PMLE Monitoring ML Solutions Practice Question
A data scientist has deployed a classification model on a Vertex AI Endpoint and wants to monitor for feature drift in the serving data compared to the training data. Which Vertex AI service should be used?
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
✓
Vertex AI Model Monitoring
Vertex AI Model Monitoring is specifically designed to monitor deployed models for feature skew, feature drift, and prediction drift. It supports algorithms like Jensen-Shannon divergence and Population Stability Index.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Vertex AI Explainable AI
Why it's wrong here
Used for model explanations, not drift monitoring.
- ✗
Vertex AI Model Evaluation
Why it's wrong here
Used for evaluating model performance on datasets, not real-time monitoring.
- ✗
Vertex AI Continuous Training
Why it's wrong here
Involves retraining pipelines, not monitoring drift.
- ✓
Vertex AI Model Monitoring
Why this is correct
Correct service for monitoring feature drift and skew.
Go deeper
Related to this question
About these practice questions
One of 990 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.