MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
A machine learning engineer deploys a new model version to a SageMaker endpoint with production variants. They want to gradually shift traffic from the old model to the new model, monitoring for errors, and automatically roll back if the error rate exceeds 5%. Which deployment pattern 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
✓
Canary deployment with CloudWatch alarms
Canary deployments gradually shift traffic and allow automated rollback based on CloudWatch alarms. Blue/green switches all at once. A/B testing is for comparing variants. Shadow testing mirrors traffic but doesn't serve the new model to users.
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