MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
A data scientist wants to compare the performance of two model versions (V1 and V2) in production by splitting traffic between them. They want to gradually increase the percentage of traffic to the new version while monitoring metrics. Which SageMaker feature enables this?
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 production variants with traffic splitting
Production variants with traffic splitting allow routing a percentage of inference requests to different model versions. By updating the initial variant weights, the data scientist can gradually shift traffic from V1 to V2. Shadow testing mirrors traffic but does not affect real responses. Blue/green is a deployment pattern but not a SageMaker feature for gradual traffic splitting. Canary deployments are a pattern but SageMaker implements it via production variants.
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 production variants with traffic splitting
Why this is correct
Production variants allow splitting traffic between model versions for A/B testing and gradual rollout.
- ✗
SageMaker shadow testing
Why it's wrong here
Shadow testing sends duplicate traffic to a shadow variant but does not serve real responses from it.
- ✗
SageMaker blue/green deployment
Why it's wrong here
Blue/green is a deployment strategy, but SageMaker uses production variants to implement it; the feature itself is production variants.
- ✗
SageMaker canary deployment
Why it's wrong here
Canary deployment is a pattern; SageMaker implements it via production variants with traffic splitting.
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