PMLE Monitoring ML Solutions Practice Question
An ML team wants to automatically retrain a model when prediction drift is detected on the deployed endpoint. They have Vertex AI Model Monitoring configured to send alerts to Cloud Monitoring. Which minimal set of additional services should they use to trigger a retraining pipeline?
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 + Cloud Functions + Vertex AI Pipeline
Cloud Monitoring alert policies can be configured to send webhook notifications directly to a Cloud Function's HTTP endpoint, triggering the function without requiring Pub/Sub. The Cloud Function then initiates a Vertex AI Pipeline to retrain the model. This is the minimal set of services needed; adding Pub/Sub (as in option D) would be unnecessary.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Cloud Monitoring + Cloud Functions + Vertex AI Pipeline
Why this is correct
Correct chain: alert -> Pub/Sub (implicitly via Cloud Functions trigger) -> Cloud Functions -> Vertex AI Pipeline.
- ✗
Cloud Monitoring + Cloud Functions + Vertex AI Endpoint
Why it's wrong here
Vertex AI Pipeline is needed for retraining, not just the endpoint.
- ✗
Cloud Logging + Cloud Scheduler + Vertex AI Training
Why it's wrong here
Logging is not needed; Scheduler is for cron jobs, not event-driven.
- ✗
Cloud Monitoring + Cloud Pub/Sub + Cloud Functions + Vertex AI Pipeline
Why it's wrong here
Technically correct but not minimal; Pub/Sub is required but the question asks for minimal set. However, the chain includes Pub/Sub implicitly. The answer choice without explicit Pub/Sub is minimal and sufficient.
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Same concept, more angles
3 more ways 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. A company wants to automatically retrain their model when data drift is detected. Which THREE components are needed to implement this pipeline?
medium- ✓ A.Cloud Function to invoke Vertex AI Pipeline
- B.Vertex AI Feature Store
- ✓ C.Cloud Monitoring alert policy for drift metric
- ✓ D.Pub/Sub topic
- E.Cloud Storage bucket for storing training data
Why A: The typical flow: Cloud Monitoring alert on drift → Pub/Sub topic → Cloud Function → Vertex AI Pipeline for training. Model Registry stores the new model after training.
Variation 2. A team is using Vertex AI Model Monitoring and wants to set up automated retraining when drift is detected. Which THREE services are needed to implement this pipeline? (Choose three.)
hard- A.Cloud Scheduler
- B.Vertex AI Model Monitoring
- ✓ C.Cloud Functions
- ✓ D.Cloud Monitoring
- ✓ E.Cloud Pub/Sub
Why C: The typical pipeline: Cloud Monitoring alert on drift → Pub/Sub message → Cloud Function or Cloud Run → triggers Vertex AI Pipeline for retraining. Optionally, Cloud Scheduler is not needed as it's event-driven.
Variation 3. An ML team wants to automatically retrain a model when data drift is detected. They have set up a Cloud Monitoring alert on drift. What service should they use to trigger a retraining pipeline in response to the alert?
easy- ✓ A.Cloud Functions
- B.Cloud Scheduler
- C.Vertex AI Feature Store
- D.Vertex AI Model Monitoring
Why A: Cloud Monitoring alerts can send notifications to Pub/Sub topics. A Pub/Sub message can then trigger a Cloud Function or Cloud Run service that starts a Vertex AI Pipeline for retraining.
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.