AWS Certified Data Engineer Associate DEA-C01 Practice Question
A data engineering team must provision an Amazon EMR cluster, an S3 bucket for log storage, an IAM instance profile, and the required security groups in development, test, and production AWS accounts. The solution must be fully repeatable, allow code reviews, and integrate with their CI/CD pipeline so that deployments run automatically without manual intervention. Which approach meets these requirements with the least ongoing operational effort?
Store an AWS CloudFormation template with parameters in a version-controlled repository and use AWS CloudFormation StackSets to deploy the stack to each account through the pipeline.
Use the AWS Management Console to create the resources in the development account, export the EMR cluster template, and import it into the other accounts.
Author the infrastructure in AWS CDK (Python) and have developers run the CDK CLI from their workstations when updates are required.
Create Bash scripts that call the AWS CLI to build the resources and trigger the scripts from AWS CodePipeline for each environment.
Storing the resource definitions in an AWS CloudFormation template and deploying them with CloudFormation StackSets makes the entire environment reproducible across multiple accounts and Regions. The template can be version-controlled, reviewed through pull requests, and invoked from a CI/CD pipeline. StackSets handles propagation, drift detection, and updates, minimizing manual effort.
AWS CDK still relies on the CDK CLI for deployment from each workstation unless additional automation is built. AWS CLI scripts introduce more custom code to maintain and provide no built-in state management or drift detection. Manual console actions are not repeatable or suitable for CI/CD pipelines.
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AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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