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Can't start, delete, unpin or edit cluster: User is not part of org

PrebenOlsen
New Contributor III

Hi!

Getting error message:

DatabricksError: User XXX is not part of org: YYY. Config: host=https://adb-ZZZ.azuredatabricks.net, auth_type=runtime

I am in the admin's group, but I cannot alter this in any way. I've tried using the databricks-SDK using:

from databricks.sdk import WorkspaceClient
w = WorkspaceClient()
w.clusters.change_owner(cluster_id,username)
w.clusters.unpin(cluster_id)
 
But the same error message comes. Cannot edit it manually, rename, start, nothing. 
 
Cluster was last online yesterday at 2pm. This issue happens on the same cluster in all three environment workspaces. Maybe someone's credentials were lost yesterday after leaving the company, who knows. But how to fix this? 
 
3 REPLIES 3

karthik_p
Esteemed Contributor

@PrebenOlsen are you part of owner/azure contributor from AD, if you are admin in databricks level, you should be able to edit cluster settings 

I am both Contributor and Data Contributor in Azure. In Databricks, I belong to the Admin group.

Noone in my team can do anything with the cluster as per now. 

youssefmrini
Databricks Employee
Databricks Employee

To resolve this issue, I would recommend taking the following steps:

  1. Verify that you have the correct access and permissions:

    Check with your Databricks organization admin to ensure that your user account has the appropriate access level and permissions to work with clusters and other resources in the organization.

  2. Verify that your authentication token is valid:

    Check that your authentication token is still valid and has not expired or been revoked. If necessary, generate a new token from the Databricks workspace user settings page.

  3. Verify your configuration:

    Check that you have configured the WorkspaceClient correctly, including specifying the correct configuration file or token. Double-check the configuration settings to ensure that they match with the Databricks environment you are working with.

  4. Check for any issues with the Databricks instance or cluster configuration:

    If you are still experiencing issues after verifying your access, permissions, and configuration settings, it may be worth checking with the Databricks support team to see if there are any known issues or other troubleshooting steps to take.

I hope this helps! Let me know if you have any other questions.

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