Question

Your team provisions a new Azure Machine Learning workspace inside a resource group named 'rg-ml-prod' that also contains the associated storage account, key vault, and container registry. A group of ML engineers needs Contributor-level permissions on the workspace and every dependent resource, and you want to minimize the number of role assignments you have to manage as more supporting resources are added to the group over time. Which approach should you take?

Accepted Answer

Assign the Contributor role to the ML engineers group at the 'rg-ml-prod' resource group scope.

Answer

Assign the Contributor role to each ML engineer individually on the workspace, storage account, key vault, and container registry.

Answer

Assign the AzureML Data Scientist role to the ML engineers group at the workspace scope only.

Answer

Assign the Contributor role to the ML engineers group at the subscription scope.