Databricks Certified Generative AI Engineer - Associate
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Question: 33
You have deployed a machine learning model on Databricks for serving through a REST API. To ensure that only authorized users can access the model serving endpoint, you decide to implement token-based authentication. Which of the following is the best approach to control access to the model serving endpoint using token-based authentication?
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Explanation:
Explanation
For Databricks model serving endpoints, the recommended approach for token-based authentication is to use Databricks Personal Access Tokens (PAT). Here's why:
- PAT Authentication: Databricks PATs are specifically designed for programmatic access to Databricks services, including model serving endpoints
- Built-in Security: The serving endpoint infrastructure automatically validates PATs against Databricks authentication systems
- User Management: You can create and manage PATs for individual users through the Databricks workspace
- Access Control: PATs can be scoped with specific permissions and have expiration dates for enhanced security
- Integration: This approach integrates seamlessly with Databricks' existing authentication and authorization infrastructure
Key Benefits:
- Centralized user management through Databricks workspace
- Automatic token validation by the serving infrastructure
- No need for custom authentication logic in your model code
- Built-in security features like token expiration and scope limitations
This is the standard and most secure method for controlling access to Databricks model serving endpoints using token-based authentication.
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