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What is the Model Registry in Azure ML?
Updated May 15, 2026
Short answer
The Azure ML Model Registry stores, versions, and manages machine learning models for deployment and governance.
Deep explanation
The Model Registry is a centralized repository for managing trained ML models. It supports model versioning, metadata storage, lineage tracking, deployment integration, and governance.
Registered models contain:
- Model artifacts
- Metadata
- Training lineage
- Tags
- Deployment history
- Associated datasets and environments
Versioning ensures traceability and rollback capability. Enterprises rely on model registries to standardize deployment workflows and maintain auditability.
Real-world example
A financial institution tracks multiple versions of credit risk models for compliance audits and rollback safety.
Common mistakes
- Overwriting models without versioning, poor naming conventions, and failing to store metadata.
Follow-up questions
- Why is model versioning important?
- What metadata should be stored with models?
- Can Azure ML deploy directly from the registry?