A company is building an ecommerce application on AWS and wants to ensure that the application can withstand sudden traffic increases.
The company uses AWS CodePipeline for its CI/CD process. It must implement a solution that integrates automated load testing into the CI/CD pipeline to validate the application's performance. The solution must deploy to production only when performance exceeds a threshold.
Which solution meets these requirements with the LEAST operational overhead?
A Deploy the application by using AWS Elastic Beanstalk. Enable load balancing. Use Elastic Beanstalk to deploy tools for load tests. Run the tests during each deployment, and roll back the deployment if performance thresholds are unmet. Create an AWS Lambda function to monitor test metrics. Set up alarms for performance thresholds. Configure Amazon EventBridge to return an error if a test fails and to proceed with production deployment if a test passes. B Implement AWS Fargate tasks to run tools for load tests. Use Amazon Elastic container Service (Amazon ECS) to manage the test containers. Create AWS Lambda functions to analyze the test results. Integrate the functions with CodePipeline by using custom actions to initiate and evaluate the tests. Program the functions to return an error if a test fails and to proceed with production deployment if a test passes. C Launch Amazon EC2 instances to run tools for load tests. Store test scripts in a GitHub repository. Use AWS Step Functions to orchestrate the tests and result analysis in the CodePipeline workflow. Use Amazon EventBridge to invoke an AWS Lambda function based on the test results. Program the function to return an error if a test fails and to proceed with production deployment if a test passes. D Use AWS CodeBuild to run tools for load tests, store the test artifacts in Amazon S3, and configure a CodePipeline stage to invoke the CodeBuild project. Use Amazon CloudWatch to monitor the test metrics and to set up alarms for performance thresholds. Integrate an AWS Lambda function into the pipeline by using a custom action. Program the function to return an error if a test fails and to proceed with production deployment if a test passes. Show Answer Answer Explanation AWS CodeBuild provides managed compute for running load-testing tools and integrates directly with AWS CodePipeline as a build or test action. Test artifacts can be stored in Amazon S3, while Amazon CloudWatch can evaluate performance metrics and alarms against the required threshold. A Lambda-based pipeline action can return failure when the threshold is not met, preventing the production deployment; this avoids managing test EC2 instances or ECS/Fargate infrastructure.
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