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Microservices-Based Digital eCommerce Platform

Client

Our client is one of Asia’s largest clothing retailers with over 2500 stores across the globe.

Industry

Retail

Overview

The digital eCommerce platform comprises a Single Page Application and a Mobile App with microservices architecture forming the backend. Microservices, based on Java Spring Boot were implemented for merchandising, costing, and inventory platforms. This provided the information for the frontend. REST API calls were used to communicate with each microservice and this was handled by the BFF layer (Backend for Frontend).

One of the main advantages of our code is that it can be easily configured for different regions and brands. Using the same codebase, we deployed the system in eight countries for three different brands. The code can also be customized with features specific to one country.

Performance testing revealed that our solution was able to handle twice the load when compared to the previous year. Being a global retail player, implementing Microservices resolved their biggest problems related to expansion and scaling of their IT systems, while bringing in flexibility and agility.

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Business Requirement

Our client used multiple third party systems for order management with individual deployments in regions such as Canada, China, and the United States. They faced several challenges with the existing system and wanted to replace it with an in-house, global order management system.

QBurst Solution

The microservices-based architecture provides the foundation for the digital eCommerce solution, comprising over 20 platforms that cater to all the functions of the EC store. Following is an overview of the main ones developed:

Order Fulfillment: Core, Basket, Payment, Inventory, Order History, Cost, and Sales

Frontend: CMS, SPA, Web and Mobile BFF

Customer: Account, Coupon, Newsletter, Analytics, Catalog

Store: Customer Support, Order Management, POS, and Reporting

Business Benefits

  • Performance testing revealed that the eCommerce system was able to handle twice the load compared to the previous year
  • Ability to handle up to a million requests per hour
  • Solution deployed across geographies by enabling features location-wise
  • Sales of a seasonal product increased six times in a single day
  • Increased control over inventory
  • Significant cost savings with in-house solution when compared to older system

Highlights

  • Distributed caching layer (Redis) stores a copy of data fetched from the database and other microservices, reducing the number of expensive API/database calls, and improving performance
  • Query optimization and replacement of certain libraries with those having lower processing costs improved response time
  • Optimal use of in-memory data to avoid repetitive calls to database
  • Asynchronous processing of orders ensures stability during spikes in demand
  • Server-side rendering for a few pages helped cache data and display results faster

Technologies

  • Java 11
  • Spring Batch
  • Node
  • PHP
  • Redis
  • Docker
  • Flyway
  • Spring Boot
  • Maven
  • Golang
  • Kubernetes
  • PostgreSQL
  • Kafka
  • React/Redux-Saga

Business Requirement

Our client used multiple third party systems for order management with individual deployments in regions such as Canada, China, and the United States. They faced several challenges with the existing system and wanted to replace it with an in-house, global order management system.

QBurst Solution

The microservices-based architecture provides the foundation for the digital eCommerce solution, comprising over 20 platforms that cater to all the functions of the EC store. Following is an overview of the main ones developed:

Order Fulfillment: Core, Basket, Payment, Inventory, Order History, Cost, and Sales

Frontend: CMS, SPA, Web and Mobile BFF

Customer: Account, Coupon, Newsletter, Analytics, Catalog

Store: Customer Support, Order Management, POS, and Reporting

Business Benefits

  • Performance testing revealed that the eCommerce system was able to handle twice the load compared to the previous year
  • Ability to handle up to a million requests per hour
  • Solution deployed across geographies by enabling features location-wise
  • Sales of a seasonal product increased six times in a single day
  • Increased control over inventory
  • Significant cost savings with in-house solution when compared to older system

Highlights

  • Distributed caching layer (Redis) stores a copy of data fetched from the database and other microservices, reducing the number of expensive API/database calls, and improving performance
  • Query optimization and replacement of certain libraries with those having lower processing costs improved response time
  • Optimal use of in-memory data to avoid repetitive calls to database
  • Asynchronous processing of orders ensures stability during spikes in demand
  • Server-side rendering for a few pages helped cache data and display results faster

Technologies

  • Java 11
  • Spring Batch
  • Node
  • PHP
  • Redis
  • Docker
  • Flyway
  • Spring Boot
  • Maven
  • Golang
  • Kubernetes
  • PostgreSQL
  • Kafka
  • React/Redux-Saga

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