AWS Certified Data Engineer - Associate DEA-C01Demo

By Amazon · Question Mode

QuestionQ226

Data Ingestion and Transformation

A company uses Apache Airflow to orchestrate its existing on-premises data pipelines. As part of these pipelines, the company runs SQL data-quality-check tasks. The company wants to migrate the pipelines to AWS and use AWS managed services.

Which solution meets these requirements with the LEAST refactoring?

  • A Setup AWS Outposts in the AWS Region that is nearest to the location where the company uses Airflow. Migrate the servers into Outposts hosted Amazon EC2 instances. Update the pipelines to interact with the Outposts hosted EC2 instances instead of the on-premises pipelines.
  • B Create a custom Amazon Machine Image (AMI) that contains the Airflow application and the code that the company needs to migrate. Use the custom AMI to deploy Amazon EC2 instances. Update the network connections to interact with the newly deployed EC2 instances.
  • C Migrate the existing Airflow orchestration configuration into Amazon Managed Workflows for Apache Airflow (Amazon MWAA). Create the data quality checks during the ingestion to validate the data quality by using SQL tasks in Airflow.
  • D Convert the pipelines to AWS Step Functions workflows. Recreate the data quality checks in SQL as Python based AWS Lambda functions.
Explanation

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is AWS’s managed Apache Airflow service and provides a migration path for self-managed Apache Airflow workloads. Migrating the existing Airflow configuration retains the DAG-based orchestration and existing SQL tasks, minimizing refactoring while removing responsibility for operating the Airflow infrastructure.

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