecting bogus route advertising information into the BGP-distributed routing database by malicious sources, accidentally or routers can disrupt Internet backbone operations. Blackholing traffic: Blackhole route is a network route, i.e., routing table entry, that goes nowhere and packets matching the route prefix are dropped or ignored. Blackhole routes can only be detected by monitoring the lost traffic. Blackhole routes are best defence against many common viral attacks where the traffic is dropped from infected machines to/from command control masters. Infamous BGP Injection attack on Youtube - EX: In 2008, Pakistan decided to block YouTube by creating a BGP route that led into a black hole. Instead this routing information got transmitted to a hong kong ISP and from there accidentally got propagated to the rest of the world meaning millions were routed through to this black hole and therefore unable to access YouTube. - Potentially, the greatest risk to BGP occurs in a denial of service attack in which a router is flooded with more packets than it can handle. Network overload and router resource exhaustion happen when the network begins carrying an excessive number of BGP messages, overloading the router control processors, memory, routing table and reducing the bandwidth available for data traffic. - Refer : https://medium.com/bugbountywriteup/bgp-the-weak-link-in-the-internet-what-is-bgp-and-how-do-hackers-exploit-it-d899a68ba5bb - Router flapping is another type of attack. Route flapping refers to repetitive changes to the BGP routing table, often several times a minute. Withdrawing and re-advertising at a high-rate can cause a serious problem for routers, since they propagate the announcements of routes. If these route flaps happen fast enough, e.g., 30 to 50 times per second, the router becomes overloaded, which eventually prevents convergence on valid routes. The potential impact for Internet users is a slowdown in message delivery, and in some cases packets may not be delivered at all. BGP Security Border Gateway Protocol Security recommends the use of BGP peer authentication, since it is one of the strongest mechanisms for preventing malicious activity. The authentication mechanisms are Internet Protocol Security (IPsec) or BGP MD5. Another method, known as prefix limits, can be used to avoid filling router tables. In this approach, routers should be configured to disable or terminate a BGP peering session, and issue warning messages to administrators, when a neighbor sends in excess of a preset number of prefixes. IETF is currently working on improving this space","title":"BGP Vulnerabilities"},{"location":"security/threats_attacks_defences/#web-based-attacks","text":"","title":"Web Based Attacks"},{"location":"security/threats_attacks_defences/#http-response-splitting-attacks","text":"HTTP response splitting attack may happen where the server script embeds user data in HTTP response headers without appropriate sanitation. This typically happens when the script embeds user data in the redirection URL of a redirection response (HTTP status code 3xx), or when the script embeds user data in a cookie value or name when the response sets a cookie. HTTP response splitting attacks can be used to perform web cache poisoning and cross-site scripting attacks. HTTP response splitting is the attacker\u2019s ability to send a single HTTP request that forces the web server to form an output stream, which is then interpreted by the target as two HTTP responses instead of one response.","title":"HTTP Response Splitting Attacks"},{"location":"security/threats_attacks_defences/#cross-site-request-forgery-csrf-or-xsrf","text":"A Cross-Site Request Forgery attack tricks the victim\u2019s browser into issuing a command to a vulnerable web application. Vulnerability is caused by browsers automatically including user authentication data, session ID, IP address, Windows domain credentials, etc with each request. Attackers typically use CSRF to initiate transactions such as transfer funds, login/logout user, close account, access sensitive data, and change account details. The vulnerability is caused by web browsers that automatically include credentials with each request, even for requests caused by a form, script, or image on another site. CSRF can also be dynamically constructed as part of a payload for a cross-site scripting attack All sites relying on automatic credentials are vulnerable. Popular browsers cannot prevent cross-site request forgery. Logging out of high-value sites as soon as possible can mitigate CSRF risk. It is recommended that a high-value website must require a client to manually provide authentication data in the same HTTP request used to perform any operation with security implications. Limiting the lifetime of session cookies can also reduce the chance of being used by other malicious sites. OWASP recommends website developers include a required security token in HTTP requests associated with sensitive business functions in order to mitigate CSRF attacks","title":"Cross-Site Request Forgery (CSRF or XSRF)"},{"location":"security/threats_attacks_defences/#cross-site-scripting-xss-attacks","text":"Cross-Site Scripting occurs when dynamically generated web pages display user input, such as login information, that is not properly validated, allowing an attacker to embed malicious scripts into the generated page and then execute the script on the machine of any user that views the site. If successful, Cross-Site Scripting vulnerabilities can be exploited to manipulate or steal cookies, create requests that can be mistaken for those of a valid user, compromise confidential information, or execute malicious code on end user systems. Cross-Site Scripting (XSS or CSS) attacks involve the execution of malicious scripts on the victim\u2019s browser. The victim is simply a user\u2019s host and not the server. XSS results from a failure to validate user input by a web-based application.","title":"Cross-Site Scripting (XSS) Attacks"},{"location":"security/threats_attacks_defences/#document-object-model-dom-xss-attacks","text":"The Document Object Model (DOM) based XSS does not require the web server to receive the XSS payload for a successful attack. The attacker abuses the runtime by embedding their data on the client side. An attacker can force the client (browser) to render the page with parts of the DOM controlled by the attacker. When the page is rendered and the data is processed by the page, typically by a client side HTML-embedded script such as JavaScript, the page\u2019s code may insecurely embed the data in the page itself, thus delivering the cross-site scripting payload. There are several DOM objects which can serve as an attack vehicle for delivering malicious script to victims browser.","title":"Document Object Model (DOM) XSS Attacks"},{"location":"security/threats_attacks_defences/#clickjacking","text":"The technique works by hiding malicious link/scripts under the cover of the content of a legitimate site. Buttons on a website actually contain invisible links, placed there by the attacker. So, an individual who clicks on an object they can visually see, is actually being duped into visiting a malicious page or executing a malicious script. When mouseover is used together with clickjacking, the outcome is devastating. Facebook users have been hit by a clickjacking attack, which tricks people into \u201cliking\u201d a particular Facebook page, thus enabling the attack to spread since Memorial Day 2010. There is not yet effective defense against clickjacking, and disabling JavaScript is the only viable method","title":"Clickjacking"},{"location":"security/threats_attacks_defences/#database-attacks-defenses","text":"","title":"DataBase Attacks & Defenses"},{"location":"security/threats_attacks_defences/#sql-injection-attacks","text":"It exploits improper input validation in database queries. A successful exploit will allow attackers to access, modify, or delete information in the database. It permits attackers to steal sensitive information stored within the backend databases of affected websites, which may include such things as user credentials, email addresses, personal information, and credit card numbers","title":"SQL injection Attacks"},{"location":"security/threats_attacks_defences/#sql-injection-attack-defenses","text":"SQL injection can be protected by filtering the query to eliminate malicious syntax, which involves the employment of some tools in order to (a) scan the source code. In addition, the input fields should be restricted to the absolute minimum, typically anywhere from 7-12 characters, and validate any data, e.g., if a user inputs an age make sure the input is an integer with a maximum of 3 digits.","title":"SQL Injection Attack Defenses"},{"location":"security/threats_attacks_defences/#vpn","text":"A virtual private network (VPN) is a service that offers a secure, reliable connection over a shared public infrastructure such as the Internet. Cisco defines a VPN as an encrypted connection between private networks over a public network. To date, there are three types of VPNs: Remote access Site-to-site Firewall-based","title":"VPN"},{"location":"security/threats_attacks_defences/#security-breach","text":"In spite of the most aggressive steps to protect computers from attacks, attackers sometimes get through. Any event that results in a violation of any of the confidentiality, integrity, or availability (CIA) security tenets is a security breach.","title":"Security Breach"},{"location":"security/threats_attacks_defences/#denial-of-service-attacks","text":"Denial of service (DoS) attacks result in downtime or inability of a user to access a system. DoS attacks impact the availability tenet of information systems security. A DoS attack is a coordinated attempt to deny service by occupying a computer to perform large amounts of unnecessary tasks. This excessive activity makes the system unavailable to perform legitimate operations Two common types of DoS attacks are as follows: Logic attacks\u2014Logic attacks use software flaws to crash or seriously hinder the performance of remote servers. You can prevent many of these attacks by installing the latest patches to keep your software up to date. Flooding attacks\u2014Flooding attacks overwhelm the victim computer\u2019s CPU, memory, or network resources by sending large numbers of useless requests to the machine. Most DoS attacks target weaknesses in the overall system architecture rather than a software bug or security flaw One popular technique for launching a packet flood is a SYN flood. One of the best defenses against DoS attacks is to use intrusion prevention system (IPS) software or devices to detect and stop the attack.","title":"Denial of Service Attacks"},{"location":"security/threats_attacks_defences/#distributed-denial-of-service-attacks","text":"DDoS attacks differ from regular DoS attacks in their scope. In a DDoS attack, attackers hijack hundreds or even thousands of Internet computers, planting automated attack agents on those systems. The attacker then instructs the agents to bombard the target site with forged messages. This overloads the site and blocks legitimate traffic. The key here is strength in numbers. The attacker does more damage by distributing the attack across multiple computers.","title":"Distributed Denial of Service Attacks"},{"location":"security/threats_attacks_defences/#wiretapping","text":"Although the term wiretapping is generally associated with voice telephone communications, attackers can also use wiretapping to intercept data communications. Attackers can tap telephone lines and data communication lines. Wiretapping can be active, where the attacker makes modifications to the line. It can also be passive, where an unauthorized user simply listens to the transmission without changing the contents. Passive intrusion can include the copying of data for a subsequent active attack. Two methods of active wiretapping are as follows: Between-the-lines wiretapping\u2014This type of wiretapping does not alter the messages sent by the legitimate user but inserts additional messages into the communication line when the legitimate user pauses. Piggyback-entry wiretapping\u2014This type of wiretapping intercepts and modifies the original message by breaking the communications line and routing the message to another computer that acts as a host.","title":"Wiretapping"},{"location":"security/threats_attacks_defences/#backdoors","text":"Software developers sometimes include hidden access methods, called backdoors, in their programs. Backdoors give developers or support personnel easy access to a system without having to struggle with security controls. The problem is that backdoors don\u2019t always stay hidden. When an attacker discovers a backdoor, he or she can use it to bypass existing security controls such as passwords, encryption, and so on. Where legitimate users log on through front doors using a user ID and password, attackers use backdoors to bypass these normal access controls.","title":"Backdoors"},{"location":"security/threats_attacks_defences/#malicious-attacks","text":"","title":"Malicious Attacks"},{"location":"security/threats_attacks_defences/#birthday-attack","text":"Once an attacker compromises a hashed password file, a birthday attack is performed. A birthday attack is a type of cryptographic attack that is used to make brute-force attack of one-way hashes easier. It is a mathematical exploit that is based on the birthday problem in probability theory. Further Reading: https://www.sciencedirect.com/topics/computer-science/birthday-attack https://www.internetsecurity.tips/birthday-attack/","title":"Birthday Attack"},{"location":"security/threats_attacks_defences/#brute-force-password-attacks","text":"In a brute-force password attack, the attacker tries different passwords on a system until one of them is successful. Usually the attacker employs a software program to try all possible combinations of a likely password, user ID, or security code until it locates a match. This occurs rapidly and in sequence. This type of attack is called a brute-force password attack because the attacker simply hammers away at the code. There is no skill or stealth involved\u2014just brute force that eventually breaks the code. Further Reading: https://owasp.org/www-community/attacks/Brute_force_attack https://owasp.org/www-community/controls/Blocking_Brute_Force_Attacks","title":"Brute-Force Password Attacks"},{"location":"security/threats_attacks_defences/#dictionary-password-attacks","text":"A dictionary password attack is a simple attack that relies on users making poor password choices. In a dictionary password attack, a simple password-cracker program takes all the words from a dictionary file and attempts to log on by entering each dictionary entry as a password. Further Reading: https://capec.mitre.org/data/definitions/16.html","title":"Dictionary Password Attacks"},{"location":"security/threats_attacks_defences/#replay-attacks","text":"Replay attacks involve capturing data packets from a network and retransmitting them to produce an unauthorized effect. The receipt of duplicate, authenticated IP packets may disrupt service or have some other undesired consequence. Systems can be broken through replay attacks when attackers reuse old messages or parts of old messages to deceive system users. This helps intruders to gain information that allows unauthorized access into a system. Further reading: https://study.com/academy/lesson/replay-attack-definition-examples-prevention.html","title":"Replay Attacks"},{"location":"security/threats_attacks_defences/#man-in-the-middle-attacks","text":"A man-in-the-middle attack takes advantage of the multihop process used by many types of networks. In this type of attack, an attacker intercepts messages between two parties before transferring them on to their intended destination. Web spoofing is a type of man-in-the-middle attack in which the user believes a secure session exists with a particular web server. In reality, the secure connection exists only with the attacker, not the web server. The attacker then establishes a secure connection with the web server, acting as an invisible go-between. The attacker passes traffic between the user and the web server. In this way, the attacker can trick the user into supplying passwords, credit card information, and other private data. Further Reading: https://owasp.org/www-community/attacks/Man-in-the-middle_attack","title":"Man-in-the-Middle Attacks"},{"location":"security/threats_attacks_defences/#masquerading","text":"In a masquerade attack, one user or computer pretends to be another user or computer. Masquerade attacks usually include one of the other forms of active attacks, such as IP address spoofing or replaying. Attackers can capture authentication sequences and then replay them later to log on again to an application or operating system. For example, an attacker might monitor usernames and passwords sent to a weak web application. The attacker could then use the intercepted credentials to log on to the web application and impersonate the user. Further Reading: https://dl.acm.org/doi/book/10.5555/2521792 https://ieeexplore.ieee.org/document/1653228","title":"Masquerading"},{"location":"security/threats_attacks_defences/#eavesdropping","text":"Eavesdropping, or sniffing, occurs when a host sets its network interface on promiscuous mode and copies packets that pass by for later analysis. Promiscuous mode enables a network device to intercept and read each network packet(ofcourse given some conditions) given sec, even if the packet\u2019s address doesn\u2019t match the network device. It is possible to attach hardware and software to monitor and analyze all packets on that segment of the transmission media without alerting any other users. Candidates for eavesdropping include satellite, wireless, mobile, and other transmission methods.","title":"Eavesdropping"},{"location":"security/threats_attacks_defences/#social-engineering","text":"Attackers often use a deception technique called social engineering to gain access to resources in an IT infrastructure. In nearly all cases, social engineering involves tricking authorized users into carrying out actions for unauthorized users. The success of social engineering attacks depends on the basic tendency of people to want to be helpful.","title":"Social Engineering"},{"location":"security/threats_attacks_defences/#phreaking","text":"Phone phreaking, or simply phreaking, is a slang term that describes the activity of a subculture of people who study, experiment with, or explore telephone systems, telephone company equipment, and systems connected to public telephone networks. Phreaking is the art of exploiting bugs and glitches that exist in the telephone system.","title":"Phreaking"},{"location":"security/threats_attacks_defences/#phishing","text":"Phishing is a type of fraud in which an attacker attempts to trick the victim into providing private information such as credit card numbers, passwords, dates of birth, bank account numbers, automated teller machine (ATM) PINs, and Social Security numbers.","title":"Phishing"},{"location":"security/threats_attacks_defences/#pharming","text":"Pharming is another type of attack that seeks to obtain personal or private financial information through domain spoofing. A pharming attack doesn\u2019t use messages to trick victims into visiting spoofed websites that appear legitimate, however. Instead, pharming \u201cpoisons\u201d a domain name on the domain name server (DNS), a process known as DNS poisoning. The result is that when a user enters the poisoned server\u2019s web address into his or her address bar, that user navigates to the attacker\u2019s site. The user\u2019s browser still shows the correct website, which makes pharming difficult to detect\u2014and therefore more serious. Where phishing attempts to scam people one at a time with an email or instant message, pharming enables scammers to target large groups of people at one time through domain spoofing.","title":"Pharming"},{"location":"security/writing_secure_code/","text":"PART IV: Writing Secure Code More The first and most important step in reducing security and reliability issues is to educate developers. However, even the best-trained engineers make mistakes, security experts can write insecure code and SREs can miss reliability issues. It\u2019s difficult to keep the many considerations and tradeoffs involved in building secure and reliable systems in mind simultaneously, especially if you\u2019re also responsible for producing software. Use frameworks to enforce security and reliability while writing code A better approach is to handle security and reliability in common frameworks, languages, and libraries. Ideally, libraries only expose an interface that makes writing code with common classes of security vulnerabilities impossible. Multiple applications can use each library or framework. When domain experts fix an issue, they remove it from all the applications the framework supports, allowing this engineering approach to scale better. Common Security Vulnerabilities In large codebases, a handful of classes account for the majority of security vulnerabilities, despite ongoing efforts to educate developers and introduce code review. OWASP and SANS publish lists of common vulnerability classes Write Simple Code Try to keep your code clean and simple. Avoid Multi Level Nesting Multilevel nesting is a common anti-pattern that can lead to simple mistakes. If the error is in the most common code path, it will likely be captured by the unit tests. However, unit tests don\u2019t always check error handling paths in multilevel nested code. The error might result in decreased reliability (for example, if the service crashes when it mishandles an error) or a security vulnerability (like a mishandled authorization check error). Eliminate YAGNI Smells Sometimes developers overengineer solutions by adding functionality that may be useful in the future, \u201cjust in case.\u201d This goes against the YAGNI (You Aren\u2019t Gonna Need It) principle, which recommends implementing only the code that you need. YAGNI code adds unnecessary complexity because it needs to be documented, tested, and maintained. To summarize, avoiding YAGNI code leads to improved reliability, and simpler code leads to fewer security bugs, fewer opportunities to make mistakes, and less developer time spent maintaining unused code. Repay Technical Debt It is a common practice for developers to mark places that require further attention with TODO or FIXME annotations. In the short term, this habit can accelerate the delivery velocity for the most critical functionality, and allow a team to meet early deadlines\u2014but it also incurs technical debt. Still, it\u2019s not necessarily a bad practice, as long as you have a clear process (and allocate time) for repaying such debt. Refactoring Refactoring is the most effective way to keep a codebase clean and simple. Even a healthy codebase occasionally needs to be Regardless of the reasons behind refactoring, you should always follow one golden rule: never mix refactoring and functional changes in a single commit to the code repository. Refactoring changes are typically significant and can be difficult to understand. If a commit also includes functional changes, there\u2019s a higher risk that an author or reviewer might overlook bugs. Unit Testing Unit testing can increase system security and reliability by pinpointing a wide range of bugs in individual software components before a release. This technique involves breaking software components into smaller, self-contained \u201cunits\u201d that have no external dependencies, and then testing each unit. Fuzz Testing Fuzz testing is a technique that complements the previously mentioned testing techniques. Fuzzing involves using a fuzz engine to generate a large number of candidate inputs that are then passed through a fuzz driver to the fuzz target. The fuzzer then analyzes how the system handles the input. Complex inputs handled by all kinds of software are popular targets for fuzzing - for example file parsers, compression algo, network protocol implementation and audio codec. Integration Testing Integration testing moves beyond individual units and abstractions, replacing fake or stubbed-out implementations of abstractions like databases or network services with real implementations. As a result, integration tests exercise more complete code paths. Because you must initialize and configure these other dependencies, integration testing may be slower and flakier than unit testing\u2014to execute the test, this approach incorporates real-world variables like network latency as services communicate end-to-end. As you move from testing individual low-level units of code to testing how they interact when composed together, the net result is a higher degree of confidence that the system is behaving as expected. Last But not the least Code Reviews Rely on Automation Don\u2019t check in Secrets Verifiable Builds","title":"Writing Secure code"},{"location":"security/writing_secure_code/#part-iv-writing-secure-code-more","text":"The first and most important step in reducing security and reliability issues is to educate developers. However, even the best-trained engineers make mistakes, security experts can write insecure code and SREs can miss reliability issues. It\u2019s difficult to keep the many considerations and tradeoffs involved in building secure and reliable systems in mind simultaneously, especially if you\u2019re also responsible for producing software.","title":"PART IV: Writing Secure Code & More"},{"location":"security/writing_secure_code/#use-frameworks-to-enforce-security-and-reliability-while-writing-code","text":"A better approach is to handle security and reliability in common frameworks, languages, and libraries. Ideally, libraries only expose an interface that makes writing code with common classes of security vulnerabilities impossible. Multiple applications can use each library or framework. When domain experts fix an issue, they remove it from all the applications the framework supports, allowing this engineering approach to scale better.","title":"Use frameworks to enforce security and reliability while writing code"},{"location":"security/writing_secure_code/#common-security-vulnerabilities","text":"In large codebases, a handful of classes account for the majority of security vulnerabilities, despite ongoing efforts to educate developers and introduce code review. OWASP and SANS publish lists of common vulnerability classes","title":"Common Security Vulnerabilities"},{"location":"security/writing_secure_code/#write-simple-code","text":"Try to keep your code clean and simple.","title":"Write Simple Code"},{"location":"security/writing_secure_code/#avoid-multi-level-nesting","text":"Multilevel nesting is a common anti-pattern that can lead to simple mistakes. If the error is in the most common code path, it will likely be captured by the unit tests. However, unit tests don\u2019t always check error handling paths in multilevel nested code. The error might result in decreased reliability (for example, if the service crashes when it mishandles an error) or a security vulnerability (like a mishandled authorization check error).","title":"Avoid Multi Level Nesting"},{"location":"security/writing_secure_code/#eliminate-yagni-smells","text":"Sometimes developers overengineer solutions by adding functionality that may be useful in the future, \u201cjust in case.