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Amazon Exam MLA-C01 Topic 3 Question 1 Discussion

Actual exam question for Amazon's MLA-C01 exam
Question #: 1
Topic #: 3
[All MLA-C01 Questions]

Case Study

A company is building a web-based AI application by using Amazon SageMaker. The application will provide the following capabilities and features: ML experimentation, training, a

central model registry, model deployment, and model monitoring.

The application must ensure secure and isolated use of training data during the ML lifecycle. The training data is stored in Amazon S3.

The company needs to run an on-demand workflow to monitor bias drift for models that are deployed to real-time endpoints from the application.

Which action will meet this requirement?

Show Suggested Answer Hide Answer
Suggested Answer: A

by Filiberto at Jun 14, 2025, 02:05 AM

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Mirta
7 days ago
I'm not sure about option C. AWS Glue Data Quality may not be as effective in monitoring bias drift compared to SageMaker Clarify.
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Vanna
10 days ago
I agree with Walker. Using SageMaker Clarify will ensure that bias drift is monitored effectively in real-time endpoints.
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Teri
13 days ago
Hold on, why are we even considering SageMaker notebooks? That's overkill for just comparing bias. Option D is a bit of a stretch, in my opinion.
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Walker
24 days ago
I think option A is the best choice because SageMaker Clarify is specifically designed for monitoring bias in ML models.
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Mauricio
24 days ago
I'm not so sure about that. Isn't AWS Glue Data Quality designed for more general data quality monitoring? Option C might be a better fit for this specific use case.
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Anabel
27 days ago
I'm not sure about that. Wouldn't it be easier to just use the built-in SageMaker image for model monitoring? Option B seems more efficient to me.
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Ryan
1 days ago
Option B seems like a good choice. It would definitely make model monitoring easier.
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Lindsey
1 months ago
Option A looks like the way to go here. Invoking a Lambda function to run a SageMaker Clarify job seems like the most straightforward approach to monitoring bias drift.
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Nidia
6 days ago
User 3: It's important to ensure secure and isolated use of training data during the ML lifecycle.
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Danilo
30 days ago
User 2: Definitely, using a Lambda function to run a SageMaker Clarify job is a good solution.
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Valda
1 months ago
User 1: I agree, option A seems like the best choice for monitoring bias drift.
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