📡 R.A.D.A.R - Real-time Anomaly Detection & Response

RADAR is a next-generation security monitoring tool that uses Autoencoders (Deep Learning) to detect anomalies in system logs in real-time.

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🏗️ Architecture

The system is built as a Microservices Architecture:

Service	Badge	Description	Port
Web Service	services/web	Flask UI, Dashboard, and MongoDB Connector	5000
ML Service	services/ml	PyTorch Autoencoder Inference Engine	5001

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🚀 Quick Start (No Docker Required)

If you just want to run the app immediately without installing extra tools:

Prerequisites

• Python 3.9+
• MongoDB URI (Pre-configured in config/settings.py)

Run the Script

We have included a helper script that installs dependencies and launches both services.

.\run_locally.ps1

Note: Open http://localhost:5000 in your browser.

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🐳 Run with Docker (Recommended)

For a production-grade, isolated environment.

1. Install Docker Desktop
2. Run the composition:

docker-compose up --build

The services will orchestrate automatically.

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☁️ Deployment

Render.com (Free Tier)

This project is configured for Render.

1. Connect your GitHub repository.
2. Create Web Services for radar-ml and radar-web.
3. See DEPLOYMENT.md for step-by-step free tier instructions.

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🛠️ Tech Stack

• Backend: Flask, Python
• ML Engine: PyTorch, Scikit-Learn, Sentence-Transformers
• Database: MongoDB Atlas (Cloud)
• Frontend: HTML5, CSS3, Vanilla JS (Dark Mode Optimized)

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Created by CyberMetrics