Distributed Order Management System

A real-world, event-driven microservices system that models how large e-commerce platforms process orders using Kafka, Redis, and Spring Boot. This project demonstrates how independent services communicate asynchronously to handle order creation, inventory reservation, payment processing, and customer notifications.

This project includes a lightweight interactive web UI built with Streamlit to visualize and test the entire distributed order flow in real time. The UI allows you to place orders, track them, and observe how they move through Kafka-driven microservices — without reading logs. Use the demo UI like this

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Tech Stack

Layer	Technology
Demo Frontend	Streamlit
Backend	Spring Boot (Java)
Messaging	Apache Kafka
Cache / Inventory	Redis
Database	PostgreSQL
Containerization	Docker + Docker Compose
Serialization	JSON (Jackson)

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Microservices

1️⃣ Order Service

• Creates new orders
• Publishes order.created events
• Stores orders in PostgreSQL

2️⃣ Inventory Service

• Consumes order.created
• Reserves stock in Redis
• Publishes inventory.reserved

3️⃣ Payment Service

• Consumes inventory.reserved
• Simulates payment success/failure
• Publishes payment.success or payment.failed

4️⃣ Notification Service

• Consumes payment events
• Logs success or failure notifications

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Order Event Format

{
  "orderId": "uuid",
  "userId": "uuid",
  "totalAmount": 500,
  "items": {
    "product-id-1": 2,
    "product-id-2": 1
  }
}

Event Flow

All communication is event-driven — services never call each other directly.

How to Run

Use Demo UI

1. Running the UI

cd doms-ui
pip install -r requirements.txt
streamlit run app.py

Then open:

http://localhost:8501

2. Example Flow

Enter a User ID -> Add Product IDs & Quantities -> Click Place Order -> Click Refresh Orders -> Get Order Table

Use CLI

1. Start the system

docker compose up --build

This launches:

• Kafka
• Zookeeper
• Redis
• PostgreSQL
• All microservices

2. Create an order

curl -X POST http://localhost:8081/orders \
-H "Content-Type: application/json" \
-d '{
  "userId": "11111111-1111-1111-1111-111111111111",
  "amount": 500,
  "items": {
    "aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa": 2,
    "bbbbbbbb-bbbb-bbbb-bbbb-bbbbbbbbbbbb": 1
  }
}'

3. Verify the Flow

Watch logs:

docker logs distributed-order-management-inventory-service-1
docker logs distributed-order-management-payment-service-1
docker logs distributed-order-management-notification-service-1

You will see:

Inventory reserved
Payment success
Notification sent

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Key Design Patterns Used

• Event-Driven Architecture
• Saga-style workflow
• Loose coupling via Kafka
• Idempotent message handling
• Redis atomic operations
• Asynchronous fault-tolerant processing

Author: Abhash Kumar