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MLA-C01 Practice Question: A company uses SageMaker Pipelines for model…
A company uses SageMaker Pipelines for model training and wants to incorporate model evaluation before deployment into production. Which THREE components are essential? (Choose three.)
⚠ Common exam trap
It's easy for candidates to confuse batch transform (used for inference) with model evaluation (which requires a Processing step to compute metrics), and they overlook that a condition step is the core decision-making component, not a human review step.
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
✓
A model registry approval step
A model registry approval step is essential because it gates the deployment of a model based on its evaluation results. In SageMaker Pipelines, you register the model to the Model Registry after training, and the approval status (e.g., Approved or Rejected) determines whether downstream deployment steps execute. This ensures only models meeting quality thresholds are promoted to production.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
A model registry approval step
Why this is correct
Approval step creates a model version with approval status to gate deployment.
- ✗
A batch transform step for evaluation
Why it's wrong here
Batch transform can evaluate but is less typical; processing step is more common.
- ✓
A condition step in the pipeline
Why this is correct
Condition step compares evaluation metrics against thresholds to decide approval.
- ✗
A human review step
Why it's wrong here
Human review is optional, not essential for automated evaluation.
- ✓
A SageMaker Processing step for evaluation
Why this is correct
Processing step runs custom evaluation scripts on test data.
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