Intelligent Network Monitoring System (INMS)

Overview

The Intelligent Network Monitoring System (INMS) is a full-stack network monitoring and outage analysis platform designed to simulate enterprise network operations. It combines real-time device monitoring, topology visualization, automated impact analysis, alert generation, and AI-assisted troubleshooting within a single dashboard.

The system continuously monitors network devices, detects failures, identifies affected downstream nodes using graph traversal algorithms, and provides diagnostic suggestions for remediation.

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Features

Network Monitoring

• Real-time device status tracking
• ICMP reachability checks
• SNMP-based telemetry collection
• Automated polling scheduler

Topology Visualization

• Interactive network topology graph
• Dynamic node status indicators
• Device relationship mapping
• Zoom and drag support

Failure Detection

• UP / SUSPECT / DOWN state machine
• Automatic outage detection
• Incident generation and tracking

Impact Analysis

• Graph-based network modeling using NetworkX
• BFS reachability analysis
• Downstream isolation detection
• Blast radius assessment

AI Incident Copilot

• Automated root cause hypotheses
• Diagnostic command recommendations
• Impact assessment summaries
• Remediation guidance

Real-Time Dashboard

• WebSocket-powered updates
• Alert feed
• Device inventory management
• Live telemetry display

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Technology Stack

Backend

• Python
• FastAPI
• SQLAlchemy
• APScheduler
• NetworkX
• PySNMP
• SQLite / PostgreSQL

Frontend

• React
• Vite
• D3.js
• Recharts

Infrastructure

• Docker
• Docker Compose
• Caddy Reverse Proxy

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Project Structure

inms/
├── backend/
│   ├── core/
│   ├── models/
│   ├── routers/
│   ├── schemas/
│   ├── services/
│   ├── tests/
│   └── main.py
│
├── frontend/
│   ├── src/
│   │   ├── components/
│   │   ├── hooks/
│   │   └── assets/
│   └── vite.config.js
│
├── docker-compose.yml
├── Caddyfile
└── .env.example

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System Architecture

Network Devices
       │
       ▼
Polling Services
(ICMP + SNMP)
       │
       ▼
Failure Detection Engine
       │
       ▼
Impact Analyzer (NetworkX)
       │
       ▼
Alert Engine
       │
       ▼
AI Incident Copilot
       │
       ▼
WebSocket Broadcast Layer
       │
       ▼
React Dashboard

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Local Setup

Backend

cd backend

python -m venv venv

# macOS / Linux
source venv/bin/activate

# Windows
venv\Scripts\activate

pip install -r requirements.txt

uvicorn main:app --reload

Backend API:

http://localhost:8000

Swagger Documentation:

http://localhost:8000/docs

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Frontend

cd frontend

npm install

npm run dev

Frontend:

http://localhost:3000

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Docker Deployment

docker-compose up --build

Open:

http://localhost

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Demonstration Scenario

1. Launch the dashboard.

2. Select agg-sw-a from the device inventory.

3. Click Kill Node.

4. Observe:

   • Device state changes to DOWN
   • Alert generated automatically
   • Downstream devices become isolated
   • AI Copilot generates troubleshooting guidance

5. Click Boot Node to restore service.

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Automated Testing

Run the backend test suite:

cd backend

pytest tests/

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Key Concepts Demonstrated

• Network Monitoring
• Failure Detection Systems
• Graph Algorithms
• Breadth-First Search (BFS)
• Network Topology Analysis
• WebSocket Communication
• FastAPI Backend Development
• React Frontend Development
• Real-Time Dashboards
• AI-Assisted Operations

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Future Enhancements

• Real device integration using SNMP
• Packet Tracer / GNS3 support
• Authentication and role management
• Historical analytics dashboard
• Predictive outage detection
• Multi-site network monitoring

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License

This project was developed for educational, research, and portfolio purposes.

Note: To run this project locally, clone the repository and follow the setup instructions provided above.