- A
The sampling rate is too low, leading to insufficient data for reliable drift statistics.
10% sampling may result in small sample sizes, causing high variance in drift estimates.
- B
Prediction drift monitoring is not enabled; only feature drift is configured.
Why wrong: The scenario mentions drift metrics, but the issue is sample size, not missing prediction drift.
- C
The drift detection algorithm is not suited for this model; try changing from JS divergence to L-infinity distance.
Why wrong: The algorithm is not the primary cause; low sample size causes inconsistency.
- D
The monitoring frequency is too low; it should be set to every 5 minutes.
Why wrong: Hourly frequency is typical; the issue is sampling rate, not frequency.
Question 817 of 1,000
PMLE Monitoring ML Solutions Practice Question
This PMLE practice question tests your understanding of monitoring ml solutions. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
An ML engineer has set up Vertex AI Model Monitoring on an endpoint with a sampling rate of 0.1 (10%). They notice that the monitoring job runs hourly but the reported drift metrics seem inconsistent. What is the most likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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 sampling rate is too low, leading to insufficient data for reliable drift statistics.
A low sampling rate means only a small fraction of requests are logged for monitoring, which can lead to statistical noise and inconsistent drift metrics. Increasing the sampling rate would improve accuracy.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 sampling rate is too low, leading to insufficient data for reliable drift statistics.
Why this is correct
10% sampling may result in small sample sizes, causing high variance in drift estimates.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Prediction drift monitoring is not enabled; only feature drift is configured.
Why it's wrong here
The scenario mentions drift metrics, but the issue is sample size, not missing prediction drift.
- ✗
The drift detection algorithm is not suited for this model; try changing from JS divergence to L-infinity distance.
Why it's wrong here
The algorithm is not the primary cause; low sample size causes inconsistency.
- ✗
The monitoring frequency is too low; it should be set to every 5 minutes.
Why it's wrong here
Hourly frequency is typical; the issue is sampling rate, not frequency.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Trap categories for this question
Scenario analysis trap
The scenario mentions drift metrics, but the issue is sample size, not missing prediction drift.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which PMLE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this PMLE question test?
Monitoring ML Solutions — This question tests Monitoring ML Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The sampling rate is too low, leading to insufficient data for reliable drift statistics. — A low sampling rate means only a small fraction of requests are logged for monitoring, which can lead to statistical noise and inconsistent drift metrics. Increasing the sampling rate would improve accuracy.
What should I do if I get this PMLE question wrong?
Identify which PMLE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
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.
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