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MLA-C01 Practice Question: An MLOps engineer is building an automated…

An MLOps engineer is building an automated retraining pipeline for a fraud detection model. The model must be retrained weekly, and the new model should only be promoted to production if it meets predefined performance thresholds compared to the current model. Which combination of SageMaker capabilities should the engineer use?

⚠ Common exam trap

AWS often tests the distinction between monitoring tools (Model Monitor, Debugger) and orchestration/registry services (Pipelines, Model Registry), so the trap here is that candidates may confuse Model Monitor's drift detection with the need for a retraining pipeline, overlooking that the question specifically requires automated retraining and conditional promotion.

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 and Amazon SageMaker Model Registry

Amazon SageMaker Pipelines provides the orchestration for the automated retraining workflow (including weekly scheduling and conditional logic), while SageMaker Model Registry enables versioning, approval, and promotion of models based on performance thresholds. Together, they allow the engineer to define a pipeline that trains a new model, evaluates it against the current production model, and only registers it for deployment if it meets the predefined criteria.

Answer analysis

Option-by-option breakdown

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

  • Amazon SageMaker Debugger and Amazon SageMaker Clarify

    Why it's wrong here

    Debugger for training issues, Clarify for bias.

  • Amazon SageMaker Model Monitor and Amazon SageMaker Ground Truth

    Why it's wrong here

    Model Monitor for data quality, Ground Truth for labeling, not for conditional promotion.

  • Amazon SageMaker Autopilot and Amazon SageMaker Experiments

    Why it's wrong here

    Autopilot automates model building, Experiments for tracking.

  • Amazon SageMaker Pipelines and Amazon SageMaker Model Registry

    Why this is correct

    Pipelines orchestrate the workflow, Model Registry manages model versions and approvals.

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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.