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ML Model Lifecycle And OperationshardMultiple ChoiceObjective-mapped

AI-300 ML Model Lifecycle And Operations Practice Question

You are managing model versioning in Azure Machine Learning Registry. You need to promote a model from 'Staging' to 'Production' without creating a new asset version. Which command or action should you perform?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Update the model asset by adding a 'Production' tag via the SDK or CLI.

You should use the 'update' command on the existing model version asset to update its tags or properties to reflect the production status.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Change the 'run_id' in the model metadata.

    Why it's wrong here

    Run IDs are immutable once the run finishes.

  • Delete the old version and re-register as 'Production'.

    Why it's wrong here

    This breaks lineage and audit logs.

  • Update the model asset by adding a 'Production' tag via the SDK or CLI.

    Why this is correct

    Tags are the standard way to track status without changing the asset version.

  • Run 'az ml model create' with a new version number.

    Why it's wrong here

    This creates a new version, which is not required.

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Last reviewed August 2026 · checked against the official Microsoft exam blueprint

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