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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 All Questions

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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 topic 1 question 83 discussion

A company wants to reduce the cost of its containerized ML applications. The applications use ML models that run on Amazon EC2 instances, AWS Lambda functions, and an Amazon Elastic Container Service (Amazon ECS) cluster. The EC2 workloads and ECS workloads use Amazon Elastic Block Store (Amazon EBS) volumes to save predictions and artifacts.
An ML engineer must identify resources that are being used inefficiently. The ML engineer also must generate recommendations to reduce the cost of these resources.
Which solution will meet these requirements with the LEAST development effort?

  • A. Create code to evaluate each instance's memory and compute usage.
  • B. Add cost allocation tags to the resources. Activate the tags in AWS Billing and Cost Management.
  • C. Check AWS CloudTrail event history for the creation of the resources.
  • D. Run AWS Compute Optimizer.
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Suggested Answer: D 🗳️

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aws_Tamilan
2 weeks, 5 days ago
Selected Answer: D
🔑 Keyword: Identify inefficient ML resources, generate cost recommendations with minimal effort ✅ Correct Answer: D. Run AWS Compute Optimizer. Why? AWS Compute Optimizer provides automated recommendations for optimizing EC2 instances, EBS volumes, and Lambda. It minimizes development effort by analyzing workloads automatically. Why Others Are Wrong? ❌ A. Writing custom code for resource evaluation is manual and inefficient. ❌ B. Cost allocation tags help track expenses but do not provide recommendations. ❌ C. CloudTrail shows historical logs but does not analyze cost inefficiencies.
upvoted 1 times
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Saransundar
4 months, 2 weeks ago
Selected Answer: D
AWS Compute Optimizer finds wasted resources in EC2, EBS and suggests easy ways to save money and boost performance.
upvoted 2 times
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GiorgioGss
4 months, 3 weeks ago
Selected Answer: D
All is compute related so, D.
upvoted 1 times
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