How We Built a Scalable Pricing Engine for E‑commerce Promotions

This article explains the design and implementation of a modular, configurable pricing engine that handles real‑time and simulated price calculations for complex e‑commerce promotions, addressing rule fragmentation, extensibility, priority conflicts, and transaction‑level precision while ensuring high performance and reliability.

Backend ArchitectureMicroservicese‑commerce

0 likes · 10 min read

How We Built a Scalable Pricing Engine for E‑commerce Promotions

NetEase Yanxuan Technology Product Team

Aug 20, 2021 · Backend Development

Design and Implementation of a Pricing Calculation Engine for E-commerce Promotions

The article details the design and implementation of a dedicated pricing calculation engine that decouples complex e‑commerce promotion logic from transaction services, using componentized rules, configurable pipelines, multi‑level caching, and lane‑based simulations to achieve high extensibility, low latency, and accurate pricing across browsing and checkout scenarios.

Configurationbackend-developmentpricing engine

0 likes · 9 min read

Design and Implementation of a Pricing Calculation Engine for E-commerce Promotions

vivo Internet Technology

Aug 18, 2021 · Backend Development

Design and Implementation of Vivo Mall Promotion Pricing Engine

The article details Vivo Mall’s new promotion pricing engine, which replaces duplicated site‑level logic with a layered model (product, shop, platform) that supports configurable stacking, processes discounts through three calculation stages, and uses a meta‑driven rule engine to flexibly interpret JSON promotion templates, ensuring extensible, stable pricing functionality.

backend-developmentdiscount modele‑commerce

0 likes · 12 min read

Design and Implementation of Vivo Mall Promotion Pricing Engine

Qunar Tech Salon

Nov 29, 2017 · Backend Development

Optimizing the Pricing Engine for High‑Volume Flight Search: Hash Sharding, Caching, and Response‑Time Improvements

This article explains how Qunar's international ticket pricing engine was optimized by redesigning hash rules for sharding, enhancing local cache replication, employing multi‑stage result delivery, and applying common distributed‑system patterns to boost computational capacity and reduce response latency for massive flight‑search workloads.

cachingflight searchpricing engine

0 likes · 8 min read

Optimizing the Pricing Engine for High‑Volume Flight Search: Hash Sharding, Caching, and Response‑Time Improvements

Qunar Tech Salon

Nov 28, 2017 · Backend Development

Optimizing the TTS Pricing Engine: From Monolithic V1 to Scalable V2 Architecture

This article details the evolution of Qunar's TTS pricing engine from a monolithic V1 implementation with dual-level caching and blocking HTTP interfaces to a scalable V2 architecture featuring service separation, asynchronous processing, CQRS-based rule storage, canal synchronization, Solr and Redis indexing, and Kafka-driven data pipelines.

CQRSSolrcaching

0 likes · 10 min read

Optimizing the TTS Pricing Engine: From Monolithic V1 to Scalable V2 Architecture

Qunar Tech Salon

Oct 25, 2017 · Backend Development

Design and Optimization of a High‑Performance Flight Search and Pricing System

This article outlines the design, challenges, and performance optimizations of a large‑scale flight search and pricing platform, covering system requirements, architecture layers, caching strategies, indexing, real‑time data synchronization, memory reduction techniques, and high‑availability solutions to handle massive, low‑latency queries.

cachingflight searchhigh availability

0 likes · 19 min read