Amazon Fixes AI Deployment Glitch That Could Cost You Money
If your company uses Amazon's AI, this fix could save hours and prevent costly errors.
Updating an Amazon SageMaker AI real-time endpoint configuration—such as changing the instance type, instance count, or environment variables—can cause deployments through AWS CloudFormation or the AWS CDK to fail. SageMaker AI requires deregistering the scalable target before the endpoint update, but once it is deregistered, CloudFormation can’t track the AWS Application Auto Scaling resources.
The article shows how to use a reusable CDK construct with AWS CloudFormation custom resources to automatically orchestrate deregister and register auto scaling during endpoint updates, so you can update the endpoint configuration and auto scaling parameters in a single deployment without manual intervention. It also walks through deploying a SageMaker AI endpoint with auto scaling using an example stack and verifying that configuration updates work correctly.
- Updating AI on Amazon SageMaker used to fail or leave auto-scaling off, risking crashes or extra costs.
- AWS's new tool automates the update process, so auto-scaling is always properly reset.
- This means more reliable AI services and potentially lower cloud bills for companies.
Why It Matters
This fix reduces downtime and costs for companies using AI, leading to more reliable services for everyone.