PMLE A company uses Vertex AI for AutoML training Practice Question

A company uses Vertex AI for AutoML training. Which THREE are best practices for managing model versions?

⚠ Common exam trap

Many exam-takers think deploying each version to a separate endpoint is necessary for isolation, but Vertex AI's traffic splitting on a single endpoint is the correct and cost-effective approach for managing multiple model versions.

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

✓

Use Vertex AI Model Registry to version models

Vertex AI Model Registry is the central repository for managing and versioning models, allowing you to track iterations, compare performance, and control deployments. It provides a structured way to organize models, roll back to previous versions if needed, and maintain lineage for compliance and reproducibility.

Answer analysis

Option-by-option breakdown

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

✗
Deploy each model version to a separate endpoint
Why it's wrong here
Wrong: Unnecessary and costly; use traffic splitting.
✓
Use Vertex AI Model Registry to version models
Why this is correct
Correct: Centralized model versioning.
✓
Use evaluation metrics to compare versions
Why this is correct
Correct: Helps choose the best performing version.
✓
Use labels to tag models for tracking
Why this is correct
Correct: Helps organize and track models.
✗
Automatically delete old versions after 30 days
Why it's wrong here
Wrong: Not a best practice without considering governance.

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PMLE A company uses Vertex AI for AutoML training Practice Question

Why each option matters

Option-by-option breakdown

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