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PDE Practice Question: Which TWO are best practices for monitoring a…
Which TWO are best practices for monitoring a deployed machine learning model in production on Vertex AI?
⚠ Common exam trap
Many candidates confuse operational maintenance tasks (like scheduled retraining) with monitoring tasks, or they focus on infrastructure metrics (like job duration or file size) instead of data and prediction distribution monitoring, which directly impact model accuracy in production.
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
✓
Enable Vertex AI Model Monitoring to track feature drift and skew
Vertex AI Model Monitoring automatically tracks feature drift and skew by comparing the serving data distribution against the training data distribution using statistical tests like the Kolmogorov-Smirnov test. This is a best practice for detecting data quality issues that can degrade model performance in production.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set up a weekly retraining pipeline triggered by calendar schedule
Why it's wrong here
This is not monitoring; it's a fixed schedule.
- ✓
Enable Vertex AI Model Monitoring to track feature drift and skew
Why this is correct
Model Monitoring automatically detects drift.
- ✗
Monitor the training job duration to detect anomalies
Why it's wrong here
Training duration is not a production monitoring metric.
- ✓
Monitor the distribution of predictions over time to detect concept drift
Why this is correct
Monitoring predictions helps identify when the model's behavior changes.
- ✗
Monitor the model's file size to ensure it hasn't changed
Why it's wrong here
File size is not indicative of model quality.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PDE 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 PDE exam.