Managed Identity for ML Workloads Quiz

What you'll be asked

1. What is the primary benefit of using Managed Identity for an ML workload compared to using connection strings or API keys?
2. An ML engineer needs to grant a training job running on an Azure Machine Learning compute cluster access to a specific Blob Storage container. What is the most secure way to implement this?
3. What is the difference between a System-Assigned and a User-Assigned Managed Identity?
4. When configuring a distributed training job that requires access to both Azure Container Registry (for images) and Azure Key Vault (for secrets), which Managed Identity configuration is best practice?
5. An ML pipeline fails with a 403 Forbidden error when attempting to access an Azure Data Lake Gen2 store, despite the compute cluster having a User-Assigned Managed Identity. What is the most likely cause?

Answers and explanations come after you submit.