LFC MLflow Model Registry 3

Question 1

How can you retrieve the latest model version in the 'Production' stage using MlflowClient?

Accepted Answer

client.get_latest_versions(name, stages=['Production'])

Answer

`client.get_latest_versions(name, stages=['Production'])` returns the most recent model version(s) currently in the Production stage.

Question 2

In Databricks Unity Catalog, which permission is required to register a new model in a schema?

Accepted Answer

CREATE MODEL

Answer

The `CREATE MODEL` privilege on the target schema is required to register a new model under that schema in Unity Catalog.

Question 3

What information is captured automatically when a model is logged and registered via an MLflow run?

Accepted Answer

Model artifacts, parameters, metrics, and the source run ID

Answer

MLflow automatically links the registered model version to its source run, capturing artifacts, parameters, metrics, tags, and the run ID for full lineage.

Question 4

Which MLflow UI section allows you to compare metrics across multiple versions of the same registered model?

Accepted Answer

The registered model's version list with linked run comparisons

Answer

From the Model Registry UI, each version links back to its source run, and you can navigate to the Experiments page to compare runs side-by-side.

Question 5

What happens to model versions already in Production when you use `archive_existing_versions=True` during a stage transition?

Accepted Answer

They are moved to the Archived stage automatically

Answer

Setting `archive_existing_versions=True` automatically moves all current Production versions to Archived when a new version is transitioned to Production.

(LFC) Lakehouse Fundamentals Certification Practice Test

(LFC) Lakehouse Fundamentals Certification Practice Test

LFC MLflow Model Registry 3