- A
Use Cloud Monitoring to create a custom dashboard with a confusion matrix chart
Why wrong: Cloud Monitoring does not compute confusion matrices from prediction data directly.
- B
Export predictions to Cloud Storage and run a Dataflow job to compute confusion matrices
Why wrong: While possible, Vertex AI Model Monitoring provides this functionality natively, making it the simplest approach.
- C
Upload ground truth data to BigQuery and use Vertex AI Model Monitoring's model quality monitoring
Model quality monitoring in Vertex AI Model Monitoring uses ground truth from BigQuery to generate confusion matrices.
- D
Enable Vertex AI Explainable AI and configure it to output confusion matrices
Why wrong: Explainable AI does not compute confusion matrices.
Question 329 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.
A company has a model serving predictions on Vertex AI Endpoints and wants to monitor for prediction drift. They enable Vertex AI Model Monitoring but also need to see a confusion matrix over time. How should they set up the confusion matrix monitoring?
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
✓
Upload ground truth data to BigQuery and use Vertex AI Model Monitoring's model quality monitoring
Vertex AI Model Monitoring can compute confusion matrices when ground truth labels are provided in BigQuery. The service compares predictions against actuals and can output confusion matrices over time windows.
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.
- ✗
Use Cloud Monitoring to create a custom dashboard with a confusion matrix chart
Why it's wrong here
Cloud Monitoring does not compute confusion matrices from prediction data directly.
- ✗
Export predictions to Cloud Storage and run a Dataflow job to compute confusion matrices
Why it's wrong here
While possible, Vertex AI Model Monitoring provides this functionality natively, making it the simplest approach.
- ✓
Upload ground truth data to BigQuery and use Vertex AI Model Monitoring's model quality monitoring
Why this is correct
Model quality monitoring in Vertex AI Model Monitoring uses ground truth from BigQuery to generate confusion matrices.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Enable Vertex AI Explainable AI and configure it to output confusion matrices
Why it's wrong here
Explainable AI does not compute confusion matrices.
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
Similar concept trap
Cloud Monitoring does not compute confusion matrices from prediction data directly.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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: Upload ground truth data to BigQuery and use Vertex AI Model Monitoring's model quality monitoring — Vertex AI Model Monitoring can compute confusion matrices when ground truth labels are provided in BigQuery. The service compares predictions against actuals and can output confusion matrices over time windows.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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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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