Azebot
Headless e-commerce API powering an online fashion platform with complete shopping experience.
01 Project Overview
Azebot is a high-performance headless e-commerce API built to power a fashion retail platform. It provides the complete backend for product management, shopping cart, order processing, wishlist functionality, user management, and financial tracking, all exposed through a clean RESTful API consumed by the frontend application.
02 Problem Statement
The fashion brand needed a robust backend that could handle their growing online catalog, process orders reliably, manage inventory, and support a modern frontend without being tightly coupled to any particular UI framework. The solution needed to be performant, maintainable, and easy to deploy.
03 Solution Overview
A headless e-commerce architecture with Django REST Framework providing a clean API layer. The backend handles all business logic: product catalog with image management, shopping cart operations, order lifecycle, wishlist, user authentication, and financial reporting, while the frontend consumes the API independently.
04 Key Features
Product Catalog
Full product management with categories, variants, image handling via S3, pricing, and inventory tracking.
Shopping Cart
Server-side cart management with quantity updates, price calculations, and cart persistence across sessions.
Order Processing
Complete order lifecycle: placement, payment confirmation, fulfillment tracking, and order history.
Wishlist & Finances
User wishlist functionality and comprehensive financial tracking for business reporting and analytics.
05 System Architecture
06 Technology Stack
07 DevOps & Deployment
I deploy and maintain this system on AWS infrastructure. The application runs in Docker containers behind an Nginx reverse proxy. Product images are served through S3 storage. Database backups are automated, and the deployment process uses Docker Compose for consistent environment management.
08 Challenges & Solutions
Image Management at Scale
Challenge: Managing hundreds of product images efficiently. Solution: Implemented S3 storage with CDN-ready URLs, image optimization, and lazy loading support in the API responses.
API Performance
Challenge: Keeping API response times low with complex product queries. Solution: Implemented database query optimization, proper indexing, queryset prefetching, and Redis caching for frequently accessed product data.
09 Scalability & Performance
The headless architecture allows the frontend and backend to scale independently. Redis caching reduces database load for product listings. S3 offloads image serving from the application server. The API supports pagination, filtering, and search to handle large catalogs efficiently.
10 Security
JWT-based authentication with secure token management. Input validation on all endpoints. CORS configuration for frontend-only access. Secure file upload handling with type validation. Environment-based configuration for all sensitive settings.
11 Results & Impact
The API powers the Azebot Dress fashion platform in production, handling the complete product catalog, customer orders, and business operations. The headless architecture has enabled the business to iterate on their frontend independently while the backend remains stable and reliable.