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AWS Certified Data Engineer Associate DEA-C01 Practice Question

Your team needs a managed, serverless workflow that starts when an object arrives under s3://sales/landing/. The workflow must invoke a Lambda function to validate each file, run an AWS Glue Spark job to transform the data, then call another Lambda to load the result into Amazon Redshift. It must provide automatic per-step retries, execution history, and one-click resume from failures. Which solution is most cost-effective?

  • Set up an Amazon EventBridge pipe to invoke the first Lambda function; have that function synchronously call the Glue job and second Lambda while implementing all retries in code.

  • Deploy an Amazon MWAA environment and author an Apache Airflow DAG that coordinates the two Lambda tasks and the Glue job.

  • Build an AWS Glue Workflow that runs the Glue job and add the two Lambda steps as Python shell jobs inside the workflow.

  • Create an AWS Step Functions state machine that invokes the two Lambda functions and the AWS Glue job, and trigger the state machine with an Amazon EventBridge rule for the S3 prefix.

AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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