With Application Auto Scaling, you can configure automatic scaling for the following resources:
Amazon AppStream 2.0 fleets
Amazon Aurora Replicas
Amazon Comprehend document classification and entity recognizer endpoints
Amazon DynamoDB tables and global secondary indexes throughput capacity
Amazon ECS services
Amazon ElastiCache for Redis clusters (replication groups)
Amazon EMR clusters
Amazon Keyspaces (for Apache Cassandra) tables
Lambda function provisioned concurrency
Amazon Managed Streaming for Apache Kafka broker storage
Amazon Neptune clusters
Amazon SageMaker endpoint variants
Spot Fleets (Amazon EC2)
Custom resources provided by your own applications or services
To learn more about Application Auto Scaling, see the Application Auto Scaling User Guide.
API Summary
The Application Auto Scaling service API includes three key sets of actions:
Register and manage scalable targets - Register Amazon Web Services 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 API action for any Application Auto Scaling scalable target. You can suspend and resume (individually or in combination) scale-out activities that are triggered by a scaling policy, scale-in activities that are triggered by a scaling policy, and scheduled scaling.
Use this page to mock Application Auto Scaling in your testing and development.
Run our mock API sample using the open source WireMock library, or in the free edition of WireMock Cloud. You'll have a working API server simulating the behavior of Application Auto Scaling, which will allow you to keep building and testing even if the actual API you isn't currently available.