initial project setup

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glenn schrooyen
2025-09-11 22:08:12 +02:00
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# LabFusion Development Progress
## Project Overview
LabFusion is a unified dashboard and integration hub for homelab services, built with a polyglot microservices architecture.
## Architecture Decisions
- **Modular Services**: Each service is independently deployable
- **Polyglot**: Services can use different languages (Java, Python, Go, Node.js)
- **Message Bus**: Redis for inter-service communication
- **Database**: PostgreSQL for persistent data
- **Containerization**: Docker for all services
## Completed Tasks ✅
### Phase 1: Project Structure & Foundation
- [x] **Project Structure Setup** (2024-11-09)
- Created modular `services/` directory structure
- Moved from `backend/` to `services/` for better modularity
- Each service has its own directory with independent Docker setup
- [x] **API Gateway Service** (2024-11-09)
- Java Spring Boot application
- JPA entities for User, Dashboard, Widget, Event, DeviceState
- REST controllers for dashboard management
- PostgreSQL integration
- Redis message bus support
- JWT authentication framework
- [x] **Service Adapters** (2024-11-09)
- Python FastAPI application
- Integration endpoints for Home Assistant, Frigate, Immich, n8n
- Redis event publishing
- Configurable service connections
- Mock data for development
- [x] **Frontend Dashboard** (2024-11-09)
- React application with Ant Design
- System metrics visualization
- Service status monitoring
- Settings configuration
- Responsive design
- [x] **Infrastructure Setup** (2024-11-09)
- Docker Compose for production and development
- PostgreSQL database configuration
- Redis message bus setup
- Environment configuration templates
- [x] **Documentation** (2024-11-09)
- Comprehensive README with setup instructions
- Service-specific README files
- Progress tracking document
- Updated project structure documentation
## Current Status 🚧
### Services Directory Structure
```
services/
├── api-gateway/ # Java Spring Boot (Port 8080) ✅
├── service-adapters/ # Python FastAPI (Port 8000) ✅
├── metrics-collector/ # Go service (Port 8081) 🚧
└── notification-service/ # Node.js service (Port 8082) 🚧
```
### Infrastructure
- **Database**: PostgreSQL (Port 5432) ✅
- **Message Bus**: Redis (Port 6379) ✅
- **Frontend**: React (Port 3000) ✅
- **Containerization**: Docker Compose ✅
## Next Steps 🎯
### Phase 2: Service Implementation
- [ ] **Metrics Collector Service** (Go)
- Implement Docker API integration
- Add Prometheus metrics collection
- Create Redis publishing mechanism
- Add configuration management
- [ ] **Notification Service** (Node.js/TypeScript)
- Implement notification channels (email, webhook, push)
- Create alert rule engine
- Add notification preferences
- Integrate with Redis for event processing
### Phase 3: Real Service Integrations
- [ ] **Home Assistant Integration**
- Implement actual HA API calls
- Add WebSocket support for real-time updates
- Create entity state synchronization
- [ ] **Frigate Integration**
- Implement Frigate API integration
- Add event processing and filtering
- Create detection timeline visualization
- [ ] **Immich Integration**
- Implement Immich API calls
- Add photo metadata processing
- Create asset management features
### Phase 4: Advanced Features
- [ ] **Real-time Updates**
- WebSocket implementation for live data
- Event streaming from Redis
- Frontend real-time UI updates
- [ ] **Data Correlation Engine**
- Cross-service event correlation
- Timeline analysis
- Pattern detection
- [ ] **Authentication & Security**
- JWT token implementation
- User management
- Role-based access control
### Phase 5: Production Readiness
- [ ] **Monitoring & Logging**
- Centralized logging
- Health checks
- Performance monitoring
- [ ] **CI/CD Pipeline**
- GitHub Actions setup
- Automated testing
- Deployment automation
- [ ] **Kubernetes Migration**
- Helm charts
- Kubernetes manifests
- Production deployment
## Development Notes
### Service Independence
Each service is designed to be:
- Independently deployable
- Language-agnostic
- Self-contained with its own dependencies
- Communicating via Redis message bus
### Future Service Additions
The modular structure allows for easy addition of new services:
- **Data Processing Service** (Rust) - For heavy data processing
- **ML Service** (Python) - For machine learning features
- **API Gateway v2** (Go) - For high-performance routing
- **Cache Service** (C++) - For high-performance caching
## Technical Debt
- [ ] Add comprehensive error handling
- [ ] Implement proper logging across all services
- [ ] Add unit and integration tests
- [ ] Create API documentation with OpenAPI/Swagger
- [ ] Add health check endpoints for all services
## Resources
- [Project Specifications](specs.md)
- [Project Structure](structure.txt)
- [Main README](../README.md)

