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.

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:

git clone git@github.com:jackccrawford/gpu-sentinel-pro.git
cd gpu-sentinel-pro

2. Set up the backend:

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:

cd frontend
npm install

4. Start the services:

# 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

  {
    "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

# config.py
SETTINGS = {
    'update_interval': 1000,  # ms
    'retention_period': '30d',
    'log_level': 'INFO',
    'enable_analytics': True,
    'alert_cooldown': 300,  # seconds
}

Frontend Configuration

// 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

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]

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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
• 🐛 Issue Tracker
• 💬 Discussions
• 📧 Contact Support

License

This project is licensed under the MIT License - see the LICENSE file for details.

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