Question 439 of 506
Serving and scaling modelsmediumMultiple ChoiceObjective-mapped

Quick Answer

The answer is that the autoscaling metric is not configured because the endpoint is set to manual scaling. When manual scaling is selected on Vertex AI endpoints, the system will not automatically add or remove compute instances regardless of traffic load, which directly explains why the endpoint fails to scale up during spikes despite low CPU utilization. This question tests your understanding of the fundamental difference between manual vs automatic scaling on Vertex AI, a critical concept for the Google Professional Machine Learning Engineer exam where configuration details are often hidden in plain sight. A common trap is assuming that low CPU utilization means scaling is working correctly, but with manual scaling, the endpoint simply ignores load metrics entirely. Remember: manual scaling means you are the autoscaler—if you see “strategy: manual” in a configuration, no amount of traffic will trigger instance growth.

PMLE Serving and scaling models Practice Question

This PMLE practice question tests your understanding of serving and scaling models. 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.

Exhibit

deployments:
- model: projects/my-project/locations/us-central1/models/123
  displayName: model_v1
  trafficPercentage: 100
  minReplicaCount: 2
  maxReplicaCount: 10
  machineType: n1-standard-4
  acceleratorType: NVIDIA_TESLA_T4
  acceleratorCount: 1
  strategy: manual

Refer to the exhibit. A team deploys a model with the above configuration. They observe that during traffic spikes, the endpoint does not scale up quickly enough, causing increased latency. The average CPU utilization never exceeds 50%. What is the most likely reason for the slow scaling?

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.

  • Clue: "never"

    Why it matters: Absolute qualifier. True only if the statement has zero exceptions — be cautious of options that seem obvious but break down in edge cases.

Question 1mediummultiple choice
Full question →

Exhibit

deployments:
- model: projects/my-project/locations/us-central1/models/123
  displayName: model_v1
  trafficPercentage: 100
  minReplicaCount: 2
  maxReplicaCount: 10
  machineType: n1-standard-4
  acceleratorType: NVIDIA_TESLA_T4
  acceleratorCount: 1
  strategy: manual

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 metric is not configured

Option C is correct. The configuration shows strategy: manual, meaning autoscaling is disabled. Without autoscaling, the endpoint does not add instances in response to load. Option A increases min replicas but still manual. Option B changes machine type but scaling remains manual. Option D is irrelevant because CPU utilization is low.

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 metric is not configured

    Why this is correct

    The strategy is 'manual', so autoscaling is not configured; changing to 'autoscaling' with a target metric would resolve the issue.

    Clue confirmation

    The clue words "most likely", "never" in the question point toward this answer.

    Related concept

    Read the scenario before looking for a memorised answer.

  • The minReplicaCount is too low

    Why it's wrong here

    Increasing min replicas would only set a floor, not enable dynamic scaling.

  • The accelerator is causing a bottleneck

    Why it's wrong here

    Accelerator would affect compute, not scaling logic.

  • The machineType does not have enough CPU

    Why it's wrong here

    CPU utilization is below 50%, so CPU is not the bottleneck.

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.

Related practice questions

Related PMLE practice-question pages

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: The autoscaling metric is not configured — Option C is correct. The configuration shows strategy: manual, meaning autoscaling is disabled. Without autoscaling, the endpoint does not add instances in response to load. Option A increases min replicas but still manual. Option B changes machine type but scaling remains manual. Option D is irrelevant because CPU utilization is low.

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", "never". 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.

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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.