E-Commerce Microservices Platform

A production-ready e-commerce platform built with a modern microservices architecture. This project demonstrates enterprise-level implementation of:

• Service mesh with gRPC inter-service communication
• Event-driven architecture using Apache Kafka
• GraphQL API gateway for unified client access
• Elasticsearch-powered product search and cataloging
• ML-based product recommendations with Python
• Container orchestration with Docker Compose

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📚 Table of Contents

• Overview
• Architecture Diagram
• Services
• Getting Started
• Usage
• Contributing
• Author
• License

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🧭 Overview

The system comprises several microservices:

• Account (Go): Manages user accounts, authentication, and authorization.
• Product (Go): CRUD for products; indexes product data in Elasticsearch.
• Order (Go): Handles order creation and persistence; publishes events to Kafka.
• Payment (Go): Handles payment operations and sends updates to order microservice
• Recommender (Python): Consumes Kafka events and builds product recommendations.
• API Gateway (Go): A GraphQL service exposing a unified API for front-end clients.

The entire ecosystem is containerized using Docker Compose. Datastores include PostgreSQL, Elasticsearch, and Kafka.

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🏗 Architecture Diagram

Below is a high-level overview of the system architecture:

Communication Overview

• API Gateway (GraphQL) talks to:

  • Account client → Account server → Postgres
  • Product client → Product server → ElasticSearch + Kafka
  • Order client → Order server → Postgres + Kafka (also communicates with Product service via gRPC)
  • Payment client → Payment service → payment provider + Postgres + Kafka
  • Recommender client → Recommender server (Python) → Postgres (Replica) + Kafka

• Event Flow:

  • Order and Product services act as Kafka producers.
  • Payment service is a Kafka consumer, ingesting product events and saving them in payment provider (DodoPayments).
  • Recommender service is also a Kafka consumer, ingesting order/product events and updating internal state for recommendations.

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⚙ Services

🧑‍💼 Account Service (Go)

• Responsibilities: Register, login, fetch account data, generate JWT tokens.
• Database: PostgreSQL

📦 Product Service (Go)

• Responsibilities: Product CRUD operations, indexing to Elasticsearch, event publishing to Kafka.
• Database: Elasticsearch

🛒 Order Service (Go)

• Responsibilities: Order creation, price calculation, data persistence, Kafka event publishing.
• Dependencies: Calls product service to retrieve product info.

🧠 Recommender Service (Python)

• Responsibilities: Kafka consumer that builds recommendations based on product/order events.
• Tech Stack: Python + gRPC + PostgreSQL (replica of product DB)

🚪 API Gateway (Go)

• Responsibilities: Unified GraphQL endpoint at /graphql.
• Implementation: Uses gRPC clients for all microservices and schema stitching.

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🚀 Getting Started

✅ Prerequisites

Before running the project, ensure you have the following installed:

• Docker & Docker Compose
• Git

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📥 Clone the Repository

git clone https://github.com/tigriscloud/go-ecommerce-api.git
cd go-ecommerce-api

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🐳 Run the Stack

To build and start all services using Docker Compose, run:

# Step 1: Build the base image
docker compose build base

# Step 2: Build and start all services
docker compose up -d --build```

This will start:

• Go microservices (account, order, product, payment, graphql)
• Python-based recommender service
• Databases: PostgreSQL, Elasticsearch
• Kafka + Zookeeper
• GraphQL gateway

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🌐 Access the API

Once everything is running, open your browser to:

• GraphQL API endpoint: http://localhost:8080/graphql
• GraphQL Playground: http://localhost:8080/playground

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📬 Usage (GraphQL)

Below are example GraphQL queries and mutations you can test in the GraphQL Playground.

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📝 Register a New Account

mutation {
  register(account: {
    name: "Alice"
    email: "alice@example.com"
    password: "secret123"
  }) {
    token
  }
}

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🔐 Login

mutation {
  login(account: {
    email: "alice@example.com"
    password: "secret123"
  }) {
    token
  }
}

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➕ Create a Product

mutation {
  createProduct(product: {
    name: "Camera"
    description: "A digital camera"
    price: 99.99
  }) {
    id
    name
  }
}

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🔍 Query Products

query {
  product(pagination: { skip: 0, take: 10 }) {
    id
    name
    price
  }
}

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🛒 Create an Order

mutation {
  createOrder(order: {
    products: [
      { id: "PRODUCT_ID", quantity: 2 }
    ]
  }) {
    id
    totalPrice
    products {
      name
      quantity
    }
  }
}

🤝 Contributing

We welcome contributions! To contribute:

Fork the repository

Create a new branch

Commit and push your changes

Open a Pull Request

� Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📝 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.