\u201d This goes against the YAGNI (You Aren\u2019t Gonna Need It) principle, which recommends implementing only the code that you need. YAGNI code adds unnecessary complexity because it needs to be documented, tested, and maintained. To summarize, avoiding YAGNI code leads to improved reliability, and simpler code leads to fewer security bugs, fewer opportunities to make mistakes, and less developer time spent maintaining unused code.","title":"Eliminate YAGNI Smells"},{"location":"security/writing_secure_code/#repay-technical-debt","text":"It is a common practice for developers to mark places that require further attention with TODO or FIXME annotations. In the short term, this habit can accelerate the delivery velocity for the most critical functionality, and allow a team to meet early deadlines\u2014but it also incurs technical debt. Still, it\u2019s not necessarily a bad practice, as long as you have a clear process (and allocate time) for repaying such debt.","title":"Repay Technical Debt"},{"location":"security/writing_secure_code/#refactoring","text":"Refactoring is the most effective way to keep a codebase clean and simple. Even a healthy codebase occasionally needs to be Regardless of the reasons behind refactoring, you should always follow one golden rule: never mix refactoring and functional changes in a single commit to the code repository. Refactoring changes are typically significant and can be difficult to understand. If a commit also includes functional changes, there\u2019s a higher risk that an author or reviewer might overlook bugs.","title":"Refactoring"},{"location":"security/writing_secure_code/#unit-testing","text":"Unit testing can increase system security and reliability by pinpointing a wide range of bugs in individual software components before a release. This technique involves breaking software components into smaller, self-contained \u201cunits\u201d that have no external dependencies, and then testing each unit.","title":"Unit Testing"},{"location":"security/writing_secure_code/#fuzz-testing","text":"Fuzz testing is a technique that complements the previously mentioned testing techniques. Fuzzing involves using a fuzz engine to generate a large number of candidate inputs that are then passed through a fuzz driver to the fuzz target. The fuzzer then analyzes how the system handles the input. Complex inputs handled by all kinds of software are popular targets for fuzzing - for example file parsers, compression algo, network protocol implementation and audio codec.","title":"Fuzz Testing"},{"location":"security/writing_secure_code/#integration-testing","text":"Integration testing moves beyond individual units and abstractions, replacing fake or stubbed-out implementations of abstractions like databases or network services with real implementations. As a result, integration tests exercise more complete code paths. Because you must initialize and configure these other dependencies, integration testing may be slower and flakier than unit testing\u2014to execute the test, this approach incorporates real-world variables like network latency as services communicate end-to-end. As you move from testing individual low-level units of code to testing how they interact when composed together, the net result is a higher degree of confidence that the system is behaving as expected.","title":"Integration Testing"},{"location":"security/writing_secure_code/#last-but-not-the-least","text":"Code Reviews Rely on Automation Don\u2019t check in Secrets Verifiable Builds","title":"Last But not the least"},{"location":"systems_design/availability/","text":"HA - Availability - Common \u201cNines\u201d Availability is generally expressed as \u201cNines\u201d, common \u2018Nines\u2019 are listed below. Availability % Downtime per year Downtime per month Downtime per week Downtime per day 99%(Two Nines) 3.65 days 7.31 hours 1.68 hours 14.40 minutes 99.5%(Two and a half Nines) 1.83 days 3.65 hours 50.40 minutes 7.20 minutes 99.9%(Three Nines) 8.77 hours 43.83 minutes 10.08 minutes 1.44 minutes 99.95%(Three and a half Nines) 4.38 hours 21.92 minutes 5.04 minutes 43.20 seconds 99.99%(Four Nines) 52.60 minutes 4.38 minutes 1.01 minutes 8.64 seconds 99.995%(Four and a half Nines) 26.30 minutes 2.19 minutes 30.24 seconds 4.32 seconds 99.999%(Five Nines) 5.26 minutes 26.30 seconds 6.05 seconds 864.0 ms Refer https://en.wikipedia.org/wiki/High_availability#Percentage_calculation HA - Availability Serial Components A System with components is operating in the series If failure of a part leads to the combination becoming inoperable. For example if LB in our architecture fails, all access to app tiers will fail. LB and app tiers are connected serially. The combined availability of the system is the product of individual components availability A = Ax x Ay x \u2026.. Refer http://www.eventhelix.com/RealtimeMantra/FaultHandling/system_reliability_availability.htm HA - Availability Parallel Components A System with components is operating in parallel If failure of a part leads to the other part taking over the operations of the failed part. If we have more than one LB and if rest of the LBs can take over the traffic during one LB failure then LBs are operating in parallel The combined availability of the system is A = 1 - ( (1-Ax) x (1-Ax) x \u2026.. ) Refer http://www.eventhelix.com/RealtimeMantra/FaultHandling/system_reliability_availability.htm HA - Core Principles Elimination of single points of failure (SPOF) This means adding redundancy to the system so that the failure of a component does not mean failure of the entire system. Reliable crossover In redundant systems, the crossover point itself tends to become a single point of failure. Reliable systems must provide for reliable crossover. Detection of failures as they occur If the two principles above are observed, then a user may never see a failure Refer https://en.wikipedia.org/wiki/High_availability#Principles HA - SPOF WHAT: Never implement and always eliminate single points of failure. WHEN TO USE: During architecture reviews and new designs. HOW TO USE: Identify single instances on architectural diagrams. Strive for active/active configurations. At the very least we should have a standby to take control when active instances fail. WHY: Maximize availability through multiple instances. KEY TAKEAWAYS: Strive for active/active rather than active/passive solutions. Use load balancers to balance traffic across instances of a service. Use control services with active/passive instances for patterns that require singletons. HA - Reliable Crossover WHAT: Ensure when system components failover they do so reliably. WHEN TO USE: During architecture reviews, failure modeling, and designs. HOW TO USE: Identify how available a system is during the crossover and ensure it is within acceptable limits. WHY: Maximize availability and ensure data handling semantics are preserved. KEY TAKEAWAYS: Strive for active/active rather than active/passive solutions, they have a lesser risk of cross over being unreliable. Use LB and right load balancing methods to ensure reliable failover. Model and build your data systems to ensure data is correctly handled when crossover happens. Generally DB systems follow active/passive semantics for writes. Masters accept writes and when master goes down, follower is promoted to master(active from being passive) to accept writes. We have to be careful here that the cutover never introduces more than one masters. This problem is called a split brain. SRE Use cases SRE works on deciding an acceptable SLA and make sure system is available to achieve the SLA SRE is involved in architecture design right from building the data center to make sure site is not affected by network switch, hardware, power or software failures SRE also run mock drills of failures to see how the system behaves in uncharted territory and comes up with a plan to improve availability if there are misses. https://engineering.linkedin.com/blog/2017/11/resilience-engineering-at-linkedin-with-project-waterbear Post our understanding about HA, our architecture diagram looks something like this below","title":"Availability"},{"location":"systems_design/availability/#ha-availability-common-nines","text":"Availability is generally expressed as \u201cNines\u201d, common \u2018Nines\u2019 are listed below. Availability % Downtime per year Downtime per month Downtime per week Downtime per day 99%(Two Nines) 3.65 days 7.31 hours 1.68 hours 14.40 minutes 99.5%(Two and a half Nines) 1.83 days 3.65 hours 50.40 minutes 7.20 minutes 99.9%(Three Nines) 8.77 hours 43.83 minutes 10.08 minutes 1.44 minutes 99.95%(Three and a half Nines) 4.38 hours 21.92 minutes 5.04 minutes 43.20 seconds 99.99%(Four Nines) 52.60 minutes 4.38 minutes 1.01 minutes 8.64 seconds 99.995%(Four and a half Nines) 26.30 minutes 2.19 minutes 30.24 seconds 4.32 seconds 99.999%(Five Nines) 5.26 minutes 26.30 seconds 6.05 seconds 864.0 ms","title":"HA - Availability - Common \u201cNines\u201d"},{"location":"systems_design/availability/#refer","text":"https://en.wikipedia.org/wiki/High_availability#Percentage_calculation","title":"Refer"},{"location":"systems_design/availability/#ha-availability-serial-components","text":"A System with components is operating in the series If failure of a part leads to the combination becoming inoperable. For example if LB in our architecture fails, all access to app tiers will fail. LB and app tiers are connected serially. The combined availability of the system is the product of individual components availability A = Ax x Ay x \u2026..","title":"HA - Availability Serial Components"},{"location":"systems_design/availability/#refer_1","text":"http://www.eventhelix.com/RealtimeMantra/FaultHandling/system_reliability_availability.htm","title":"Refer"},{"location":"systems_design/availability/#ha-availability-parallel-components","text":"A System with components is operating in parallel If failure of a part leads to the other part taking over the operations of the failed part. If we have more than one LB and if rest of the LBs can take over the traffic during one LB failure then LBs are operating in parallel The combined availability of the system is A = 1 - ( (1-Ax) x (1-Ax) x \u2026.. )","title":"HA - Availability Parallel Components"},{"location":"systems_design/availability/#refer_2","text":"http://www.eventhelix.com/RealtimeMantra/FaultHandling/system_reliability_availability.htm","title":"Refer"},{"location":"systems_design/availability/#ha-core-principles","text":"Elimination of single points of failure (SPOF) This means adding redundancy to the system so that the failure of a component does not mean failure of the entire system. Reliable crossover In redundant systems, the crossover point itself tends to become a single point of failure. Reliable systems must provide for reliable crossover. Detection of failures as they occur If the two principles above are observed, then a user may never see a failure","title":"HA - Core Principles"},{"location":"systems_design/availability/#refer_3","text":"https://en.wikipedia.org/wiki/High_availability#Principles","title":"Refer"},{"location":"systems_design/availability/#ha-spof","text":"WHAT: Never implement and always eliminate single points of failure. WHEN TO USE: During architecture reviews and new designs. HOW TO USE: Identify single instances on architectural diagrams. Strive for active/active configurations. At the very least we should have a standby to take control when active instances fail. WHY: Maximize availability through multiple instances. KEY TAKEAWAYS: Strive for active/active rather than active/passive solutions. Use load balancers to balance traffic across instances of a service. Use control services with active/passive instances for patterns that require singletons.","title":"HA - SPOF"},{"location":"systems_design/availability/#ha-reliable-crossover","text":"WHAT: Ensure when system components failover they do so reliably. WHEN TO USE: During architecture reviews, failure modeling, and designs. HOW TO USE: Identify how available a system is during the crossover and ensure it is within acceptable limits. WHY: Maximize availability and ensure data handling semantics are preserved. KEY TAKEAWAYS: Strive for active/active rather than active/passive solutions, they have a lesser risk of cross over being unreliable. Use LB and right load balancing methods to ensure reliable failover. Model and build your data systems to ensure data is correctly handled when crossover happens. Generally DB systems follow active/passive semantics for writes. Masters accept writes and when master goes down, follower is promoted to master(active from being passive) to accept writes. We have to be careful here that the cutover never introduces more than one masters. This problem is called a split brain.","title":"HA - Reliable Crossover"},{"location":"systems_design/availability/#sre-use-cases","text":"SRE works on deciding an acceptable SLA and make sure system is available to achieve the SLA SRE is involved in architecture design right from building the data center to make sure site is not affected by network switch, hardware, power or software failures SRE also run mock drills of failures to see how the system behaves in uncharted territory and comes up with a plan to improve availability if there are misses. https://engineering.linkedin.com/blog/2017/11/resilience-engineering-at-linkedin-with-project-waterbear Post our understanding about HA, our architecture diagram looks something like this below","title":"SRE Use cases"},{"location":"systems_design/conclusion/","text":"Conclusion Armed with these principles, we hope the course will give a fresh perspective to design software systems. It might be over engineering to get all this on day zero. But some are really important from day 0 like eliminating single points of failure, making scalable services by just increasing replicas. As a bottleneck is reached, we can split code by services, shard data to scale. As the organisation matures, bringing in chaos engineering to measure how systems react to failure will help in designing robust software systems.","title":"Conclusion"},{"location":"systems_design/conclusion/#conclusion","text":"Armed with these principles, we hope the course will give a fresh perspective to design software systems. It might be over engineering to get all this on day zero. But some are really important from day 0 like eliminating single points of failure, making scalable services by just increasing replicas. As a bottleneck is reached, we can split code by services, shard data to scale. As the organisation matures, bringing in chaos engineering to measure how systems react to failure will help in designing robust software systems.","title":"Conclusion"},{"location":"systems_design/fault-tolerance/","text":"Fault Tolerance Failures are not avoidable in any system and will happen all the time, hence we need to build systems that can tolerate failures or recover from them. In systems, failure is the norm rather than the exception. \"Anything that can go wrong will go wrong\u201d -- Murphy\u2019s Law \u201cComplex systems contain changing mixtures of failures latent within them\u201d -- How Complex Systems Fail. Fault Tolerance - Failure Metrics Common failure metrics that get measured and tracked for any system. Mean time to repair (MTTR): The average time to repair and restore a failed system. Mean time between failures (MTBF): The average operational time between one device failure or system breakdown and the next. Mean time to failure (MTTF): The average time a device or system is expected to function before it fails. Mean time to detect (MTTD): The average time between the onset of a problem and when the organization detects it. Mean time to investigate (MTTI): The average time between the detection of an incident and when the organization begins to investigate its cause and solution. Mean time to restore service (MTRS): The average elapsed time from the detection of an incident until the affected system or component is again available to users. Mean time between system incidents (MTBSI): The average elapsed time between the detection of two consecutive incidents. MTBSI can be calculated by adding MTBF and MTRS (MTBSI = MTBF + MTRS). Failure rate: Another reliability metric, which measures the frequency with which a component or system fails. It is expressed as a number of failures over a unit of time. Refer https://www.splunk.com/en_us/data-insider/what-is-mean-time-to-repair.html Fault Tolerance - Fault Isolation Terms Systems should have a short circuit. Say in our content sharing system, if \u201cNotifications\u201d is not working, the site should gracefully handle that failure by removing the functionality instead of taking the whole site down. Swimlane is one of the commonly used fault isolation methodology. Swimlane adds a barrier to the service from other services so that failure on either of them won\u2019t affect the other. Say we roll out a new feature \u2018Advertisement\u2019 in our content sharing app. We can have two architectures If Ads are generated on the fly synchronously during each Newsfeed request, the faults in Ads feature gets propagated to Newsfeed feature. Instead if we swimlane \u201cGeneration of Ads\u201d service and use a shared storage to populate Newsfeed App, Ads failures won\u2019t cascade to Newsfeed and worst case if Ads don\u2019t meet SLA , we can have Newsfeed without Ads. Let's take another example, we come up with a new model for our Content sharing App. Here we roll out enterprise content sharing App where enterprises pay for the service and the content should never be shared outside the enterprise. Swimlane Principles Principle 1: Nothing is shared (also known as \u201cshare as little as possible\u201d). The less that is shared within a swim lane, the more fault isolative the swim lane becomes. (as shown in Enterprise usecase) Principle 2: Nothing crosses a swim lane boundary. Synchronous (defined by expecting a request\u2014not the transfer protocol) communication never crosses a swim lane boundary; if it does, the boundary is drawn incorrectly. (as shown in Ads feature) Swimlane Approaches Approach 1: Swim lane the money-maker. Never allow your cash register to be compromised by other systems. (Tier 1 vs Tier 2 in enterprise use case) Approach 2: Swim lane the biggest sources of incidents. Identify the recurring causes of pain and isolate them.(if Ads feature is in code yellow, swim laning it is the best option) Approach 3: Swim lane natural barriers. Customer boundaries make good swim lanes.(Public vs Enterprise customers) Refer https://learning.oreilly.com/library/view/the-art-of/9780134031408/ch21.html#ch21 SRE Use cases: Work with the DC tech or cloud team to distribute infrastructure such that its immune to switch or power failures by creating fault zones within a Data Center https://docs.microsoft.com/en-us/azure/virtual-machines/manage-availability#use-availability-zones-to-protect-from-datacenter-level-failures Work with the partners and design interaction between services such that one service breakdown is not amplified in a cascading fashion to all upstreams","title":"Fault Tolerance"},{"location":"systems_design/fault-tolerance/#fault-tolerance","text":"Failures are not avoidable in any system and will happen all the time, hence we need to build systems that can tolerate failures or recover from them. In systems, failure is the norm rather than the exception. \"Anything that can go wrong will go wrong\u201d -- Murphy\u2019s Law \u201cComplex systems contain changing mixtures of failures latent within them\u201d -- How Complex Systems Fail.","title":"Fault Tolerance"},{"location":"systems_design/fault-tolerance/#fault-tolerance-failure-metrics","text":"Common failure metrics that get measured and tracked for any system. Mean time to repair (MTTR): The average time to repair and restore a failed system. Mean time between failures (MTBF): The average operational time between one device failure or system breakdown and the next. Mean time to failure (MTTF): The average time a device or system is expected to function before it fails. Mean time to detect (MTTD): The average time between the onset of a problem and when the organization detects it. Mean time to investigate (MTTI): The average time between the detection of an incident and when the organization begins to investigate its cause and solution. Mean time to restore service (MTRS): The average elapsed time from the detection of an incident until the affected system or component is again available to users. Mean time between system incidents (MTBSI): The average elapsed time between the detection of two consecutive incidents. MTBSI can be calculated by adding MTBF and MTRS (MTBSI = MTBF + MTRS). Failure rate: Another reliability metric, which measures the frequency with which a component or system fails. It is expressed as a number of failures over a unit of time.","title":"Fault Tolerance - Failure Metrics"},{"location":"systems_design/fault-tolerance/#refer","text":"https://www.splunk.com/en_us/data-insider/what-is-mean-time-to-repair.html","title":"Refer"},{"location":"systems_design/fault-tolerance/#fault-tolerance-fault-isolation-terms","text":"Systems should have a short circuit. Say in our content sharing system, if \u201cNotifications\u201d is not working, the site should gracefully handle that failure by removing the functionality instead of taking the whole site down. Swimlane is one of the commonly used fault isolation methodology. Swimlane adds a barrier to the service from other services so that failure on either of them won\u2019t affect the other. Say we roll out a new feature \u2018Advertisement\u2019 in our content sharing app. We can have two architectures If Ads are generated on the fly synchronously during each Newsfeed request, the faults in Ads feature gets propagated to Newsfeed feature. Instead if we swimlane \u201cGeneration of Ads\u201d service and use a shared storage to populate Newsfeed App, Ads failures won\u2019t cascade to Newsfeed and worst case if Ads don\u2019t meet SLA , we can have Newsfeed without Ads. Let's take another example, we come up with a new model for our Content sharing App. Here we roll out enterprise content sharing App where enterprises pay for the service and the content should never be shared outside the enterprise.","title":"Fault Tolerance - Fault Isolation Terms"},{"location":"systems_design/fault-tolerance/#swimlane-principles","text":"Principle 1: Nothing is shared (also known as \u201cshare as little as possible\u201d). The less that is shared within a swim lane, the more fault isolative the swim lane becomes. (as shown in Enterprise usecase) Principle 2: Nothing crosses a swim lane boundary. Synchronous (defined by expecting a request\u2014not the transfer protocol) communication never crosses a swim lane boundary; if it does, the boundary is drawn incorrectly. (as shown in Ads feature)","title":"Swimlane Principles"},{"location":"systems_design/fault-tolerance/#swimlane-approaches","text":"Approach 1: Swim lane the money-maker. Never allow your cash register to be compromised by other systems. (Tier 1 vs Tier 2 in enterprise use case) Approach 2: Swim lane the biggest sources of incidents. Identify the recurring causes of pain and isolate them.(if Ads feature is in code yellow, swim laning it is the best option) Approach 3: Swim lane natural barriers. Customer boundaries make good swim lanes.(Public vs Enterprise customers)","title":"Swimlane Approaches"},{"location":"systems_design/fault-tolerance/#refer_1","text":"https://learning.oreilly.com/library/view/the-art-of/9780134031408/ch21.html#ch21","title":"Refer"},{"location":"systems_design/fault-tolerance/#sre-use-cases","text":"Work with the DC tech or cloud team to distribute infrastructure such that its immune to switch or power failures by creating fault zones within a Data Center https://docs.microsoft.com/en-us/azure/virtual-machines/manage-availability#use-availability-zones-to-protect-from-datacenter-level-failures Work with the partners and design interaction between services such that one service breakdown is not amplified in a cascading fashion to all upstreams","title":"SRE Use cases:"},{"location":"systems_design/intro/","text":"Systems Design Pre - Requisites Fundamentals of common software system components: - Operating Systems - Networking - Databases RDBMS/NoSQL What to expect from this training Thinking about and designing for scalability, availability, and reliability of large scale software systems. What is not covered under this training Individual software components\u2019 scalability and reliability concerns like e.g. Databases, while the same scalability principles and thinking can be applied, these individual components have their own specific nuances when scaling them and thinking about their reliability. More light will be shed on concepts rather than on setting up and configuring components like Loadbalancers to achieve scalability, availability and reliability of systems Training Content Introduction Scalability High Availability Fault Tolerance Introduction So, how do you go about learning to design a system? \u201d Like most great questions, it showed a level of naivety that was breathtaking. The only short answer I could give was, essentially, that you learned how to design a system by designing systems and finding out what works and what doesn\u2019t work.