PMLE Monitoring ML Solutions Practice Question
An ML engineer is configuring Vertex AI Model Monitoring for drift detection on a deployed endpoint. Which TWO settings directly affect the frequency and accuracy of drift detection? (Choose 2)
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
✓
Sampling rate
Sampling rate controls what fraction of predictions is analyzed; monitoring frequency controls how often the distribution comparison is performed. Both directly impact detection speed and accuracy.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Model version
Why it's wrong here
Model version does not affect drift detection settings.
- ✗
Explanation method
Why it's wrong here
Explanation method is for feature attributions, not drift detection.
- ✓
Sampling rate
Why this is correct
Determines the fraction of predictions used for analysis; a higher rate gives more data for accurate drift detection.
- ✗
Alerting threshold
Why it's wrong here
Threshold determines when an alert fires, not the frequency or accuracy of detection.
- ✓
Monitoring frequency
Why this is correct
How often the monitoring job runs to compare distributions; more frequent runs detect drift sooner.
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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.