A single developer currently stores project source code in an S3 bucket. The company will add developers and needs to avoid code conflicts and lost work, provide a test environment for newer versions, and let developers automatically deploy to test and production when repository code changes. What is the most efficient solution?

The correct solution leverages AWS CodeCommit for version control, which is designed to manage source code collaboratively. Using a main branch for production, a testing branch for test deployments, and feature branches with pull requests for development and merging is a standard and efficient Git workflow. This approach prevents code conflicts, allows for testing new versions without impacting production, and enables automated deployments through integration with CI/CD services. Incorrect options: Using S3 buckets for source code management is not ideal for collaborative development as it lacks built-in version control features like branching, merging, and pull requests, making conflict resolution difficult. Using the main branch for both production and test environments in CodeCommit is risky as it doesn't provide a clear separation, potentially leading to unintended deployments or issues. S3 buckets do not support Git-style branching and merging, making it an unsuitable choice for the described requirements.