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This article explains how to design a backend architecture that pre‑generates article HTML with FreeMarker, stores files on cloud servers, caches data in Redis and local memory, and uses LVS, Nginx, and Sentinel to safely handle sudden traffic spikes from viral news.
The article outlines a comprehensive, multi‑layer architecture—including DNS routing, L4/L7 load balancing, micro‑service or monolithic deployment, caching, database sharding, hybrid‑cloud deployment, elastic scaling, and tiered degradation—to reliably support systems handling from millions to billions of daily active users under sudden traffic spikes.
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The article details JD.com's technical strategies for scaling product detail pages under massive traffic, covering service decomposition, KV‑based dynamic rendering with Nginx+Lua, unified service gateways, isolation, caching, monitoring, degradation, and performance testing to achieve sub‑50 ms response times.
The article explains why high‑traffic web pages need robust fallback and disaster‑recovery mechanisms, outlines common failure scenarios, and presents practical solutions such as request retries, local caching, backup interfaces, and hard‑coded data with illustrative JavaScript code.
The article explains why adding servers and shifting traffic, often dismissed as low‑effort tricks, actually require substantial architectural planning, state management, load balancing, sharding, and multi‑datacenter coordination to reliably handle high‑traffic scenarios.