AWS Certified Data Engineer Associate DEA-C01 Practice Question
Your team maintains a single AWS CloudFormation template that provisions an Amazon Kinesis Data Stream, an AWS Lambda function, and an Amazon DynamoDB table for an ingestion pipeline. The template must be deployed automatically by the CI/CD system to dev, test, and prod accounts that belong to the same AWS Organization, in both us-east-1 and us-west-2. The solution must minimize template duplication, avoid storing long-lived cross-account credentials in the pipeline, and make it easy to onboard future accounts. Which approach satisfies these requirements according to AWS best practices?
Maintain three copies of the template, update the account IDs manually, and deploy each copy with CloudFormation change sets from the administration account.
Run AWS CDK synth to generate Region-specific stacks and commit separate templates for each environment, then deploy them with individual CodePipeline stages.
Use a nested CloudFormation stack and configure a CodeBuild project to assume an IAM role in each account and Region to run AWS CLI deploy commands.
Create a CloudFormation StackSet with service-managed permissions, target the OU that contains the dev, test, and prod accounts, and specify both Regions for deployment.
CloudFormation StackSets let you deploy the same template to multiple AWS accounts and Regions from a single administration account. When StackSets are configured with service-managed permissions, CloudFormation automatically creates and manages the necessary execution roles in each member account, so the CI/CD pipeline does not need to store or assume cross-account credentials. Targeting an organization unit (OU) means that any new accounts added to the OU will receive the stack automatically, eliminating template duplication while meeting least-privilege and scalability goals.
The other options either require manual credential management, maintain separate templates, or add operational overhead that the question specifically seeks to avoid.
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AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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