\u201d Jim Waldo, Sun Microsystems, On System Design As software and hardware systems have multiple moving parts, we need to think about how those parts will grow, their failure modes, their inter-dependencies, how it will impact the users and the business. There is no one-shot method or way to learn or do system design, we only learn to design systems by designing and iterating on them. This course will be a starter to make one think about scalability, availability, and fault tolerance during systems design. Backstory Let\u2019s design a simple content sharing application where users can share photos, media in our application which can be liked by their friends. Let\u2019s start with a simple design of the application and evolve it as we learn system design concepts","title":"Intro"},{"location":"systems_design/intro/#systems-design","text":"","title":"Systems Design"},{"location":"systems_design/intro/#pre-requisites","text":"Fundamentals of common software system components: - Operating Systems - Networking - Databases RDBMS/NoSQL","title":"Pre - Requisites"},{"location":"systems_design/intro/#what-to-expect-from-this-training","text":"Thinking about and designing for scalability, availability, and reliability of large scale software systems.","title":"What to expect from this training"},{"location":"systems_design/intro/#what-is-not-covered-under-this-training","text":"Individual software components\u2019 scalability and reliability concerns like e.g. Databases, while the same scalability principles and thinking can be applied, these individual components have their own specific nuances when scaling them and thinking about their reliability. More light will be shed on concepts rather than on setting up and configuring components like Loadbalancers to achieve scalability, availability and reliability of systems","title":"What is not covered under this training"},{"location":"systems_design/intro/#training-content","text":"Introduction Scalability High Availability Fault Tolerance","title":"Training Content"},{"location":"systems_design/intro/#introduction","text":"So, how do you go about learning to design a system? \u201d Like most great questions, it showed a level of naivety that was breathtaking. The only short answer I could give was, essentially, that you learned how to design a system by designing systems and finding out what works and what doesn\u2019t work.\u201d Jim Waldo, Sun Microsystems, On System Design As software and hardware systems have multiple moving parts, we need to think about how those parts will grow, their failure modes, their inter-dependencies, how it will impact the users and the business. There is no one-shot method or way to learn or do system design, we only learn to design systems by designing and iterating on them. This course will be a starter to make one think about scalability, availability, and fault tolerance during systems design.","title":"Introduction"},{"location":"systems_design/intro/#backstory","text":"Let\u2019s design a simple content sharing application where users can share photos, media in our application which can be liked by their friends. Let\u2019s start with a simple design of the application and evolve it as we learn system design concepts","title":"Backstory"},{"location":"systems_design/scalability/","text":"Scalability What does scalability mean for a system/service? A system is composed of services/components, each service/component scalability needs to be tackled separately, and the scalability of the system as a whole. A service is said to be scalable if, as resources are added to the system, it results in increased performance in a manner proportional to resources added An always-on service is said to be scalable if adding resources to facilitate redundancy does not result in a loss of performance Refer https://www.allthingsdistributed.com/2006/03/a_word_on_scalability.html Scalability - AKF Scale Cube The Scale Cube is a model for segmenting services, defining microservices, and scaling products. It also creates a common language for teams to discuss scale related options in designing solutions. Following section talks about certain scaling patterns based on our inferences from AKF cube Scalability - Horizontal scaling Horizontal scaling stands for cloning of an application or service such that work can easily be distributed across instances with absolutely no bias. Lets see how our monolithic application improves with this principle Here DB is scaled separately from the application. This is to let you know each component\u2019s scaling capabilities can be different. Usually web applications can be scaled by adding resources unless there is no state stored inside the application. But DBs can be scaled only for Reads by adding more followers but Writes have to go to only one master to make sure data is consistent. There are some DBs which support multi master writes but we are keeping them out of scope at this point. Apps should be able to differentiate between Read and Writes to choose appropriate DB servers. Load balancers can split traffic between identical servers transparently. WHAT: Duplication of services or databases to spread transaction load. WHEN TO USE: Databases with a very high read-to-write ratio (5:1 or greater\u2014the higher the better). Because only read replicas of DBs can be scaled, not the Master. HOW TO USE: Simply clone services and implement a load balancer. For databases, ensure that the accessing code understands the difference between a read and a write. WHY: Allows for fast scale of transactions at the cost of duplicated data and functionality. KEY TAKEAWAYS: This is fast to implement, is low cost from a developer effort perspective, and can scale transaction volumes nicely. However, they tend to be high cost from the perspective of the operational cost of data. Cost here means if we have 3 followers and 1 Master DB, the same database will be stored as 4 copies in the 4 servers. Hence added storage cost Refer https://learning.oreilly.com/library/view/the-art-of/9780134031408/ch23.html Scalability Pattern - Load Balancing Improves the distribution of workloads across multiple computing resources, such as computers, a computer cluster, network links, central processing units, or disk drives. Commonly used technique is load balancing traffic across identical server clusters. Similar philosophy is used to load balance traffic across network links by ECMP , disk drives by RAID etc Aims to optimize resource use, maximize throughput, minimize response time, and avoid overload of any single resource. Using multiple components with load balancing instead of a single component may increase reliability and availability through redundancy. In our updated architecture diagram we have 4 servers to handle app traffic instead of a single server The device or system that performs load balancing is called a load balancer, abbreviated as LB. Refer https://en.wikipedia.org/wiki/Load_balancing_(computing) https://blog.envoyproxy.io/introduction-to-modern-network-load-balancing-and-proxying-a57f6ff80236 https://learning.oreilly.com/library/view/load-balancing-in/9781492038009/ https://learning.oreilly.com/library/view/practical-load-balancing/9781430236801/ http://shop.oreilly.com/product/9780596000509.do Scalability Pattern - LB Tasks What does an LB do? Service discovery: What backends are available in the system? In our architecture, 4 servers are available to serve App traffic. LB acts as a single endpoint that clients can use transparently to reach one of the 4 servers. Health checking: What backends are currently healthy and available to accept requests? If one out of the 4 App servers turns bad, LB should automatically short circuit the path so that clients don\u2019t sense any application downtime Load balancing: What algorithm should be used to balance individual requests across the healthy backends? There are many algorithms to distribute traffic across one of the four servers. Based on observations/experience, SRE can pick the algorithm that suits their pattern Scalability Pattern - LB Methods Common Load Balancing Methods Least Connection Method directs traffic to the server with the fewest active connections. Most useful when there are a large number of persistent connections in the traffic unevenly distributed between the servers. Works if clients maintain long lived connections Least Response Time Method directs traffic to the server with the fewest active connections and the lowest average response time. Here response time is used to provide feedback of server\u2019s health Round Robin Method rotates servers by directing traffic to the first available server and then moves that server to the bottom of the queue. Most useful when servers are of equal specification and there are not many persistent connections. IP Hash the IP address of the client determines which server receives the request. This can sometimes cause skewness in distribution but is useful if apps store some state locally and need some stickiness More advanced client/server-side example techniques - https://docs.nginx.com/nginx/admin-guide/load-balancer/ - http://cbonte.github.io/haproxy-dconv/2.2/intro.html#3.3.5 - https://twitter.github.io/finagle/guide/Clients.html#load-balancing Scalability Pattern - Caching - Content Delivery Networks (CDN) CDNs are added closer to the client\u2019s location. If the app has static data like images, Javascript, CSS which don\u2019t change very often, they can be cached. Since our example is a content sharing site, static content can be cached in CDNs with a suitable expiry. WHAT: Use CDNs (content delivery networks) to offload traffic from your site. WHEN TO USE: When speed improvements and scale warrant the additional cost. HOW TO USE: Most CDNs leverage DNS to serve content on your site\u2019s behalf. Thus you may need to make minor DNS changes or additions and move content to be served from new subdomains. Eg media-exp1.licdn.com is a domain used by Linkedin to serve static content Here a CNAME points the domain to the DNS of CDN provider dig media-exp1.licdn.com +short 2-01-2c3e-005c.cdx.cedexis.net. WHY: CDNs help offload traffic spikes and are often economical ways to scale parts of a site\u2019s traffic. They also often substantially improve page download times. KEY TAKEAWAYS: CDNs are a fast and simple way to offset the spikiness of traffic as well as traffic growth in general. Make sure you perform a cost-benefit analysis and monitor the CDN usage. If CDNs have a lot of cache misses, then we don\u2019t gain much from CDN and are still serving requests using our compute resources. Scalability - Microservices This pattern represents the separation of work by service or function within the application. Microservices are meant to address the issues associated with growth and complexity in the code base and data sets. The intent is to create fault isolation as well as to reduce response times. Microservices can scale transactions, data sizes, and codebase sizes. They are most effective in scaling the size and complexity of your codebase. They tend to cost a bit more than horizontal scaling because the engineering team needs to rewrite services or, at the very least, disaggregate them from the original monolithic application. WHAT: Sometimes referred to as scale through services or resources, this rule focuses on scaling by splitting data sets, transactions, and engineering teams along verb (services) or noun (resources) boundaries. WHEN TO USE: Very large data sets where relations between data are not necessary. Large, complex systems where scaling engineering resources requires specialization. HOW TO USE: Split up actions by using verbs, or resources by using nouns, or use a mix. Split both the services and the data along the lines defined by the verb/noun approach. WHY: Allows for efficient scaling of not only transactions but also very large data sets associated with those transactions. It also allows for the efficient scaling of teams. KEY TAKEAWAYS: Microservices allow for efficient scaling of transactions, large data sets, and can help with fault isolation. It helps reduce the communication overhead of teams. The codebase becomes less complex as disjoint features are decoupled and spun as new services thereby letting each service scale independently specific to its requirement. Refer https://learning.oreilly.com/library/view/the-art-of/9780134031408/ch23.html Scalability - Sharding This pattern represents the separation of work based on attributes that are looked up or determined at the time of the transaction. Most often, these are implemented as splits by requestor, customer, or client. Very often, a lookup service or deterministic algorithm will need to be written for these types of splits. Sharding aids in scaling transaction growth, scaling instruction sets, and decreasing processing time (the last by limiting the data necessary to perform any transaction). This is more effective at scaling growth in customers or clients. It can aid with disaster recovery efforts, and limit the impact of incidents to only a specific segment of customers. Here the auth data is sharded based on user names so that DBs can respond faster as the amount of data DBs have to work on has drastically reduced during queries. There can be other ways to split Here the whole data centre is split and replicated and clients are directed to a data centre based on their geography. This helps in improving performance as clients are directed to the closest Data centre and performance increases as we add more data centres. There are some replication and consistency overhead with this approach one needs to be aware of. This also gives fault tolerance by rolling out test features to one site and rollback if there is an impact to that geography WHAT: This is very often a split by some unique aspect of the customer such as customer ID, name, geography, and so on. WHEN TO USE: Very large, similar data sets such as large and rapidly growing customer bases or when the response time for a geographically distributed customer base is important. HOW TO USE: Identify something you know about the customer, such as customer ID, last name, geography, or device, and split or partition both data and services based on that attribute. WHY: Rapid customer growth exceeds other forms of data growth, or you have the need to perform fault isolation between certain customer groups as you scale. KEY TAKEAWAYS: Shards are effective at helping you to scale customer bases but can also be applied to other very large data sets that can\u2019t be pulled apart using the microservices methodology. Refer https://learning.oreilly.com/library/view/the-art-of/9780134031408/ch23.html SRE Use cases SREs in coordination with the network team work on how to map users traffic to a particular site. https://engineering.linkedin.com/blog/2017/05/trafficshift--load-testing-at-scale SREs work closely with the Dev team to split monoliths to multiple microservices that are easy to run and manage SREs work on improving Load Balancers' reliability, service discovery and performance SREs work closely to split Data into shards and manage data integrity and consistency. https://engineering.linkedin.com/espresso/introducing-espresso-linkedins-hot-new-distributed-document-store SREs work to set up, configure and improve CDN cache hit rate.","title":"Scalability"},{"location":"systems_design/scalability/#scalability","text":"What does scalability mean for a system/service? A system is composed of services/components, each service/component scalability needs to be tackled separately, and the scalability of the system as a whole. A service is said to be scalable if, as resources are added to the system, it results in increased performance in a manner proportional to resources added An always-on service is said to be scalable if adding resources to facilitate redundancy does not result in a loss of performance","title":"Scalability"},{"location":"systems_design/scalability/#refer","text":"https://www.allthingsdistributed.com/2006/03/a_word_on_scalability.html","title":"Refer"},{"location":"systems_design/scalability/#scalability-akf-scale-cube","text":"The Scale Cube is a model for segmenting services, defining microservices, and scaling products. It also creates a common language for teams to discuss scale related options in designing solutions. Following section talks about certain scaling patterns based on our inferences from AKF cube","title":"Scalability - AKF Scale Cube"},{"location":"systems_design/scalability/#scalability-horizontal-scaling","text":"Horizontal scaling stands for cloning of an application or service such that work can easily be distributed across instances with absolutely no bias. Lets see how our monolithic application improves with this principle Here DB is scaled separately from the application. This is to let you know each component\u2019s scaling capabilities can be different. Usually web applications can be scaled by adding resources unless there is no state stored inside the application. But DBs can be scaled only for Reads by adding more followers but Writes have to go to only one master to make sure data is consistent. There are some DBs which support multi master writes but we are keeping them out of scope at this point. Apps should be able to differentiate between Read and Writes to choose appropriate DB servers. Load balancers can split traffic between identical servers transparently. WHAT: Duplication of services or databases to spread transaction load. WHEN TO USE: Databases with a very high read-to-write ratio (5:1 or greater\u2014the higher the better). Because only read replicas of DBs can be scaled, not the Master. HOW TO USE: Simply clone services and implement a load balancer. For databases, ensure that the accessing code understands the difference between a read and a write. WHY: Allows for fast scale of transactions at the cost of duplicated data and functionality. KEY TAKEAWAYS: This is fast to implement, is low cost from a developer effort perspective, and can scale transaction volumes nicely. However, they tend to be high cost from the perspective of the operational cost of data. Cost here means if we have 3 followers and 1 Master DB, the same database will be stored as 4 copies in the 4 servers. Hence added storage cost","title":"Scalability - Horizontal scaling"},{"location":"systems_design/scalability/#refer_1","text":"https://learning.oreilly.com/library/view/the-art-of/9780134031408/ch23.html","title":"Refer"},{"location":"systems_design/scalability/#scalability-pattern-load-balancing","text":"Improves the distribution of workloads across multiple computing resources, such as computers, a computer cluster, network links, central processing units, or disk drives. Commonly used technique is load balancing traffic across identical server clusters. Similar philosophy is used to load balance traffic across network links by ECMP , disk drives by RAID etc Aims to optimize resource use, maximize throughput, minimize response time, and avoid overload of any single resource. Using multiple components with load balancing instead of a single component may increase reliability and availability through redundancy. In our updated architecture diagram we have 4 servers to handle app traffic instead of a single server The device or system that performs load balancing is called a load balancer, abbreviated as LB.","title":"Scalability Pattern - Load Balancing"},{"location":"systems_design/scalability/#refer_2","text":"https://en.wikipedia.org/wiki/Load_balancing_(computing) https://blog.envoyproxy.io/introduction-to-modern-network-load-balancing-and-proxying-a57f6ff80236 https://learning.oreilly.com/library/view/load-balancing-in/9781492038009/ https://learning.oreilly.com/library/view/practical-load-balancing/9781430236801/ http://shop.oreilly.com/product/9780596000509.do","title":"Refer"},{"location":"systems_design/scalability/#scalability-pattern-lb-tasks","text":"What does an LB do?","title":"Scalability Pattern - LB Tasks"},{"location":"systems_design/scalability/#service-discovery","text":"What backends are available in the system? In our architecture, 4 servers are available to serve App traffic. LB acts as a single endpoint that clients can use transparently to reach one of the 4 servers.","title":"Service discovery:"},{"location":"systems_design/scalability/#health-checking","text":"What backends are currently healthy and available to accept requests? If one out of the 4 App servers turns bad, LB should automatically short circuit the path so that clients don\u2019t sense any application downtime","title":"Health checking:"},{"location":"systems_design/scalability/#load-balancing","text":"What algorithm should be used to balance individual requests across the healthy backends? There are many algorithms to distribute traffic across one of the four servers. Based on observations/experience, SRE can pick the algorithm that suits their pattern","title":"Load balancing:"},{"location":"systems_design/scalability/#scalability-pattern-lb-methods","text":"Common Load Balancing Methods","title":"Scalability Pattern - LB Methods"},{"location":"systems_design/scalability/#least-connection-method","text":"directs traffic to the server with the fewest active connections. Most useful when there are a large number of persistent connections in the traffic unevenly distributed between the servers. Works if clients maintain long lived connections","title":"Least Connection Method"},{"location":"systems_design/scalability/#least-response-time-method","text":"directs traffic to the server with the fewest active connections and the lowest average response time. Here response time is used to provide feedback of server\u2019s health","title":"Least Response Time Method"},{"location":"systems_design/scalability/#round-robin-method","text":"rotates servers by directing traffic to the first available server and then moves that server to the bottom of the queue. Most useful when servers are of equal specification and there are not many persistent connections.","title":"Round Robin Method"},{"location":"systems_design/scalability/#ip-hash","text":"the IP address of the client determines which server receives the request. This can sometimes cause skewness in distribution but is useful if apps store some state locally and need some stickiness More advanced client/server-side example techniques - https://docs.nginx.com/nginx/admin-guide/load-balancer/ - http://cbonte.github.io/haproxy-dconv/2.2/intro.html#3.3.5 - https://twitter.github.io/finagle/guide/Clients.html#load-balancing","title":"IP Hash"},{"location":"systems_design/scalability/#scalability-pattern-caching-content-delivery-networks-cdn","text":"CDNs are added closer to the client\u2019s location. If the app has static data like images, Javascript, CSS which don\u2019t change very often, they can be cached. Since our example is a content sharing site, static content can be cached in CDNs with a suitable expiry. WHAT: Use CDNs (content delivery networks) to offload traffic from your site. WHEN TO USE: When speed improvements and scale warrant the additional cost. HOW TO USE: Most CDNs leverage DNS to serve content on your site\u2019s behalf. Thus you may need to make minor DNS changes or additions and move content to be served from new subdomains. Eg media-exp1.licdn.com is a domain used by Linkedin to serve static content Here a CNAME points the domain to the DNS of CDN provider dig media-exp1.licdn.com +short 2-01-2c3e-005c.cdx.cedexis.net. WHY: CDNs help offload traffic spikes and are often economical ways to scale parts of a site\u2019s traffic. They also often substantially improve page download times. KEY TAKEAWAYS: CDNs are a fast and simple way to offset the spikiness of traffic as well as traffic growth in general. Make sure you perform a cost-benefit analysis and monitor the CDN usage. If CDNs have a lot of cache misses, then we don\u2019t gain much from CDN and are still serving requests using our compute resources.","title":"Scalability Pattern - Caching - Content Delivery Networks (CDN)"},{"location":"systems_design/scalability/#scalability-microservices","text":"This pattern represents the separation of work by service or function within the application. Microservices are meant to address the issues associated with growth and complexity in the code base and data sets. The intent is to create fault isolation as well as to reduce response times. Microservices can scale transactions, data sizes, and codebase sizes. They are most effective in scaling the size and complexity of your codebase. They tend to cost a bit more than horizontal scaling because the engineering team needs to rewrite services or, at the very least, disaggregate them from the original monolithic application. WHAT: Sometimes referred to as scale through services or resources, this rule focuses on scaling by splitting data sets, transactions, and engineering teams along verb (services) or noun (resources) boundaries. WHEN TO USE: Very large data sets where relations between data are not necessary. Large, complex systems where scaling engineering resources requires specialization. HOW TO USE: Split up actions by using verbs, or resources by using nouns, or use a mix. Split both the services and the data along the lines defined by the verb/noun approach. WHY: Allows for efficient scaling of not only transactions but also very large data sets associated with those transactions. It also allows for the efficient scaling of teams. KEY TAKEAWAYS: Microservices allow for efficient scaling of transactions, large data sets, and can help with fault isolation. It helps reduce the communication overhead of teams. The codebase becomes less complex as disjoint features are decoupled and spun as new services thereby letting each service scale independently specific to its requirement.","title":"Scalability - Microservices"},{"location":"systems_design/scalability/#refer_3","text":"https://learning.oreilly.com/library/view/the-art-of/9780134031408/ch23.html","title":"Refer"},{"location":"systems_design/scalability/#scalability-sharding","text":"This pattern represents the separation of work based on attributes that are looked up or determined at the time of the transaction. Most often, these are implemented as splits by requestor, customer, or client. Very often, a lookup service or deterministic algorithm will need to be written for these types of splits. Sharding aids in scaling transaction growth, scaling instruction sets, and decreasing processing time (the last by limiting the data necessary to perform any transaction). This is more effective at scaling growth in customers or clients. It can aid with disaster recovery efforts, and limit the impact of incidents to only a specific segment of customers. Here the auth data is sharded based on user names so that DBs can respond faster as the amount of data DBs have to work on has drastically reduced during queries. There can be other ways to split Here the whole data centre is split and replicated and clients are directed to a data centre based on their geography. This helps in improving performance as clients are directed to the closest Data centre and performance increases as we add more data centres. There are some replication and consistency overhead with this approach one needs to be aware of. This also gives fault tolerance by rolling out test features to one site and rollback if there is an impact to that geography WHAT: This is very often a split by some unique aspect of the customer such as customer ID, name, geography, and so on. WHEN TO USE: Very large, similar data sets such as large and rapidly growing customer bases or when the response time for a geographically distributed customer base is important. HOW TO USE: Identify something you know about the customer, such as customer ID, last name, geography, or device, and split or partition both data and services based on that attribute. WHY: Rapid customer growth exceeds other forms of data growth, or you have the need to perform fault isolation between certain customer groups as you scale. KEY TAKEAWAYS: Shards are effective at helping you to scale customer bases but can also be applied to other very large data sets that can\u2019t be pulled apart using the microservices methodology.","title":"Scalability - Sharding"},{"location":"systems_design/scalability/#refer_4","text":"https://learning.oreilly.com/library/view/the-art-of/9780134031408/ch23.html","title":"Refer"},{"location":"systems_design/scalability/#sre-use-cases","text":"SREs in coordination with the network team work on how to map users traffic to a particular site. https://engineering.linkedin.com/blog/2017/05/trafficshift--load-testing-at-scale SREs work closely with the Dev team to split monoliths to multiple microservices that are easy to run and manage SREs work on improving Load Balancers' reliability, service discovery and performance SREs work closely to split Data into shards and manage data integrity and consistency. https://engineering.linkedin.com/espresso/introducing-espresso-linkedins-hot-new-distributed-document-store SREs work to set up, configure and improve CDN cache hit rate.","title":"SRE Use cases"}]}
