What is the MOST efficient way to meet these requirements?
Create an AWS CodeCommit repository for each project, use the main branch for production code, and create a testing branch for code deployed to testing. Use feature branches to develop new features and pull requests to merge code to testing and main branches.
Create another S3 bucket for each project for testing code, and use an AWS Lambda function to promote code changes between testing and production buckets. Enable versioning on all buckets to prevent code conflicts.
Create an AWS CodeCommit repository for each project, and use the main branch for production and test code with different deployment pipelines for each environment. Use feature branches to develop new features.
Enable versioning and branching on each S3 bucket, use the main branch for production code, and create a testing branch for code deployed to testing. Have developers use each branch for developing in each environment.
Explanations:
Using AWS CodeCommit for version control allows multiple developers to collaborate without conflicts. Branching strategies (main for production, testing for pre-deployment, and feature branches for development) enable organized workflow and code review through pull requests, reducing the risk of lost work. Code can be automatically deployed based on changes in the repository, meeting the company’s requirements effectively.
Storing code in S3 is not suitable for version control and collaboration among multiple developers, as S3 lacks built-in mechanisms for handling code conflicts. Using Lambda functions for promoting code changes adds unnecessary complexity and does not facilitate collaborative development. Versioning in S3 also does not replace a proper source control system.
While AWS CodeCommit is suitable for managing source code, using the same main branch for both production and test code could lead to conflicts and confusion. It is better practice to have separate branches for production and testing to maintain clear separation and allow for stable deployments, which is not addressed in this option.
Enabling versioning and branching in S3 does not provide a robust version control system. S3 is not designed for collaborative coding, leading to potential code conflicts and loss of work among developers. Developers need a dedicated source control system like CodeCommit to manage branches and features effectively.
I believe the answer is:
Create an AWS CodeCommit repository for each project, use the main branch for production code, and create a testing branch for code deployed to testing. Use feature branches to develop new features and pull requests to merge code to testing and main branches.