https://github.com/jackccrawford/gpu-sentinel-pro
Enterprise-grade NVIDIA GPU monitoring suite with real-time dashboard, time-series analytics, and intelligent alerts. Features React frontend, FastAPI backend, and Supabase for data persistence. Tracks utilization, memory, temperature, power with microsecond precision. Perfect for ML/AI, render farms.
https://github.com/jackccrawford/gpu-sentinel-pro
Last synced: about 2 months ago
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Enterprise-grade NVIDIA GPU monitoring suite with real-time dashboard, time-series analytics, and intelligent alerts. Features React frontend, FastAPI backend, and Supabase for data persistence. Tracks utilization, memory, temperature, power with microsecond precision. Perfect for ML/AI, render farms.
- Host: GitHub
- URL: https://github.com/jackccrawford/gpu-sentinel-pro
- Owner: jackccrawford
- License: mit
- Created: 2024-11-21T06:44:24.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-02-17T18:12:51.000Z (3 months ago)
- Last Synced: 2025-04-14T12:06:23.576Z (about 2 months ago)
- Language: Python
- Size: 34.9 MB
- Stars: 7
- Watchers: 1
- Forks: 1
- Open Issues: 23
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Security: SECURITY.md
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README
# GPU Sentinel Pro
> "Information should not be displayed all at once; let people gradually become familiar with it." - Edward Tufte
Transform GPU monitoring from complex metrics into intuitive visual patterns. Enterprise-grade NVIDIA GPU monitoring with real-time analytics, intelligent alerts, and historical analysis.
[](https://github.com/jackccrawford/gpu-sentinel-pro/actions/workflows/codeql.yml)
[](https://x.com/intent/follow?screen_name=jackccrawford)
[](https://choosealicense.com/licenses/mit/)
[](https://codeium.com)
*Real-time GPU metrics visualized for instant comprehension*
## Quick Start
### Prerequisites
- NVIDIA GPU with compute capability 3.0 or higher
- NVIDIA Driver 450.80.02 or higher
- Python 3.8+ and Node.js 16.0+
- 4GB RAM (8GB recommended)
- 1GB free disk space
### Installation
1. Clone the repository:
```bash
git clone [email protected]:jackccrawford/gpu-sentinel-pro.git
cd gpu-sentinel-pro
```
2. Set up the backend:
```bash
cd backend
python -m venv venv
source venv/bin/activate # On Windows: .\venv\Scripts\activate
pip install -r requirements.txt
```
3. Set up the frontend:
```bash
cd frontend
npm install
```
4. Start the services:
```bash
# Terminal 1 - Backend
cd backend
python src/service/app.py
# Terminal 2 - Frontend
cd frontend
npm run dev
```
5. Access the dashboard at http://localhost:5173
## Pro Features
### 🎯 Enterprise-Grade Monitoring
- **Real-time Visual Dashboard**
- Modern React components with Material UI
- Responsive design for desktop and mobile
- Dark/light mode with automatic system preference detection
- Multi-GPU support with individual monitoring panels
- **Advanced Metrics**
- Temperature and utilization with color-coded ranges
- Memory usage and bandwidth monitoring
- Power consumption and efficiency tracking
- Process-level GPU utilization
- Custom metric aggregation
### 🔔 Intelligent Alert System
- **Configurable Thresholds**
```json
{
"temperature": {
"warning": 75,
"critical": 85
},
"memory": {
"warning": 85,
"critical": 95
}
}
```
- **Alert Types**
- Temperature spikes
- Memory leaks
- Process crashes
- Power anomalies
- Custom conditions
### 📊 Analytics & Reporting
- **Historical Data**
- Time-series metrics storage
- Customizable retention policies
- Data export in multiple formats
- Trend analysis and forecasting
- **Performance Insights**
- Workload pattern recognition
- Resource utilization heatmaps
- Efficiency recommendations
- Cost analysis tools
### 🛠 Enterprise Integration
- **API Access**
- RESTful API with OpenAPI documentation
- Secure authentication
- Rate limiting and quotas
- Webhook support
- **Security**
- Role-based access control
- Audit logging
- SSL/TLS encryption
- Regular security updates
## Configuration
### Backend Settings
```python
# config.py
SETTINGS = {
'update_interval': 1000, # ms
'retention_period': '30d',
'log_level': 'INFO',
'enable_analytics': True,
'alert_cooldown': 300, # seconds
}
```
### Frontend Configuration
```typescript
// config.ts
export const CONFIG = {
API_URL: 'http://localhost:8000',
REFRESH_RATE: 1000,
THEME_MODE: 'system', // 'light' | 'dark' | 'system'
CHART_HISTORY: 300, // data points
};
```
## System Architecture
```mermaid
graph TD
A[Frontend React App] -->|HTTP/WebSocket| B[FastAPI Backend]
B -->|NVML| C[GPU Hardware]
B -->|Time Series| D[Supabase]
B -->|Alerts| E[Notification Service]
```
## Contributing
1. Fork the repository
2. Create a feature branch: `git checkout -b feature/amazing-feature`
3. Commit your changes: `git commit -m 'feat: add amazing feature'`
4. Push to the branch: `git push origin feature/amazing-feature`
5. Open a pull request
## Support
- 📚 [Documentation](docs/)
- 🐛 [Issue Tracker](https://github.com/jackccrawford/gpu-sentinel-pro/issues)
- 💬 [Discussions](https://github.com/jackccrawford/gpu-sentinel-pro/discussions)
- 📧 [Contact Support](mailto:[email protected])
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
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