[Bug] Azure ML MSI support is missing

[bgavrilMS]

Azure ML Studio uses similar environment variables to other hosting environments such as Azure App Service. In our previous implementation, we attempted to detect Azure App Service's environment variables before CloudShell. Because CloudShell uses a subset of the environment variables, it will be wrongly detected if it is attempted first in an AzureML environment and fails to add the value of the MSI_SECRET env var in a required header named secret.

See MSAL Python's implementation: https://github.com/AzureAD/microsoft-authentication-library-for-python/blob/dev/msal/managed_identity.py#L415

Original issue:

AzureAD/microsoft-authentication-library-for-dotnet#4984

[SimardeepSingh-zsh]

To address the issue with Azure ML MSI support, you can follow these steps:

Update Environment Variables: Ensure that the MSI_ENDPOINT and MSI_SECRET environment variables are correctly set in your Azure ML environment. These variables are crucial for Managed Identity authentication1.

Modify Authentication Code: Update your authentication code to correctly detect and use these environment variables. You can refer to the implementation in MSAL Python for guidance on how to handle these variables2.

Test Locally: Before deploying to the cloud, test your setup locally using local deployment. This allows you to debug and ensure that the environment variables are correctly used3.

Check Logs: Use container logs to debug any issues that arise during deployment. This can help you identify and fix problems related to environment variables and authentication3.

Consult Documentation: Refer to the Azure Machine Learning documentation for troubleshooting and resolving common deployment issues.