\ No newline at end of file
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deleted file mode 100644
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+++ /dev/null
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- $.getScript(base_path + script).done(function () {
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- }).fail(function (jqxhr, settings, exception) {
- console.log('Error: ' + exception);
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- if (scripts.length === 0) {
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- getScript(scripts[0], function() {
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- if (lang.length > 1) {
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diff --git a/site/security/fundamentals/index.html b/site/security/fundamentals/index.html
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- Fundamentals of Security - school_of_sre
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If you look closely, both Site Reliability Engineering and Security Engineering are concerned with keeping a system usable.
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Issues like broken releases, capacity shortages, and misconfigurations can make a system unusable (at least temporarily).
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Security or privacy incidents that break the trust of users also undermine the usefulness of a system.
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Consequently, system security should be top of mind for SREs.
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SREs should be involved in both significant design discussions and actual system changes.
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They have quite a big role in System design & hence are quite sometimes the first line of defense.
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SRE’s help in preventing bad design & implementations which can affect the overall security of the infrastructure.
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Successfully designing, implementing, and maintaining systems requires a commitment to the full system lifecycle. This commitment is possible only when security and reliability are central elements in the architecture of systems.
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Core Pillars of Information Security :
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Confidentiality – only allow access to data for which the user is permitted
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Integrity – ensure data is not tampered or altered by unauthorized users
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Availability – ensure systems and data are available to authorized users when they need it
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Thinking like a Security Engineer
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When starting a new application or re-factoring an existing application, you should consider each functional feature, and consider:
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Is the process surrounding this feature as safe as possible? In other words, is this a flawed process?
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If I were evil, how would I abuse this feature? Or more specifically failing to address how a feature can be abused can cause design flaws.
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Is the feature required to be on by default? If so, are there limits or options that could help reduce the risk from this feature?
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Security Principles By OWASP (Open Web Application Security Project)
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Minimize attack surface area :
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Every feature that is added to an application adds a certain amount of risk to the overall application. The aim for secure development is to reduce the overall risk by reducing the attack surface area.
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For example, a web application implements online help with a search function. The search function may be vulnerable to SQL injection attacks. If the help feature was limited to authorized users, the attack likelihood is reduced. If the help feature’s search function was gated through centralized data validation routines, the ability to perform SQL injection is dramatically reduced. However, if the help feature was re-written to eliminate the search function (through better user interface, for example), this almost eliminates the attack surface area, even if the help feature was available to the Internet at large.
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Establish secure defaults:
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There are many ways to deliver an “out of the box” experience for users. However, by default, the experience should be secure, and it should be up to the user to reduce their security – if they are allowed.
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For example, by default, password aging and complexity should be enabled. Users might be allowed to turn these two features off to simplify their use of the application and increase their risk.
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Default Passwords of routers, IOT devices should be changed
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Principle of Least privilege
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The principle of least privilege recommends that accounts have the least amount of privilege required to perform their business processes. This encompasses user rights, resource permissions such as CPU limits, memory, network, and file system permissions.
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For example, if a middleware server only requires access to the network, read access to a database table, and the ability to write to a log, this describes all the permissions that should be granted. Under no circumstances should the middleware be granted administrative privileges.
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Principle of Defense in depth
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The principle of defense in depth suggests that where one control would be reasonable, more controls that approach risks in different fashions are better. Controls, when used in-depth, can make severe vulnerabilities extraordinarily difficult to exploit and thus unlikely to occur.
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With secure coding, this may take the form of tier-based validation, centralized auditing controls, and requiring users to be logged on all pages.
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For example, a flawed administrative interface is unlikely to be vulnerable to an anonymous attack if it correctly gates access to production management networks, checks for administrative user authorization, and logs all access.
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Fail securely
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Applications regularly fail to process transactions for many reasons. How they fail can determine if an application is secure or not.
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-- If either codeWhichMayFail() or isUserInRole fails or throws an exception, the user is an admin by default. This is obviously a security risk.
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Don’t trust services
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Many organizations utilize the processing capabilities of third-party partners, who more than likely have different security policies and posture than you. It is unlikely that you can influence or control any external third party, whether they are home users or major suppliers or partners.
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Therefore, the implicit trust of externally run systems is not warranted. All external systems should be treated in a similar fashion.
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For example, a loyalty program provider provides data that is used by Internet Banking, providing the number of reward points and a small list of potential redemption items. However, the data should be checked to ensure that it is safe to display to end-users, and that the reward points are a positive number, and not improbably large.
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Separation of duties
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The key to fraud control is the separation of duties. For example, someone who requests a computer cannot also sign for it, nor should they directly receive the computer. This prevents the user from requesting many computers and claiming they never arrived.
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Certain roles have different levels of trust than normal users. In particular, administrators are different from normal users. In general, administrators should not be users of the application.
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For example, an administrator should be able to turn the system on or off, set password policy but shouldn’t be able to log on to the storefront as a super privileged user, such as being able to “buy” goods on behalf of other users.
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Avoid security by obscurity
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Security through obscurity is a weak security control, and nearly always fails when it is the only control. This is not to say that keeping secrets is a bad idea, it simply means that the security of systems should not be reliant upon keeping details hidden.
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For example, the security of an application should not rely upon knowledge of the source code being kept secret. The security should rely upon many other factors, including reasonable password policies, defense in depth, business transaction limits, solid network architecture, and fraud, and audit controls.
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A practical example is Linux. Linux’s source code is widely available, and yet when properly secured, Linux is a secure and robust operating system.
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Keep security simple
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Attack surface area and simplicity go hand in hand. Certain software engineering practices prefer overly complex approaches to what would otherwise be a relatively straightforward and simple design.
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Developers should avoid the use of double negatives and complex architectures when a simpler approach would be faster and simpler.
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For example, although it might be fashionable to have a slew of singleton entity beans running on a separate middleware server, it is more secure and faster to simply use global variables with an appropriate mutex mechanism to protect against race conditions.
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Fix security issues correctly
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Once a security issue has been identified, it is important to develop a test for it and to understand the root cause of the issue. When design patterns are used, it is likely that the security issue is widespread amongst all codebases, so developing the right fix without introducing regressions is essential.
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For example, a user has found that they can see another user’s balance by adjusting their cookie. The fix seems to be relatively straightforward, but as the cookie handling code is shared among all applications, a change to just one application will trickle through to all other applications. The fix must, therefore, be tested on all affected applications.
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Reliability & Security
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Reliability and security are both crucial components of a truly trustworthy system,but building systems that are both reliable and secure is difficult. While the requirements for reliability and security share many common properties, they also require different design considerations. It is easy to miss the subtle interplay between reliability and security that can cause unexpected outcomes
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Ex: A password management application failure was triggered by a reliability problem i.e poor load-balancing and load-shedding strategies and its recovery was later complicated by multiple measures (HSM mechanism which needs to be plugged into server racks , which works as an authentication & the HSM token supposedly locked inside a case.. & the problem can be further elongated ) designed to increase the security of the system.
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Authentication vs Authorization
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Authentication is the act of validating that users are who they claim to be. Passwords are the most common authentication factor—if a user enters the correct password, the system assumes the identity is valid and grants access.
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Other technologies such as One-Time Pins, authentication apps, and even biometrics can also be used to authenticate identity. In some instances, systems require the successful verification of more than one factor before granting access. This multi-factor authentication (MFA) requirement is often deployed to increase security beyond what passwords alone can provide.
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Authorization in system security is the process of giving the user permission to access a specific resource or function. This term is often used interchangeably with access control or client privilege. Giving someone permission to download a particular file on a server or providing individual users with administrative access to an application are good examples. In secure environments, authorization must always follow authentication, users should first prove that their identities are genuine before an organization’s administrators grant them access to the requested resources.
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Common authentication flow (local authentication)
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The user registers using an identifier like username/email/mobile
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The application stores user credentials in the database
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The application sends a verification email/message to validate the registration
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Post successful registration, the user enters credentials for logging in
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On successful authentication, the user is allowed access to specific resources
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OpenID/OAuth
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OpenID is an authentication protocol that allows us to authenticate users without using a local auth system. In such a scenario, a user has to be registered with an OpenID Provider and the same provider should be integrated with the authentication flow of your application. To verify the details, we have to forward the authentication requests to the provider. On successful authentication, we receive a success message and/or profile details with which we can execute the necessary flow.
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OAuth is an authorization mechanism that allows your application user access to a provider(Gmail/Facebook/Instagram/etc). On successful response, we (your application) receive a token with which the application can access certain APIs on behalf of a user. OAuth is convenient in case your business use case requires some certain user-facing APIs like access to Google Drive or sending tweets on your behalf. Most OAuth 2.0 providers can be used for pseudo authentication. Having said that, it can get pretty complicated if you are using multiple OAuth providers to authenticate users on top of the local authentication system.
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Cryptography
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It is the science and study of hiding any text in such a way that only the intended recipients or authorized persons can read it and that any text can even use things such as invisible ink or the mechanical cryptography machines of the past.
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Cryptography is necessary for securing critical or proprietary information and is used to encode private data messages by converting some plain text into ciphertext. At its core, there are two ways of doing this, more advanced methods are all built upon.
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Ciphers
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Ciphers are the cornerstone of cryptography. A cipher is a set of algorithms that performs encryption or decryption on a message. An encryption algorithm (E) takes a secret key (k) and a message (m), and produces a ciphertext (c). Similarly, a Decryption algorithm (D) takes a secret key (K) and the previous resulting Ciphertext (C). They are represented as follows:
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This also means that in order for it to be a cipher, it must satisfy the consistency equation as follows, making it possible to decrypt.
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Stream Ciphers:
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The message is broken into characters or bits and enciphered with a key or keystream(should be random and generated independently of the message stream) that is as long as the plaintext bitstream.
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sIf the keystream is random, this scheme would be unbreakable unless the keystream was acquired, making it unconditionally secure. The keystream must be provided to both parties in a secure way to prevent its release.
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Block Ciphers:
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Block ciphers — process messages in blocks, each of which is then encrypted or decrypted.
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A block cipher is a symmetric cipher in which blocks of plaintext are treated as a whole and used to produce ciphertext blocks. The block cipher takes blocks that are b bits long and encrypts them to blocks that are also b bits long. Block sizes are typically 64 or 128 bits long.
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Encryption
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Secret Key (Symmetric Key): the same key is used for encryption and decryption
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Public Key (Asymmetric Key) in an asymmetric, the encryption and decryption keys are different but related. The encryption key is known as the public key and the decryption key is known as the private key. The public and private keys are known as a key pair.
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Symmetric Key Encryption
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DES
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The Data Encryption Standard (DES) has been the worldwide encryption standard for a long time. IBM developed DES in 1975, and it has held up remarkably well against years of cryptanalysis. DES is a symmetric encryption algorithm with a fixed key length of 56 bits. The algorithm is still good, but because of the short key length, it is susceptible to brute-force attacks that have sufficient resources.
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DES usually operates in block mode, whereby it encrypts data in 64-bit blocks. The same algorithm and key are used for both encryption and decryption.
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Because DES is based on simple mathematical functions, it can be easily implemented and accelerated in hardware.
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Triple DES
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With advances in computer processing power, the original 56-bit DES key became too short to withstand an attacker with even a limited budget. One way of increasing the effective key length of DES without changing the well-analyzed algorithm itself is to use the same algorithm with different keys several times in a row.
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The technique of applying DES three times in a row to a plain text block is called Triple DES (3DES). The 3DES technique is shown in Figure. Brute-force attacks on 3DES are considered unfeasible today. Because the basic algorithm has been tested in the field for more than 25 years, it is considered to be more trustworthy than its predecessor.
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AES
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On October 2, 2000, The U.S. National Institute of Standards and Technology (NIST) announced the selection of the Rijndael cipher as the AES algorithm. This cipher, developed by Joan Daemen and Vincent Rijmen, has a variable block length and key length. The algorithm currently specifies how to use keys with a length of 128, 192, or 256 bits to encrypt blocks with a length of 128, 192, or 256 bits (all nine combinations of key length and block length are possible). Both block and key lengths can be extended easily to multiples of 32 bits.
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AES was chosen to replace DES and 3DES because they are either too weak (DES, in terms of key length) or too slow (3DES) to run on modern, efficient hardware. AES is more efficient and much faster, usually by a factor of 5 compared to DES on the same hardware. AES is also more suitable for high throughput, especially if pure software encryption is used. However, AES is a relatively young algorithm, and as the golden rule of cryptography states, “A more mature algorithm is always more trusted.”
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Asymmetric Key Algorithm
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In a symmetric key system, Alice first puts the secret message in a box and then padlocks the box using a lock to which she has a key. She then sends the box to Bob through regular mail. When Bob receives the box, he uses an identical copy of Alice's key (which he has obtained previously) to open the box and read the message.
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In an asymmetric key system, instead of opening the box when he receives it, Bob simply adds his own personal lock to the box and returns the box through public mail to Alice. Alice uses her key to remove her lock and returns the box to Bob, with Bob's lock still in place. Finally, Bob uses his key to remove his lock and reads the message from Alice.
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The critical advantage in an asymmetric system is that Alice never needs to send a copy of her key to Bob. This reduces the possibility that a third party (for example, an unscrupulous postmaster) can copy the key while it is in transit to Bob, allowing that third party to spy on all future messages sent by Alice. In addition, if Bob is careless and allows someone else to copy his key, Alice's messages to Bob are compromised, but Alice's messages to other people remain secret
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NOTE: In terms of TLS key exchange, this is the common approach.
