hardMultiple SelectObjective-mapped
PMLE Practice Question: A company has a prototype ML model that predicts…
A company has a prototype ML model that predicts equipment failure. They want to deploy it to production using Vertex AI. The model must be retrained weekly with new data. They also need to monitor for data drift and model performance. Which THREE components should they include in their MLOps pipeline? (Choose 3)
⚠ Common exam trap
Google Cloud often tests the distinction between necessary manual oversight and fully automated MLOps practices, leading candidates to overestimate the need for human approval steps in a production pipeline that demands speed and scalability.
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
✓
A scheduled training pipeline that retrains the model weekly.
The requirement specifies weekly retraining, which is best implemented as a scheduled training pipeline in Vertex AI using Cloud Scheduler or a recurring AI Platform Pipeline run. This automates the retraining process without manual intervention, ensuring the model stays current with new data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
A scheduled training pipeline that retrains the model weekly.
Why this is correct
Scheduled retraining is essential for keeping the model up-to-date.
- ✗
A manual QA step where data scientists approve each deployment.
Why it's wrong here
Manual steps reduce automation and slow down the pipeline.
- ✗
A manual review of new data before it is used for training.
Why it's wrong here
Manual review is not scalable and introduces delays.
- ✓
An automated trigger that redeploys the model when performance drops below a threshold.
Why this is correct
Automated redeployment based on performance ensures quick recovery.
- ✓
A monitoring system that checks for data drift and triggers alerts.
Why this is correct
Monitoring is critical for detecting when the model degrades.
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Written by Johnson Ajibi, MSc IT Security
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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.