payguard-poc

4 Commits 1 Branch 0 Tags

2 Commits

Include renames

Author	SHA1	Message	Date
John Patrick TeruelandCopilot	e169bc8b36	Add React frontend to Docker Compose - Created frontend/Dockerfile with multi-stage build for optimized production bundle - Created frontend/.dockerignore to exclude node_modules and build artifacts - Added frontend service to docker-compose.yml with: - Auto-build from frontend/Dockerfile - Port 3000 mapping - Health checks (wget to http://localhost:3000) - Dependency on healthy Kafka and Redis - Production environment (NODE_ENV=production) - Auto-restart on failure - Proper network connectivity - Created DOCKER_QUICK_START.md with simplified setup guide: - Single docker compose up starts infrastructure + frontend - Cleaner workflow (2-3 terminals instead of 4) - Production-like testing (not dev mode) - Complete troubleshooting section - Updated FULLSTACK_GUIDE.md to highlight Docker-integrated frontend - Frontend now runs as optimized 63KB gzip production build in Docker All components now start together: docker compose up # Infrastructure + React frontend (Docker) uvicorn api.main:app # API (your terminal) python pipeline.py # Consumer (your terminal) Access frontend at: http://localhost:3000 Co-authored-by: Copilot <[email protected]>	2026-04-24 19:58:44 +08:00
John Patrick TeruelandCopilot	aa4dd497e2	Initial PayGuard fraud detection system implementation - Complete dual-layer architecture for fraud detection - Phase 1: Docker Compose infrastructure (Kafka, Zookeeper, Redis) - Phase 2: Mock ML models (Layer 1 fast, Layer 2 deep) - Phase 3: FastAPI transaction ingestion with JWT auth - Phase 4: Kafka consumer pipeline with feature extraction - Phase 5: Test transaction producer with demo scenarios - Phase 6: Clean code structure and comprehensive documentation - Phase 7: End-to-end validation and demo readiness Demonstrates key system design patterns: - Microservices architecture with decoupled components - Asynchronous event processing via Kafka - Tiered decision-making (fast path vs deep analysis) - Resilience patterns (circuit breaker for graceful degradation) - Behavioral profiling with Redis caching Ready for academic demonstration with clear pipeline observability. Co-authored-by: Copilot <[email protected]>	2026-04-24 19:47:18 +08:00

Author

SHA1

Message

Date

John Patrick TeruelandCopilot

e169bc8b36

Add React frontend to Docker Compose

- Created frontend/Dockerfile with multi-stage build for optimized production bundle
- Created frontend/.dockerignore to exclude node_modules and build artifacts
- Added frontend service to docker-compose.yml with:
  - Auto-build from frontend/Dockerfile
  - Port 3000 mapping
  - Health checks (wget to http://localhost:3000)
  - Dependency on healthy Kafka and Redis
  - Production environment (NODE_ENV=production)
  - Auto-restart on failure
  - Proper network connectivity
- Created DOCKER_QUICK_START.md with simplified setup guide:
  - Single docker compose up starts infrastructure + frontend
  - Cleaner workflow (2-3 terminals instead of 4)
  - Production-like testing (not dev mode)
  - Complete troubleshooting section
- Updated FULLSTACK_GUIDE.md to highlight Docker-integrated frontend
- Frontend now runs as optimized 63KB gzip production build in Docker

All components now start together:
  docker compose up      # Infrastructure + React frontend (Docker)
  uvicorn api.main:app   # API (your terminal)
  python pipeline.py     # Consumer (your terminal)

Access frontend at: http://localhost:3000

Co-authored-by: Copilot <[email protected]>

2026-04-24 19:58:44 +08:00

John Patrick TeruelandCopilot

aa4dd497e2

Initial PayGuard fraud detection system implementation

- Complete dual-layer architecture for fraud detection
- Phase 1: Docker Compose infrastructure (Kafka, Zookeeper, Redis)
- Phase 2: Mock ML models (Layer 1 fast, Layer 2 deep)
- Phase 3: FastAPI transaction ingestion with JWT auth
- Phase 4: Kafka consumer pipeline with feature extraction
- Phase 5: Test transaction producer with demo scenarios
- Phase 6: Clean code structure and comprehensive documentation
- Phase 7: End-to-end validation and demo readiness

Demonstrates key system design patterns:
- Microservices architecture with decoupled components
- Asynchronous event processing via Kafka
- Tiered decision-making (fast path vs deep analysis)
- Resilience patterns (circuit breaker for graceful degradation)
- Behavioral profiling with Redis caching

Ready for academic demonstration with clear pipeline observability.

Co-authored-by: Copilot <[email protected]>

2026-04-24 19:47:18 +08:00