29
Oct
This post is part of an ongoing series on governing the machine learning (ML) lifecycle at scale. To start from the beginning, refer to Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker. A multi-account strategy is essential not only for improving governance but also for enhancing security and control over the resources that support your organization’s business. This approach enables various teams within your organization to experiment, innovate, and integrate more rapidly while keeping the production environment secure and available for your customers. However, because multiple teams might use your ML…