A company uses AWS CodePipeline to deploy an application to an Amazon EC2 Auto Scaling group. All resources are defined in CloudFormation templates. Application artifacts are stored in Amazon S3 and deployed using instance user data scripts. As the application grew, recent changes to CloudFormation templates caused unexpected downtime. How should the solutions architect improve the CI/CD pipeline to reduce the chance that template changes cause outages?

The correct option provides a comprehensive strategy to prevent outages. Automated testing with CodeBuild in a test environment validates template changes and application functionality before production. CloudFormation change sets allow for a preview of how template changes will affect existing resources, mitigating unexpected modifications. Using CodeDeploy with blue/green deployments enables zero-downtime updates, allowing verification of the new version before routing production traffic and providing an easy rollback mechanism if issues arise. The other options are less effective. Detecting and reporting errors (first option) is reactive, not preventative. Manual testing (first and third options) is slow and prone to human error. Validating syntax with IDE plugins or CLI (third option) is a basic step but doesn't test the operational impact of template changes. Manual verification on new instances (fourth option) is inefficient and doesn't scale.