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Amazon CloudWatch with Anomaly Detection

Contents

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Metrics and Anomaly Detection
1
Introduction
PREVIEW3m 12s
4
Summary
3m 42s

The course is part of this learning path

Introduction
Overview
Difficulty
Intermediate
Duration
38m
Students
42
Ratings
5/5
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Description

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

Prerequisites

To get the most out of this course, 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.

Transcript

Hello and welcome to this course on Amazon CloudWatch Anomaly Detection. My name is Stephen Cole and I’ll be your instructor.  I’ve been working in the cloud for several years and currently hold many active AWS certifications.

My contact information is shown on the screen.  Please feel free to reach out to me with any questions, comments, or concerns. Alternatively, you can always get in touch with us here at Cloud Academy by sending an email to support@cloudacademy.com and one of our cloud experts will follow up with you.

I've written this course for people that want to learn about creating Amazon CloudWatch Alarms using Anomaly Detection.  While I was writing it, I realized that while people might be interested in learning how it works because they've heard about it.  There is probably a large number of people that don't know that they need to learn about this feature of Amazon CloudWatch.

Through the years, I've found that one of life's truths is that naming things is hard. Anomaly Detection is a great example of this difficulty.   While it accurately describes what it does inside Amazon CloudWatch, as a name, it does a disservice to what makes it useful.  It does not really describe the pain point that it addresses.

Amazon CloudWatch Anomaly Detection is for people that want or need to create CloudWatch Alarms that are almost completely automated.  There's some human intervention required.  However, most of the behind-the-scenes work is done by AWS.

I expect that, before you start taking this course, you have some experience running workloads in the AWS cloud, have a basic understanding of what Amazon CloudWatch is, know how to create CloudWatch Alarms, and how to trigger an action or notification based on an Alarm's state.

Having this knowledge will help you get the most out of the materials presented. However, it's not required. In these lectures, I do take some time to review Amazon CloudWatch and how it works.  That said, some of the details might not be as clear as they could be if this is your first exposure to monitoring metrics and creating alarms using Amazon CloudWatch.

I have several objectives for this course. I am going to cover Amazon CloudWatch and CloudWatch Alarms using Anomaly Detection. I will review, at a very high level, what Amazon CloudWatch is and how monitored metrics go into an ALARM state. I will then talk about the challenges of creating CloudWatch Alarms, explain the benefits of Machine Learning, and outline how these benefits improve creating Alarms.

When you're finished with this course, you should be able to create a CloudWatch Alarm using Anomaly Detection and see a visualization of it.  You will also be aware of what types of metrics are suitable for use with Anomaly Detection.

Please note that, at the time this content was written, the course information was accurate. AWS implements hundreds of updates every month as part of its ongoing drive to innovate and enhance its services. As a result, minor discrepancies may appear in the course content over time.  Here at Cloud Academy, we strive to keep our courses up to date in order to provide the best training available.

If you notice any information that is outdated, please contact support@cloudacademy.comThis will allow us to update the course during the next release cycle.  We would love to hear from you. I would love to hear from you.  Tell me what you learned, what could use some attention, or what worked really well for you.  

That said, let's get started.

About the Author
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Stephen Cole
AWS Certification Specialist
Students
6036
Courses
10
Learning Paths
4

Stephen is the AWS Certification Specialist at Cloud Academy. His content focuses heavily on topics related to certification on Amazon Web Services technologies. He loves teaching and believes that there are no shortcuts to certification but it is possible to find the right path and course of study.

Stephen has worked in IT for over 25 years in roles ranging from tech support to systems engineering. At one point, he taught computer network technology at a community college in Washington state.

Before coming to Cloud Academy, Stephen worked as a trainer and curriculum developer at AWS and brings a wealth of knowledge and experience in cloud technologies.

In his spare time, Stephen enjoys reading, sudoku, gaming, and modern square dancing.