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MLA-C01 Practice Question: Automate the deployment of a SageMaker model into…

A company wants to automate the deployment of a SageMaker model into production whenever a new model version is approved in the Model Registry. Which service can be used to trigger the deployment pipeline?

⚠ Common exam trap

A common mix-up: candidates confuse the event source (SageMaker Model Registry) with the trigger mechanism (EventBridge), mistakenly selecting Lambda or SNS as the trigger service instead of recognizing EventBridge as the event bus that detects and routes the approval event.

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

Amazon CloudWatch Events (EventBridge)

Amazon EventBridge (formerly CloudWatch Events) can detect state changes in SageMaker Model Registry, such as when a model version is approved. It can then trigger a target like AWS CodePipeline or a Lambda function to automate the deployment pipeline, making it the correct choice for event-driven automation of model deployment.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • AWS Lambda

    Why it's wrong here

    Lambda can be triggered but EventBridge is the service that routes events to targets.

  • Amazon CloudWatch Events (EventBridge)

    Why this is correct

    Correct. EventBridge can capture Model Registry events and trigger downstream actions like CodePipeline.

  • Amazon S3 Events

    Why it's wrong here

    S3 events are triggered by S3 actions, not Model Registry changes.

  • Amazon SNS

    Why it's wrong here

    SNS is a notification service; it can be a target but is not the primary trigger service.

  • AWS Config

    Why it's wrong here

    AWS Config evaluates resource compliance, not event-driven triggers.

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

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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.