Amazon Exam MLA-C01 Topic 1 Question 5 Discussion

Actual exam question for Amazon's MLA-C01 exam

Question #: 5
Topic #: 1

An ML engineer needs to implement a solution to host a trained ML model. The rate of requests to the model will be inconsistent throughout the day.

The ML engineer needs a scalable solution that minimizes costs when the model is not in use. The solution also must maintain the model's capacity to respond to requests during times of peak usage.

Which solution will meet these requirements?

ACreate AWS Lambda functions that have fixed concurrency to host the model. Configure the Lambda functions to automatically scale based on the number of requests to the model.

BDeploy the model on an Amazon Elastic Container Service (Amazon ECS) cluster that uses AWS Fargate. Set a static number of tasks to handle requests during times of peak usage.

CDeploy the model to an Amazon SageMaker endpoint. Deploy multiple copies of the model to the endpoint. Create an Application Load Balancer to route traffic between the different copies of the model at the endpoint.

DDeploy the model to an Amazon SageMaker endpoint. Create SageMaker endpoint auto scaling policies that are based on Amazon CloudWatch metrics to adjust the number of instances dynamically.

Show Suggested Answer

Suggested Answer: D

by Josphine at Jun 11, 2025, 09:48 PM

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Cordelia

1 days ago

I think option A is the best choice because it can automatically scale based on the number of requests.

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Winfred

4 days ago

Option D seems the most suitable. The ability to dynamically scale the SageMaker endpoint based on CloudWatch metrics is exactly what the problem statement is looking for.

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