API Gateway with ML

Intelligent API Gateway with Anomaly Detection using Isolation Forest

Project Overview

API Gateway with ML is a robust, scalable, and intelligent API management system that acts as a single entry point for multiple backend services. It incorporates Machine Learning (Isolation Forest) to detect anomalies and potential threats in real-time API traffic.

The project includes a modern frontend built with Next.js, a Node.js backend, a Python-based ML microservice, and PostgreSQL as the primary database. It supports both Dockerized and non-Docker deployments for maximum flexibility.

Key Features

• Centralized API routing and management
• Real-time anomaly detection using Isolation Forest ML model
• Rate limiting, authentication, and logging
• Separate Python ML microservice for high-performance inference
• Support for Docker and non-Docker environments
• PostgreSQL database for storing logs, metrics, and user data
• Scalable microservices architecture
• Comprehensive monitoring and analytics

Tech Stack

Architecture

The system is designed with modularity in mind:

• Frontend: Next.js for admin dashboard and monitoring interface
• API Gateway: Node.js + Express.js handles routing, authentication, and request validation
• ML Service: Python FastAPI service running Isolation Forest model for anomaly detection
• Database: PostgreSQL for persistent storage

Deployment Options

• Docker Compose (recommended for production-like setup)
• Non-Docker local development setup

Contribution & Collaboration

This project is open for contributions. Feel free to improve the ML model, enhance the dashboard, add new features, or optimize performance by submitting pull requests.