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Machine Learning Implementation and Operations →hardMultiple SelectObjective-mapped

Minimizing Downtime with Canary and Blue/Green Deployments

This MLS-C01 practice question tests your understanding of machine learning implementation and operations. 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 is deploying a machine learning model on Amazon SageMaker. The model needs to be updated frequently with new versions. The team wants to minimize downtime and test the new model version before routing all traffic to it. Which TWO strategies should be used together?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

A
Use a rolling update strategy.
Why wrong: Rolling updates are not natively supported by SageMaker endpoints.
B
Use a multi-model endpoint.
Why wrong: Multi-model endpoints host multiple models but do not provide deployment strategies.
C
Use Amazon SageMaker A/B testing.
Why wrong: A/B testing is for comparing model versions, not specifically for traffic shifting with canary.
D
Use Amazon SageMaker canary deployment.
Canary deployment sends a small percentage of traffic to the new version.
E
Use Amazon SageMaker blue/green deployment.
Blue/green deploys a new endpoint and shifts traffic after validation.

Full breakdown with real-world context →

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 Amazon SageMaker canary deployment.

The correct answers are D (canary deployment) and E (blue/green deployment). In Amazon SageMaker, blue/green deployment allows you to deploy a new model version alongside the existing one (blue) and then shift traffic gradually. Canary deployment is a feature of SageMaker that routes a small percentage of traffic to the new version for testing before shifting more. Together, these strategies minimize downtime and allow testing. Option A (rolling update) is not directly supported in SageMaker for endpoints; SageMaker uses deployment variants. Option B (multi-model endpoint) is for hosting multiple models on the same endpoint but does not provide traffic shifting for updates. Option C (A/B testing) in SageMaker is typically achieved using production variants with traffic weights, but the specific feature for gradual traffic shifting is called canary deployment, so option C is incorrect as stated.

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 a rolling update strategy.
Why it's wrong here
Rolling updates are not natively supported by SageMaker endpoints.
✗
Use a multi-model endpoint.
Why it's wrong here
Multi-model endpoints host multiple models but do not provide deployment strategies.
✗
Use Amazon SageMaker A/B testing.
Why it's wrong here
A/B testing is for comparing model versions, not specifically for traffic shifting with canary.
✓
Use Amazon SageMaker canary deployment.
Why this is correct
Canary deployment sends a small percentage of traffic to the new version.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✓
Use Amazon SageMaker blue/green deployment.
Why this is correct
Blue/green deploys a new endpoint and shifts traffic after validation.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.

Detailed technical explanation

How to think about this question

This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.

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.
Use explanations to understand the rule behind the answer.

TExam Day Tips

Underline the problem statement mentally.
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.

Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.

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FAQ

Questions learners often ask

What does this MLS-C01 question test?

Machine Learning Implementation and Operations — This question tests Machine Learning Implementation and Operations — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Use Amazon SageMaker canary deployment. — The correct answers are D (canary deployment) and E (blue/green deployment). In Amazon SageMaker, blue/green deployment allows you to deploy a new model version alongside the existing one (blue) and then shift traffic gradually. Canary deployment is a feature of SageMaker that routes a small percentage of traffic to the new version for testing before shifting more. Together, these strategies minimize downtime and allow testing. Option A (rolling update) is not directly supported in SageMaker for endpoints; SageMaker uses deployment variants. Option B (multi-model endpoint) is for hosting multiple models on the same endpoint but does not provide traffic shifting for updates. Option C (A/B testing) in SageMaker is typically achieved using production variants with traffic weights, but the specific feature for gradual traffic shifting is called canary deployment, so option C is incorrect as stated.

What should I do if I get this MLS-C01 question wrong?

Are there clue words in this question I should notice?

Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

About these practice questions

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Same concept, more angles

2 more ways this is tested on MLS-C01

These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.

Variation 1. A company is deploying a machine learning model using Amazon SageMaker. The model must be updated frequently without downtime. Which TWO strategies can achieve this? (Choose two.)

hard

A.Update the model artifact on the existing endpoint.
B.Delete the existing endpoint and create a new one.
✓ C.Use blue/green deployment with endpoint variants.
D.Use rolling update with multiple instances.
✓ E.Use canary deployment by gradually shifting traffic.

Why C: Option C is correct because Amazon SageMaker supports blue/green deployment using endpoint variants, where you can deploy a new model version alongside the current one and then shift all traffic to the new variant once validated. This approach ensures zero downtime because the existing endpoint remains active during the transition, and traffic is switched atomically. Option E is correct because canary deployment with SageMaker allows you to gradually shift a small percentage of traffic to a new model variant, monitor its performance, and then ramp up to 100% if successful, all without interrupting the service.

Variation 2. A company is deploying a machine learning model using Amazon SageMaker. The model needs to be updated frequently with new data. Which TWO approaches can be used to update the model without downtime? (Choose TWO.)

medium

A.Delete the existing endpoint and create a new one with the updated model.
B.Directly update the model artifact in the existing endpoint configuration.
✓ C.Use SageMaker A/B testing to gradually shift traffic to the new model variant.
D.Stop the endpoint, update the model, and restart the endpoint.
✓ E.Use a blue/green deployment by deploying the new model on a separate endpoint and then updating the DNS record.

Why C: Option C is correct because Amazon SageMaker supports deploying multiple model variants behind a single endpoint using production variants. By using A/B testing (traffic shifting), you can gradually route a percentage of inference requests to the new model variant while the old variant continues serving the majority of traffic, enabling updates with zero downtime.

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