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Diffie-Hellman
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The protocol has two system parameters, p and g. They are both public and may be used by everybody. Parameter p is a prime number, and parameter g (usually called a generator) is an integer that is smaller than p, but with the following property: For every number n between 1 and p – 1 inclusive, there is a power k of g such that n = gk mod p.
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Diffie Hellman algorithm is an asymmetric algorithm used to establish a shared secret for a symmetric key algorithm. Nowadays most of the people use hybrid cryptosystem i.e, combination of symmetric and asymmetric encryption. Asymmetric Encryption is used as a technique in key exchange mechanism to share secret key and after the key is shared between sender and receiver, the communication will take place using symmetric encryption. The shared secret key will be used to encrypt the communication.
The RSA algorithm is very flexible and has a variable key length where, if necessary, speed can be traded for the level of security of the algorithm. The RSA keys are usually 512 to 2048 bits long. RSA has withstood years of extensive cryptanalysis. Although those years neither proved nor disproved RSA's security, they attest to a confidence level in the algorithm. RSA security is based on the difficulty of factoring very large numbers. If an easy method of factoring these large numbers were discovered, the effectiveness of RSA would be destroyed.
NOTE : RSA Keys can be used for key exchange just like Deffie Hellman
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Hashing Algorithms
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Hashing is one of the mechanisms used for data integrity assurance. Hashing is based on a one-way mathematical function, which is relatively easy to compute but significantly harder to reverse.
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A hash function, which is a one-way function to input data to produce a fixed-length digest (fingerprint) of output data. The digest is cryptographically strong; that is, it is impossible to recover input data from its digest. If the input data changes just a little, the digest (fingerprint) changes substantially in what is called an avalanche effect.
MD5 is a one-way function with which it is easy to compute the hash from the given input data, but it is unfeasible to compute input data given only a hash.
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SHA-1
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MD5 is considered less secure than SHA-1 because MD5 has some weaknesses.
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HA-1 also uses a stronger, 160-bit digest, which makes MD5 the second choice as hash methods are concerned.
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The algorithm takes a message of less than 264 bits in length and produces a 160-bit message digest. This algorithm is slightly slower than MD5.
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NOTE: SHA-1 is also recently demonstrated to be broken, Minimum current recommendation is SHA-256
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Digital Certificates
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Digital signatures, provide a means to digitally authenticate devices and individual users. In public-key cryptography, such as the RSA encryption system, each user has a key-pair containing both a public key and a private key. The keys act as complements, and anything encrypted with one of the keys can be decrypted with the other. In simple terms, a signature is formed when data is encrypted with a user's private key. The receiver verifies the signature by decrypting the message with the sender's public key.
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Key management is often considered the most difficult task in designing and implementing cryptographic systems. Businesses can simplify some of the deployment and management issues that are encountered with secured data communications by employing a Public Key Infrastructure (PKI). Because corporations often move security-sensitive communications across the Internet, an effective mechanism must be implemented to protect sensitive information from the threats presented on the Internet.
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PKI provides a hierarchical framework for managing digital security attributes. Each PKI participant holds a digital certificate that has been issued by a CA (either public or private). The certificate contains a number of attributes that are used when parties negotiate a secure connection. These attributes must include the certificate validity period, end-host identity information, encryption keys that will be used for secure communications, and the signature of the issuing CA. Optional attributes may be included, depending on the requirements and capability of the PKI.
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A CA can be a trusted third party, such as VeriSign or Entrust, or a private (in-house) CA that you establish within your organization.
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The fact that the message could be decrypted using the sender's public key means that the holder of the private key created the message. This process relies on the receiver having a copy of the sender's public key and knowing with a high degree of certainty that it really does belong to the sender and not to someone pretending to be the sender.
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To validate the CA's signature, the receiver must know the CA's public key. Normally, this is handled out-of-band or through an operation performed during installation of the certificate. For instance, most web browsers are configured with the root certificates of several CAs by default.
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CA Enrollment process
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The end host generates a private-public key pair.
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The end host generates a certificate request, which it forwards to the CA.
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Manual human intervention is required to approve the enrollment request, which is received by the CA.
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After the CA operator approves the request, the CA signs the certificate request with its private key and returns the completed certificate to the end host.
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The end host writes the certificate into a nonvolatile storage area (PC hard disk or NVRAM on Cisco routers).
SSH, the Secure Shell, is a popular, powerful, software-based approach to network security.
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Whenever data is sent by a computer to the network, SSH automatically encrypts (scrambles) it. Then, when the data reaches its intended recipient, SSH automatically decrypts (unscrambles) it.
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The result is transparent encryption: users can work normally, unaware that their communications are safely encrypted on the network. In addition, SSH can use modern, secure encryption algorithms based on how it's being configured and is effective enough to be found within mission-critical applications at major corporations.
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SSH has a client/server architecture
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An SSH server program, typically installed and run by a system administrator, accepts or rejects incoming connections to its host computer. Users then run SSH client programs, typically on other computers, to make requests of the SSH server, such as “Please log me in,” “Please send me a file,” or “Please execute this command.” All communications between clients and servers are securely encrypted and protected from modification.
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What SSH is not:
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Although SSH stands for Secure Shell, it is not a true shell in the sense of the Unix Bourne shell and C shell. It is not a command interpreter, nor does it provide wildcard expansion, command history, and so forth. Rather, SSH creates a channel for running a shell on a remote computer, with end-to-end encryption between the two systems.
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The major features and guarantees of the SSH protocol are:
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Privacy of your data, via strong encryption
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Integrity of communications, guaranteeing they haven’t been altered
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Authentication, i.e., proof of identity of senders and receivers
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Authorization, i.e., access control to accounts
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Forwarding or tunneling to encrypt other TCP/IP-based sessions
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Kerberos
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According to Greek mythology Kerberos (Cerberus) was the gigantic, three-headed dog that guards the gates of the underworld to prevent the dead from leaving.
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So when it comes to Computer Science, Kerberos is a network authentication protocol, and is currently the default authentication technology used by Microsoft Active Directory to authenticate users to services within a local area network.
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Kerberos uses symmetric key cryptography and requires trusted third-party authentication service to verify user identities. So they used the name of Kerberos for their computer network authentication protocol as the three heads of the Kerberos represent:
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a client : A user/ a service
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a server : Kerberos protected hosts reside
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The KDC includes following two servers:
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Authentication Server (AS) that performs the initial authentication and issues ticket-granting tickets (TGT) for users.
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Ticket-Granting Server (TGS) that issues service tickets that are based on the initial ticket-granting tickets (TGT).
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Certificate Chain
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The first part of the output of the OpenSSL command shows three certificates numbered 0, 1, and 2(not 2 anymore). Each certificate has a subject, s, and an issuer, i. The first certificate, number 0, is called the end-entity certificate. The subject line tells us it’s valid for any subdomain of google.com because its subject is set to *.google.com.
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$ openssl s_client -connect www.google.com:443 -CApath /etc/ssl/certs
-CONNECTED(00000005)
-depth=2 OU = GlobalSign Root CA - R2, O = GlobalSign, CN = GlobalSign
-verify return:1
-depth=1 C = US, O = Google Trust Services, CN = GTS CA 1O1
-verify return:1
-depth=0 C = US, ST = California, L = Mountain View, O = Google LLC, CN = www.google.com
-verify return:1
----
-Certificate chain
- 0 s:/C=US/ST=California/L=Mountain View/O=Google LLC/CN=www.google.com
- i:/C=US/O=Google Trust Services/CN=GTS CA 1O1
- 1 s:/C=US/O=Google Trust Services/CN=GTS CA 1O1
- i:/OU=GlobalSign Root CA - R2/O=GlobalSign/CN=GlobalSign
----
-Server certificate
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The issuer line indicates it’s issued by Google Internet Authority G2, which also happens to be the subject of the second certificate, number 1
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What the OpenSSL command line doesn’t show here is the trust store that contains the list of CA certificates trusted by the system OpenSSL runs on.
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The public certificate of GlobalSign Authority must be present in the system’s trust store to close the verification chain. This is called a chain of trust, and figure below summarizes its behavior at a high level.
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High-level view of the concept of chain of trust applied to verifying the authenticity of a website. The Root CA in the Firefox trust store provides the initial trust to verify the entire chain and trust the end-entity certificate.
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TLS Handshake
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The client sends a HELLO message to the server with a list of protocols and algorithms it supports.
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The server says HELLO back and sends its chain of certificates. Based on the capabilities of the client, the server picks a cipher suite.
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If the cipher suite supports ephemeral key exchange, like ECDHE does(ECDHE is an algorithm known as the Elliptic Curve Diffie-Hellman Exchange), the server and the client negotiate a pre master key with the Diffie-Hellman algorithm. The pre master key is never sent over the wire.
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The client and server create a session key that will be used to encrypt the data transiting through the connection.
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At the end of the handshake, both parties possess a secret session key used to encrypt data for the rest of the connection. This is what OpenSSL refers to as Master-Key
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NOTE
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There are 3 versions of TLS , TLS 1.0, 1.1 & 1.2
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TLS 1.0 was released in 1999, making it a nearly two-decade-old protocol. It has been known to be vulnerable to attacks—such as BEAST and POODLE—for years, in addition to supporting weak cryptography, which doesn’t keep modern-day connections sufficiently secure.
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TLS 1.1 is the forgotten “middle child.” It also has bad cryptography like its younger sibling. In most software it was leapfrogged by TLS 1.2 and it’s rare to see TLS 1.1 used.
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“Perfect” Forward Secrecy
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The term “ephemeral” in the key exchange provides an important security feature mis-named perfect forward secrecy (PFS) or just “Forward Secrecy”.
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In a non-ephemeral key exchange, the client sends the pre-master key to the server by encrypting it with the server’s public key. The server then decrypts the pre-master key with its private key. If, at a later point in time, the private key of the server is compromised, an attacker can go back to this handshake, decrypt the pre-master key, obtain the session key, and decrypt the entire traffic. Non-ephemeral key exchanges are vulnerable to attacks that may happen in the future on recorded traffic. And because people seldom change their password, decrypting data from the past may still be valuable for an attacker.
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An ephemeral key exchange like DHE, or its variant on elliptic curve, ECDHE, solves this problem by not transmitting the pre-master key over the wire. Instead, the pre-master key is computed by both the client and the server in isolation, using nonsensitive information exchanged publicly. Because the pre-master key can’t be decrypted later by an attacker, the session key is safe from future attacks: hence, the term perfect forward secrecy.
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Keys are changed every X blocks along the stream. That prevents an attacker from simply sniffing the stream and applying brute force to crack the whole thing. "Forward secrecy" means that just because I can decrypt block M, does not mean that I can decrypt block Q
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Downside:
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The downside to PFS is that all those extra computational steps induce latency on the handshake and slow the user down. To avoid repeating this expensive work at every connection, both sides cache the session key for future use via a technique called session resumption. This is what the session-ID and TLS ticket are for: they allow a client and server that share a session ID to skip over the negotiation of a session key, because they already agreed on one previously, and go directly to exchanging data securely.
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- Inro - school_of_sre
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Fundamental classroom courseware for people getting started with SRE & developing an understanding of the need for security in day to day operations
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Target Audience
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The material is suitable for new SRE hires or graduate computer science majors straight out of college, anyone who has a basic technical background, or readers who have a basic understanding of IT security and want to expand their knowledge.
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The approach being covered here deals with the fundamentals of computer security in the modern IT landscape moreover it sheds light on most of the dangerous "things" out there on public internet which are potentially a gateway to compromising systems. As an SRE, you are expected to design, build and develop products, this course will give you that ‘security knob’ into your thinking and problem-solving approach which is expected to be turned on as a critical area that always takes precedence over anything else.
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Pre Requirements
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Basics of Linux fundamentals & command line usage
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Networking Module
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What to expect from this training
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The course covers fundamentals of information security along with touching on subjects of system security, network & web security. The aim of this course is to get familiar with the basics of information security in day to day operations & then as an SRE develop the mindset of ensuring that security takes a front-seat while developing solutions. The course also serves as an introduction to common risks and best practices along with practical ways to find out vulnerable systems and loopholes which might become compromised if not secured.
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What is not covered under this training
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The courseware is not an ethical hacking workshop or a very deep dive into the fundamentals of the problems. The course does not deal with hacking or breaking into systems but rather an approach on how to ensure you don’t get into those situations and also to make you aware of different ways a system can be compromised.
TCP/IP is the dominant networking technology today. It is a five-layer architecture. These layers are, from top to bottom, the application layer, the transport layer (TCP), the network layer (IP), the data-link layer, and the physical layer. In addition to TCP/IP, there also are other networking technologies. For convenience, we use the OSI network model to represent non-TCP/IP network technologies. Different networks are interconnected using gateways. A gateway can be placed at any layer.
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The OSI model is a seven-layer architecture. The OSI architecture is similar to the TCP/IP architecture, except that the OSI model specifies two additional layers between the application layer and the transport layer in the TCP/IP architecture. These two layers are the presentation layer and the session layer. Figure 5.1 shows the relation between the TCP/IP layers and the OSI layers. The application layer in TCP/IP corresponds to the application layer and the presentation layer in OSI. The transport layer in TCP/IP corresponds to the session layer and the transport layer in OSI. The remaining three layers in the TCP/IP architecture are one-to-one correspondent to the remaining three layers in the OSI model.
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-Correspondence between layers of the TCP/IP architecture and the OSI model. Also shown are placements of cryptographic algorithms in network layers, where the dotted arrows indicate actual communications of cryptographic algorithms
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The functionalities of OSI layers are briefly described as follows:
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The application layer serves as an interface between applications and network programs. It supports application programs and end-user processing. Common application-layer programs include remote logins, file transfer, email, and Web browsing.
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The presentation layer is responsible for dealing with data that is formed differently. This protocol layer allows application-layer programs residing on different sides of a communication channel with different platforms to understand each other's data formats regardless of how they are presented.
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The session layer is responsible for creating, managing, and closing a communication connection.
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The transport layer is responsible for providing reliable connections, such as packet sequencing, traffic control, and congestion control.
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The network layer is responsible for routing device-independent data packets from the current hop to the next hop.
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The data-link layer is responsible for encapsulating device-independent data packets into device-dependent data frames. It has two sublayers: logical link control and media access control.
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The physical layer is responsible for transmitting device-dependent frames through some physical media.
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Starting from the application layer, data generated from an application program is passed down layer-by-layer to the physical layer. Data from the previous layer is enclosed in a new envelope at the current layer, where the data from the previous layer is also just an envelope containing the data from the layer before it. This is similar to enclosing a smaller envelope in a larger one. The envelope added at each layer contains sufficient information for handling the packet. Application-layer data are divided into blocks small enough to be encapsulated in an envelope at the next layer.
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Application data blocks are “dressed up” in the TCP/IP architecture according to the following basic steps. At the sending side, an application data block is encapsulated in a TCP packet when it is passed down to the TCP layer. In other words, a TCP packet consists of a header and a payload, where the header corresponds to the TCP envelope and the payload is the application data block. Likewise, the TCP packet will be encapsulated in an IP packet when it is passed down to the IP layer. An IP packet consists of a header and a payload, which is the TCP packet passed down from the TCP layer. The IP packet will be encapsulated in a device-dependent frame (e.g., an Ethernet frame) when it is passed down to the data-link layer. A frame has a header, and it may also have a trailer. For example, in addition to having a header, an Ethernet frame also has a 32-bit cyclic redundancy check (CRC) trailer. When it is passed down to the physical layer, a frame will be transformed to a sequence of media signals for transmission
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- Flow Diagram of a Packet Generation
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At the destination side, the medium signals are converted by the physical layer into a frame, which is passed up to the data-link layer. The data-link layer passes the frame payload (i.e., the IP packet encapsulated in the frame) up to the IP layer. The IP layer passes the IP payload, namely, the TCP packet encapsulated in the IP packet, up to the TCP layer. The TCP layer passes the TCP payload, namely, the application data block, up to the application layer. When a packet arrives at a router, it only goes up to the IP layer, where certain fields in the IP header are modified (e.g., the value of TTL is decreased by 1). This modified packet is then passed back down layer-by-layer to the physical layer for further transmission.
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Public Key Infrastructure
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To deploy cryptographic algorithms in network applications, we need a way to distribute secret keys using open networks. Public-key cryptography is the best way to distribute these secret keys. In order to use public-key cryptography, we need to build a public-key infrastructure (PKI) to support and manage public-key certificates and certificate authority (CA) networks. In particular, PKIs are set up to perform the following functions:
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Determine the legitimacy of users before issuing public-key certificates to them.
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Issue public-key certificates upon user requests.
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Extend public-key certificates valid time upon user requests.
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Revoke public-key certificates upon users' requests or when the corresponding private keys are compromised.
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Store and manage public-key certificates.
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Prevent digital signature signers from denying their signatures.
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Support CA networks to allow different CAs to authenticate public-key certificates issued by other CAs.
IPsec is a major security protocol at the network layer
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IPsec provides a potent platform for constructing virtual private networks (VPN). VPNs are private networks overlayed on public networks.
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The purpose of deploying cryptographic algorithms at the network layer is to encrypt or authenticate IP packets (either just the payloads or the whole packets).
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IPsec also specifies how to exchange keys. Thus, IPsec consists of authentication protocols, encryption protocols, and key exchange protocols. They are referred to, respectively, as authentication header (AH), encapsulating security payload (ESP), and Internet key exchange (IKE).
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PGP & S/MIME : Email Security
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There are a number of security protocols at the application layer. The most used of these protocols are email security protocols namely PGP and S/MIME.
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SMTP (“Simple Mail Transfer Protocol”) is used for sending and delivering from a client to a server via port 25: it’s the outgoing server. On the contrary, POP (“Post Office Protocol”) allows the user to pick up the message and download it into his own inbox: it’s the incoming server. The latest version of the Post Office Protocol is named POP3, and it’s been used since 1996; it uses port 110
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PGP
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PGP implements all major cryptographic algorithms, the ZIP compression algorithm, and the Base64 encoding algorithm.
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It can be used to authenticate a message, encrypt a message, or both. PGP follows the following general process: authentication, ZIP compression, encryption, and Base64 encoding.
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The Base64 encoding procedure makes the message ready for SMTP transmission
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GPG (GnuPG)
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GnuPG is another free encryption standard that companies may use that is based on OpenPGP.
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GnuPG serves as a replacement for Symantec’s PGP.
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The main difference is the supported algorithms. However, GnuPG plays nice with PGP by design. Because GnuPG is open, some businesses would prefer the technical support and the user interface that comes with Symantec’s PGP.
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It is important to note that there are some nuances between compatibility of GnuPG and PGP, such as the compatibility between certain algorithms, but in most applications such as email, there are workarounds. One such algorithm is the IDEA Module which isn’t included in GnuPG out of the box due to patent issues.
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S/MIME
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SMTP can only handle 7-bit ASCII text (You can use UTF-8 extensions to alleviate this limitations, ) messages. While POP can handle other content types besides 7-bit ASCII, POP may, under a common default setting, download all the messages stored in the mail server to the user's local computer. After that, if POP removes these messages from the mail server. This makes it difficult for the user to read his messages from multiple computers.
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The Multipurpose Internet Mail Extension protocol (MIME) was designed to support sending and receiving email messages in various formats, including nontext files generated by word processors, graphics files, sound files, and video clips. Moreover, MIME allows a single message to include mixed types of data in any combination of these formats.
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The Internet Mail Access Protocol (IMAP), operated on TCP port 143(only for non-encrypted), stores (Configurable on both server & client just like PoP) incoming email messages in the mail server until the user deletes them deliberately. This allows the user to access his mailbox from multiple machines and download messages to a local machine without deleting it from the mailbox in the mail server.
