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MLA-C01 Practice Question: A company uses SageMaker to orchestrate a…
A company uses SageMaker to orchestrate a training pipeline with multiple steps including preprocessing, training, and evaluation. They want to ensure that each step can be reused and tracked. Which three SageMaker features support this? (Select THREE.)
⚠ Common exam trap
A common mix-up: candidates confuse SageMaker Clarify and Model Monitor as pipeline orchestration tools, when they are actually separate services for model governance and production monitoring, not for step reuse and tracking.
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 Pipelines
SageMaker Pipelines is correct because it provides a directed acyclic graph (DAG) of steps that can be defined, parameterized, and reused across different runs. Each step (preprocessing, training, evaluation) is a distinct, versioned component that can be independently tracked and re-executed, enabling modular orchestration of ML workflows.
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 Pipelines
Why this is correct
Pipelines orchestrate multiple steps and support reuse.
- ✓
SageMaker Experiments
Why this is correct
Experiments track and compare training runs and outputs.
- ✓
SageMaker Processing Jobs
Why this is correct
Processing Jobs can be reused for data processing steps.
- ✗
SageMaker Clarify
Why it's wrong here
Clarify is for bias detection and explainability.
- ✗
SageMaker Model Monitor
Why it's wrong here
Model Monitor is for inference monitoring, not for step reuse.
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