GeoProximity – Microservices Backend (Spring Boot)

📌 Overview

GeoProximity is a Spring Boot–based microservices backend focused on geo-aware processing, asynchronous pipelines, and scalable service-to-service communication. The current repository reflects an early but solid microservices foundation, built around service discovery, Kafka-based messaging, and background workers.

This project is intentionally designed to evolve toward a location-based, event-driven platform.

---

🗂️ Repository Structure

GeoProximity/
│
├── business-service/        # Core business logic + Kafka producer
├── es-worker-service/       # Background worker (Kafka consumer / ES indexing)
├── register-server/         # Eureka Service Registry
├── README.md

---

🧠 Architectural Principles

• Microservice architecture
• Event-driven communication (Kafka)
• Loose coupling between services
• Horizontal scalability
• Clean separation of concerns

---

🏗️ High-Level Architecture

            ┌──────────────────┐
            │  Business Service │
            │ (Kafka Producer)  │
            └────────┬─────────┘
                     │
               Kafka Topics
                     │
            ┌────────▼─────────┐
            │ ES Worker Service │
            │ (Kafka Consumer)  │
            └────────┬─────────┘
                     │
             Elasticsearch (future)

        ┌─────────────────────────┐
        │     Eureka Registry      │
        │   (register-server)     │
        └─────────────────────────┘

---

🔧 Tech Stack

Core Technologies

• Java 17
• Spring Boot 3.x
• Spring Cloud Netflix Eureka
• Apache Kafka

Data & Messaging

• Kafka Producer / Consumer
• Elasticsearch (planned / external)

Dev & Infra

• Docker (planned)
• Git / GitHub

---

🧩 Microservices Description

1️⃣ register-server (Eureka Server)

Role: Service Discovery

• Central registry for all microservices
• Enables dynamic service registration
• Avoids hard-coded service URLs

Port: 8761

---

2️⃣ business-service

Role: Core business logic + event producer

Responsibilities:

• Handles main domain operations
• Produces Kafka events when business actions occur
• Acts as the entry point for future APIs

Key Features:

• Kafka producer configuration
• Clean separation between controller, service, and messaging layers

---

3️⃣ es-worker-service

Role: Asynchronous background worker

Responsibilities:

• Consumes Kafka events
• Processes data asynchronously
• Prepares data for indexing/search use cases

Typical Use Cases:

• Elasticsearch indexing
• Geo-based search preparation
• Analytics pipelines

---

📡 Event-Driven Flow (Kafka)

Example flow:

1. Business Service performs an operation
2. Event is published to Kafka
3. ES Worker Service consumes the event
4. Data is processed / indexed asynchronously

This design ensures:

• High throughput
• Non-blocking operations
• Easy extensibility with new consumers

---

🔐 Service Communication

• Services discover each other via Eureka
• Kafka decouples producers from consumers
• No direct tight coupling between services

---

🚀 Running the Project (Basic)

Prerequisites

• Java 17+
• Maven
• Kafka (local or Docker)

Run Eureka Server

cd register-server
mvn spring-boot:run

Run Business Service

cd business-service
mvn spring-boot:run

Run ES Worker Service

cd es-worker-service
mvn spring-boot:run

---

🛣️ Roadmap

• Add API Gateway
• Add Keycloak authentication
• Add Redis caching
• Integrate Elasticsearch fully
• Add geo-proximity queries
• Docker Compose setup
• Kubernetes deployment

---

👨‍💻 Author

Boutmedjet Software Engineering Student Backend & Distributed Systems

---

⭐ Notes

This repository represents a clean starting point for a scalable, geo-aware, event-driven backend. The architecture is intentionally simple but follows real-world system design principles to allow future growth.