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SSL/TLS
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SSL uses a PKI to decide if a server’s public key is trustworthy by requiring servers to use a security certificate signed by a trusted CA.
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When Netscape Navigator 1.0 was released, it trusted a single CA operated by the RSA Data Security corporation.
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The server’s public RSA keys were used to be stored in the security certificate, which can then be used by the browser to establish a secure communication channel. The security certificates we use today still rely on the same standard (named X.509) that Netscape Navigator 1.0 used back then.
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Netscape’s intent was to train users(though this didn’t work out later) to differentiate secure communications from insecure ones, so they put a lock icon next to the address bar. When the lock is open, the communication is insecure. A closed lock means communication has been secured with SSL, which required the server to provide a signed certificate. You’re obviously familiar with this icon as it’s been in every browser ever since. The engineers at Netscape truly created a standard for secure internet communications.
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A year after releasing SSL 2.0, Netscape fixed several security issues and released SSL 3.0, a protocol that, albeit being officially deprecated since June 2015, remains in use in certain parts of the world more than 20 years after its introduction. In an effort to standardize SSL, the Internet Engineering Task Force (IETF) created a slightly modified SSL 3.0 and, in 1999, unveiled it as Transport Layer Security (TLS) 1.0. The name change between SSL and TLS continues to confuse people today. Officially, TLS is the new SSL, but in practice, people use SSL and TLS interchangeably to talk about any version of the protocol.
Let us see how we keep a check on the perimeter i.e the edges, the first layer of protection
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General Firewall Framework
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Firewalls are needed because encryption algorithms cannot effectively stop malicious packets from getting into an edge network.
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This is because IP packets, regardless of whether they are encrypted, can always be forwarded into an edge network.
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Firewalls that were developed in the 1990s are important instruments to help restrict network access. A firewall may be a hardware device, a software package, or a combination of both.
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Packets flowing into the internal network from the outside should be evaluated before they are allowed to enter. One of the critical elements of a firewall is its ability to examine packets without imposing a negative impact on communication speed while providing security protections for the internal network.
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The packet inspection that is carried out by firewalls can be done using several different methods. On the basis of the particular method used by the firewall, it can be characterized as either a packet filter, circuit gateway, application gateway, or dynamic packet filter.
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Packet Filters
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It inspects ingress packets coming to an internal network from outside and inspects egress packets going outside from an internal network
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Packing filtering only inspects IP headers and TCP headers, not the payloads generated at the application layer
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A packet filtering firewall uses a set of rules to determine whether a packet should be allowed or denied to pass through.
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2 types:
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Stateless
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It treats each packet as an independent object, and it does not keep track of any previously processed packets. In other words, stateless filtering inspects a packet when it arrives and makes a decision without leaving any record of the packet being inspected.
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Stateful
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Stateful filtering, also referred to as connection-state filtering, keeps track of connections between an internal host and an external host. A connection state (or state, for short) indicates whether it is a TCP connection or a UDP connection and whether the connection is established.
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Circuit Gateways
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Circuit gateways, also referred to as circuit-level gateways, are typically operated at the transportation layer
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They evaluate the information of the IP addresses and the port numbers contained in TCP (or UDP) headers and use it to determine whether to allow or to disallow an internal host and an external host to establish a connection.
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It is common practice to combine packet filters and circuit gateways to form a dynamic packet filter (DPF).
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Application Gateways(ALG)
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Aka PROXY Servers
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An Application Level Gateway (ALG) acts like a proxy for internal hosts, processing service requests from external clients.
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An ALG performs deep inspections on each IP packet (ingress or egress).
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In particular, an ALG inspects application program formats contained in the packet (e.g., MIME format or SQL format) and examines whether its payload is permitted.
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Thus, an ALG may be able to detect a computer virus contained in the payload. Because an ALG inspects packet payloads, it may be able to detect malicious code and quarantine suspicious packets, in addition to blocking packets with suspicious IP addresses and TCP ports. On the other hand, an ALG also incurs substantial computation and space overheads.
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Trusted Systems & Bastion Hosts
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A Trusted Operating System (TOS) is an operating system that meets a particular set of security requirements. Whether an operating system can be trusted or not depends on a number of elements. For example, for an operating system on a particular computer to be certified trusted, one needs to validate that, among other things, the following four requirements are satisfied:
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Its system design contains no defects;
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Its system software contains no loopholes;
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Its system is configured properly; and
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Its system management is appropriate.
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Bastion Hosts
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Bastion hosts are computers with strong defense mechanisms. They often serve as host computers for implementing application gateways, circuit gateways, and other types of firewalls. A bastion host is operated on a trusted operating system that must not contain unnecessary functionalities or programs. This measure helps to reduce error probabilities and makes it easier to conduct security checks. Only those network application programs that are absolutely necessary, for example, SSH, DNS, SMTP, and authentication programs, are installed on a bastion host.
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Bastion hosts are also primarily used as controlled ingress points so that the security monitoring can focus more narrowly on actions happening at a single point closely.
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Common Techniques & Scannings, Packet Capturing
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Scanning Ports with Nmap
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Nmap ("Network Mapper") is a free and open source (license) utility for network discovery and security auditing. Many systems and network administrators also find it useful for tasks such as network inventory, managing service upgrade schedules, and monitoring host or service uptime.
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The best thing about Nmap is it’s free and open source and is very flexible and versatile
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Nmap is often used to determine alive hosts in a network, open ports on those hosts, services running on those open ports, and version identification of that service on that port.
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More at http://scanme.nmap.org/
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Nmap uses 6 different port states:
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Open — An open port is one that is actively accepting TCP, UDP or SCTP connections. Open ports are what interests us the most because they are the ones that are vulnerable to attacks. Open ports also show the available services on a network.
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Closed — A port that receives and responds to Nmap probe packets but there is no application listening on that port. Useful for identifying that the host exists and for OS detection.
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Filtered — Nmap can’t determine whether the port is open because packet filtering prevents its probes from reaching the port. Filtering could come from firewalls or router rules. Often little information is given from filtered ports during scans as the filters can drop the probes without responding or respond with useless error messages e.g. destination unreachable.
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Unfiltered — Port is accessible but Nmap doesn’t know if its open or closed. Only used in ACK scan which is used to map firewall rulesets. Other scan types can be used to identify whether the port is open.
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Open/filtered — Nmap is unable to determine between open and filtered. This happens when an open port gives no response. No response could mean that the probe was dropped by a packet filter or any response is blocked.
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Closed/filtered — Nmap is unable to determine whether a port is closed or filtered. Only used in the IP ID idle scan.
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Types of Nmap Scan:
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TCP Connect
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TCP Connect scan completes the 3-way handshake.
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If a port is open, the operating system completes the TCP three-way handshake and the port scanner immediately closes the connection to avoid DOS. This is “noisy” because the services can log the sender IP address and might trigger Intrusion Detection Systems.
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UDP Scan
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This scan checks to see if there are any UDP ports listening.
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Since UDP does not respond with a positive acknowledgment like TCP and only responds to an incoming UDP packet when the port is closed,
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SYN Scan
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SYN scan is another form of TCP scanning.
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This scan type is also known as “half-open scanning” because it never actually opens a full TCP connection.
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The port scanner generates a SYN packet. If the target port is open, it will respond with an SYN-ACK packet. The scanner host responds with an RST packet, closing the connection before the handshake is completed.
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If the port is closed but unfiltered, the target will instantly respond with an RST packet.
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SYN scan has the advantage that the individual services never actually receive a connection.
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FIN Scan
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This is a stealthy scan, like the SYN scan, but sends a TCP FIN packet instead.
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ACK Scan
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Ack scanning determines whether the port is filtered or not.
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Null Scan
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Another very stealthy scan that sets all the TCP header flags to off or null.
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This is not normally a valid packet and some hosts will not know what to do with this.
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XMAS Scan
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Similar to the NULL scan except for all the flags in the TCP header is set to on
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RPC Scan
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This special type of scan looks for machine answering to RPC (Remote Procedure Call) services
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IDLE Scan
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It is a super stealthy method whereby the scan packets are bounced off an external host.
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You don’t need to have control over the other host but it does have to set up and meet certain requirements. You must input the IP address of our “zombie” host and what port number to use. It is one of the more controversial options in Nmap since it really only has a use for malicious attacks.
tcp.flags.syn==1 or (tcp.seq==1 and tcp.ack==1 and tcp.len==0 and tcp.analysis.initial_rtt)
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Find files by type
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frame contains “(attachment|tar|exe|zip|pdf)”
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Find traffic based on keyword
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tcp contains facebook
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frame contains facebook
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Detecting SYN Floods
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tcp.flags.syn == 1 and tcp.flags.ack == 0
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Wireshark Promiscuous Mode
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DumpCap
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Dumpcap is a network traffic dump tool. It captures packet data from a live network and writes the packets to a file. Dumpcap’s native capture file format is pcapng, which is also the format used by Wireshark.
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By default, Dumpcap uses the pcap library to capture traffic from the first available network interface and writes the received raw packet data, along with the packets’ time stamps into a pcapng file. The capture filter syntax follows the rules of the pcap library.
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The Wireshark command line utility called 'dumpcap.exe' can be used to capture LAN traffic over an extended period of time.
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Wireshark itself can also be used, but dumpcap does not significantly utilize the computer's memory while capturing for long periods of time.
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DaemonLogger
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Daemonlogger is a packet logging application designed specifically for use in Network and Systems Management (NSM) environments.
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The biggest benefit Daemonlogger provides is that, like Dumpcap, it is simple to use for capturing packets. In order to begin capturing, you need only to invoke the command and specify an interface.
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daemonlogger –i eth1
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This option, by default, will begin capturing packets and logging them to the current working directory.
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Packets will be collected until the capture file size reaches 2 GB, and then a new file will be created. This will continue indefinitely until the process is halted.
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NetSniff-NG
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Netsniff-NG is a high-performance packet capture utility
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While the utilities we’ve discussed to this point rely on Libpcap for capture, Netsniff-NG utilizes zero-copy mechanisms to capture packets. This is done with the intent to support full packet capture over high throughput links.
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In order to begin capturing packets with Netsniff-NG, we have to specify an input and output. In most cases, the input will be a network interface, and the output will be a file or folder on disk.
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netsniff-ng –i eth1 –o data.pcap
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Netflow
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NetFlow is a feature that was introduced on Cisco routers around 1996 that provides the ability to collect IP network traffic as it enters or exits an interface. By analyzing the data provided by NetFlow, a network administrator can determine things such as the source and destination of traffic, class of service, and the causes of congestion. A typical flow monitoring setup (using NetFlow) consists of three main components:[1]
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Flow exporter: aggregates packets into flows and exports flow records towards one or more flow collectors.
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Flow collector: responsible for reception, storage and pre-processing of flow data received from a flow exporter.
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Analysis application: analyzes received flow data in the context of intrusion detection or traffic profiling, for example.
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Routers and switches that support NetFlow can collect IP traffic statistics on all interfaces where NetFlow is enabled, and later export those statistics as NetFlow records toward at least one NetFlow collector—typically a server that does the actual traffic analysis.
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IDS
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A security solution that detects security-related events in your environment but does not block them.
-IDS sensors can be software and hardware based used to collect and analyze the network traffic. These sensors are available in two varieties, network IDS and host IDS.
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A host IDS is a server-specific agent running on a server with a minimum of overhead to monitor the operating system.
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A network IDS can be embedded in a networking device, a standalone appliance, or a module monitoring the network traffic.
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Signature Based IDS
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The signature-based IDS monitors the network traffic or observes the system and sends an alarm if a known malicious event is happening.
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It does so by comparing the data flow against a database of known attack patterns
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These signatures explicitly define what traffic or activity should be considered as malicious.
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Signature-based detection has been the bread and butter of network-based defensive security for over a decade, partially because it is very similar to how malicious activity is detected at the host level with antivirus utilities
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The formula is fairly simple: an analyst observes a malicious activity, derives indicators from the activity and develops them into signatures, and then those signatures will alert whenever the activity occurs again.
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ex: SNORT & SURICATA
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Policy Based IDS
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The policy-based IDSs (mainly host IDSs) trigger an alarm whenever a violation occurs against the configured policy.
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This configured policy is or should be a representation of the security policies.
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This type of IDS is flexible and can be customized to a company's network requirements because it knows exactly what is permitted and what is not.
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On the other hand, the signature-based systems rely on vendor specifics and default settings.
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Anomaly Based IDS
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The anomaly-based IDS looks for traffic that deviates from the normal, but the definition of what is a normal network traffic pattern is the tricky part
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Two types of anomaly-based IDS exist: statistical and nonstatistical anomaly detection
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Statistical anomaly detection learns the traffic patterns interactively over a period of time.
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In the nonstatistical approach, the IDS has a predefined configuration of the supposedly acceptable and valid traffic patterns.
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Host Based IDS & Network Based IDS
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A host IDS can be described as a distributed agent residing on each server of the network that needs protection. These distributed agents are tied very closely to the underlying operating system.
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Network IDSs, on the other hand, can be described as intelligent sniffing devices. Data (raw packets) is captured from the network by a network IDS, whereas host IDSs capture the data from the host on which they are installed.
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Honeypots
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The use of decoy machines to direct intruders' attention away from the machines under protection is a major technique to preclude intrusion attacks. Any device, system, directory, or file used as a decoy to lure attackers away from important assets and to collect intrusion or abusive behaviors is referred to as a honeypot.
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A honeypot may be implemented as a physical device or as an emulation system. The idea is to set up decoy machines in a LAN, or decoy directories/files in a file system and make them appear important, but with several exploitable loopholes, to lure attackers to attack these machines or directories/files, so that other machines, directories, and files can evade intruders' attentions. A decoy machine may be a host computer or a server computer. Likewise, we may also set up decoy routers or even decoy LANs.
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Chinks In The Armour (TCP/IP Security Issues)
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IP Spoofing
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In this type of attack, the attacker replaces the IP address of the sender, or in some rare cases the destination, with a different address.
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IP spoofing is normally used to exploit a target host. In other cases, it is used to start a denial-of-service (DoS) attack.
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In a DoS attack, an attacker modifies the IP packet to mislead the target host into accepting the original packet as a packet sourced at a trusted host. The attacker must know the IP address of the trusted host to modify the packet headers (source IP address) so that it appears that the packets are coming from that host.
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IP Spoofing Detection Techniques
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Direct TTL Probes
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In this technique we send a packet to a host of suspect spoofed IP that triggers reply and compare TTL with suspect packet; if the TTL in the reply is not the same as the packet being checked; it is a spoofed packet.
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This Technique is successful when the attacker is in a different subnet from the victim.
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IP Identification Number.
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Send a probe to the host of suspect spoofed traffic that triggers a reply and compare IP ID with suspect traffic.
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If IP IDs are not in the near value of packet being checked, suspect traffic is spoofed
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TCP Flow Control Method
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Attackers sending spoofed TCP packets will not receive the target’s SYN-ACK packets.
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Attackers cannot therefore be responsive to change in the congestion window size
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When the receiver still receives traffic even after a windows size is exhausted, most probably the packets are spoofed.
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Covert Channel
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A covert or clandestine channel can be best described as a pipe or communication channel between two entities that can be exploited by a process or application transferring information in a manner that violates the system's security specifications.
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More specifically for TCP/IP, in some instances, covert channels are established, and data can be secretly passed between two end systems.
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Ex: ICMP resides at the Internet layer of the TCP/IP protocol suite and is implemented in all TCP/IP hosts. Based on the specifications of the ICMP Protocol, an ICMP Echo Request message should have an 8-byte header and a 56-byte payload. The ICMP Echo Request packet should not carry any data in the payload. However, these packets are often used to carry secret information. The ICMP packets are altered slightly to carry secret data in the payload. This makes the size of the packet larger, but no control exists in the protocol stack to defeat this behavior. The alteration of ICMP packets gives intruders the opportunity to program specialized client-server pairs. These small pieces of code export confidential information without alerting the network administrator.
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ICMP can be leveraged for more than data exfiltration. For eg. some C&C tools such as Loki used ICMP channel to establish encrypted interactive session back in 1996.
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Deep packet inspection has since come a long way. A lot of IDS/IPS detect ICMP tunneling.
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Check for echo responses that do not contain the same payload as request
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Check for volume of ICMP traffic specially for volumes beyond an acceptable threshold
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IP Fragmentation Attack
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The TCP/IP protocol suite, or more specifically IP, allows the fragmentation of packets.(this is a feature & not a bug)
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IP fragmentation offset is used to keep track of the different parts of a datagram.
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The information or content in this field is used at the destination to reassemble the datagrams
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All such fragments have the same Identification field value, and the fragmentation offset indicates the position of the current fragment in the context of the original packet.
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Many access routers and firewalls do not perform packet reassembly. In normal operation, IP fragments do not overlap, but attackers can create artificially fragmented packets to mislead the routers or firewalls. Usually, these packets are small and almost impractical for end systems because of data and computational overhead.
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A good example of an IP fragmentation attack is the Ping of Death attack. The Ping of Death attack sends fragments that, when reassembled at the end station, create a larger packet than the maximum permissible length.
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TCP Flags
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Data exchange using TCP does not happen until a three-way handshake has been successfully completed. This handshake uses different flags to influence the way TCP segments are processed.
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There are 6 bits in the TCP header that are often called flags. Namely:
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6 different flags are part of the TCP header: Urgent pointer field (URG), Acknowledgment field (ACK), Push function (PSH), Reset the connection (RST), Synchronize sequence numbers (SYN), and sender is finished with this connection (FIN).
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Abuse of the normal operation or settings of these flags can be used by attackers to launch DoS attacks. This causes network servers or web servers to crash or hang.
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The attacker's ultimate goal is to write special programs or pieces of code that are able to construct these illegal combinations resulting in an efficient DoS attack.
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SYN FLOOD
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The timers (or lack of certain timers) in 3 way handshake are often used and exploited by attackers to disable services or even to enter systems.
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After step 2 of the three-way handshake, no limit is set on the time to wait after receiving a SYN. The attacker initiates many connection requests to the web server of Company XYZ (almost certainly with a spoofed IP address).
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The SYN+ACK packets (Step 2) sent by the web server back to the originating source IP address are not replied to. This leaves a TCP session half-open on the web server. Multiple packets cause multiple TCP sessions to stay open.
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Based on the hardware limitations of the server, a limited number of TCP sessions can stay open, and as a result, the web server refuses further connection establishments attempts from any host as soon as a certain limit is reached. These half-open connections need to be completed or timed out before new connections can be established.
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FIN Attack
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In normal operation, the sender sets the TCP FIN flag indicating that no more data will be transmitted and the connection can be closed down.
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This is a four-way handshake mechanism, with both sender and receiver expected to send an acknowledgement on a received FIN packet.
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During an attack that is trying to kill connections, a spoofed FIN packet is constructed. This packet also has the correct sequence number, so the packets are seen as valid by the targeted host. These sequence numbers are easy to predict. This process is referred to as TCP sequence number prediction, whereby the attacker either sniffs the current Sequence and Acknowledgment (SEQ/ACK) numbers of the connection or can algorithmically predict these numbers.
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Connection Hijacking
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An authorized user (Employee X) sends HTTP requests over a TCP session with the web server.
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The web server accepts the packets from Employee X only when the packet has the correct SEQ/ACK numbers. As seen previously, these numbers are important for the web server to distinguish between different sessions and to make sure it is still talking to Employee X. Imagine that the cracker starts sending packets to the web server spoofing the IP address of Employee X, using the correct SEQ/ACK combination. The web server accepts the packet and increments the ACK number.
