Scheduled Scaling

Contents

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AWS Auto Scaling Policies
1
Introduction
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2
7
Summary
1m 8s
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Overview
Difficulty
Intermediate
Duration
16m
Students
72
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Description

This course explores the various auto scaling policies that exist within AWS. We'll cover what each of the policies do, their strengths and weaknesses, and when best to use them. Understanding the ins and outs of these policies will help you save a lot of money and keep your customers happy by removing latency and downtime.

Learning Objectives

By the end of this course, you will understand how each of the AWS auto scaling policies works and in what situations they perform best.

Intended Audience

This course is recommended for solutions architects and developers who are working on creating highly available systems within AWS.

Prerequisites

To get the most out of this course, you should already have a basic working knowledge of AWS.

Transcript

The final bit of scaling that we should mention is time based or scheduled scaling. Scheduled scaling is when you add or remove instances from your auto scaling groups based on certain time parameters. For example, you might have a fleet of batch processing instances that you only want to go online during the middle of the night when spot instance prices are generally lower. You can have a scheduled scaling mechanism set in place to load up on these instances and get your work done during those specific hours. Scheduled scaling is a great way to help reduce costs by setting time periods in which your architectures run.

Another example is using scheduled scaling to turn off your dev environments after business hours have concluded. Why would you want to have any extra instances running when they don't need to be. With scheduled scaling you can turn off all of those test and dev workloads when they are not being used, and simply schedule them to turn back on in the morning.

And you can still have combinations of these scaling mechanisms working together. Maybe you have your dev and test environments set to turn on and off at night, but during the day, they can use dynamic scaling to increase the number of instances when needed, and tune back down to a minimum requirement when no tests are being performed.

Using scheduled scaling can save you quite a bit of money if you are able to work it into your architectures. It works especially well when you have harnessed the power of spot instances, which does require some allowances from your solution - like being able to handle stopping and starting.

 

About the Author
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Will Meadows
Senior Content Developer
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William Meadows is a passionately curious human currently living in the Bay Area in California. His career has included working with lasers, teaching teenagers how to code, and creating classes about cloud technology that are taught all over the world. His dedication to completing goals and helping others is what brings meaning to his life. In his free time, he enjoys reading Reddit, playing video games, and writing books.