DatabricksApiException Error in Microsoft Azure Databricks

[KailashLohar]

I am doing a course on Machine Learning Associate course , at the starting itseld i am getting error while running in Azure Databricks.
Can somebody help me in solving this error.

[KailashLohar]

getting exactly this error:
DatabricksApiException: DatabricksApiException(message='Workspace Feature Store has been deprecated in the current workspace. Databricks recommends using Feature Engineering in Unity Catalog.

[SabtainSaleem]

It sounds like you're facing a Databricks API exception in Microsoft Azure. These errors often stem from issues related to authentication, permissions, or the configuration of your Azure Databricks workspace. Start by checking your Azure Active Directory (AAD) setup and ensuring that the permissions for your service principal or token are correctly assigned. Additionally, ensure your workspace and clusters are properly configured in Databricks to avoid connection or API failures. You may also want to examine any recent changes in your environment that could have triggered this error.

[KailashLohar]

Tried every above method, nothing worked.
Problem still remain same.

[LaalMukhopadhy]

A DatabricksApiException in Microsoft Azure Databricks typically occurs when there is an issue interacting with the Databricks REST API. This can result from various factors, such as incorrect API request formatting, authentication problems, or network connectivity issues. Additionally, permission errors or the Databricks service itself encountering an internal issue can trigger such exceptions. To resolve this, you should first check the error message details provided in the exception to pinpoint the cause.

[usmankhan36]

The error message indicates that Workspace Feature Store has been deprecated in your Azure Databricks workspace. The error occurs because the Feature Store API is no longer supported in your environment.

How to Fix It:

1. Check If Your Databricks Workspace Uses Unity Catalog

   • If your workspace uses Unity Catalog, you should use Feature Engineering in Unity Catalog instead of the older Feature Store.

2. Update Your Code to Use Unity Catalog

   • Modify the code to use Unity Catalog for feature storage instead of the deprecated Workspace Feature Store.
   • If your course notebook relies on the old Feature Store, try updating the feature storage location to Unity Catalog.

3. Contact Your Administrator

   • If you don’t have access to modify feature storage settings, ask your Databricks system administrator to enable Feature Engineering in Unity Catalog.

Temporary Workarounds:

• If this issue occurs in a course-provided notebook, try commenting out the line that calls reset_lesson() and see if you can proceed with the next steps.
• Try using a different Databricks workspace where the Feature Store might still be available.

Would you like help modifying your notebook to work without the deprecated Feature Store?