PMLE Monitoring ML Solutions Practice Question
An ML team has set up automated retraining triggered by Cloud Monitoring alerts. When a feature drift alert fires, a Cloud Function publishes to Pub/Sub, which triggers a Vertex AI Pipeline. However, the retraining pipeline is failing because the training data is not updated. What is the most likely cause?
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
✓
The training data in the pipeline input is stale or not refreshed
Cloud Monitoring alerts can trigger retraining, but the pipeline typically expects the most recent data. If the training data is not refreshed, the pipeline may fail or produce a stale model.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The Cloud Function does not have permission to start the pipeline
Why it's wrong here
This would cause a different error (e.g., permission denied), not a data issue.
- ✗
The Pub/Sub topic is incorrectly configured
Why it's wrong here
Pub/Sub misconfiguration would prevent the pipeline from being triggered at all.
- ✓
The training data in the pipeline input is stale or not refreshed
Why this is correct
Correct: Retraining requires fresh data; if the pipeline uses the same old data, it may fail or not address drift.
- ✗
The model endpoint is overloaded
Why it's wrong here
Endpoint overload is unrelated to retraining pipeline failures.
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Same concept, more angles
2 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 implement a retraining trigger for their ML model. They have set up Cloud Monitoring alerts that fire when drift exceeds a threshold. What should be the target of the alert to automatically start a Vertex AI Pipeline for retraining?
medium- A.Vertex AI Model Registry
- B.Cloud Storage bucket
- C.Cloud Functions HTTP trigger
- ✓ D.Pub/Sub topic
Why D: Cloud Monitoring alerts can send notifications to Pub/Sub topics. A Pub/Sub message can then trigger a Cloud Function that starts a Vertex AI Pipeline run.
Variation 2. An ML engineer needs to set up automated retraining triggered by data drift. They have decided to use Cloud Monitoring alerts to detect drift. Which TWO additional services are required to complete the retraining pipeline? (Choose 2)
medium- A.Cloud Dataflow
- B.Cloud Build
- C.Cloud Scheduler
- ✓ D.Vertex AI Pipeline
- ✓ E.Cloud Functions
Why D: The typical architecture uses Cloud Monitoring alert -> Pub/Sub -> Cloud Functions -> Vertex AI Pipeline. Cloud Functions processes the alert and triggers the pipeline. Vertex AI Pipeline orchestrates training and deployment.
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.