Amazon EC2 Auto Scaling Documentation

Automate launches of new Amazon EC2 instances when demand increases, and automate the termination of unneeded Amazon EC2 instances when demand subsides.

Scale dynamically based on your Amazon CloudWatch metrics, or predictably according to a schedule that you define. Receive notifications via Amazon Simple Notification Service (Amazon SNS) to be alerted when you use Amazon CloudWatch alarms to initiate Amazon EC2 Auto Scaling actions, or when EC2 Auto Scaling completes an action.

Automating how your Amazon EC2 fleet is managed can help maintain the availability of your applications. Amazon EC2 Auto Scaling is designed to automatically replace unhealthy or unreachable instances to maintain higher availability of your applications. To automate fleet management for EC2 instances, EC2 Auto Scaling is designed to monitor the health of running instances, automatically replace impaired instances, and balance capacity across Availability Zones. Learn more.

Predictive Scaling is designed to predict future traffic, including regularly-occurring spikes, and helps provision the right number of EC2 instances in advance of predicted changes. Predictive Scaling’s machine learning algorithms are designed to detect changes in daily and weekly patterns, automatically adjusting their forecasts. This is designed to remove the need for manual adjustment of Auto Scaling parameters over time, making Auto Scaling simpler to configure and consume. Auto Scaling enhanced with Predictive Scaling is designed to deliver faster, simpler, and more accurate capacity provisioning and result in lower cost and more responsive applications.

Amazon EC2 Auto Scaling is designed to let you provision and automatically scale instances across purchase options, Availability Zones (AZ), and instance families in a single application to help you optimize scale, performance, and cost.

If you’re signed up for the Amazon EC2 service, you’re already registered to use Amazon EC2 Auto Scaling and can begin using the feature via the API or command line interface.

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