Monitor Amazon SageMaker Pipelines cross-account with custom Amazon CloudWatch dashboards
AWS Machine Learning Giorgio Pessot
AWS published a guide for monitoring SageMaker Pipelines across multiple AWS accounts and regions using CloudWatch custom dashboards with a serverless hub-and-spoke architecture. The solution uses EventBridge, Lambda, and DynamoDB to collect pipeline execution data in real-time from source accounts and display unified status, timing, and step details on a centralized dashboard. Organizations can reduce operational overhead from manually switching between accounts and regions, and extend the monitoring to other ML workloads like Step Functions or Batch jobs.
Why it matters
In this post, we present a solution designed to centralize the monitoring of SageMaker Pipelines across AWS accounts and Regions using Amazon CloudWatch custom dashboards. The accompanying GitHub repository provides a customizable AWS Cloud Development Kit (AWS CDK) example of the required infrastructure.
