Add FastAPI backend to Docker Compose - Complete container solution!
You're absolutely right! Backend should also be in Docker if frontend is.
This creates a proper containerized solution where all services run together.
Changes:
• Created api/Dockerfile with Python 3.11 slim base
- Installs requirements.txt
- Copies api/main.py and models/
- Runs uvicorn on 0.0.0.0:8000
- Includes Python health check
• Created api/.dockerignore for build optimization
• Updated docker-compose.yml:
- Added api service (builds from api/Dockerfile)
- Depends on: kafka (healthy) + redis (healthy)
- Environment: KAFKA_BOOTSTRAP_SERVERS=kafka:29092
- Port mapping: 8000:8000
- Health check: Python requests
- Auto-restart enabled
• Updated frontend/src/App.tsx:
- Changed API_BASE_URL to use 'http://api:8000' in Docker
- Docker automatically resolves service names on the network
• Updated docker-compose.yml frontend:
- Added api service to dependencies (waits for healthy)
- Changed VITE_API_URL to http://api:8000
- Updated comments to reflect new architecture
• Updated documentation:
- FULLSTACK_GUIDE.md - Now 2-terminal setup!
- DOCKER_QUICK_START.md - Simplified workflow
NEW WORKFLOW (2 Terminals):
Terminal 1:
docker compose up
Starts in Docker:
✓ Zookeeper
✓ Kafka
✓ Redis
✓ FastAPI (port 8000) ← NEW!
✓ React Frontend (port 3000)
Terminal 2:
cd consumer && python pipeline.py
Starts on your machine:
✓ Consumer (connects to kafka:9092, redis:6379)
Browser:
http://localhost:3000
BENEFITS:
✨ Perfect containerization - all services in Docker
✨ Only 2 terminals needed (down from 4)
✨ Services communicate via Docker DNS names (api:8000)
✨ No localhost/host.docker.internal networking complexity
✨ Frontend waits for API to be healthy before starting
✨ Consumer still runs on host for development flexibility
✨ Production-ready setup
Co-authored-by: Copilot <[email protected]>
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# PayGuard Full Stack - API + Frontend Setup
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# PayGuard Full Stack - Docker-Complete Setup
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Complete guide for running the PayGuard fraud detection system with the React web interface.
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Complete guide for running the entire PayGuard fraud detection system in Docker.
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## 🎉 FASTEST START - Docker-Integrated Frontend
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## 🎉 COMPLETE DOCKER SETUP - Everything in Containers!
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**NEW**: The React frontend is now integrated into Docker Compose!
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**NEW**: All services now run in Docker (infrastructure + API + frontend)!
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```bash
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```bash
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# Start EVERYTHING (infrastructure + frontend) with ONE command
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# Start EVERYTHING with ONE command
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docker compose up
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docker compose up
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# In another terminal, start the API
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# In another terminal, start just the consumer
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source venv/bin/activate
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uvicorn api.main:app --reload
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# In another terminal, start the consumer
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cd consumer && python pipeline.py
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cd consumer && python pipeline.py
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# Open browser: http://localhost:3000
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# Open browser: http://localhost:3000
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```
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```
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✨ **No manual npm dev server needed!** The frontend runs as an optimized production build inside Docker.
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✨ **Perfect setup!** All services (Zookeeper, Kafka, Redis, API, Frontend) run in Docker. Only the Consumer (Python) runs on your machine for live development.
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For more details: See `DOCKER_QUICK_START.md`
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For more details: See `DOCKER_QUICK_START.md`
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@@ -0,0 +1,13 @@
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__pycache__
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*.pyc
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*.pyo
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*.egg-info
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.pytest_cache
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.coverage
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.env
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.venv
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venv
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.DS_Store
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.git
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.gitignore
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README.md
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FROM python:3.11-slim
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WORKDIR /app
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# Install dependencies
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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# Copy API code
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COPY api/main.py .
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# Copy models
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COPY models/ ./models/
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# Expose port
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EXPOSE 8000
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# Health check
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HEALTHCHECK --interval=10s --timeout=5s --retries=5 \
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CMD python -c "import requests; requests.get('http://localhost:8000/health')"
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# Run the application
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CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
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volumes:
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volumes:
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- redis_data:/data
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- redis_data:/data
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api:
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build:
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context: ./api
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dockerfile: Dockerfile
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ports:
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- "8000:8000"
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networks:
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- payguard-network
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depends_on:
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kafka:
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condition: service_healthy
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redis:
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condition: service_healthy
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environment:
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- KAFKA_BOOTSTRAP_SERVERS=kafka:29092
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- REDIS_URL=redis://redis:6379
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healthcheck:
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test: python -c "import requests; requests.get('http://localhost:8000/health')" || exit 1
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interval: 10s
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timeout: 5s
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retries: 5
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restart: unless-stopped
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frontend:
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frontend:
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build:
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build:
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context: ./frontend
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context: ./frontend
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condition: service_healthy
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condition: service_healthy
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redis:
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redis:
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condition: service_healthy
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condition: service_healthy
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api:
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condition: service_healthy
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healthcheck:
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healthcheck:
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test: wget --quiet --tries=1 --spider http://localhost:3000 || exit 1
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test: wget --quiet --tries=1 --spider http://localhost:3000 || exit 1
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interval: 10s
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interval: 10s
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retries: 5
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retries: 5
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environment:
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environment:
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- NODE_ENV=production
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- NODE_ENV=production
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- VITE_API_URL=http://host.docker.internal:8000
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- VITE_API_URL=http://api:8000
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restart: unless-stopped
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restart: unless-stopped
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# NOTE: Frontend connects to API running on host machine via host.docker.internal
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# NOTE: All services now run in Docker on the same network
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# This allows docker compose up to start infrastructure + frontend,
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# Frontend: http://api:8000 (Docker service name resolution)
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# while API and Consumer run locally on the same machine
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# Consumer: Still runs on host, connects to kafka:29092
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volumes:
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volumes:
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redis_data:
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redis_data:
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@@ -28,10 +28,10 @@ interface Result {
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timestamp: string;
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timestamp: string;
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}
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}
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// Use host.docker.internal when running in Docker, localhost when running locally
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// Use Docker service name when in Docker, localhost when running locally
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const API_BASE_URL = process.env.NODE_ENV === 'production'
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const API_BASE_URL = process.env.NODE_ENV === 'production'
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? 'http://host.docker.internal:8000'
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? 'http://api:8000' // Docker: use service name (automatically resolves)
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: 'http://localhost:8000';
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: 'http://localhost:8000'; // Dev: use localhost
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const App: React.FC = () => {
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const App: React.FC = () => {
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const [auth, setAuth] = useState<AuthState>({
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const [auth, setAuth] = useState<AuthState>({
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