Tutorials
Govern models with MLflow and Amazon SageMaker AI Model Registry sync: Part 1
Managed MLflow on Amazon SageMaker AI now syncs richer model metadata (training metrics, evaluation results, inference specs, and lineage) into the SageMaker AI Model Registry, with lifecycle stage pr
Managed MLflow on Amazon SageMaker AI now syncs richer model metadata (training metrics, evaluation results, inference specs, and lineage) into the SageMaker AI Model Registry, with lifecycle stage promotion. Part 1 shows how to govern candidate models in a single account using IAM guardrails.
Related
- End-to-end lineage with DVC and Amazon SageMaker AI MLflow apps
- Build a custom portal with embedded Amazon SageMaker AI MLflow Apps
- Streamline external access to Amazon SageMaker MLflow using a REST API proxy
Source: AWS ML Blog | 2026-09-08