Topic 1 Question 79
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?
Create an S3 Lifecycle rule to transfer the data to the SageMaker training instance and to initiate training.
Create an AWS Lambda function that scans the S3 bucket. Program the Lambda function to initiate the pipeline when new data is uploaded.
Create an Amazon EventBridge rule that has an event pattern that matches the S3 upload. Configure the pipeline as the target of the rule.
Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to orchestrate the pipeline when new data is uploaded.
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コメント(2)
- 正解だと思う選択肢: C
"run the pipeline when new data is uploaded to the S3 bucket." This is plain event-driven architecture.
👍 1GiorgioGss2024/11/28 - 正解だと思う選択肢: C
Amazon EventBridge can automatically trigger the SageMaker pipeline when new data is uploaded to S3, making it a simple and efficient soln.
👍 1Saransundar2024/12/04
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