EC2 Auto Scaling Groups: Hands-on Guide to AWS Autoscaling

EC2 Auto Scaling Groups: a guided lab

One of the key elements – and built-in advantages – of Cloud Computing is elasticity. Or, in other words, cloud deployments should allow you to quickly and intelligently adjust compute and storage capacity to match your project’s real-time needs.

The cost-control and efficiency payoffs you can achieve through this kind of elasticity are significant. For AWS-based applications, these adjustments can be managed through EC2 Auto Scaling groups, which automatically add or remove compute resources in response to changes in demand.

The EC2 Auto Scaling Groups Lab

Working with Amazon EC2 Auto Scaling Groups and Network Load Balancer

Cloud Academy’s own senior DevOps engineer (and in-house tech guru) Antonio Angelino, has created a guided lab that allows you to jump right into the Amazon Web Services console environment and work through the configuration of an EC2 Auto Scaling group. This lab offers you the kind of confidence-building experience that you would normally find only through work in an actual production environment.

Specifically, Antonio’s lab will walk you through…

  • Configuring Auto Scaling to automatically launch web server instances
  • Building an elastic cluster by integrating Auto Scaling with an Elastic Load Balancer
  • Setting CloudWatch alarms to automatically adjust the size of a web farm based on CPU utilization
  • Utilizing Auto Scaling to ensure the availability of steady-state resources

You’ll log in to Amazon Web Service Console, create an Auto Scaling configuration, create a load balancer using ELB, and successfully create an Auto Scaling Group. And all without leaving the safety and comfort of your web browser!

Need the kind of familiarity and comfort with EC2 Auto Scaling groups that usually only comes with practical experience?

Take Cloud Academy’s Auto Scaling lab today!

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Written by

David Clinton

A Linux system administrator with twenty years' experience as a high school teacher, David has been around the industry long enough to have witnessed decades of technology trend predictions; most of them turning out to be dead wrong.


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