Source Control and deployment for AWS Lambda
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Source Control and Deployment for AWS Lambda
AWS Lambda is a serverless computing service that allows developers to run code without provisioning or managing servers. With its "pay only for what you use" pricing model, AWS Lambda enables companies to deploy scalable applications efficiently. One of the key aspects of managing AWS Lambda functions effectively is implementing a robust source control and deployment strategy. This article delves into the technical aspects of source control and deployment processes for AWS Lambda, providing examples and best practices to streamline these critical operations.
Source Control
Source control is a system that manages changes to code over time, allowing multiple developers to collaborate seamlessly. The choice of a source control system is crucial as it impacts team productivity and the integrity of the codebase. Popular source control systems include Git, Subversion (SVN), and Mercurial. Git is the most widely used because of its distributed nature and robust feature set.
Benefits of Source Control in AWS Lambda
- Collaboration: Developers can work on features simultaneously without interference.
- Versioning: Keep track of every modification to the codebase.
- Code Integrity: Ensure that buggy code can be rolled back to a stable version.
- Branching Model: Facilitate seamless feature or environment branching for better workflow management.
Recommended Git Workflows
- Feature Branch Workflow: Create a separate branch for each new feature or task.
- Gitflow Workflow: Use distinct branches for feature development, releases, and hotfixes.
- Forking Workflow: Decentralized model where contributors fork repositories and manage pull requests independently.
Deployment to AWS Lambda
The deployment process for AWS Lambda involves packaging function code, uploading it to AWS, and configuring suitable execution policies and environment variables. This deployment process can be streamlined using AWS services like AWS CLI, AWS SDKs, AWS CloudFormation, or third-party CI/CD tools.
AWS CLI and SDKs
AWS offers a powerful Command Line Interface (CLI) and Software Development Kits (SDKs) for several programming languages to facilitate deployment.
Using AWS CLI:
- AWS CodePipeline: Automate the build, test, and deploy phases.
- AWS CodeBuild: Compile source code, run tests, and produce packages ready for deployment.
- AWS CodeDeploy: Automate code deployment across Lambda functions.
Related reading
- Spark on Kubernetes Executor pods silently get killed
- Specify log group for an AWS lambda?
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- Spring boot startup error for AWS application There is not EC2 meta data available
- Spark executor metrics don't reach prometheus sink
- Specify the order Dockers run on Kubernetes pod
- Spring boot startup error for AWS application There is not EC2 meta data available
- Spring Cloud - SQS - The specified queue does not exist for this wsdl version

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Work through 120+ system design problems with detailed solutions, from rate limiters to multi-region storage.