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In the meantime, Employee X continues to send packets but with incorrect SEQ/ACK numbers. As a result of sending unsynchronized packets, all data from Employee X is discarded when received by the web server. The attacker pretends to be Employee X using the correct numbers. This finally results in the cracker hijacking the connection, whereby Employee X is completely confused and the web server replies assuming the cracker is sending correct synchronized data.
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STEPS:
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The attacker examines the traffic flows with a network monitor and notices traffic from Employee X to a web server.
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The web server returns or echoes data back to the origination station (Employee X).
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Employee X acknowledges the packet.
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The cracker launches a spoofed packet to the server.
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The web server responds to the cracker. The cracker starts verifying SEQ/ACK numbers to double-check success. At this time, the cracker takes over the session from Employee X, which results in a session hanging for Employee X.
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The cracker can start sending traffic to the web server.
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The web server returns the requested data to confirm delivery with the correct ACK number.
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The cracker can continue to send data (keeping track of the correct SEQ/ACK numbers) until eventually setting the FIN flag to terminate the session.
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Buffer Overflow
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A buffer is a temporary data storage area used to store program code and data.
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When a program or process tries to store more data in a buffer than it was originally anticipated to hold, a buffer overflow occurs.
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Buffers are temporary storage locations in memory (memory or buffer sizes are often measured in bytes) that are able to store a fixed amount of data in bytes. When more data is retrieved than can be stored in a buffer location, the additional information must go into an adjacent buffer, resulting in overwriting the valid data held in them.
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Mechanism:
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Buffer overflow vulnerabilities exist in different types. But the overall goal for all buffer overflow attacks is to take over the control of a privileged program and, if possible, the host. The attacker has two tasks to achieve this goal. First, the dirty code needs to be available in the program's code address space. Second, the privileged program should jump to that particular part of the code, which ensures that the proper parameters are loaded into memory.
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The first task can be achieved in two ways: by injecting the code in the right address space or by using the existing code and modifying certain parameters slightly. The second task is a little more complex because the program's control flow needs to be modified to make the program jump to the dirty code.
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CounterMeasure:
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The most important approach is to have a concerted focus on writing correct code.
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A second method is to make the data buffers (memory locations) address space of the program code non executable. This type of address space makes it impossible to execute code, which might be infiltrated in the program's buffers during an attack.
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More Spoofing
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Address Resolution Protocol Spoofing
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The Address Resolution Protocol (ARP) provides a mechanism to resolve, or map, a known IP address to a MAC sublayer address.
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Using ARP spoofing, the cracker can exploit this hardware address authentication mechanism by spoofing the hardware address of Host B. Basically, the attacker can convince any host or network device on the local network that the cracker's workstation is the host to be trusted. This is a common method used in a switched environment.
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ARP spoofing can be prevented with the implementation of static ARP tables in all the hosts and routers of your network. Alternatively, you can implement an ARP server that responds to ARP requests on behalf of the target host.
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DNS Spoofing
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DNS spoofing is the method whereby the hacker convinces the target machine that the system it wants to connect to is the machine of the cracker.
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The cracker modifies some records so that name entries of hosts correspond to the attacker's IP address. There have been instances in which the complete DNS server was compromised by an attack.
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To counter DNS spoofing, the reverse lookup detects these attacks. The reverse lookup is a mechanism to verify the IP address against a name. The IP address and name files are usually kept on different servers to make compromise much more difficult
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Search
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- From here you can search these documents. Enter
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Since DNS responses are cached, a quick response can be provided for repeated translations.
-DNS negative queries are also cached, e.g., misspelled words, and all cached data periodically times out.
-Cache poisoning is an issue in what is known as pharming. This term is used to describe a hacker’s attack in which a website’s traffic is redirected to a bogus website by forging the DNS mapping. In this case, an attacker attempts to insert a fake address record for an Internet domain into the DNS.
-If the server accepts the fake record, the cache is poisoned and subsequent requests for the address of the domain are answered with the address of a server controlled by the attacker. As long as the fake entry is cached by the server, browsers or e-mail servers will automatically go to the address provided by the compromised DNS server.
-the typical time to live (TTL) for cached entries is a couple of hours, thereby permitting ample time for numerous users to be affected by the attack.
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DNSSEC (Security Extension)
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The long-term solution to these DNS problems is authentication. If a resolver cannot distinguish between valid and invalid data in a response, then add source authentication to verify that the data received in a response is equal to the data entered by the zone administrator
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DNS Security Extensions (DNSSEC) protects against data spoofing and corruption, and provides mechanisms to authenticate servers and requests, as well as mechanisms to establish authenticity and integrity.
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When authenticating DNS responses, each DNS zone signs its data using a private key. It is recommended that this signing be done offline and in advance. The query for a particular record returns the requested resource record set (RRset) and signature (RRSIG) of the requested resource record set. The resolver then authenticates the response using a public key, which is pre-configured or learned via a sequence of key records in the DNS hierarchy.
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The goals of DNSSEC are to provide authentication and integrity for DNS responses without confidentiality or DDoS protection.
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BGP
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BGP stands for border gateway protocol. It is a routing protocol that exchanges routing information among multiple Autonomous Systems (AS)
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An Autonomous system is a collection of routers or networks with the same network policy usually under a single administrative control.
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BGP tells routers which hop to use in order to reach the destination network.
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BGP is used for both communicating information among routers in an AS (interior) and between multiple ASes (exterior).
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How BGP Works
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BGP is responsible for finding a path to a destination router & the path it chooses should be the shortest and most reliable one.
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This decision is done through a protocol known as Link state. With the link state protocol each router broadcasts to all other routers in the network the state of its links and IP subnets. Each router then receives information from the other routers and constructs a complete topology view of the entire network. The next hop routing table is based on this topology view.
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The link state protocol uses a famous algorithm in the field of computer science, Dijkstra’s shortest path algorithm:
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We start from our router considering the path cost to all our direct neighbors.
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The shortest path is then taken
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We then re-look at all our neighbors that we can reach and update our link state table with the cost information. We then continue taking the shortest path until every router has been visited.
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BGP Vulnerabilities
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By corrupting the BGP routing table we are able to influence the direction traffic flows on the internet! This action is known as BGP hijacking.
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Injecting bogus route advertising information into the BGP-distributed routing database by malicious sources, accidentally or routers can disrupt Internet backbone operations.
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Blackholing traffic:
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Blackhole route is a network route, i.e., routing table entry, that goes nowhere and packets matching the route prefix are dropped or ignored. Blackhole routes can only be detected by monitoring the lost traffic.
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Blackhole routes are best defence against many common viral attacks where the traffic is dropped from infected machines to/from command & control masters.
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Infamous BGP Injection attack on Youtube
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-- EX: In 2008, Pakistan decided to block YouTube by creating a BGP route that led into a black hole. Instead this routing information got transmitted to a hong kong ISP and from there accidentally got propagated to the rest of the world meaning millions were routed through to this black hole and therefore unable to access YouTube.
-- Potentially, the greatest risk to BGP occurs in a denial of service attack in which a router is flooded with more packets than it can handle. Network overload and router resource exhaustion happen when the network begins carrying an excessive number of BGP messages, overloading the router control processors, memory, routing table and reducing the bandwidth available for data traffic.
-- Refer : https://medium.com/bugbountywriteup/bgp-the-weak-link-in-the-internet-what-is-bgp-and-how-do-hackers-exploit-it-d899a68ba5bb
-- Router flapping is another type of attack. Route flapping refers to repetitive changes to the BGP routing table, often several times a minute. Withdrawing and re-advertising at a high-rate can cause a serious problem for routers, since they propagate the announcements of routes. If these route flaps happen fast enough, e.g., 30 to 50 times per second, the router becomes overloaded, which eventually prevents convergence on valid routes. The potential impact for Internet users is a slowdown in message delivery, and in some cases packets may not be delivered at all.
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BGP Security
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Border Gateway Protocol Security recommends the use of BGP peer authentication, since it is one of the strongest mechanisms for preventing malicious activity.
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The authentication mechanisms are Internet Protocol Security (IPsec) or BGP MD5.
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Another method, known as prefix limits, can be used to avoid filling router tables. In this approach, routers should be configured to disable or terminate a BGP peering session, and issue warning messages to administrators, when a neighbor sends in excess of a preset number of prefixes.
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IETF is currently working on improving this space
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Web Based Attacks
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HTTP Response Splitting Attacks
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HTTP response splitting attack may happen where the server script embeds user data in HTTP response headers without appropriate sanitation.
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This typically happens when the script embeds user data in the redirection URL of a redirection response (HTTP status code 3xx), or when the script embeds user data in a cookie value or name when the response sets a cookie.
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HTTP response splitting attacks can be used to perform web cache poisoning and cross-site scripting attacks.
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HTTP response splitting is the attacker’s ability to send a single HTTP request that forces the web server to form an output stream, which is then interpreted by the target as two HTTP responses instead of one response.
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Cross-Site Request Forgery (CSRF or XSRF)
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A Cross-Site Request Forgery attack tricks the victim’s browser into issuing a command to a vulnerable web application.
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Vulnerability is caused by browsers automatically including user authentication data, session ID, IP address, Windows domain credentials, etc with each request.
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Attackers typically use CSRF to initiate transactions such as transfer funds, login/logout user, close account, access sensitive data, and change account details.
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The vulnerability is caused by web browsers that automatically include credentials with each request, even for requests caused by a form, script, or image on another site. CSRF can also be dynamically constructed as part of a payload for a cross-site scripting attack
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All sites relying on automatic credentials are vulnerable. Popular browsers cannot prevent cross-site request forgery. Logging out of high-value sites as soon as possible can mitigate CSRF risk. It is recommended that a high-value website must require a client to manually provide authentication data in the same HTTP request used to perform any operation with security implications. Limiting the lifetime of session cookies can also reduce the chance of being used by other malicious sites.
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OWASP recommends website developers include a required security token in HTTP requests associated with sensitive business functions in order to mitigate CSRF attacks
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Cross-Site Scripting (XSS) Attacks
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Cross-Site Scripting occurs when dynamically generated web pages display user input, such as login information, that is not properly validated, allowing an attacker to embed malicious scripts into the generated page and then execute the script on the machine of any user that views the site.
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If successful, Cross-Site Scripting vulnerabilities can be exploited to manipulate or steal cookies, create requests that can be mistaken for those of a valid user, compromise confidential information, or execute malicious code on end user systems.
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Cross-Site Scripting (XSS or CSS) attacks involve the execution of malicious scripts on the victim’s browser. The victim is simply a user’s host and not the server. XSS results from a failure to validate user input by a web-based application.
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Document Object Model (DOM) XSS Attacks
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The Document Object Model (DOM) based XSS does not require the web server to receive the XSS payload for a successful attack. The attacker abuses the runtime by embedding their data on the client side. An attacker can force the client (browser) to render the page with parts of the DOM controlled by the attacker.
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When the page is rendered and the data is processed by the page, typically by a client side HTML-embedded script such as JavaScript, the page’s code may insecurely embed the data in the page itself, thus delivering the cross-site scripting payload. There are several DOM objects which can serve as an attack vehicle for delivering malicious script to victims browser.
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Clickjacking
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The technique works by hiding malicious link/scripts under the cover of the content of a legitimate site.
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Buttons on a website actually contain invisible links, placed there by the attacker. So, an individual who clicks on an object they can visually see, is actually being duped into visiting a malicious page or executing a malicious script.
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When mouseover is used together with clickjacking, the outcome is devastating. Facebook users have been hit by a clickjacking attack, which tricks people into “liking” a particular Facebook page, thus enabling the attack to spread since Memorial Day 2010.
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There is not yet effective defense against clickjacking, and disabling JavaScript is the only viable method
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DataBase Attacks & Defenses
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SQL injection Attacks
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It exploits improper input validation in database queries.
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A successful exploit will allow attackers to access, modify, or delete information in the database.
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It permits attackers to steal sensitive information stored within the backend databases of affected websites, which may include such things as user credentials, email addresses, personal information, and credit card numbers
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SQL Injection Attack Defenses
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SQL injection can be protected by filtering the query to eliminate malicious syntax, which involves the employment of some tools in order to (a) scan the source code.
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In addition, the input fields should be restricted to the absolute minimum, typically anywhere from 7-12 characters, and validate any data, e.g., if a user inputs an age make sure the input is an integer with a maximum of 3 digits.
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VPN
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A virtual private network (VPN) is a service that offers a secure, reliable connection over a shared public infrastructure such as the Internet. Cisco defines a VPN as an encrypted connection between private networks over a public network. To date, there are three types of VPNs:
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Remote access
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Site-to-site
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Firewall-based
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Security Breach
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In spite of the most aggressive steps to protect computers from attacks, attackers sometimes get through. Any event that results in a violation of any of the confidentiality, integrity, or availability (CIA) security tenets is a security breach.
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Denial of Service Attacks
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Denial of service (DoS) attacks result in downtime or inability of a user to access a system. DoS attacks impact the availability tenet of information systems security. A DoS attack is a coordinated attempt to deny service by occupying a computer to perform large amounts of unnecessary tasks. This excessive activity makes the system unavailable to perform legitimate operations
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Two common types of DoS attacks are as follows:
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Logic attacks—Logic attacks use software flaws to crash or seriously hinder the performance of remote servers. You can prevent many of these attacks by installing the latest patches to keep your software up to date.
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Flooding attacks—Flooding attacks overwhelm the victim computer’s CPU, memory, or network resources by sending large numbers of useless requests to the machine.
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Most DoS attacks target weaknesses in the overall system architecture rather than a software bug or security flaw
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One popular technique for launching a packet flood is a SYN flood.
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One of the best defenses against DoS attacks is to use intrusion prevention system (IPS) software or devices to detect and stop the attack.
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Distributed Denial of Service Attacks
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DDoS attacks differ from regular DoS attacks in their scope. In a DDoS attack, attackers hijack hundreds or even thousands of Internet computers, planting automated attack agents on those systems. The attacker then instructs the agents to bombard the target site with forged messages. This overloads the site and blocks legitimate traffic. The key here is strength in numbers. The attacker does more damage by distributing the attack across multiple computers.
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Wiretapping
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Although the term wiretapping is generally associated with voice telephone communications, attackers can also use wiretapping to intercept data communications.
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Attackers can tap telephone lines and data communication lines. Wiretapping can be active, where the attacker makes modifications to the line. It can also be passive, where an unauthorized user simply listens to the transmission without changing the contents. Passive intrusion can include the copying of data for a subsequent active attack.
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Two methods of active wiretapping are as follows:
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Between-the-lines wiretapping—This type of wiretapping does not alter the messages sent by the legitimate user but inserts additional messages into the communication line when the legitimate user pauses.
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Piggyback-entry wiretapping—This type of wiretapping intercepts and modifies the original message by breaking the communications line and routing the message to another computer that acts as a host.
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Backdoors
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Software developers sometimes include hidden access methods, called backdoors, in their programs. Backdoors give developers or support personnel easy access to a system without having to struggle with security controls. The problem is that backdoors don’t always stay hidden. When an attacker discovers a backdoor, he or she can use it to bypass existing security controls such as passwords, encryption, and so on. Where legitimate users log on through front doors using a user ID and password, attackers use backdoors to bypass these normal access controls.
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Malicious Attacks
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Birthday Attack
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Once an attacker compromises a hashed password file, a birthday attack is performed. A birthday attack is a type of cryptographic attack that is used to make brute-force attack of one-way hashes easier. It is a mathematical exploit that is based on the birthday problem in probability theory.
In a brute-force password attack, the attacker tries different passwords on a system until one of them is successful. Usually the attacker employs a software program to try all possible combinations of a likely password, user ID, or security code until it locates a match. This occurs rapidly and in sequence. This type of attack is called a brute-force password attack because the attacker simply hammers away at the code. There is no skill or stealth involved—just brute force that eventually breaks the code.
A dictionary password attack is a simple attack that relies on users making poor password choices. In a dictionary password attack, a simple password-cracker program takes all the words from a dictionary file and attempts to log on by entering each dictionary entry as a password.
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Further Reading:
-https://capec.mitre.org/data/definitions/16.html
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Replay Attacks
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Replay attacks involve capturing data packets from a network and retransmitting them to produce an unauthorized effect. The receipt of duplicate, authenticated IP packets may disrupt service or have some other undesired consequence. Systems can be broken through replay attacks when attackers reuse old messages or parts of old messages to deceive system users. This helps intruders to gain information that allows unauthorized access into a system.
A man-in-the-middle attack takes advantage of the multihop process used by many types of networks. In this type of attack, an attacker intercepts messages between two parties before transferring them on to their intended destination.
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Web spoofing is a type of man-in-the-middle attack in which the user believes a secure session exists with a particular web server. In reality, the secure connection exists only with the attacker, not the web server. The attacker then establishes a secure connection with the web server, acting as an invisible go-between. The attacker passes traffic between the user and the web server. In this way, the attacker can trick the user into supplying passwords, credit card information, and other private data.
In a masquerade attack, one user or computer pretends to be another user or computer. Masquerade attacks usually include one of the other forms of active attacks, such as IP address spoofing or replaying. Attackers can capture authentication sequences and then replay them later to log on again to an application or operating system. For example, an attacker might monitor usernames and passwords sent to a weak web application. The attacker could then use the intercepted credentials to log on to the web application and impersonate the user.
Eavesdropping, or sniffing, occurs when a host sets its network interface on promiscuous mode and copies packets that pass by for later analysis. Promiscuous mode enables a network device to intercept and read each network packet(ofcourse given some conditions) given sec, even if the packet’s address doesn’t match the network device. It is possible to attach hardware and software to monitor and analyze all packets on that segment of the transmission media without alerting any other users. Candidates for eavesdropping include satellite, wireless, mobile, and other transmission methods.
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Social Engineering
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Attackers often use a deception technique called social engineering to gain access to resources in an IT infrastructure. In nearly all cases, social engineering involves tricking authorized users into carrying out actions for unauthorized users. The success of social engineering attacks depends on the basic tendency of people to want to be helpful.
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Phreaking
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Phone phreaking, or simply phreaking, is a slang term that describes the activity of a subculture of people who study, experiment with, or explore telephone systems, telephone company equipment, and systems connected to public telephone networks. Phreaking is the art of exploiting bugs and glitches that exist in the telephone system.
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Phishing
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Phishing is a type of fraud in which an attacker attempts to trick the victim into providing private information such as credit card numbers, passwords, dates of birth, bank account numbers, automated teller machine (ATM) PINs, and Social Security numbers.
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Pharming
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Pharming is another type of attack that seeks to obtain personal or private financial information through domain spoofing. A pharming attack doesn’t use messages to trick victims into visiting spoofed websites that appear legitimate, however. Instead, pharming “poisons” a domain name on the domain name server (DNS), a process known as DNS poisoning. The result is that when a user enters the poisoned server’s web address into his or her address bar, that user navigates to the attacker’s site. The user’s browser still shows the correct website, which makes pharming difficult to detect—and therefore more serious. Where phishing attempts to scam people one at a time with an email or instant message, pharming enables scammers to target large groups of people at one time through domain spoofing.
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The first and most important step in reducing security and reliability issues is to educate developers. However, even the best-trained engineers make mistakes, security experts can write insecure code and SREs can miss reliability issues. It’s difficult to keep the many considerations and tradeoffs involved in building secure and reliable systems in mind simultaneously, especially if you’re also responsible for producing software.
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Use frameworks to enforce security and reliability while writing code
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A better approach is to handle security and reliability in common frameworks, languages, and libraries. Ideally, libraries only expose an interface that makes writing code with common classes of security vulnerabilities impossible.
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Multiple applications can use each library or framework. When domain experts fix an issue, they remove it from all the applications the framework supports, allowing this engineering approach to scale better.
