MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
A team uses SageMaker real-time endpoints for inference. They want to deploy a new model version and compare its performance with the current version under live traffic without affecting user experience. Which method should they use?
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
✓
Shadow testing with SageMaker
Shadow testing (or shadow deployment) sends a copy of live traffic to the new model variant while the current variant serves the actual response. The shadow variant's performance can be monitored without impacting the user.
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/B testing with production variant traffic splitting
Why it's wrong here
A/B testing splits traffic between variants, impacting user experience if the new model is poor; shadow testing keeps the user unaffected.
- ✗
Batch transform on a holdout test set
Why it's wrong here
Batch transform uses offline data, not live traffic, and does not compare under real conditions.
- ✗
Blue/green deployment
Why it's wrong here
Blue/green switches all traffic at once, not suitable for comparing under live traffic.
- ✓
Shadow testing with SageMaker
Why this is correct
Shadow testing duplicates traffic to a shadow variant without serving it to users, allowing safe comparison.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLA-C01 exam.