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MLA-C01 Practice Question: Automate its machine learning pipeline using AWS…

A company wants to automate its machine learning pipeline using AWS CodePipeline and Amazon SageMaker. The pipeline should train a model, evaluate it, and if the evaluation passes, register the model in the SageMaker Model Registry. Which service should the company use to orchestrate the training and evaluation steps?

⚠ Common exam trap

Many exam-takers confuse AWS Step Functions (a general-purpose orchestrator) with SageMaker Pipelines (a specialized ML orchestrator), overlooking that SageMaker Pipelines provides built-in SageMaker step types and native Model Registry integration, which Step Functions lacks without custom Lambda functions.

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 SageMaker Pipelines

Amazon SageMaker Pipelines is the correct choice because it is a purpose-built, fully managed service for creating end-to-end machine learning workflows directly within the SageMaker ecosystem. It natively integrates with SageMaker training jobs, processing jobs for evaluation, and the Model Registry for conditional registration, allowing the entire pipeline—train, evaluate, and conditionally register—to be defined as a directed acyclic graph (DAG) of steps without needing to stitch together separate services.

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 CodePipeline

    Why it's wrong here

    CodePipeline is for CI/CD, not for orchestrating training steps.

  • AWS Glue Workflows

    Why it's wrong here

    Glue workflows are for ETL, not ML training.

  • AWS Step Functions

    Why it's wrong here

    Step Functions can orchestrate but requires extra configuration compared to Pipelines.

  • Amazon SageMaker Pipelines

    Why this is correct

    SageMaker Pipelines natively supports ML steps like training, evaluation, and model registration.

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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.