This guide walks through practical techniques to push MySQL performance from a few thousand to tens of millions of queries per second, covering single‑node tuning, read/write splitting, caching layers, and horizontal/vertical sharding with concrete configuration tips and architecture diagrams.
This article explains why a million‑QPS flood can cripple systems, outlines attackers' tactics, and presents a three‑layer defense strategy—including gateway rate limiting with Nginx + Lua, distributed circuit breaking via Sentinel, device fingerprinting, behavior analysis, and a dynamic rule engine—to protect high‑traffic services.
The article presents the Universal Recommendation Model (URM), a large‑language‑model‑based recall framework that integrates world knowledge and e‑commerce expertise through knowledge injection and prompt‑driven alignment, achieving significant offline recall gains and a 3.1% increase in ad consumption while meeting high‑QPS, low‑latency production constraints.
RTAMS‑GANNS, the award‑winning real‑time adaptive multi‑stream GPU system for online approximate nearest neighbor search, eliminates costly memory allocations and serial execution by using a dynamic memory‑block insertion algorithm and separate CUDA streams, cutting latency by 40‑80% and reliably serving over 100 million daily users in production.
This article summarizes the challenges and optimization techniques for building a high‑performance long‑connection service with Netty, covering non‑blocking I/O, Linux kernel tuning, client‑side testing, VM‑based scaling, data‑structure tweaks, CPU and GC bottlenecks, and the final results of achieving hundreds of thousands of connections and tens of thousands of QPS on a single server.
This article explores how naive timestamp retrieval can become a CPU bottleneck under high concurrency, demonstrates cache‑based optimizations used in Alibaba's Cobar and Sentinel projects, presents benchmark results, and proposes an adaptive algorithm to enable or disable caching based on real‑time QPS.
The Xianyu fan‑tag system solves the challenge of displaying full‑history purchase counts with real‑time updates and low‑latency, high‑throughput queries by daily exporting multi‑system data to a LevelDB‑based KV store, converting schemas, and applying real‑time compensation from transaction and follow‑change messages, merging offline and live data to produce sorted fan lists at ~10 k QPS.
This article details ByteDance's wallet asset middle platform designed for the 2022 Spring Festival, covering eight‑app reward interoperability, high‑QPS challenges, token‑based asynchronous入账, budget control, stability measures, and fund‑safety guarantees, and includes practical solutions for hot‑key handling, budget throttling, and multi‑stage activity isolation.
This article details a step‑by‑step engineering experiment that reproduces a high‑throughput "red‑envelope" service, outlining the required hardware, software stack, load‑generation logic, monitoring setup, and performance results for handling up to 6 000 QPS on a 100‑million‑user scale.
This article details a step‑by‑step engineering effort to model and benchmark a high‑throughput red‑packet service capable of handling 10 billion requests, covering target metrics, hardware setup, Go implementation, load generation, monitoring, and performance analysis.
This article describes how to design, implement, and evaluate a scalable backend that can simulate 10 billion WeChat red‑envelope requests by supporting up to 1 million concurrent users and handling 30 k–60 k QPS per server using Go, Linux tools, and custom monitoring.
The article describes how a Go‑based high‑throughput service was tuned from 80k to over 200k QPS by enlarging the GC heap, reusing UDP connections with sync.Pool, reducing system‑call overhead, and applying several lightweight logging and discovery optimizations.
This article explains the concept of soft‑start in performance testing, presents Java implementations for both fixed‑thread and fixed‑QPS models, discusses error‑impact considerations, and provides practical code snippets to gradually ramp up load and improve measurement accuracy for high‑throughput services.
This article describes a backend architecture for a high‑traffic e‑commerce project, detailing a cache access component and a cache update platform that use asynchronous messaging, hotspot‑key handling, versioned cache entries, and Redis to achieve low latency, high QPS support and strong data consistency.
Meituan’s DSP system boosted high‑QPS ad serving performance by layering an LRU cache in front of Redis, then adding time‑based eviction, sharding the cache into HashLruCache instances to cut lock contention, and employing a zero‑copy, reference‑counted design, ultimately cutting average latency to about 20 % of the original and similarly reducing 99.9th‑percentile delays.
