A DevOps Engineer is building a continuous deployment pipeline for a serverless application using AWS CodePipeline and AWS CodeBuild. The source, build, and test stages have been created with the deploy stage remaining. The company wants to reduce the risk of an unsuccessful deployment by deploying to a small percentage of customers and monitoring this deployment prior to a full release to all customers. How should the deploy stage be configured to meet these requirements?

A. Use AWS CloudFormation to publish a new version on every stack update. Then set up a CodePipeline approval action for a Developer to test and approve the new version. Finally, use a CodePipeline invoke action to update an AWS Lambda function to use the production alias
B. Use CodeBuild to use the AWS CLI to update the AWS Lambda function code, then publish a new version of the function and update the production alias to point to the new version of the function.
C. Use AWS CloudFormation to define the serverless application and AWS CodeDeploy to deploy the AWS Lambda functions using DeploymentPreference: Canary10Percent15Minutes.
D. Use AWS CloudFormation to publish a new version on every stack update. Use the RoutingConfigproperty of the AWS::Lambda::Aliasresource to update the traffic routing during the stack update.