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Common Security Vulnerabilities
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In large codebases, a handful of classes account for the majority of security vulnerabilities, despite ongoing efforts to educate developers and introduce code review. OWASP and SANS publish lists of common vulnerability classes
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Write Simple Code
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Try to keep your code clean and simple.
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Avoid Multi Level Nesting
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Multilevel nesting is a common anti-pattern that can lead to simple mistakes. If the error is in the most common code path, it will likely be captured by the unit tests. However, unit tests don’t always check error handling paths in multilevel nested code. The error might result in decreased reliability (for example, if the service crashes when it mishandles an error) or a security vulnerability (like a mishandled authorization check error).
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Eliminate YAGNI Smells
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Sometimes developers overengineer solutions by adding functionality that may be useful in the future, “just in case.” This goes against the YAGNI (You Aren’t Gonna Need It) principle, which recommends implementing only the code that you need. YAGNI code adds unnecessary complexity because it needs to be documented, tested, and maintained.
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To summarize, avoiding YAGNI code leads to improved reliability, and simpler code leads to fewer security bugs, fewer opportunities to make mistakes, and less developer time spent maintaining unused code.
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Repay Technical Debt
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It is a common practice for developers to mark places that require further attention with TODO or FIXME annotations. In the short term, this habit can accelerate the delivery velocity for the most critical functionality, and allow a team to meet early deadlines—but it also incurs technical debt. Still, it’s not necessarily a bad practice, as long as you have a clear process (and allocate time) for repaying such debt.
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Refactoring
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Refactoring is the most effective way to keep a codebase clean and simple. Even a healthy codebase occasionally needs to be
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Regardless of the reasons behind refactoring, you should always follow one golden rule: never mix refactoring and functional changes in a single commit to the code repository. Refactoring changes are typically significant and can be difficult to understand.
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If a commit also includes functional changes, there’s a higher risk that an author or reviewer might overlook bugs.
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Unit Testing
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Unit testing can increase system security and reliability by pinpointing a wide range of bugs in individual software components before a release. This technique involves breaking software components into smaller, self-contained “units” that have no external dependencies, and then testing each unit.
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Fuzz Testing
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Fuzz testing is a technique that complements the previously mentioned testing techniques. Fuzzing involves using a fuzz engine to generate a large number of candidate inputs that are then passed through a fuzz driver to the fuzz target. The fuzzer then analyzes how the system handles the input. Complex inputs handled by all kinds of software are popular targets for fuzzing - for example file parsers, compression algo, network protocol implementation and audio codec.
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Integration Testing
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Integration testing moves beyond individual units and abstractions, replacing fake or stubbed-out implementations of abstractions like databases or network services with real implementations. As a result, integration tests exercise more complete code paths. Because you must initialize and configure these other dependencies, integration testing may be slower and flakier than unit testing—to execute the test, this approach incorporates real-world variables like network latency as services communicate end-to-end. As you move from testing individual low-level units of code to testing how they interact when composed together, the net result is a higher degree of confidence that the system is behaving as expected.
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Last But not the least
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Code Reviews
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Rely on Automation
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Don’t check in Secrets
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Verifiable Builds
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Elimination of single points of failure (SPOF) This means adding redundancy to the system so that the failure of a component does not mean failure of the entire system.
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Reliable crossover In redundant systems, the crossover point itself tends to become a single point of failure. Reliable systems must provide for reliable crossover.
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Detection of failures as they occur If the two principles above are observed, then a user may never see a failure
WHAT: Never implement and always eliminate single points of failure.
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WHEN TO USE: During architecture reviews and new designs.
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HOW TO USE: Identify single instances on architectural diagrams. Strive for active/active configurations. At the very least we should have a standby to take control when active instances fail.
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WHY: Maximize availability through multiple instances.
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KEY TAKEAWAYS: Strive for active/active rather than active/passive solutions. Use load balancers to balance traffic across instances of a service. Use control services with active/passive instances for patterns that require singletons.
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HA - Reliable Crossover
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WHAT: Ensure when system components failover they do so reliably.
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WHEN TO USE: During architecture reviews, failure modeling, and designs.
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HOW TO USE: Identify how available a system is during the crossover and ensure it is within acceptable limits.
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WHY: Maximize availability and ensure data handling semantics are preserved.
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KEY TAKEAWAYS: Strive for active/active rather than active/passive solutions, they have a lesser risk of cross over being unreliable. Use LB and right load balancing methods to ensure reliable failover. Model and build your data systems to ensure data is correctly handled when crossover happens. Generally DB systems follow active/passive semantics for writes. Masters accept writes and when master goes down, follower is promoted to master(active from being passive) to accept writes. We have to be careful here that the cutover never introduces more than one masters. This problem is called a split brain.
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SRE Use cases
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SRE works on deciding an acceptable SLA and make sure system is available to achieve the SLA
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SRE is involved in architecture design right from building the data center to make sure site is not affected by network switch, hardware, power or software failures
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SRE also run mock drills of failures to see how the system behaves in uncharted territory and comes up with a plan to improve availability if there are misses.
-https://engineering.linkedin.com/blog/2017/11/resilience-engineering-at-linkedin-with-project-waterbear
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Post our understanding about HA, our architecture diagram looks something like this below
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Armed with these principles, we hope the course will give a fresh perspective to design software systems. It might be over engineering to get all this on day zero. But some are really important from day 0 like eliminating single points of failure, making scalable services by just increasing replicas. As a bottleneck is reached, we can split code by services, shard data to scale. As the organisation matures, bringing in chaos engineering to measure how systems react to failure will help in designing robust software systems.
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Failures are not avoidable in any system and will happen all the time, hence we need to build systems that can tolerate failures or recover from them.
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In systems, failure is the norm rather than the exception.
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"Anything that can go wrong will go wrong” -- Murphy’s Law
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“Complex systems contain changing mixtures of failures latent within them” -- How Complex Systems Fail.
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Fault Tolerance - Failure Metrics
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Common failure metrics that get measured and tracked for any system.
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Mean time to repair (MTTR): The average time to repair and restore a failed system.
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Mean time between failures (MTBF): The average operational time between one device failure or system breakdown and the next.
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Mean time to failure (MTTF): The average time a device or system is expected to function before it fails.
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Mean time to detect (MTTD): The average time between the onset of a problem and when the organization detects it.
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Mean time to investigate (MTTI): The average time between the detection of an incident and when the organization begins to investigate its cause and solution.
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Mean time to restore service (MTRS): The average elapsed time from the detection of an incident until the affected system or component is again available to users.
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Mean time between system incidents (MTBSI): The average elapsed time between the detection of two consecutive incidents. MTBSI can be calculated by adding MTBF and MTRS (MTBSI = MTBF + MTRS).
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Failure rate: Another reliability metric, which measures the frequency with which a component or system fails. It is expressed as a number of failures over a unit of time.
Systems should have a short circuit. Say in our content sharing system, if “Notifications” is not working, the site should gracefully handle that failure by removing the functionality instead of taking the whole site down.
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Swimlane is one of the commonly used fault isolation methodology. Swimlane adds a barrier to the service from other services so that failure on either of them won’t affect the other. Say we roll out a new feature ‘Advertisement’ in our content sharing app.
-We can have two architectures
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If Ads are generated on the fly synchronously during each Newsfeed request, the faults in Ads feature gets propagated to Newsfeed feature. Instead if we swimlane “Generation of Ads” service and use a shared storage to populate Newsfeed App, Ads failures won’t cascade to Newsfeed and worst case if Ads don’t meet SLA , we can have Newsfeed without Ads.
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Let's take another example, we come up with a new model for our Content sharing App. Here we roll out enterprise content sharing App where enterprises pay for the service and the content should never be shared outside the enterprise.
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Swimlane Principles
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Principle 1: Nothing is shared (also known as “share as little as possible”). The less that is shared within a swim lane, the more fault isolative the swim lane becomes. (as shown in Enterprise usecase)
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Principle 2: Nothing crosses a swim lane boundary. Synchronous (defined by expecting a request—not the transfer protocol) communication never crosses a swim lane boundary; if it does, the boundary is drawn incorrectly. (as shown in Ads feature)
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Swimlane Approaches
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Approach 1: Swim lane the money-maker. Never allow your cash register to be compromised by other systems. (Tier 1 vs Tier 2 in enterprise use case)
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Approach 2: Swim lane the biggest sources of incidents. Identify the recurring causes of pain and isolate them.(if Ads feature is in code yellow, swim laning it is the best option)
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Approach 3: Swim lane natural barriers. Customer boundaries make good swim lanes.(Public vs Enterprise customers)
Work with the DC tech or cloud team to distribute infrastructure such that its immune to switch or power failures by creating fault zones within a Data Center
-https://docs.microsoft.com/en-us/azure/virtual-machines/manage-availability#use-availability-zones-to-protect-from-datacenter-level-failures
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Work with the partners and design interaction between services such that one service breakdown is not amplified in a cascading fashion to all upstreams
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Fundamentals of common software system components:
-- Operating Systems
-- Networking
-- Databases RDBMS/NoSQL
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What to expect from this training
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Thinking about and designing for scalability, availability, and reliability of large scale software systems.
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What is not covered under this training
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Individual software components’ scalability and reliability concerns like e.g. Databases, while the same scalability principles and thinking can be applied, these individual components have their own specific nuances when scaling them and thinking about their reliability.
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More light will be shed on concepts rather than on setting up and configuring components like Loadbalancers to achieve scalability, availability and reliability of systems
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Training Content
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Introduction
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Scalability
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High Availability
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Fault Tolerance
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Introduction
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So, how do you go about learning to design a system?
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” Like most great questions, it showed a level of naivety that was breathtaking. The only short answer I could give was, essentially, that you learned how to design a system by designing systems and finding out what works and what doesn’t work.”
-Jim Waldo, Sun Microsystems, On System Design
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As software and hardware systems have multiple moving parts, we need to think about how those parts will grow, their failure modes, their inter-dependencies, how it will impact the users and the business.
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There is no one-shot method or way to learn or do system design, we only learn to design systems by designing and iterating on them.
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This course will be a starter to make one think about scalability, availability, and fault tolerance during systems design.
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Backstory
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Let’s design a simple content sharing application where users can share photos, media in our application which can be liked by their friends. Let’s start with a simple design of the application and evolve it as we learn system design concepts
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What does scalability mean for a system/service? A system is composed of services/components, each service/component scalability needs to be tackled separately, and the scalability of the system as a whole.
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A service is said to be scalable if, as resources are added to the system, it results in increased performance in a manner proportional to resources added
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An always-on service is said to be scalable if adding resources to facilitate redundancy does not result in a loss of performance
The Scale Cube is a model for segmenting services, defining microservices, and scaling products. It also creates a common language for teams to discuss scale related options in designing solutions. Following section talks about certain scaling patterns based on our inferences from AKF cube
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Scalability - Horizontal scaling
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Horizontal scaling stands for cloning of an application or service such that work can easily be distributed across instances with absolutely no bias.
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Lets see how our monolithic application improves with this principle
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Here DB is scaled separately from the application. This is to let you know each component’s scaling capabilities can be different. Usually web applications can be scaled by adding resources unless there is no state stored inside the application. But DBs can be scaled only for Reads by adding more followers but Writes have to go to only one master to make sure data is consistent. There are some DBs which support multi master writes but we are keeping them out of scope at this point.
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Apps should be able to differentiate between Read and Writes to choose appropriate DB servers. Load balancers can split traffic between identical servers transparently.
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WHAT: Duplication of services or databases to spread transaction load.
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WHEN TO USE: Databases with a very high read-to-write ratio (5:1 or greater—the higher the better). Because only read replicas of DBs can be scaled, not the Master.
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HOW TO USE: Simply clone services and implement a load balancer. For databases, ensure that the accessing code understands the difference between a read and a write.
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WHY: Allows for fast scale of transactions at the cost of duplicated data and functionality.
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KEY TAKEAWAYS: This is fast to implement, is low cost from a developer effort perspective, and can scale transaction volumes nicely. However, they tend to be high cost from the perspective of the operational cost of data. Cost here means if we have 3 followers and 1 Master DB, the same database will be stored as 4 copies in the 4 servers. Hence added storage cost
Improves the distribution of workloads across multiple computing resources, such as computers, a computer cluster, network links, central processing units, or disk drives. Commonly used technique is load balancing traffic across identical server clusters. Similar philosophy is used to load balance traffic across network links by ECMP, disk drives by RAID etc
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Aims to optimize resource use, maximize throughput, minimize response time, and avoid overload of any single resource.
-Using multiple components with load balancing instead of a single component may increase reliability and availability through redundancy. In our updated architecture diagram we have 4 servers to handle app traffic instead of a single server
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The device or system that performs load balancing is called a load balancer, abbreviated as LB.
What backends are available in the system? In our architecture, 4 servers are available to serve App traffic. LB acts as a single endpoint that clients can use transparently to reach one of the 4 servers.
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Health checking:
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What backends are currently healthy and available to accept requests? If one out of the 4 App servers turns bad, LB should automatically short circuit the path so that clients don’t sense any application downtime
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Load balancing:
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What algorithm should be used to balance individual requests across the healthy backends? There are many algorithms to distribute traffic across one of the four servers. Based on observations/experience, SRE can pick the algorithm that suits their pattern
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Scalability Pattern - LB Methods
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Common Load Balancing Methods
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Least Connection Method
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directs traffic to the server with the fewest active connections. Most useful when there are a large number of persistent connections in the traffic unevenly distributed between the servers. Works if clients maintain long lived connections
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Least Response Time Method
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directs traffic to the server with the fewest active connections and the lowest average response time. Here response time is used to provide feedback of server’s health
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Round Robin Method
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rotates servers by directing traffic to the first available server and then moves that server to the bottom of the queue. Most useful when servers are of equal specification and there are not many persistent connections.
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IP Hash
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the IP address of the client determines which server receives the request. This can sometimes cause skewness in distribution but is useful if apps store some state locally and need some stickiness
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More advanced client/server-side example techniques
-- https://docs.nginx.com/nginx/admin-guide/load-balancer/
-- http://cbonte.github.io/haproxy-dconv/2.2/intro.html#3.3.5
-- https://twitter.github.io/finagle/guide/Clients.html#load-balancing
CDNs are added closer to the client’s location. If the app has static data like images, Javascript, CSS which don’t change very often, they can be cached. Since our example is a content sharing site, static content can be cached in CDNs with a suitable expiry.
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WHAT: Use CDNs (content delivery networks) to offload traffic from your site.
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WHEN TO USE: When speed improvements and scale warrant the additional cost.
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HOW TO USE: Most CDNs leverage DNS to serve content on your site’s behalf. Thus you may need to make minor DNS changes or additions and move content to be served from new subdomains.
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Eg
-media-exp1.licdn.com is a domain used by Linkedin to serve static content
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Here a CNAME points the domain to the DNS of CDN provider
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dig media-exp1.licdn.com +short
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2-01-2c3e-005c.cdx.cedexis.net.
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WHY: CDNs help offload traffic spikes and are often economical ways to scale parts of a site’s traffic. They also often substantially improve page download times.
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KEY TAKEAWAYS: CDNs are a fast and simple way to offset the spikiness of traffic as well as traffic growth in general. Make sure you perform a cost-benefit analysis and monitor the CDN usage. If CDNs have a lot of cache misses, then we don’t gain much from CDN and are still serving requests using our compute resources.
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Scalability - Microservices
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This pattern represents the separation of work by service or function within the application. Microservices are meant to address the issues associated with growth and complexity in the code base and data sets. The intent is to create fault isolation as well as to reduce response times.
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Microservices can scale transactions, data sizes, and codebase sizes. They are most effective in scaling the size and complexity of your codebase. They tend to cost a bit more than horizontal scaling because the engineering team needs to rewrite services or, at the very least, disaggregate them from the original monolithic application.
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WHAT: Sometimes referred to as scale through services or resources, this rule focuses on scaling by splitting data sets, transactions, and engineering teams along verb (services) or noun (resources) boundaries.
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WHEN TO USE: Very large data sets where relations between data are not necessary. Large, complex systems where scaling engineering resources requires specialization.
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HOW TO USE: Split up actions by using verbs, or resources by using nouns, or use a mix. Split both the services and the data along the lines defined by the verb/noun approach.
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WHY: Allows for efficient scaling of not only transactions but also very large data sets associated with those transactions. It also allows for the efficient scaling of teams.
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KEY TAKEAWAYS: Microservices allow for efficient scaling of transactions, large data sets, and can help with fault isolation. It helps reduce the communication overhead of teams. The codebase becomes less complex as disjoint features are decoupled and spun as new services thereby letting each service scale independently specific to its requirement.
This pattern represents the separation of work based on attributes that are looked up or determined at the time of the transaction. Most often, these are implemented as splits by requestor, customer, or client.
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Very often, a lookup service or deterministic algorithm will need to be written for these types of splits.
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Sharding aids in scaling transaction growth, scaling instruction sets, and decreasing processing time (the last by limiting the data necessary to perform any transaction). This is more effective at scaling growth in customers or clients. It can aid with disaster recovery efforts, and limit the impact of incidents to only a specific segment of customers.
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Here the auth data is sharded based on user names so that DBs can respond faster as the amount of data DBs have to work on has drastically reduced during queries.
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There can be other ways to split
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Here the whole data centre is split and replicated and clients are directed to a data centre based on their geography. This helps in improving performance as clients are directed to the closest Data centre and performance increases as we add more data centres. There are some replication and consistency overhead with this approach one needs to be aware of. This also gives fault tolerance by rolling out test features to one site and rollback if there is an impact to that geography
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WHAT: This is very often a split by some unique aspect of the customer such as customer ID, name, geography, and so on.
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WHEN TO USE: Very large, similar data sets such as large and rapidly growing customer bases or when the response time for a geographically distributed customer base is important.
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HOW TO USE: Identify something you know about the customer, such as customer ID, last name, geography, or device, and split or partition both data and services based on that attribute.
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WHY: Rapid customer growth exceeds other forms of data growth, or you have the need to perform fault isolation between certain customer groups as you scale.
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KEY TAKEAWAYS: Shards are effective at helping you to scale customer bases but can also be applied to other very large data sets that can’t be pulled apart using the microservices methodology.
SREs in coordination with the network team work on how to map users traffic to a particular site.
-https://engineering.linkedin.com/blog/2017/05/trafficshift--load-testing-at-scale
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SREs work closely with the Dev team to split monoliths to multiple microservices that are easy to run and manage
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SREs work on improving Load Balancers' reliability, service discovery and performance
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SREs work closely to split Data into shards and manage data integrity and consistency.
-https://engineering.linkedin.com/espresso/introducing-espresso-linkedins-hot-new-distributed-document-store
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SREs work to set up, configure and improve CDN cache hit rate.
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-- If either codeWhichMayFail() or isUserInRole fails or throws an exception, the user is an admin by default. This is obviously a security risk.
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- - a Key Distribution Center (KDC), which acts as the trusted third-party authentication service.
-Correspondence between layers of the TCP/IP architecture and the OSI model. Also shown are placements of cryptographic algorithms in network layers, where the dotted arrows indicate actual communications of cryptographic algorithms
- Flow Diagram of a Packet Generation
-- EX: In 2008, Pakistan decided to block YouTube by creating a BGP route that led into a black hole. Instead this routing information got transmitted to a hong kong ISP and from there accidentally got propagated to the rest of the world meaning millions were routed through to this black hole and therefore unable to access YouTube.
-- Potentially, the greatest risk to BGP occurs in a denial of service attack in which a router is flooded with more packets than it can handle. Network overload and router resource exhaustion happen when the network begins carrying an excessive number of BGP messages, overloading the router control processors, memory, routing table and reducing the bandwidth available for data traffic.
-- Refer : 
