PMLE Monitoring ML Solutions Practice Question
A team wants to monitor prediction drift on a Vertex AI Endpoint for a classification model. They have configured Vertex AI Model Monitoring with default settings. Which metric will be used to detect prediction drift?
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
✓
Jensen-Shannon divergence
Vertex AI Model Monitoring uses Jensen-Shannon divergence as the default algorithm for prediction drift detection. It compares the distribution of predicted classes over time against a reference distribution (e.g., training predictions).
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Kullback-Leibler divergence
Why it's wrong here
Not directly used; JS divergence is a symmetric version of KL divergence.
- ✗
L-infinity distance
Why it's wrong here
Not a supported drift metric in Vertex AI Model Monitoring.
- ✗
Population Stability Index (PSI)
Why it's wrong here
PSI is also supported but not the default for prediction drift; JS divergence is default.
- ✓
Jensen-Shannon divergence
Why this is correct
Default algorithm for prediction drift.
Go deeper
Related to this question
About these practice questions
Courseiva writes every PMLE question from scratch — 990 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more way this is tested on PMLE
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Which algorithm does Vertex AI Model Monitoring use by default to detect feature drift in a categorical feature?
easy- A.Population Stability Index (PSI)
- B.Wasserstein distance
- ✓ C.Jensen-Shannon divergence
- D.Kullback-Leibler divergence
Why C: Vertex AI Model Monitoring uses Jensen-Shannon divergence (JS divergence) as the default metric for drift detection on categorical features.
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.