Cross-Account Monitoring for SageMaker Pipelines
AWS ML Blog · rss · 2026-07-16
AWS introduced a solution using a CloudWatch custom dashboard to centrally monitor SageMaker Pipelines across multiple accounts and Regions.
The post highlights that managing scattered SageMaker Pipelines forces admins to constantly switch consoles, driving up monitoring costs. To solve this, the solution adopts a hub-and-spoke architecture:
- The Dashboard stack is deployed in the primary account/Region, managing the dashboard UI, DynamoDB storage, and backend Lambda functions.
- The Forwarder stack is deployed in monitored accounts/Regions, using EventBridge to forward events back to the central hub.
The data flow works as follows:
- SageMaker AI generates pipeline events.
- EventBridge captures the events and triggers a Lambda function for data enrichment.
- Enriched events are sent back to the monitoring hub via EventBridge.
- The central Lambda function writes the data to DynamoDB.
- The CloudWatch dashboard reads the data to display pipeline execution status, duration, Region, account, and step details.
Additional highlights include:
- A serverless, event-driven implementation that avoids polling.
- Cross-account security using IAM and resource policies.
- Dashboard filtering to view detailed steps for individual pipeline executions.
- CloudWatch alarms triggered by widget usage thresholds, sending alerts via SNS.
Overall, it serves as a solid blueprint for AI/MLOps observability infrastructure.
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