PMLE Monitoring ML Solutions Practice Question
An ML team is using Population Stability Index (PSI) to monitor feature drift on a Vertex AI Endpoint. The PSI value for a feature is 0.25, which exceeds the alert threshold of 0.2. The feature has high SHAP importance. The team wants to automatically retrain the model. What is the correct end-to-end setup?
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
✓
Cloud Monitoring alert → Pub/Sub → Cloud Functions → Vertex AI Pipeline (with training and deployment steps)
The correct setup involves Cloud Monitoring alert (based on PSI metric) → Pub/Sub → Cloud Function → Vertex AI Pipeline to trigger retraining with updated 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.
- ✗
Vertex AI Model Monitoring alert → Cloud Scheduler → Vertex AI Training
Why it's wrong here
Model Monitoring does not generate alerts directly; Cloud Monitoring does. Also, Cloud Scheduler is for cron jobs, not event-driven.
- ✗
Cloud Functions → Pub/Sub → Cloud Monitoring → Vertex AI Pipeline
Why it's wrong here
The order is reversed; Cloud Monitoring triggers Pub/Sub, not the other way around.
- ✓
Cloud Monitoring alert → Pub/Sub → Cloud Functions → Vertex AI Pipeline (with training and deployment steps)
Why this is correct
Correct: This is the recommended architecture for automated retraining.
- ✗
Cloud Monitoring alert → Cloud Logging → Cloud Functions → Vertex AI Training
Why it's wrong here
Cloud Logging is not a direct trigger; Pub/Sub is used for decoupling.
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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.