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Tencent Cloud Developer
Tencent Cloud Developer
Aug 30, 2023 · Backend Development

Redesign of a Large‑Scale Content Ingestion System: From Microservices to a Plugin‑Based Monolith

By replacing over 90 fragmented micro‑services with a single‑process, plugin‑based monolith, QQ Browser’s content ingestion pipeline achieved up to ten‑fold throughput gains, near‑100 % CPU utilization, dramatically lower latency, and an 82 % reduction in development lead‑time through modern C++ design, fault‑tolerant Kafka buffering, and streamlined CI/CD.

Backend DevelopmentCPerformance Optimization
0 likes · 21 min read
Redesign of a Large‑Scale Content Ingestion System: From Microservices to a Plugin‑Based Monolith
HelloTech
HelloTech
Jul 17, 2023 · Backend Development

Map Services SDK and Caching Strategies

The Map Services SDK unifies Haro and Gaode LBS capabilities into a single component package with full TypeScript declarations and auto‑generated VuePress documentation, adds optimized request strategies with fallback to Gaode, implements an LRU cache for high‑volume reverse‑geocoding, provides a flexible data‑conversion library, and plans online mock‑API documentation to streamline developer integration.

GeoHashLRU CacheSDK
0 likes · 9 min read
Map Services SDK and Caching Strategies
ByteFE
ByteFE
Nov 26, 2022 · Frontend Development

Curated Technical Articles on Frontend Development, High Concurrency, 3D Web, and Related Topics

This curated collection presents technical insights on plugin-based frontend design, high‑concurrency architecture, modern 3D web development, Next.js innovations, React Three Fiber particle effects, functional programming perspectives, a face‑api.js virtual avatar demo, and Base64 encoding fundamentals.

3D webNext.jsReact
0 likes · 6 min read
Curated Technical Articles on Frontend Development, High Concurrency, 3D Web, and Related Topics
vivo Internet Technology
vivo Internet Technology
Mar 17, 2021 · Artificial Intelligence

Design and Architecture of the Vivo App Store Recommendation System

The Vivo App Store recommendation system uses a modular, hot‑plug architecture—layered from plugins to base services and employing Template Method, Strategy, and Composite patterns—to integrate unchanged data sources, deliver high‑performance personalized recommendations, reduce development effort by ~75%, and enable rapid, low‑bug scene‑specific upgrades.

Vivobackend architecturepersonalization
0 likes · 12 min read
Design and Architecture of the Vivo App Store Recommendation System