Quick Answer
The answer is blue/green and canary deployment. Both strategies achieve zero-downtime updates by routing traffic gradually between an existing production endpoint and a new endpoint hosting the updated model, ensuring no requests are dropped during the transition. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of SageMaker’s deployment modes and the critical distinction that you cannot update a model in-place on a live endpoint—you must create a new endpoint configuration. A common trap is choosing “rolling update” or “direct model update,” which SageMaker does not support natively, or “delete and recreate,” which causes downtime. For the exam, remember that any option involving immediate traffic switching or in-place model changes is wrong; zero-downtime always requires a separate new endpoint. Memory tip: think “two endpoints, one traffic shift”—blue/green swaps all at once, canary does it gradually, but both keep the old endpoint alive until the new one is fully validated.
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 using Amazon SageMaker. The model must be updated frequently without downtime. Which TWO strategies can achieve this? (Choose two.)
Update the model artifact on the existing endpoint.
Why wrong: Not supported.
Delete the existing endpoint and create a new one.
Why wrong: Causes downtime.
Use blue/green deployment with endpoint variants.
Traffic is shifted gradually.
Use rolling update with multiple instances.
Why wrong: SageMaker does not support rolling updates natively.
Use canary deployment by gradually shifting traffic.
Zero-downtime update.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Use blue/green deployment with endpoint variants.
Options B and D are correct. Blue/green deployment and canary deployment both allow zero-downtime updates by routing traffic gradually. Option A is wrong because deleting and recreating the endpoint causes downtime. Option C is wrong because updating the model directly on the endpoint is not supported without creating a new endpoint. Option E is wrong because SageMaker does not support rolling updates natively.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Update the model artifact on the existing endpoint.
Why it's wrong here
Not supported.
Delete the existing endpoint and create a new one.
Why it's wrong here
Causes downtime.
Use blue/green deployment with endpoint variants.
Why this is correct
Traffic is shifted gradually.
Related concept
Static NAT maps one inside address to one outside address.
Use rolling update with multiple instances.
Why it's wrong here
SageMaker does not support rolling updates natively.
Use canary deployment by gradually shifting traffic.
Why this is correct
Zero-downtime update.
Related concept
Static NAT maps one inside address to one outside address.
Common exam traps
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
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. NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated. 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
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related MLS-C01 NAT questions on configuration and troubleshooting.
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FAQ
Machine Learning Implementation and Operations — This question tests Machine Learning Implementation and Operations — Static NAT maps one inside address to one outside address..
The correct answer is: Use blue/green deployment with endpoint variants. — Options B and D are correct. Blue/green deployment and canary deployment both allow zero-downtime updates by routing traffic gradually. Option A is wrong because deleting and recreating the endpoint causes downtime. Option C is wrong because updating the model directly on the endpoint is not supported without creating a new endpoint. Option E is wrong because SageMaker does not support rolling updates natively.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related MLS-C01 NAT questions on configuration and troubleshooting.
Static NAT maps one inside address to one outside address.
About these practice questions
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Same concept, more angles
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 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?
hardWhy D: Option A (blue/green deployment) and Option D (canary deployment) are correct. Blue/green allows a new version to be deployed alongside the old one, and canary deployment routes a small percentage of traffic to the new version for testing. Option B is wrong because A/B testing in SageMaker is typically done with production variants but does not inherently include canary routing; canary is a specific feature. Option C is wrong because rolling update is not a native SageMaker feature for endpoints. Option E is wrong because multi-model endpoints host multiple models but do not facilitate traffic shifting for updates.
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.)
mediumWhy C: Option A and C are correct because A/B testing allows gradual rollout, and blue/green deployment with production variants ensures zero downtime. Option B is wrong because recreating the endpoint causes downtime. Option D is wrong because updating the model artifact while endpoint is active is not supported without redeployment. Option E is wrong because stopping the endpoint causes downtime.
Last reviewed: Jun 20, 2026
This MLS-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 MLS-C01 exam.
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