This article demonstrates how the Qoder AI plugin for JetBrains IDEA can transform lengthy backend tasks—such as deep‑pagination optimization and legacy code refactoring—into rapid, automated workflows, cutting development time from days to under ten minutes while preserving code quality.
The article enumerates common reasons why APIs become slow—ranging from database slow queries and complex business logic to poorly designed thread pools, locks, and machine issues—and offers concrete mitigation strategies such as query optimization, caching, asynchronous processing, and proper resource configuration.
Didi solved Hive’s MySQL metadata bottleneck by building a federation architecture—using waggle_dance to route requests to multiple MySQL instances based on database names—enabling horizontal scaling, read/write support, and seamless compatibility with existing Hive clients while improving stability and performance.
This article explores how a web system can evolve from handling 100,000 daily visits to over 100 million by implementing multi‑layered load‑balancing strategies, optimizing MySQL with indexing and connection pooling, leveraging Redis and cache clusters, and employing geographic distribution and disaster‑recovery techniques to ensure performance and reliability.
An in‑depth recap of Hong Xiaojun’s QCon presentation reveals how Meipai’s architecture evolved from a minimalist design to a highly scalable, high‑availability system, tackling MySQL bottlenecks, cache challenges, monitoring, CDN resilience, and technology migrations to support rapid growth to over a hundred million users.
