MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
A data science team uses SageMaker Pipelines for automated training. They need to conditionally register a model only if evaluation metrics exceed a threshold. Which pipeline step type should they use after the evaluation 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
✓
Condition step
The Condition step evaluates a condition and branches the pipeline; if the condition is met, the pipeline proceeds to register the model.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Condition step
Why this is correct
Condition step allows branching based on a Boolean condition, such as metric threshold.
- ✗
Processing step
Why it's wrong here
Processing step runs data processing, not conditional branching.
- ✗
Transform step
Why it's wrong here
Transform step runs batch inference, not conditional logic.
- ✗
RegisterModel step
Why it's wrong here
RegisterModel registers the model but does not include conditional logic.
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