Question 361 of 506
Serving and scaling modelsmediumMultiple ChoiceObjective-mapped

Quick Answer

The correct choice is to enable basic autoscaling with a target CPU utilization of 0.6, setting a minimum of 2 replicas and a maximum of 10. This configuration works because basic autoscaling on Vertex AI Prediction dynamically adjusts the number of replicas based on the specified target metric—here, CPU utilization—so the endpoint scales up during traffic spikes and scales down when load decreases, directly minimizing cost during normal traffic while handling promotional events. On the Google Professional Machine Learning Engineer exam, this scenario tests your understanding of the trade-off between cost and performance for online predictions; a common trap is selecting manual scaling or no scaling, which cannot adapt to variable load, or overcomplicating with custom metrics when basic CPU-based scaling is sufficient for CPU-bound models. Remember the memory tip: “60% CPU is the sweet spot—scale up to ten, down to two, and let the load decide.”

PMLE Serving and scaling models Practice Question

This PMLE practice question tests your understanding of serving and scaling models. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 Endpoint and expects high traffic spikes during promotional events. The current configuration uses manual scaling with 2 replicas. Which autoscaling configuration should they use to handle spikes while minimizing cost during normal traffic?

Question 1mediummultiple choice
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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

Enable basic scaling with target_cpu_utilization=0.6 and set min_replica_count=2, max_replica_count=10.

Option B is correct because basic scaling with a target metric (e.g., CPU utilization) automatically adjusts replicas based on load, reducing cost during low traffic and scaling up during spikes. Option A is wrong because no scaling cannot adapt. Option C is wrong because manual scaling requires constant adjustments. Option D is wrong because custom metric scaling is possible but basic scaling is simpler and sufficient for CPU-bound models.

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 manual scaling but increase replicas to 10.

    Why it's wrong here

    Manual scaling wastes resources during low traffic.

  • Set min_replica_count=2 and max_replica_count=10 with no scaling metric.

    Why it's wrong here

    Without a scaling metric, replicas stay at min, failing to handle spikes.

  • Enable basic scaling with target_cpu_utilization=0.6 and set min_replica_count=2, max_replica_count=10.

    Why this is correct

    Basic scaling adjusts replicas based on CPU load.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Use custom metric scaling with a Cloud Monitoring metric for prediction latency.

    Why it's wrong here

    Custom metric scaling is possible but not necessary; basic scaling works.

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

A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.

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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Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.

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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: Enable basic scaling with target_cpu_utilization=0.6 and set min_replica_count=2, max_replica_count=10. — Option B is correct because basic scaling with a target metric (e.g., CPU utilization) automatically adjusts replicas based on load, reducing cost during low traffic and scaling up during spikes. Option A is wrong because no scaling cannot adapt. Option C is wrong because manual scaling requires constant adjustments. Option D is wrong because custom metric scaling is possible but basic scaling is simpler and sufficient for CPU-bound models.

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.

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Last reviewed: Jun 24, 2026

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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.