MLflow与SageMaker AI模型注册表跨账户管理
Govern models with MLflow and Amazon SageMaker AI Model Registry sync: Part 2
精选理由
AWS教你用MLflow和SageMaker实现跨账户模型治理，支持中心化和隔离两种架构。
AWS博客介绍MLflow与Amazon SageMaker AI模型注册表同步功能，支持跨账户模型治理。文章展示了两种拓扑结构：中心化的hub-and-spoke模式，使用AWS RAM集中治理；以及保持开发账户隔离的混合模式。这些功能帮助企业在多个AWS账户间统一管理AI模型生命周期。
原文 · AWS Machine Learning Blog
Govern models with MLflow and Amazon SageMaker AI Model Registry sync: Part 2
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.
