Orchestrating SageMaker AI endpoint auto scaling with AWS CDK

This article demonstrates how to use AWS CDK with CloudFormation custom resources to automatically orchestrate SageMaker AI endpoint auto scaling during configuration updates.

• SageMaker AI requires deregistering scalable targets before updating endpoints, causing CloudFormation deployments to fail
• Solution uses three custom resources to deregister auto scaling before endpoint updates, then re-register after the endpoint reaches InService status
• Custom resources use explicit dependency ordering and ConfigHash properties to maintain auto scaling across deployments
• Includes a reusable CDK construct that can be integrated into existing stacks or deployed as a standalone example
• Asynchronous completion pattern allows waiting for endpoint readiness without blocking Lambda invocations
• Walkthrough covers cloning the repository, configuring endpoint settings, deploying, and testing updates

The construct simplifies SageMaker AI endpoint management by automating the complex orchestration of deregistering and re-registering auto scaling during configuration changes.