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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 85 discussion

Exam question from Amazon's AWS Certified Machine Learning Engineer - Associate MLA-C01
Question #: 85
Topic #: 1
[All AWS Certified Machine Learning Engineer - Associate MLA-C01 Questions]

A company has developed a new ML model. The company requires online model validation on 10% of the traffic before the company fully releases the model in production. The company uses an Amazon SageMaker endpoint behind an Application Load Balancer (ALB) to serve the model.
Which solution will set up the required online validation with the LEAST operational overhead?

  • A. Use production variants to add the new model to the existing SageMaker endpoint. Set the variant weight to 0.1 for the new model. Monitor the number of invocations by using Amazon CloudWatch.
  • B. Use production variants to add the new model to the existing SageMaker endpoint. Set the variant weight to 1 for the new model. Monitor the number of invocations by using Amazon CloudWatch.
  • C. Create a new SageMaker endpoint. Use production variants to add the new model to the new endpoint. Monitor the number of invocations by using Amazon CloudWatch.
  • D. Configure the ALB to route 10% of the traffic to the new model at the existing SageMaker endpoint. Monitor the number of invocations by using AWS CloudTrail.
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Suggested Answer: A 🗳️
by GiorgioGss at Nov. 28, 2024, 6:06 p.m.
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Saransundar
3 months ago
Selected Answer: A
https://docs.aws.amazon.com/sagemaker/latest/dg/model-ab-testing.html
upvoted 1 times
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GiorgioGss
3 months ago
Selected Answer: A
{ 'ProductionVariants': [ { 'VariantName': 'existing-model', 'ModelName': 'existing-model', 'InitialVariantWeight': 0.9 }, { 'VariantName': 'new-model', 'ModelName': 'new-model', 'InitialVariantWeight': 0.1 } ] }
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