- A
Use AWS Cloud Map to register the new variant and perform a slow rollout.
Why wrong: AWS Cloud Map is for service discovery, not for traffic shifting or rollback control.
- B
Deploy variant B as a separate endpoint and use Route 53 weighted routing to shift traffic.
Why wrong: Route 53 cannot shift traffic based on error rates; it only distributes DNS requests. Also, managing two endpoints increases complexity.
- C
Use the SageMaker UpdateEndpoint API with a linear traffic shift from variant A to variant B over 10 minutes, and configure a CloudWatch alarm on the new variant's error rate that triggers a Lambda function to revert the traffic weights.
This approach automates both the gradual shift and the rollback based on error rates.
- D
Use AWS CodeDeploy with a deployment group to shift traffic and automatically roll back if CloudWatch alarms trigger.
Why wrong: AWS CodeDeploy does not natively support SageMaker endpoints; it is for EC2, Lambda, ECS.
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 uses SageMaker endpoint with production variants for canary deployments. The team wants to gradually shift traffic from the old model variant (variant A) to the new model variant (variant B) over a period of 10 minutes. After the shift, if the new variant's error rate increases by more than 5%, they want to roll back automatically. Which solution meets these requirements with minimal manual intervention?
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
Use the SageMaker UpdateEndpoint API with a linear traffic shift from variant A to variant B over 10 minutes, and configure a CloudWatch alarm on the new variant's error rate that triggers a Lambda function to revert the traffic weights.
Option C is correct because the SageMaker UpdateEndpoint API supports a linear traffic shift between production variants, allowing you to gradually route traffic from variant A to variant B over a specified time period (here, 10 minutes). By attaching a CloudWatch alarm on the new variant's error rate that triggers a Lambda function to revert the traffic weights, you achieve automatic rollback with minimal manual intervention when the error rate exceeds the 5% threshold.
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.
- ✗
Use AWS Cloud Map to register the new variant and perform a slow rollout.
Why it's wrong here
AWS Cloud Map is for service discovery, not for traffic shifting or rollback control.
- ✗
Deploy variant B as a separate endpoint and use Route 53 weighted routing to shift traffic.
Why it's wrong here
Route 53 cannot shift traffic based on error rates; it only distributes DNS requests. Also, managing two endpoints increases complexity.
- ✓
Use the SageMaker UpdateEndpoint API with a linear traffic shift from variant A to variant B over 10 minutes, and configure a CloudWatch alarm on the new variant's error rate that triggers a Lambda function to revert the traffic weights.
Why this is correct
This approach automates both the gradual shift and the rollback based on error rates.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use AWS CodeDeploy with a deployment group to shift traffic and automatically roll back if CloudWatch alarms trigger.
Why it's wrong here
AWS CodeDeploy does not natively support SageMaker endpoints; it is for EC2, Lambda, ECS.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume AWS CodeDeploy (Option D) can manage SageMaker endpoints because it supports canary deployments for other services, but SageMaker has its own native traffic shifting and rollback mechanisms that are not integrated with CodeDeploy.
Detailed technical explanation
How to think about this question
The SageMaker UpdateEndpoint API with a linear traffic shift uses the 'BlueGreenUpdatePolicy' or 'CanaryUpdatePolicy' to gradually adjust the 'VariantWeight' of each production variant over a specified 'WaitIntervalInSeconds'. Under the hood, SageMaker orchestrates the traffic routing at the load balancer level, ensuring zero downtime during the shift. A real-world scenario where this matters is when a model update introduces subtle regressions that only manifest under production load, making a gradual shift with automated rollback critical for maintaining service reliability.
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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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: Use the SageMaker UpdateEndpoint API with a linear traffic shift from variant A to variant B over 10 minutes, and configure a CloudWatch alarm on the new variant's error rate that triggers a Lambda function to revert the traffic weights. — Option C is correct because the SageMaker UpdateEndpoint API supports a linear traffic shift between production variants, allowing you to gradually route traffic from variant A to variant B over a specified time period (here, 10 minutes). By attaching a CloudWatch alarm on the new variant's error rate that triggers a Lambda function to revert the traffic weights, you achieve automatic rollback with minimal manual intervention when the error rate exceeds the 5% threshold.
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: Jun 24, 2026
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