- A
The autoscaling is too slow to react; you should increase the max replicas to 20 and reduce the cooldown period.
Reducing cooldown and increasing max replicas helps autoscaling respond faster to bursts.
- B
The model is not optimized for parallel inference; you should enable batching in the custom container.
Why wrong: Batching helps throughput but may not address sudden spikes due to autoscaling lag.
- C
The machine type is insufficient for the model size; you should switch to a n1-highmem-8.
Why wrong: Average latency is fine; spikes are due to load, not memory.
- D
The container has a memory leak; you should restart the container periodically.
Why wrong: Memory leak would cause gradual degradation, not intermittent spikes.
Handling Traffic Bursts on Vertex AI with Autoscaling
This PMLE practice question tests your understanding of pmle exam topics. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
Your team has deployed a scikit-learn model using a custom container on Vertex AI Prediction. The model receives about 100 requests per second, and the endpoint is configured with a single n1-standard-4 machine. You notice that response times are around 200 ms on average, but occasionally spike to over 10 seconds during traffic bursts. You have set the min replicas to 1 and max replicas to 10. Despite this, spikes still occur. What is the most likely cause and the best course of action?
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.
Quick Answer
The answer is to increase max replicas to 20 and reduce the cooldown period, because the occasional 10-second latency spikes during traffic bursts indicate that Vertex AI’s autoscaling is reacting too slowly to sudden load increases. When a burst hits, the single n1-standard-4 node becomes saturated, and the autoscaler must detect the rising CPU utilization or request latency before provisioning new replicas; a long cooldown period delays this scaling action, leaving the original node overwhelmed. On the Google Professional Machine Learning Engineer exam, this scenario tests your understanding of Vertex AI Prediction’s autoscaling behavior and the trade-offs between min/max replicas, cooldown settings, and batching—a common trap is assuming that simply raising max replicas alone solves the problem, when the cooldown period is the bottleneck. Remember the mnemonic “Bursts Beat Cooldown” to recall that reducing the cooldown period is essential for handling traffic bursts effectively.
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 autoscaling is too slow to react; you should increase the max replicas to 20 and reduce the cooldown period.
Option A is correct because the occasional spikes during traffic bursts indicate that the autoscaling is not reacting quickly enough. Increasing max replicas to 20 allows more room to scale, and reducing the cooldown period makes the autoscaler add replicas faster when load increases. This addresses the immediate spikes.
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 autoscaling is too slow to react; you should increase the max replicas to 20 and reduce the cooldown period.
Why this is correct
Reducing cooldown and increasing max replicas helps autoscaling respond faster to bursts.
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 model is not optimized for parallel inference; you should enable batching in the custom container.
Why it's wrong here
Batching helps throughput but may not address sudden spikes due to autoscaling lag.
- ✗
The machine type is insufficient for the model size; you should switch to a n1-highmem-8.
Why it's wrong here
Average latency is fine; spikes are due to load, not memory.
- ✗
The container has a memory leak; you should restart the container periodically.
Why it's wrong here
Memory leak would cause gradual degradation, not intermittent spikes.
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.
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FAQ
Questions learners often ask
What does this PMLE question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: The autoscaling is too slow to react; you should increase the max replicas to 20 and reduce the cooldown period. — Option A is correct because the occasional spikes during traffic bursts indicate that the autoscaling is not reacting quickly enough. Increasing max replicas to 20 allows more room to scale, and reducing the cooldown period makes the autoscaler add replicas faster when load increases. This addresses the immediate spikes.
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: 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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