Question 459 of 1,000
ML Solution Monitoring, Maintenance, and SecuritymediumMultiple SelectObjective-mapped

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 machine learning team notices an increase in 5XXError count for a SageMaker endpoint. They want to set up automated remediation. Which THREE actions should they take? (Select THREE)

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

Add an SNS topic as the alarm action

Option A is correct because adding an SNS topic as the alarm action enables automated notifications when the CloudWatch Alarm triggers on the 5XXError metric. This allows the team to receive alerts and trigger downstream remediation workflows, such as invoking a Lambda function, without manual intervention.

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.

  • Add an SNS topic as the alarm action

    Why this is correct

    SNS sends notifications to subscribers or triggers automation.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Increase the endpoint instance count manually

    Why it's wrong here

    Manual intervention is not automated remediation.

  • Create a CloudWatch Alarm on the 5XXError metric

    Why this is correct

    The alarm triggers when error count exceeds threshold.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Enable detailed monitoring on the endpoint

    Why it's wrong here

    Detailed monitoring provides more metrics but not remediation.

  • Configure a Lambda function to restart the endpoint or scale out

    Why this is correct

    Lambda can perform remediation steps like scaling or restarting.

    Related concept

    Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse enabling detailed monitoring (which only increases metric frequency) with automated remediation, or they mistakenly think manual scaling counts as automated remediation.

Detailed technical explanation

How to think about this question

SageMaker endpoints emit the 5XXError metric to CloudWatch, which counts HTTP 5XX responses from the model container. When creating a CloudWatch Alarm on this metric, you can configure an SNS topic as the alarm action, which can then invoke a Lambda function via an SNS subscription. The Lambda function can programmatically call the UpdateEndpointWeightsAndCapacities or UpdateEndpoint API to scale out the endpoint or restart the model container, providing automated remediation without manual steps.

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.

TExam Day Tips

  • 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.

Quick reference

Cloud Service Model Comparison

ModelYou ManageProvider ManagesExamples
IaaSOS, runtime, apps, dataHardware, hypervisor, networkingEC2, Azure VMs, GCP Compute Engine
PaaSApps and dataOS, runtime, middleware, hardwareElastic Beanstalk, Azure App Service
SaaSData and settings onlyEverything elseMicrosoft 365, Salesforce, Workday
FaaS / ServerlessFunction code onlyInfra, scaling, runtimeLambda, Azure Functions, Cloud Run
CaaSContainers and appsKubernetes, OS, hardwareEKS, AKS, GKE

What to study next

Got this wrong? Here's your next step.

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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: Add an SNS topic as the alarm action — Option A is correct because adding an SNS topic as the alarm action enables automated notifications when the CloudWatch Alarm triggers on the 5XXError metric. This allows the team to receive alerts and trigger downstream remediation workflows, such as invoking a Lambda function, without manual intervention.

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

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jul 4, 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.