The CI/CD Pipeline
CI/CD (Continuous Integration/Continuous Deployment) means: every push to main automatically tests your code, builds a new Docker image, and deploys it. Here is the GitHub Actions workflow:
name: Build and Deploy
on:
push:
branches: [main]
env:
AWS_REGION: us-east-1
ECR_REPOSITORY: my-ai-app
APP_RUNNER_SERVICE: my-ai-app-service
jobs:
deploy:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Configure AWS credentials
uses: aws-actions/configure-aws-credentials@v4
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: ${{ env.AWS_REGION }}
- name: Login to Amazon ECR
id: login-ecr
uses: aws-actions/amazon-ecr-login@v2
- name: Build, tag, and push image
env:
ECR_REGISTRY: ${{ steps.login-ecr.outputs.registry }}
IMAGE_TAG: ${{ github.sha }}
run: |
docker build -t $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG .
docker push $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG
echo "image=$ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG" >> $GITHUB_OUTPUT
- name: Deploy to App Runner
uses: awslabs/amazon-app-runner-deploy@main
with:
service: ${{ env.APP_RUNNER_SERVICE }}
image: ${{ steps.build.outputs.image }}
region: ${{ env.AWS_REGION }}
wait-for-service-stability-seconds: 180
# In your GitHub repo:
# Settings → Secrets and variables → Actions → New secret
# Add these two secrets:
# AWS_ACCESS_KEY_ID = your AWS access key
# AWS_SECRET_ACCESS_KEY = your AWS secret key
# Then push to main and watch the Actions tab
💡
Image tagging: The workflow tags images with the git commit SHA (${{ github.sha }}). This means every deployment is traceable to the exact commit that produced it — critical for debugging production issues.
Day 5 ExerciseSet Up Your CI/CD Pipeline
- Create .github/workflows/deploy.yml with the workflow above.
- Add AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY to GitHub Secrets.
- Make a small change to your app (update a message or add a comment).
- Push to main and watch the Actions tab in GitHub.
- Once deployed, verify the change is live at your App Runner URL.
Course Complete — Production AI Deployment
- Containerized AI app that runs identically in dev and production.
- Docker Compose for local multi-service development (API + database + cache).
- AWS ECR + App Runner for managed production hosting with auto-scaling.
- GitHub Actions CI/CD that deploys on every push to main.
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