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Create Azure Databricks workspace

Nirav Soni 0 Reputation points
2026-04-07T17:46:10.71+00:00

I created a workspace for Azure Databricks, which continues to show "Deployment is in progress" for more than 3 hours as I post this question. There are no alerts or errors in the activity logs. When should I expect this to complete?

Azure Databricks
Azure Databricks

An Apache Spark-based analytics platform optimized for Azure.

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  1. Nirav Soni 0 Reputation points
    2026-04-07T17:56:04.6133333+00:00

    I noticed that the Provisioning State was "Running" and Status as "Created". After 4 hours, it marked as "RequestTimeOut". After logging out and logging back in, I can see the workspace created successfully.

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  2. Q&A Assist
    2026-04-07T17:46:22.7366667+00:00
    AI generated content. This question contains an answer created with AI from Q&A Assist. Learn more

    Azure Databricks workspace deployments normally complete in a few minutes, not hours. If the portal shows “Deployment is in progress” for several hours, the deployment is effectively stuck.

    For Azure Databricks workspaces, when a deployment fails or hangs, the workspace resource is still created but left in a failed state. The documented guidance is to delete that workspace and redeploy a new one that addresses any underlying issue.

    Recommended steps:

    1. In the Azure portal, go to the Databricks Workspaces page and check the workspace status:
      • Provisioning = in progress
      • Running = successful
      • Failed = failed deployment
    2. If it is still not Running after this long, delete the workspace resource (this also deletes the managed resource group and any successfully deployed resources) and create a new workspace:
      • Either via Create a resource → Analytics → Azure Databricks in the portal, or
      • Using PowerShell/ARM/Bicep if preferred.
    3. After redeployment, verify the status is Running on the Workspaces page.

    If repeated deployments hang or fail, switch region or adjust configuration and redeploy, as region-specific issues can cause long-running or failing deployments.


    References:

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