Cannot create Azure Key Vault backed Databricks Secret Scope with Service Principal (AAD Enterprise App)

Christopher Harrison 26 Reputation points
2022-03-11T14:23:10.013+00:00

In an end-to-end Databricks deployment, orchestrated by Terraform using a Service Principal (AAD Enterprise App), it is not possible to create an Azure Key Vault backed Databricks Secret Scope. You have to do this with a regular user identity. This is preventing full automation of the deployment (e.g., secret management, storage mounting, etc.).

I asked this on StackOverflow and was advised that this is a well-known and well-documented architectural problem with Azure, that I should raise with Microsoft Support for prioritisation. The exact problem that needs to be solved on the Azure side is not clear: If that alone could be described, then I can at least go to Microsoft with more useful information.

Is there a known ticket ID with Azure for this issue, or can the underlying issue be made clear?

Azure Key Vault
Azure Key Vault
An Azure service that is used to manage and protect cryptographic keys and other secrets used by cloud apps and services.
1,384 questions
Azure Databricks
Azure Databricks
An Apache Spark-based analytics platform optimized for Azure.
2,343 questions
Microsoft Entra ID
Microsoft Entra ID
A Microsoft Entra identity service that provides identity management and access control capabilities. Replaces Azure Active Directory.
23,407 questions
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  1. PRADEEPCHEEKATLA 90,556 Reputation points
    2022-03-15T05:13:45.317+00:00

    Hello @Christopher Harrison ,

    Thanks for the question and using MS Q&A platform.

    This is a known limitation with Azure Databricks. For more details, please do checkout GitHub issue which addressing same issue.

    Unfortunately, this feature is not yet available. Our product team is currently working on this feature.

    At this moment we don't have exact ETA on when will this feature will be available. And we will update this thread once it's available.

    Appreciate if you could share the feedback on our Azure Databricks feedback channel. Which would be open for the user community to upvote & comment on. This allows our product teams to effectively prioritize your request against our existing feature backlog and gives insight into the potential impact of implementing the suggested feature.

    Hope this will help. Please let us know if any further queries.

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