Amazon MLS-C01 Exam - Topic 4 Question 125 Discussion

Actual exam question for Amazon's MLS-C01 exam

Question #: 125
Topic #: 4

[Modeling]

An insurance company developed a new experimental machine learning (ML) model to replace an existing model that is in production. The company must validate the quality of predictions from the new experimental model in a production environment before the company uses the new experimental model to serve general user requests.

Which one model can serve user requests at a time. The company must measure the performance of the new experimental model without affecting the current live traffic

Which solution will meet these requirements?

AA/B testing

BCanary release

CShadow deployment

DBlue/green deployment

Show Suggested Answer

Suggested Answer: C

by Jacquline at Jan 05, 2026, 05:16 AM

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Kenny

3 days ago

B) Canary release could also work, but it might be overkill for just validating the new model.

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Vince

8 days ago

I agree, C) Shadow deployment allows the company to measure the new model's performance without affecting the live traffic.

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Jaclyn

13 days ago

C) Shadow deployment seems like the best option here.

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Dorthy

18 days ago

Blue/green deployment could be a possibility too, but I feel like it might not fit the requirement of only serving one model at a time.

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Garry

23 days ago

Shadow deployment sounds familiar, but I can't recall if it really isolates the new model's performance from the live traffic.

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Quiana

28 days ago

I remember practicing with canary releases, and it seems like a good option since it allows gradual exposure of the new model.

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Sang

1 month ago

I think A/B testing might be the right choice, but I'm not entirely sure how it would work without affecting live traffic.

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Eladia

1 month ago

Hmm, I'm not sure. I think I need to re-read the question and the options more carefully. I want to make sure I understand the requirements and the differences between the deployment strategies before I commit to an answer.

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Titus

1 month ago

I'm leaning towards B) Canary release. That would allow us to gradually roll out the new model to a small subset of users, monitor its performance, and then expand it to more users if it's performing well. Seems like a safer approach than just switching over completely.

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Paris

2 months ago

Okay, I'm pretty confident that the answer is C) Shadow deployment. That way, we can run the new model in parallel with the existing one and measure its performance without affecting the live traffic. Seems like the perfect solution for this scenario.

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Daron

2 months ago

Hmm, I'm a bit confused. I know A/B testing is used to compare two versions, but I'm not sure how that would work in this case since we can only have one model in production at a time. I'll have to think this through more carefully.

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Catina

2 months ago

I think the key here is to find a way to test the new model without disrupting the current live traffic. Based on the options, I'd say Canary release or Shadow deployment seem like the best choices.

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