Govern models with MLflow and Amazon SageMaker AI Model Registry sync: Part 2
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Governing models across accounts is the next step after automatic model registration. This post extends managed MLflow and Amazon SageMaker AI Model Registry sync to two cross-account governance topologies: a hub-and-spoke pattern that centralizes governance with AWS RAM, and a hybrid pattern that keeps development accounts isolated.
Governing models across accounts is the natural next step once automatic model registration is in place. In Part 1 we introduced how managed MLflow on Amazon SageMaker AI synchronizes registered models into the SageMaker AI Model Registry . We walked through a single-account setup where AWS Identity and Access Management (IAM) condition keys separate the data scientist and governance officer personas. Larger organizations, however, separate development from production at the account level. They…
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