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feat: add new dev workflow
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‎.github/workflows/dev-release.yml‎

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# This workflow will build and push a new container image to Amazon ECR,
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# and then will deploy a new task definition to Amazon ECS, when a release is created
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#
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# To use this workflow, you will need to complete the following set-up steps:
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#
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# 1. Create an ECR repository to store your images.
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# For example: `aws ecr create-repository --repository-name my-ecr-repo --region us-east-2`.
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# Replace the value of `ECR_REPOSITORY` in the workflow below with your repository's name.
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# Replace the value of `aws-region` in the workflow below with your repository's region.
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#
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# 2. Create an ECS task definition, an ECS cluster, and an ECS service.
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# For example, follow the Getting Started guide on the ECS console:
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# https://us-east-2.console.aws.amazon.com/ecs/home?region=us-east-2#/firstRun
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# Replace the values for `service` and `cluster` in the workflow below with your service and cluster names.
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#
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# 3. Store your ECS task definition as a JSON file in your repository.
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# The format should follow the output of `aws ecs register-task-definition --generate-cli-skeleton`.
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# Replace the value of `task-definition` in the workflow below with your JSON file's name.
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# Replace the value of `container-name` in the workflow below with the name of the container
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# in the `containerDefinitions` section of the task definition.
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#
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# 4. Store an IAM user access key in GitHub Actions secrets named `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY`.
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# See the documentation for each action used below for the recommended IAM policies for this IAM user,
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# and best practices on handling the access key credentials.
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name: Deploy App
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on:
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push:
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branches:
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- dev-release
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name: Deploy to Amazon ECS
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branches: [ dev-release ]
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jobs:
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deploy:
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name: Deploy
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runs-on: [self-hosted, linux, dev, prod]
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build-and-deploy:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout
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uses: actions/checkout@v2
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- name: Checkout code
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uses: actions/checkout@v4
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# Configure Docker Buildx to allow efficient caching
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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# Cache Docker layers to speed up future builds
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- name: Cache Docker layers
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uses: actions/cache@v3
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with:
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path: /tmp/.buildx-cache
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key: ${{ runner.os }}-buildx-${{ github.sha }}
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restore-keys: |
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${{ runner.os }}-buildx-
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- name: Configure AWS credentials
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uses: aws-actions/configure-aws-credentials@v1
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- name: Build and Export Image
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uses: docker/build-push-action@v5
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with:
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aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
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aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
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aws-region: eu-central-1
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context: .
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file: Dockerfile
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platforms: linux/amd64
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tags: superdapp-python-api-dev:latest
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outputs: type=docker,dest=/tmp/image.tar
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cache-from: type=local,src=/tmp/.buildx-cache
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cache-to: type=local,dest=/tmp/.buildx-cache-new,mode=max
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- name: Login to Amazon ECR
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id: login-ecr
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uses: aws-actions/amazon-ecr-login@v1
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# Compress the image for faster upload and move to root folder
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- name: Gzip Image and Move
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run: |
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gzip -9 /tmp/image.tar
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mv /tmp/image.tar.gz ./
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# Install AWS CLI (For local act runner)
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- name: Install AWS CLI (For local act runner)
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run: |
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if ! command -v aws &> /dev/null; then
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sudo apt-get update && sudo apt-get install -y awscli
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fi
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- name: Build, tag, and push image to Amazon ECR
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id: build-image
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# Download the environment variables from Hetzner Object Storage
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- name: Download .env from Hetzner S3
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env:
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ECR_REGISTRY: ${{ steps.login-ecr.outputs.registry }}
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ECR_REPOSITORY: superdapp-python-dev
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IMAGE_TAG: latest
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AWS_ACCESS_KEY_ID: ${{ secrets.HETZNER_ACCESS_KEY }}
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AWS_SECRET_ACCESS_KEY: ${{ secrets.HETZNER_SECRET_KEY }}
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AWS_REGION: eu-central-1 # Change to your preferred Hetzner region (e.g., fsn1, nbg1)
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run: |
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# Build a docker container and
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# push it to ECR so that it can
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# be deployed to ECS.
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docker build -t $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG .
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docker push $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG
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echo "::set-output name=image::$ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG"
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- name: Fill in the new image ID in the Amazon ECS task definition
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id: task-def
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uses: aws-actions/amazon-ecs-render-task-definition@v1
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aws s3 cp s3://superdapp-env-files/superdapp-python-dev.env .env \
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--endpoint-url https://hel1.your-objectstorage.com
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- name: Transfer Files to VPS
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uses: appleboy/scp-action@v0.1.7
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with:
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task-definition: ecs-dev-release-task-definition.json
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container-name: superdapp-python-dev
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image: ${{ steps.build-image.outputs.image }}
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host: ${{ secrets.DEV_HOST }}
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username: ${{ secrets.USER }}
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key: ${{ secrets.SSH_DEV_PRIVATE_KEY }}
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# Send the image, the updated docker-compose.dev.yml AND the downloaded .env file
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source: "image.tar.gz,docker-compose.dev.yml,.env"
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target: "~/superdapp-python-api-dev"
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- name: Deploy Amazon ECS task definition
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uses: aws-actions/amazon-ecs-deploy-task-definition@v1
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- name: Remote Deploy
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uses: appleboy/ssh-action@v1.0.3
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with:
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task-definition: ${{ steps.task-def.outputs.task-definition }}
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service: superdapp-python-dev
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cluster: dev
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wait-for-service-stability: true
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host: ${{ secrets.DEV_HOST }}
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username: ${{ secrets.USER }}
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key: ${{ secrets.SSH_DEV_PRIVATE_KEY }}
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script: |
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cd ~/superdapp-python-api-dev
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# Load the new image
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gunzip -c image.tar.gz | docker load
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# Restart the service leveraging the custom file name
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docker compose -f docker-compose.dev.yml up -d
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# Cleanup: Remove the tar file and old/dangling images
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rm image.tar.gz
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docker image prune -f
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# Buildx cache management (cleanup required for GitHub Actions)
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- name: Move cache
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run: |
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rm -rf /tmp/.buildx-cache
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mv /tmp/.buildx-cache-new /tmp/.buildx-cache

‎docker-compose.dev.yml‎

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services:
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api:
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image: superdapp-python-api-dev:latest
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container_name: python-api-dev
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restart: unless-stopped
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env_file:
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- .env
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networks:
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- traefik-net
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labels:
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- "traefik.enable=true"
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- "traefik.http.routers.python-api.rule=Host(`python-api.superdapp.dev`)"
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- "traefik.http.routers.python-api.entrypoints=websecure"
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- "traefik.http.routers.python-api.tls=true"
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- "traefik.http.routers.python-api.tls.certresolver=letsencrypt"
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- "traefik.http.services.python-api.loadbalancer.server.port=80"
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- "traefik.docker.network=traefik-net"
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deploy:
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resources:
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limits:
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cpus: '0.50'
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memory: 2048M
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reservations:
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cpus: '0.25'
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memory: 512M
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networks:
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traefik-net:
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external: true
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name: traefik-net

‎main.py‎

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]
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app = FastAPI()
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@app.get("/")
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async def root():
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return {"status": "ok", "message": "SuperDapp Python API is running"}
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# Initialize logging
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LOGFILE_PATH = os.path.join(os.path.dirname(
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os.path.abspath(__file__)), 'app.log')

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