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# Project Specification: **LabFusion**
## 1. Purpose & Goals
* Provide a **unified application** that integrates data and metrics from multiple homelab services (Home Assistant, Frigate, Immich, n8n, etc.).
* Enable creation of **dashboards** that visualize system and service performance (CPU, RAM, storage, uptime, etc.).
* Support **data mashups** (cross-service insights, e.g., "Frigate detected a person → check HA presence → enrich with Immich images").
* Serve as a **learning playground** for:
* Running **polyglot microservices** (Python, Java/Spring, modern frontend).
* Hosting everything with **Docker Compose** (extendable to Kubernetes later).
* Building **APIs and integrations** across services.
---
## 2. User Stories
### Core / First Iteration
* As a homelab owner, I want to see a **system dashboard** that shows CPU, RAM, and storage usage of all devices (Docker host, NAS, etc.).
* As a homelab owner, I want to see the **status of each service** (running, uptime, logs, alerts).
* As a homelab owner, I want to have a **dashboard builder** (predefined widgets like charts, tables, logs).
### Advanced / Later Iterations
* As a homelab owner, I want to **combine service data** (e.g., Frigate face detection + HA presence info).
* As a homelab owner, I want **notifications** (e.g., service down, high CPU, suspicious camera activity).
* As a homelab owner, I want the app to expose an **API layer** that other tools (like n8n) can consume.
---
## 3. Functional Requirements
1. **System Monitoring**
* Collect metrics from Docker hosts & containers (CPU, memory, disk, network).
* Display service health (via APIs, logs, or container status).
2. **Service Integrations**
* **Home Assistant**: read entity states via its REST/WebSocket API.
* **Frigate**: consume event data (detections, timelines).
* **Immich**: access image metadata (faces, tags, time).
* **n8n**: optional integration (trigger workflows from events).
3. **Dashboards**
* Modular widget-based UI (charts, tables, cards).
* Configurable dashboards (JSON schema for layout).
* Examples:
* Host performance overview.
* Container uptime.
* HA device states.
* Frigate detections timeline.
4. **Data Correlation (Phase 2)**
* Join data across services.
* Example: *Frigate detected “Alice” at 18:42 → HA shows Alices phone connected → Confirm Alice was home.*
---
## 4. Non-Functional Requirements
* **Performance**: Handle \~1000 events/day without lag.
* **Scalability**: Add more services without rewriting core.
* **Security**: Local auth (JWT/OAuth2), role-based access (later).
* **Resilience**: Auto-restart containers, graceful error handling.
* **Extensibility**: Plugin-like integration architecture.
---
## 5. System Architecture
* **Frontend (React, Vue, or Svelte)**
* Dashboard UI (charts, cards, widgets).
* Talks to backend via REST/WebSocket API.
* **Backend (polyglot)**
* **Java/Spring Boot**: Core API gateway, auth, user management.
* **Python FastAPI**: Service integration adapters (HA, Frigate, Immich).
* **Shared Message Bus** (e.g., Redis, Kafka, or RabbitMQ): decouple services.
* **Database**: PostgreSQL (persistent config, dashboards, event history).
* **Dockerized Deployment**
* Each component in its own container.
* Docker Compose orchestrates services.
* Future upgrade path: Kubernetes.
---
## 6. Data Model (simplified)
* **User** (id, username, roles).
* **Dashboard** (id, name, layout, widgets).
* **Widget** (id, type, config, service binding).
* **Event** (timestamp, service, type, metadata).
* **Device/Service State** (timestamp, entity\_id, value).
---
## 7. Deployment & Operations
* **Docker Compose stack** (frontend, Spring API, FastAPI adapters, DB, Redis).
* CI/CD pipeline (GitHub Actions).
* Monitoring (Prometheus + Grafana, optional since youre building dashboards).
* Config via `.env` or centralized config service.
---
## Roadmap
* **Iteration 1**: Build basic dashboards with host & container metrics.
* **Iteration 2**: Add service integrations (HA, Frigate).
* **Iteration 3**: Implement cross-service correlations (the "Alice detection" scenario).
* **Iteration 4**: Add notifications & automations.
---
## Project Title
**LabFusion** a unified dashboard and integration hub for your homelab.

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labfusion/
├── docker-compose.yml # Production Docker setup
├── docker-compose.dev.yml # Development Docker setup
├── env.example # Environment configuration template
├── .gitignore # Git ignore rules
├── README.md # Comprehensive documentation
├── services/ # Modular microservices
│ ├── api-gateway/ # Java Spring Boot API Gateway (Port 8080)
│ │ ├── src/main/java/com/labfusion/
│ │ │ ├── model/ # JPA entities (User, Dashboard, Widget, Event, DeviceState)
│ │ │ ├── repository/ # Data repositories
│ │ │ ├── service/ # Business logic
│ │ │ └── controller/ # REST controllers
│ │ ├── src/main/resources/
│ │ │ └── application.yml # Spring configuration
│ │ ├── pom.xml # Maven dependencies
│ │ ├── Dockerfile # Production container
│ │ ├── Dockerfile.dev # Development container
│ │ └── README.md # Service documentation
│ ├── service-adapters/ # Python FastAPI Service Adapters (Port 8000)
│ │ ├── main.py # FastAPI application
│ │ ├── requirements.txt # Python dependencies
│ │ ├── Dockerfile # Production container
│ │ ├── Dockerfile.dev # Development container
│ │ └── README.md # Service documentation
│ ├── metrics-collector/ # Go Metrics Collector (Port 8081) 🚧
│ │ ├── main.go # Go application (planned)
│ │ ├── go.mod # Go dependencies (planned)
│ │ ├── Dockerfile # Production container (planned)
│ │ ├── Dockerfile.dev # Development container (planned)
│ │ └── README.md # Service documentation
│ └── notification-service/ # Node.js Notification Service (Port 8082) 🚧
│ ├── src/ # TypeScript source (planned)
│ ├── package.json # Node.js dependencies (planned)
│ ├── Dockerfile # Production container (planned)
│ ├── Dockerfile.dev # Development container (planned)
│ └── README.md # Service documentation
├── frontend/ # React Frontend (Port 3000)
│ ├── src/
│ │ ├── components/ # React components
│ │ │ ├── Dashboard.js # Main dashboard
│ │ │ ├── SystemMetrics.js # Metrics visualization
│ │ │ └── Settings.js # Configuration UI
│ │ ├── App.js # Main app component
│ │ ├── index.js # App entry point
│ │ └── index.css # Global styles
│ ├── public/
│ │ └── index.html # HTML template
│ ├── package.json # Node.js dependencies
│ ├── Dockerfile # Production container
│ └── Dockerfile.dev # Development container
└── docs/ # Documentation
├── specs.md # Project specifications
├── structure.txt # Project structure
└── progress.md # Development progress tracking