Databricks Certified Generative AI Engineer Associate — Question 26

A Generative Al Engineer has already trained an LLM on Databricks and it is now ready to be deployed.
Which of the following steps correctly outlines the easiest process for deploying a model on Databricks?

Answer options

• A. Log the model as a pickle object, upload the object to Unity Catalog Volume, register it to Unity Catalog using MLflow, and start a serving endpoint
• B. Log the model using MLflow during training, directly register the model to Unity Catalog using the MLflow API, and start a serving endpoint
• C. Save the model along with its dependencies in a local directory, build the Docker image, and run the Docker container
• D. Wrap the LLM’s prediction function into a Flask application and serve using Gunicorn

Correct answer: B

Explanation

Option B is correct because it utilizes MLflow for logging and registering the model directly to Unity Catalog, streamlining the deployment process. The other options involve unnecessary steps or methods that do not align with Databricks' best practices for model deployment.