The requirement emphasizes collaboration, frequent code changes, and deploying from source control with the fewest manual steps. This aligns with a CI/CD pipeline approach where commits or merges automatically trigger builds and deployments. Using AWS CodePipeline orchestrates the stages (source, build, deploy), and AWS CodeBuild performs the build/package steps for the Lambda/serverless application. When integrated with a repository (such as CodeCommit, GitHub, or another supported provider), CodePipeline can automatically start when changes are merged into specific branches, enabling consistent, repeatable deployments.
Option C provides the least operational overhead for teams: developers push code and merge pull requests; the pipeline automatically builds artifacts, runs tests (if configured), packages dependencies, and deploys updates to Lambda (often via AWS SAM/CloudFormation under the hood). This removes manual “build on my laptop” drift, prevents inconsistent deployments between developers, and supports frequent iteration safely.
Option B (SAM CLI from a local machine) requires a developer to manually run build/deploy commands and assumes each developer’s environment is configured correctly. That increases manual steps and the risk of differences across machines. Option D (uploading zip in the console) is highly manual and not suitable for frequent changes or team collaboration. Option A is also suboptimal because storing built artifacts in source control is an anti-pattern; builds should be reproducible and produced by CI, not committed binaries.
Therefore, C is the best choice: set up CodePipeline + CodeBuild so merges to controlled branches automatically trigger builds and deployments to AWS Lambda with minimal manual intervention.
