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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 46 discussion

Exam question from Amazon's AWS Certified Machine Learning Engineer - Associate MLA-C01
Question #: 46
Topic #: 1
[All AWS Certified Machine Learning Engineer - Associate MLA-C01 Questions]

A company has AWS Glue data processing jobs that are orchestrated by an AWS Glue workflow. The AWS Glue jobs can run on a schedule or can be launched manually.
The company is developing pipelines in Amazon SageMaker Pipelines for ML model development. The pipelines will use the output of the AWS Glue jobs during the data processing phase of model development. An ML engineer needs to implement a solution that integrates the AWS Glue jobs with the pipelines.
Which solution will meet these requirements with the LEAST operational overhead?

  • A. Use AWS Step Functions for orchestration of the pipelines and the AWS Glue jobs.
  • B. Use processing steps in SageMaker Pipelines. Configure inputs that point to the Amazon Resource Names (ARNs) of the AWS Glue jobs.
  • C. Use Callback steps in SageMaker Pipelines to start the AWS Glue workflow and to stop the pipelines until the AWS Glue jobs finish running.
  • D. Use Amazon EventBridge to invoke the pipelines and the AWS Glue jobs in the desired order.
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Suggested Answer: C 🗳️
by a4002bd at Nov. 27, 2024, 6:23 a.m.
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Saransundar
1 month ago
Selected Answer: C
https://sagemaker-examples.readthedocs.io/en/latest/sagemaker-pipelines/tabular/custom_callback_pipelines_step/sagemaker-pipelines-callback-step.html This shows how to use the Callback Step and how to include a Glue ETL job as part of a SageMaker ML pipeline.
upvoted 1 times
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Wonjin7
1 month, 1 week ago
Selected Answer: B
I think it's B when I consider 'LEAST operational overhead'.
upvoted 1 times
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Linux_master
1 month, 1 week ago
Selected Answer: C
https://aws.amazon.com/blogs/machine-learning/extend-amazon-sagemaker-pipelines-to-include-custom-steps-using-callback-steps/
upvoted 2 times
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GiorgioGss
1 month, 1 week ago
Selected Answer: C
LEAST effort: https://aws.amazon.com/blogs/machine-learning/extend-amazon-sagemaker-pipelines-to-include-custom-steps-using-callback-steps/ The example is exactly for the same use-case as the question.
upvoted 2 times
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a4002bd
1 month, 1 week ago
Selected Answer: B
This approach allows you to directly integrate the outputs of AWS Glue jobs into SageMaker Pipelines, leveraging the processing steps to handle the data. It minimizes additional orchestration overhead and keeps the workflow streamlined within SageMaker Pipelines
upvoted 1 times
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