- A
The model server is crashing under load due to memory issues.
Why wrong: If it were crashing, users would see errors, not just latency spikes.
- B
Autoscaling based on CPU utilization does not react quickly to inference request spikes.
CPU utilization may lag behind request surges; Vertex AI recommends using target utilization or custom metrics for faster response.
- C
The load balancer is misconfigured and routes traffic unevenly.
Why wrong: Vertex AI endpoints include a built-in load balancer that distributes requests evenly.
- D
The container image is not optimized for the model.
Why wrong: Container optimization affects raw performance but not sudden latency spikes during scaling.
PMLE Serving and scaling models Practice Question
This PMLE practice question tests your understanding of serving and scaling models. 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 deploys a model on Vertex AI Prediction for real-time inference. Users report intermittent high latency during peak hours. The model is deployed on a single machine type with `min_replica_count=1` and `max_replica_count=5`. Autoscaling is enabled based on CPU utilization. What is the most likely cause of the latency spikes?
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
Autoscaling based on CPU utilization does not react quickly to inference request spikes.
Option B is correct because CPU utilization may not be a good proxy for inference load; the system may not scale up fast enough under sudden traffic bursts. Option A is wrong because Vertex AI automatically manages container health. Option C is wrong because Vertex AI endpoints automatically distribute traffic. Option D is wrong because the container image is built correctly.
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 model server is crashing under load due to memory issues.
Why it's wrong here
If it were crashing, users would see errors, not just latency spikes.
- ✓
Autoscaling based on CPU utilization does not react quickly to inference request spikes.
Why this is correct
CPU utilization may lag behind request surges; Vertex AI recommends using target utilization or custom metrics for faster response.
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.
- ✗
The load balancer is misconfigured and routes traffic unevenly.
Why it's wrong here
Vertex AI endpoints include a built-in load balancer that distributes requests evenly.
- ✗
The container image is not optimized for the model.
Why it's wrong here
Container optimization affects raw performance but not sudden latency spikes during scaling.
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.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
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.
- →
Serving and scaling models — study guide chapter
Learn the concepts, then practise the questions
- →
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FAQ
Questions learners often ask
What does this PMLE question test?
Serving and scaling models — This question tests Serving and scaling models — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Autoscaling based on CPU utilization does not react quickly to inference request spikes. — Option B is correct because CPU utilization may not be a good proxy for inference load; the system may not scale up fast enough under sudden traffic bursts. Option A is wrong because Vertex AI automatically manages container health. Option C is wrong because Vertex AI endpoints automatically distribute traffic. Option D is wrong because the container image is built correctly.
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
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 →
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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