Introduction: Bridging the Gap Between Code and Infrastructure
Serverless computing has revolutionized application deployment, enabling developers to focus on code without worrying about infrastructure management. AWS Lambda provides a powerful platform for running serverless applications, while GitLab CI/CD simplifies automated deployments. This guide bridges the gap between code and infrastructure, demonstrating how to deploy AWS Lambda functions seamlessly with GitLab CI/CD.
Prerequisites: Essential Tools for Seamless Deployment
Before diving into deployment, ensure you have the following tools and setups:
- AWS Account: Active account with necessary permissions.
- GitLab Account: Repository set up for your project.
- AWS CLI: Installed and configured with access credentials.
- Node.js and NPM: Installed for building and packaging Lambda functions.
- Git: Installed for version control.
- YAML Basics: Familiarity with YAML for GitLab CI/CD pipelines.
AWS Setup: Creating Users and Setting IAM Permissions
- Create an IAM User:
- Go to the AWS Management Console.
- Navigate to IAM > Users > Add User.
- Provide a username and select Programmatic Access.
- Attach Policies:
- Attach the following policies for Lambda deployments:
- AWSLambdaFullAccess
- AmazonS3FullAccess (if using S3 for code storage)
- IAMFullAccess (for role creation if needed).
- Attach the following policies for Lambda deployments:
- Save Access Keys:
- Save the Access Key ID and Secret Access Key for later use in GitLab.
GitLab Configuration: Storing Sensitive Credentials
- Securely Store AWS Credentials:
- Go to Settings > CI/CD > Variables in your GitLab repository.
- Add the following environment variables:
- AWS_ACCESS_KEY_ID
- AWS_SECRET_ACCESS_KEY
- Optional: AWS_REGION (e.g., us-east-1).
- Set Permissions:
- Ensure the variables are masked and protected to prevent exposure.
Automated Deployment Pipeline: Building, Testing, and Deploying with GitLab CI/CD
- Define .gitlab-ci.yml:
- Create a .gitlab-ci.yml file in your repository root with the following content:
stages:
– build
– deploy
build:
stage: build
image: node:latest
script:
– npm install
– zip -r function.zip .
artifacts:
paths:
– function.zip
deploy:
stage: deploy
image: amazon/aws-cli:latest
script:
– aws lambda update-function-code –function-name myLambdaFunction –zip-file fileb://function.zip
only:
– main
- Customize the Pipeline:
- Replace myLambdaFunction with your actual Lambda function name.
- Add unit tests in the build stage for better reliability.
Deployment Verification: Locating Your Lambda Function in AWS
- Check AWS Lambda Console:
- Log in to the AWS Management Console.
- Navigate to Lambda > Functions.
- Verify the updated deployment timestamp and function code.
- Test Your Function:
Use the Test tab in the Lambda console or invoke it via the AWS CLI:
aws lambda invoke –function-name myLambdaFunction out.json
Beyond the Basics: Exploring Further Deployment Possibilities
- Environment Variables: Use Lambda environment variables for configuration.
- Infrastructure as Code: Automate Lambda creation with AWS CloudFormation or Terraform.
- Event Triggers: Explore Lambda event sources like S3, DynamoDB, or API Gateway.
- Monitoring and Alerts: Use AWS CloudWatch to monitor Lambda performance.