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

A data science team uses SageMaker to train models. They need to track the lineage of each model, including the dataset used, training job, and hyperparameters. Which TWO SageMaker features can they use together? (Select TWO.)

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

SageMaker SDK

SageMaker ML Lineage Tracking captures the relationships between artifacts, actions, and contexts. SageMaker SDK automates lineage tracking when using the SDK for training jobs. SageMaker Experiments can also be used to track runs, but lineage tracking is specifically for provenance.

Answer analysis

Option-by-option breakdown

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

  • SageMaker SDK

    Why this is correct

    The SDK automatically creates lineage entities when used with SageMaker training jobs.

  • SageMaker Model Registry

    Why it's wrong here

    Model Registry manages model versions but not lineage.

  • SageMaker ML Lineage Tracking

    Why this is correct

    Lineage Tracking captures artifacts and actions for model provenance.

  • SageMaker Pipelines

    Why it's wrong here

    Pipelines can orchestrate but lineage is automatically captured by the SDK.

  • SageMaker Experiments

    Why it's wrong here

    Experiments track runs and parameters but do not capture lineage relationships automatically.

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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