SentinelOps

SentinelOps is a real-time incident management system built with FastAPI, providing RESTful APIs and WebSocket support for monitoring and managing incidents.

Features

• Incident creation, retrieval, and management
• Real-time updates via WebSocket
• RESTful API endpoints
• Database integration with SQLAlchemy
• Pydantic models for data validation
• Asynchronous operations with FastAPI
• AI-Powered Incident Analysis - Uses Google Gemini via google-genai to analyze logs and metrics for intelligent root cause analysis

Installation

1. Clone the repository:

   git clone <repository-url>
   cd SentinelOps

2. Create and activate a virtual environment:

   python -m venv env
   env\Scripts\activate  # On Windows

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables: Create a .env file in the root directory:

   GEMINI_API_KEY=your_gemini_api_key_here
   LLM_PROVIDER=gemini
   GEMINI_MODEL=gemini-3-flash-preview

Running the Application

Start the server with auto-reload:

uvicorn app.main:app --reload

The application will be available at http://localhost:8000

API Documentation

Once the server is running, visit http://localhost:8000/docs for interactive API documentation powered by Swagger UI.

WebSocket

Real-time incident updates are available via WebSocket at ws://localhost:8000/ws/incidents

AI Incident Analysis

SentinelOps includes AI-powered incident analysis that can:

• Analyze system logs and metrics
• Identify potential root causes
• Provide recommended actions
• Assess incident severity
• Generate confidence scores

Using AI Analysis

1. Automatic Analysis: Incidents created by the monitoring simulator automatically trigger AI analysis
2. Manual Analysis: Use the /incidents/analyze endpoint to analyze specific logs and metrics

Example API call:

curl -X POST "http://localhost:8000/incidents/analyze" \
  -H "Content-Type: application/json" \
  -d '{
    "logs": "[2024-01-15 10:30:45] ERROR redis: Connection timeout",
    "metrics": {
      "cpu_usage": 95,
      "memory_usage": 88,
      "api_error_rate": 0.15,
      "db_latency_ms": 2500
    }
  }'

Project Structure

• app/main.py: FastAPI application entry point
• app/api/: API route handlers
• app/core/: Core functionality (database, etc.)
• app/models/: Database models
• app/schemas/: Pydantic schemas
• app/services/: Business logic services
• app/websocket/: WebSocket handlers

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

License

This project is licensed under the MIT License.