A 500 error in Databricks typically indicates an internal server error. This means something went wrong on the Databricks side and not due to an issue with your code or configuration.

Here are some common causes and potential solutions for 500 errors in Databricks:

1. Spark UI Task Logs (HTTP 500 Error)

• Problem: You might encounter intermittent HTTP 500 errors when viewing task logs in the Spark UI.
• Solution:
  • Check if the Spark property spark.databricks.ui.logViewingEnabled is set to false. If so, set it to true to enable log viewing.

2. Cluster Issues

• Problem: The cluster might be overloaded or experiencing temporary issues.
• Solution:
  • Restart the cluster.
  • If the problem persists, contact Databricks support.

3. Incorrect Identity/Permissions

• Problem: In some cases, such as when integrating with Azure DevOps, you might encounter a 500 error if you’re signed in with the wrong identity or need more permissions.
• Solution:
  • Ensure you’re using the correct identity and have the required permissions.

4. Other Internal Errors

• Problem: Other internal issues within Databricks could lead to a 500 error.
• Solution:
  • If none of the above solutions work, contacting Databricks support for assistance is best. Please provide them with relevant details such as the cluster-ID, error message, and any steps you’ve already taken.