MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
A company wants to test a new ML model in production with minimal risk before shifting full traffic. They have an existing real-time endpoint serving model version A. They need to route 5% of live traffic to model version B and monitor performance for 24 hours. Which TWO steps should they take? (Choose TWO.)
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
✓
Configure a CloudWatch alarm to roll back if error rate exceeds a threshold
Blue/green deployment creates a new endpoint with the new model and swaps all traffic at once, not a gradual shift. Canary deployment routes a small percentage of traffic to the new version for testing. SageMaker supports canary deployments by updating the endpoint with multiple production variants and specifying initial traffic weights. The existing endpoint should be updated to include both 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.
- ✗
Deploy model B using SageMaker batch transform and compare offline metrics
Why it's wrong here
Batch transform is offline and cannot simulate live traffic conditions; the requirement is to test in production with live traffic.
- ✓
Configure a CloudWatch alarm to roll back if error rate exceeds a threshold
Why this is correct
CloudWatch alarms can be set on endpoint metrics (e.g., error rate, latency) to trigger automatic rollback or alert the team.
- ✗
Use SageMaker's blue/green deployment and shift 5% traffic initially
Why it's wrong here
Blue/green deployment creates a new endpoint and shifts all traffic at once; it does not support gradual traffic splitting.
- ✗
Create a new endpoint with model B and use Amazon Route 53 to split 5% of traffic
Why it's wrong here
Route 53 splits traffic at the DNS level, not at the application level, and is not the recommended approach for SageMaker A/B testing.
- ✓
Update the existing endpoint to include two production variants: variant A with 95% traffic and variant B with 5% traffic
Why this is correct
SageMaker endpoints support multiple production variants with traffic weights, enabling canary testing.
Go deeper
Related to this question
About these practice questions
Courseiva writes every MLA-C01 question from scratch — 835 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
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.