🌍 Real-Time Logistics Event Streaming Platform

A production-grade event-driven microservices system for real-time supply chain telemetry — inspired by architectures used at Uber, Maersk, and FedEx.

This platform showcases scalable ingestion, stream processing, and live monitoring using Kafka, Spring Boot, MongoDB, and WebSockets.

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🚀 Tech Stack

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🏗️ System Architecture

The system is composed of loosely-coupled microservices communicating via Kafka and observed in real time through a WebSocket dashboard.

1. API Gateway (Port 8080)

• Entry point for all client requests
• Uses Spring Cloud Gateway for routing
• Works as a reverse proxy / traffic controller

2. Tracking Service — Producer (Port 8081)

• High-speed REST ingestion service
• Converts telemetry into events
• Publishes events to Kafka topics

3. Processor Service — Consumer (Port 8082)

• Subscribes to Kafka events
• Performs validation & processing
• Stores history into MongoDB
• Sends live data updates via WebSockets

4. Real-Time Dashboard

• WebSocket-powered
• Live cards and status indicators
• Displays speed, temperature, fuel & location

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✨ Key Features

✔ Real-Time Visualization on WebSockets
✔ Smart Telemetry (Temperature, Speed, Fuel)
✔ Kafka Event Streaming to absorb traffic spikes
✔ Polyglot Persistence (Kafka + MongoDB)
✔ Cloud-Native Architecture using Docker Compose

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🛠️ Local Setup & Installation

1. Prerequisites

• Docker Desktop
• Java 21
• Maven

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2. Start Infrastructure

Runs Kafka, Zookeeper, and MongoDB:

docker-compose up -d

3. Start Microservices (in order)

Service	Port	Command
Tracking Service	8081	Run TrackingServiceApplication
Processor Service	8082	Run TrackingProcessorApplication
API Gateway	8080	Run ApiGatewayApplication

4. Open Real-Time Dashboard

• http://localhost:8082/index.html

5. Send Test Telemetry

• Use Postman or curl:

 POST http://localhost:8080/api/v1/tracking
   Content-Type: application/json
   {
 "shipmentId": "VACCINE-BOX-01",
 "latitude": 40.7128,
 "longitude": -74.0060,
 "status": "IN_TRANSIT",
 "temperature": -5.0,
 "speed": 80.0,
 "fuelLevel": 90.0
 }

📁 Project Structure

    📦 project-root
    ├── api-gateway/           # Spring Cloud Gateway
    ├── tracking-service/      # REST → Kafka producer
    ├── tracking-processor/    # Kafka consumer → Mongo/WebSocket
    ├── docker-compose.yml     # Infrastructure setup
    └── README.md

⭐ Future Enhancements

• Add Prometheus + Grafana monitoring
• Add distributed tracing with OpenTelemetry
• Add GeoJSON map-based visualization