mediumMultiple Select
PMLE Practice Question: A team of data scientists and ML engineers is…
A team of data scientists and ML engineers is collaborating on a shared feature store in Vertex AI Feature Store. They need to ensure that feature definitions are versioned and that changes are reviewed before being used in production pipelines. Which TWO practices should they implement?
⚠ Common exam trap
Google Cloud often tests the distinction between environment isolation (IAM and multiple feature views) and the actual versioning/review process, leading candidates to mistakenly select Option C as a versioning practice when it only addresses access control and environment separation.
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
✓
Require code reviews for all changes to feature definitions before merging to the main branch.
Requiring code reviews for all changes to feature definitions before merging to the main branch enforces a peer-review gate, ensuring that modifications are validated for correctness, consistency, and compliance before they reach production. This aligns with MLOps best practices for governance and reduces the risk of introducing errors or breaking changes into the feature store.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Allow data scientists to edit feature definitions directly in the Vertex AI Feature Store console.
Why it's wrong here
Direct edits bypass review and versioning.
- ✓
Require code reviews for all changes to feature definitions before merging to the main branch.
Why this is correct
Code reviews ensure quality and approval.
- ✗
Define multiple feature views in Vertex AI Feature Store for different environments and manage access via IAM.
Why it's wrong here
This addresses access, not versioning or review.
- ✓
Store feature definition code in a version-controlled repository such as Cloud Source Repositories.
Why this is correct
Version control provides history and collaboration.
- ✗
Use scheduled batch jobs to synchronize feature definitions from a shared spreadsheet to Vertex AI Feature Store.
Why it's wrong here
No built-in review or version control.
Go deeper
Related to this question
About these practice questions
One of 775 original PMLE practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PMLE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PMLE exam.