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ML Solution Monitoring, Maintenance, and SecuritymediumMultiple SelectObjective-mapped

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

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)

⚠ Common exam trap

Candidates often confuse enabling detailed monitoring (which only increases metric frequency) with automated remediation, or they mistakenly think manual scaling counts as automated remediation.

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

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.

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.

  • 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.

  • 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.

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

About these practice questions

Courseiva writes every MLA-C01 question from scratch — 835 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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.