Setting a baseline for Azure Machine Learning
Throughout this book, we have seen multiple services and explored several ways to secure the Azure Machine Learning workspace and its associated services in Azure. All those best practices are part of the suggested best practices. As we focus on securing our workloads, it’s essential to establish a security foundation to guide our efforts. A security baseline is a set of the minimum security controls we need to implement for a system. Let us again review what the minimum requirements are to protect workloads running in Azure Machine Learning, which we have already outlined previously in this book, and learn how to extend this functionality further by using other services.
Let us review the baseline Azure Machine Learning best practices organized by the Zero Trust model we reviewed in this book:
- Securing identity (Chapter 6):