The deployment must have the following:• Separate environment pipelines for testing and production• Automatic deployment that occurs for test environments onlyWhich steps should be taken to meet these requirements?
Configure a new AWS CodePipeline service. Create a CodeCommit repository for each environment. Set up CodePipeline to retrieve the source code from the appropriate repository. Set up the deployment step to deploy the Lambda functions with AWS CloudFormation.
Create two AWS CodePipeline configurations for test and production environments. Configure the production pipeline to have a manual approval step. Create a CodeCommit repository for each environment. Set up each CodePipeline to retrieve the source code from the appropriate repository. Set up the deployment step to deploy the Lambda functions with AWS CloudFormation.
Create two AWS CodePipeline configurations for test and production environments. Configure the production pipeline to have a manual approval step. Create one CodeCommit repository with a branch for each environment. Set up each CodePipeline to retrieve the source code from the appropriate branch in the repository. Set up the deployment step to deploy the Lambda functions with AWS CloudFormation.
Create an AWS CodeBuild configuration for test and production environments. Configure the production pipeline to have a manual approval step. Create one CodeCommit repository with a branch for each environment. Push the Lambda function code to an Amazon S3 bucket. Set up the deployment step to deploy the Lambda functions from the S3 bucket.
Explanations:
This option suggests creating a separate CodeCommit repository for each environment. However, the requirement states that there should be a single repository with branches for different environments to manage deployment effectively. Additionally, it does not specify any manual approval step for production.
This option proposes two separate CodeCommit repositories, which is not necessary according to the requirements. It does include a manual approval step for the production pipeline, but does not mention the automation for deployment happening only in the test environments as required.
This option correctly creates two CodePipeline configurations for test and production environments with a manual approval step for production. It uses one CodeCommit repository with branches for each environment, allowing for automatic deployment only for the test environments, meeting all specified requirements.
This option introduces AWS CodeBuild, which is not necessary since the requirement focuses on Lambda deployment via CodePipeline. It also proposes using S3 for storing the code, which adds unnecessary complexity and does not align with the direct deployment from CodeCommit.
I scheme that the answer is:
Create two AWS CodePipeline configurations for test and production environments. Configure the production pipeline to have a manual approval step. Create one CodeCommit repository with a branch for each environment. Set up each CodePipeline to retrieve the source code from the appropriate branch in the repository. Set up the deployment step to deploy the Lambda functions with AWS CloudFormation.