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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 79 discussion

Exam question from Amazon's AWS Certified Machine Learning Engineer - Associate MLA-C01
Question #: 79
Topic #: 1
[All AWS Certified Machine Learning Engineer - Associate MLA-C01 Questions]

A company regularly receives new training data from the vendor of an ML model. The vendor delivers cleaned and prepared data to the company's Amazon S3 bucket every 3-4 days.
The company has an Amazon SageMaker pipeline to retrain the model. An ML engineer needs to implement a solution to run the pipeline when new data is uploaded to the S3 bucket.
Which solution will meet these requirements with the LEAST operational effort?

  • A. Create an S3 Lifecycle rule to transfer the data to the SageMaker training instance and to initiate training.
  • B. Create an AWS Lambda function that scans the S3 bucket. Program the Lambda function to initiate the pipeline when new data is uploaded.
  • C. Create an Amazon EventBridge rule that has an event pattern that matches the S3 upload. Configure the pipeline as the target of the rule.
  • D. Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to orchestrate the pipeline when new data is uploaded.
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Suggested Answer: C 🗳️
by GiorgioGss at Nov. 28, 2024, 5:36 p.m.
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Saransundar
3 months ago
Selected Answer: C
Amazon EventBridge can automatically trigger the SageMaker pipeline when new data is uploaded to S3, making it a simple and efficient soln.
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GiorgioGss
3 months ago
Selected Answer: C
"run the pipeline when new data is uploaded to the S3 bucket." This is plain event-driven architecture.
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