Model lifecycle & governance
Amazon SageMaker Model Registry
AWS service for cataloguing production models as versioned model packages in model groups, with metadata, lineage, a staging construct, approval status and CI/CD deployment. Integrated SageMaker Model Cards add intended use, risk rating and evaluation records, versioned immutably on edit.
commercial · generally available · Research snapshot 2026-09-06
Visit the official product source ↗Where it fits
Model lifecycle & governance · AI risk & compliance management
Useful conversation with: ML platform engineer, MLOps lead, Model risk reviewer.
Ask for a demonstration
Demonstrate a model package moving through staging with approval status changes, and show the linked model card version history for the same model.
Capabilities and evidence
Support labels reflect the supplied research. Documentation and vendor claims are not independent product tests. “Not established” means the researcher did not find support; it does not prove a capability is absent.
Documented by provider
AWS documentation states the Model Registry catalogs models for production, manages model versions, associates metadata such as training metrics, views model lineage for traceability and reproducibility, defines a staging construct for the model lifecycle, manages a model's approval status and automates deployment with CI/CD.
Limit: Docs describe an approval status field and staging, not a multi-party approval workflow with segregation of duties; scope is models registered in SageMaker.
Source s1
Documented by provider
AWS documentation states model cards document intended use, risk rating, training details and metrics, evaluation results, considerations and recommendations in one place, are integrated with the Model Registry for auditing information, can be exported to PDF, and that any edit other than an approval-status update creates an additional card version forming an immutable record of changes.
Limit: The risk rating is a user-entered field; documentation does not validate content quality or satisfy any named regulation.
Source s2
Limitations to discuss
- Only AWS-hosted/registered models are in scope; governance of external AI is not addressed.
- No control-to-regulation mapping or evidence pack features documented.
Sources
- Model Registration Deployment with Model Registry · Amazon Web Services · official docs
Access date reported by researcher: 2026-09-06 - Amazon SageMaker Model Cards · Amazon Web Services · official docs
Access date reported by researcher: 2026-09-06
Listing does not imply partnership, supplier status, a working DutyGraph integration, or a compliance certification.
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