reorganise course folders

courses/level101/metrics_and_monitoring/alerts.md

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+##
+
+# Proactive monitoring using alerts
+Earlier we discussed different ways to collect key metric data points
+from a service and its underlying infrastructure. This data gives us a
+better understanding of how the service is performing. One of the main
+objectives of monitoring is to detect any service degradations early
+(reduce Mean Time To Detect) and notify stakeholders so that the issues
+are either avoided or can be fixed early, thus reducing Mean Time To
+Recover (MTTR). For example, if you are notified when resource usage by
+a service exceeds 90 percent, you can take preventive measures to avoid
+any service breakdown due to a shortage of resources. On the other hand,
+when a service goes down due to an issue, early detection and
+notification of such incidents can help you quickly fix the issue.
+
+![An alert notification received on Slack](images/image11.png) 
+<p align="center"> Figure 8: An alert notification received on Slack </p>
+
+Today most of the monitoring services available provide a mechanism to
+set up alerts on one or a combination of metrics to actively monitor the
+service health. These alerts have a set of defined rules or conditions,
+and when the rule is broken, you are notified. These rules can be as
+simple as notifying when the metric value exceeds n to as complex as a
+week over week (WoW) comparison of standard deviation over a period of
+time. Monitoring tools notify you about an active alert, and most of
+these tools support instant messaging (IM) platforms, SMS, email, or
+phone calls. Figure 8 shows a sample alert notification received on
+Slack for memory usage exceeding 90 percent of total RAM space on the
+host.