- A
Shadow testing
Why wrong: Shadow testing sends duplicate traffic to a shadow variant but does not serve live traffic; it's for testing without impacting users.
- B
A/B testing with traffic splitting
Why wrong: A/B testing is for comparing model performance; canary deployment is the specific pattern for gradual rollout.
- C
Canary deployment with weighted production variants
Canary deployment uses weighted variants to send a small percentage of traffic to the new model, enabling monitoring.
- D
Blue/green deployment
Why wrong: Blue/green switches all traffic at once; it does not support gradual traffic shifting.
Question 605 of 1,000
MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
This MLA-C01 practice question tests your understanding of deployment and orchestration of ml workflows. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company wants to update an existing SageMaker real-time endpoint to serve a new model version. They need to route a small percentage of traffic to the new version initially and monitor for errors before switching fully. Which deployment pattern supports 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
✓
Canary deployment with weighted production variants
Option C is correct because SageMaker real-time endpoints support canary deployments by configuring multiple production variants with weighted traffic distribution. You can assign a small weight (e.g., 5%) to the new model version variant and 95% to the existing one, then monitor CloudWatch metrics for errors before shifting all traffic to the new variant. This matches the requirement for a gradual, monitored rollout.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Shadow testing
Why it's wrong here
Shadow testing sends duplicate traffic to a shadow variant but does not serve live traffic; it's for testing without impacting users.
- ✗
A/B testing with traffic splitting
Why it's wrong here
A/B testing is for comparing model performance; canary deployment is the specific pattern for gradual rollout.
- ✓
Canary deployment with weighted production variants
Why this is correct
Canary deployment uses weighted variants to send a small percentage of traffic to the new model, enabling monitoring.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Blue/green deployment
Why it's wrong here
Blue/green switches all traffic at once; it does not support gradual traffic shifting.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between canary deployment and blue/green deployment, where candidates mistakenly choose blue/green because it sounds like a safe rollout, but it lacks the gradual traffic shifting required for monitoring a small percentage first.
Detailed technical explanation
How to think about this question
Under the hood, SageMaker uses production variants with a 'InitialVariantWeight' parameter to set traffic distribution; during a canary deployment, you update the endpoint's 'ProductionVariants' list to include the new variant with a low weight, and SageMaker's load balancer distributes requests proportionally. A subtle behavior is that you must ensure the new variant's instance type and count are sufficient to handle the small traffic slice, or latency spikes can occur. In a real-world scenario, you might start with 5% traffic to a new model version, monitor for increased error rates or latency in CloudWatch, and then gradually increase the weight to 100% using the UpdateEndpoint API.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
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Deployment and Orchestration of ML Workflows — study guide chapter
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
Deployment and Orchestration of ML Workflows — This question tests Deployment and Orchestration of ML Workflows — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Canary deployment with weighted production variants — Option C is correct because SageMaker real-time endpoints support canary deployments by configuring multiple production variants with weighted traffic distribution. You can assign a small weight (e.g., 5%) to the new model version variant and 95% to the existing one, then monitor CloudWatch metrics for errors before shifting all traffic to the new variant. This matches the requirement for a gradual, monitored rollout.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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.
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