Amazon CloudWatch with Anomaly Detection

This lesson covers Amazon CloudWatch and CloudWatch Alarms using Anomaly Detection.

Amazon CloudWatch is the monitoring and observability service from AWS.  The phrase Anomaly Detection implies that this feature is used to detect outliers but this is an understatement.  It is a feature of CloudWatch that uses Machine Learning to automate the creation of alarms and their related thresholds.

This lesson includes a review of Amazon CloudWatch and the challenges of setting and maintaining alarms.  It covers how machine learning with Anomaly Detection helps setting alarms and managing/maintaining their thresholds.

You'll learn how to create a CloudWatch Alarm using Anomaly Detection and learn what types of metrics are suitable for use with Anomaly Detection.

Learning Objectives

• Gain a high level of Amazon CloudWatch
• Review how monitored metrics go into an ALARM state
• Learn about the challenges of creating CloudWatch Alarms and the benefits of using machine learning in alarm management
• Know how to create a CloudWatch Alarm using Anomaly Detection
• Learn what types of metrics are suitable for use with Anomaly Detection

Intended Audience

This lesson is for anyone who wants or needs to create CloudWatch Alarms that are almost completely automated.

Prerequisites

To get the most out of this lesson, you should have some experience running workloads in the AWS cloud, know what Amazon CloudWatch is, know how to create CloudWatch Alarms, and how to trigger an action or notification based on an Alarm's state.