Application Auto Scaling
API Reference (API Version 2016-02-06)

Welcome

This is the Application Auto Scaling API Reference. With Application Auto Scaling, you can configure automatic scaling for the following resources:

  • Amazon ECS services

  • Amazon EC2 Spot Fleet requests

  • Amazon EMR clusters

  • Amazon AppStream 2.0 fleets

  • Amazon DynamoDB tables and global secondary indexes throughput capacity

  • Amazon Aurora Replicas

  • Amazon SageMaker endpoint variants

  • Custom resources provided by your own applications or services

  • Amazon Comprehend document classification endpoints

  • AWS Lambda function provisioned concurrency

API Summary

The Application Auto Scaling service API includes three key sets of actions:

  • Register and manage scalable targets - Register AWS or custom resources as scalable targets (a resource that Application Auto Scaling can scale), set minimum and maximum capacity limits, and retrieve information on existing scalable targets.

  • Configure and manage automatic scaling - Define scaling policies to dynamically scale your resources in response to CloudWatch alarms, schedule one-time or recurring scaling actions, and retrieve your recent scaling activity history.

  • Suspend and resume scaling - Temporarily suspend and later resume automatic scaling by calling the RegisterScalableTarget action for any Application Auto Scaling scalable target. You can suspend and resume, individually or in combination, scale-out activities triggered by a scaling policy, scale-in activities triggered by a scaling policy, and scheduled scaling.

The documentation for each action shows the Query API request syntax, the request parameters, and the response elements and provides links to language-specific SDK reference topics. For more information, see AWS SDKs.

To learn more about Application Auto Scaling, including information about granting IAM users required permissions for Application Auto Scaling actions, see the Application Auto Scaling User Guide.

This document was last published on December 7, 2019.