This article explains how to use Amazon SageMaker Model Cards sharing across AWS accounts to improve ML model governance and visibility in multi-account architectures.

• SageMaker Model Cards provide centralized documentation and single source of truth for model metadata
• Cross-account sharing enables teams to collaborate while maintaining project isolation and security
• AWS RAM (Resource Access Manager) facilitates sharing model cards across AWS accounts
• Centralized model card approach manages cards in one account, shared with Dev, Test, and Prod accounts
• Model cards progress through Draft, Pending Review, Pending Approval, and Production states
• Shared accounts can view, update, and export model cards with appropriate IAM permissions
• Multi-account strategy improves security, reliability, and scalability of ML workloads

SageMaker Model Cards sharing enables enterprises to scale ML governance across multiple accounts while maintaining transparency, access control, and audit trails throughout the model development lifecycle.