{
  "id": 16203170,
  "title": "Orchestrating SageMaker AI endpoint auto scaling with AWS CDK",
  "url": "https://urgent.news/2026/10/23/orchestrating-sagemaker-ai-endpoint-auto-scaling-with-aws-cdk",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-23T16:30:10.000Z",
  "source": {
    "name": "AWS Machine Learning",
    "slug": "aws-machine-learning",
    "url": "https://aws.amazon.com/blogs/machine-learning/orchestrating-sagemaker-ai-endpoint-auto-scaling-with-aws-cdk/"
  },
  "original_language": "en",
  "account": null,
  "summary": "AWS Machine Learning has published a post detailing the issue of updating Amazon SageMaker AI real-time endpoint configurations, which can lead to deployments failing when using AWS CloudFormation or the AWS Cloud Development Kit (AWS CDK). The problem arises because SageMaker AI requires deregistering scalable targets before updating endpoints, but CloudFormation cannot track AWS Application Auto Scaling resources when they are deregistered. To solve this issue, AWS Machine Learning introduces a reusable CDK construct with AWS CloudFormation custom resources, allowing for automatic deregister and registration of auto scaling during endpoint updates. This eliminates the need for manual intervention and ensures that endpoint configurations and auto scaling parameters can be updated in a single deployment.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}