- A
Keep the old model version deployed alongside the new one
Why wrong: Simply having both versions does not allow rollback unless traffic can be directed; this is part of traffic splitting but not sufficient alone.
- B
Configure Vertex AI Model Monitoring to compare predictions
Why wrong: Model Monitoring detects issues but does not provide a mechanism to rollback.
- C
Use traffic splitting to gradually shift traffic
Traffic splitting allows you to direct a small percentage of traffic to the new version and easily shift all traffic back if issues arise.
- D
Set up Cloud Monitoring alerts on model performance
Why wrong: Alerts notify of problems but do not automatically rollback; they are complementary but not a rollback action.
- E
Store multiple model versions in the same endpoint
Vertex AI endpoints support multiple model versions; combined with traffic splitting, this enables seamless rollback.
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 team is deploying a new model version. They want to ensure that they can quickly roll back if the new version performs poorly in production. Which TWO actions should they take? (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
Use traffic splitting to gradually shift traffic
Option C is correct because traffic splitting allows you to gradually shift a percentage of inference requests from the old model version to the new one. If the new version performs poorly, you can immediately revert the split to 0% for the new version, providing a fast and controlled rollback without redeploying or disrupting service.
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.
- ✗
Keep the old model version deployed alongside the new one
Why it's wrong here
Simply having both versions does not allow rollback unless traffic can be directed; this is part of traffic splitting but not sufficient alone.
- ✗
Configure Vertex AI Model Monitoring to compare predictions
Why it's wrong here
Model Monitoring detects issues but does not provide a mechanism to rollback.
- ✓
Use traffic splitting to gradually shift traffic
Why this is correct
Traffic splitting allows you to direct a small percentage of traffic to the new version and easily shift all traffic back if issues arise.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Set up Cloud Monitoring alerts on model performance
Why it's wrong here
Alerts notify of problems but do not automatically rollback; they are complementary but not a rollback action.
- ✓
Store multiple model versions in the same endpoint
Why this is correct
Vertex AI endpoints support multiple model versions; combined with traffic splitting, this enables seamless rollback.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse monitoring and alerting (options B and D) with the actual deployment and rollback mechanism, assuming that detecting poor performance is equivalent to being able to quickly roll back, when in fact you need a traffic management feature like traffic splitting to execute the rollback.
Detailed technical explanation
How to think about this question
Traffic splitting in Vertex AI Endpoints works by assigning a percentage of incoming requests to each model version based on a weighted random distribution. Under the hood, the endpoint uses a load balancer that routes requests according to the configured split, and changes to the split take effect within seconds, enabling near-instantaneous rollback. In a real-world scenario, if a new model version causes a spike in 5xx errors, you can set the new version's traffic to 0% via the API or console, and all requests immediately revert to the old version without any downtime.
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.
TExam Day Tips
- 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.
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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: Use traffic splitting to gradually shift traffic — Option C is correct because traffic splitting allows you to gradually shift a percentage of inference requests from the old model version to the new one. If the new version performs poorly, you can immediately revert the split to 0% for the new version, providing a fast and controlled rollback without redeploying or disrupting service.
What should I do if I get this PMLE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 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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