Question 231 of 507
ML Solution Monitoring, Maintenance and SecurityhardMultiple ChoiceObjective-mapped

Quick Answer

The answer is to migrate to a SageMaker Serverless Inference endpoint. This is correct because serverless inference automatically scales to zero when there is no traffic, directly addressing the core problem of optimizing SageMaker endpoint costs with low utilization—you only pay for the compute time used during actual inference requests, eliminating the cost of idle always-on instances. On the AWS Certified Machine Learning Engineer Associate MLA-C01 exam, this scenario tests your understanding of trade-offs between real-time, serverless, and asynchronous inference modes; a common trap is choosing a multi-model endpoint (which still keeps instances running) or reducing instance count (which risks throttling under traffic spikes). The key distinction is that serverless is purpose-built for sporadic, low-utilization workloads where latency requirements are still met. Memory tip: think “serverless = server-less idle cost” for low-utilization real-time traffic.

MLA-C01 Practice Question: ML Solution Monitoring, Maintenance and Security

This MLA-C01 practice question tests your understanding of ml solution monitoring, maintenance and security. 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 deploys a machine learning model using a SageMaker endpoint with an ML.T4 instance. After a week, they notice that the endpoint's CPU utilization is consistently below 10% and latency is low. However, the endpoint is incurring high costs. Which action should the team take to reduce costs while maintaining the ability to serve traffic?

Question 1hardmultiple 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

Migrate to a SageMaker Serverless Inference endpoint

Option C is correct because a serverless inference endpoint scales to zero when not in use, reducing cost. Option A is wrong because multi-model endpoints still have always-on instances. Option B is wrong because reducing instances may cause throttling. Option D is wrong because asynchronous inference is for batch, not real-time.

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.

  • Switch to a multi-model endpoint to share instances across models

    Why it's wrong here

    Multi-model endpoints still have fixed instances; cost savings are limited.

  • Reduce the number of instances to one

    Why it's wrong here

    Reducing instances may cause high latency during traffic spikes.

  • Migrate to a SageMaker Serverless Inference endpoint

    Why this is correct

    Serverless endpoints scale to zero when idle, reducing cost.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Implement an asynchronous inference endpoint

    Why it's wrong here

    Asynchronous inference is for batch processing, not real-time.

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 MLA-C01 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 MLA-C01 question test?

ML Solution Monitoring, Maintenance and Security — This question tests ML Solution Monitoring, Maintenance and Security — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Migrate to a SageMaker Serverless Inference endpoint — Option C is correct because a serverless inference endpoint scales to zero when not in use, reducing cost. Option A is wrong because multi-model endpoints still have always-on instances. Option B is wrong because reducing instances may cause throttling. Option D is wrong because asynchronous inference is for batch, not real-time.

What should I do if I get this MLA-C01 question wrong?

Identify which MLA-C01 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 22, 2026

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This MLA-C01 practice question is part of Courseiva's free Amazon Web Services 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 MLA-C01 exam.