0 views collected around this technical thread.
Cloudflare built Pingora, a Rust‑based HTTP proxy that processes over a trillion daily requests, to overcome Nginx's architectural limits, achieve higher performance, lower resource usage, and add features unavailable in the legacy stack.
This article explains why a Golang service running on AWS EC2 failed to use the system‑level DNS cache provided by nscd, causing excessive DNS queries that triggered request timeouts, and describes the investigation and optimization steps that resolved the issue.
This article examines three strategies for checking username uniqueness at massive scale—direct database queries, Redis caching, and Bloom filter techniques—detailing their implementations, performance trade‑offs, memory consumption, and suitability for billions of users.
This guide walks backend developers through a step‑by‑step approach to handle sudden 100‑fold traffic spikes, covering emergency response, traffic analysis, robust system design, scaling techniques, circuit breaking, message queuing, and stress testing to keep services resilient and performant.
This comprehensive guide explains the nature of high concurrency, distinguishes it from parallelism, outlines its potential consequences across application, database, and service layers, and presents a systematic set of mitigation strategies—including rate limiting, asynchronous processing, redundancy, caching, and queue‑based designs—supported by real‑world case studies and code examples.
This article presents a comprehensive set of backend optimization strategies—including batch processing, asynchronous execution, caching, pre‑processing, pooling, parallelism, indexing, transaction management, program refactoring, pagination, SQL tuning, and fine‑grained locking—to dramatically reduce API latency and improve system efficiency.
This article explains what constitutes high concurrency for Nginx, outlines the hardware and software factors that affect its performance, and provides concrete configuration examples such as worker_processes, worker_connections, and other tuning directives to help achieve stable high‑traffic handling.
The article explains how TLS handshakes significantly increase request size and upstream bandwidth consumption in high‑concurrency services, demonstrates the bandwidth calculations, and proposes using plain HTTP or Keep‑Alive connections to reduce overhead and server load.
This article explains cache prewarming—its purpose, benefits, and various strategies such as startup loading, scheduled tasks, manual triggers, and cache loaders—while providing concrete Spring Boot and Redis examples, including code snippets for ApplicationReadyEvent, CommandLineRunner, InitializingBean, @PostConstruct, @Scheduled, and Caffeine cache loader.
This article documents the investigation of a JSF asynchronous call timeout that reduced interface availability, explains the async call mechanisms, analyzes the root cause in the callback thread pool, and presents short‑term and long‑term solutions to restore 100% availability.
Distributed tracing helps reconstruct the call chain of a request across multiple services and machines, providing insights into latency, errors, and performance; this article explains tracing concepts, OpenTracing standards, and how SkyWalking implements automatic span collection, context propagation, unique trace IDs, sampling, and its architecture and performance advantages.
To eliminate the brief latency spike that occurs when new Dubbo services start, the authors introduce a @Warmup annotation and early‑startup listeners that generate mock traffic and trigger a forced GC before publishing, cutting initial response times from seconds to tens of milliseconds and improving reliability for latency‑sensitive applications.
This article explains what caching is, outlines various cache types, analyzes common high‑traffic cache issues such as penetration, breakdown, avalanche, and hot‑key handling, and presents real‑world architectures from Weibo and Zhihu to illustrate effective cache design and operation.
This article examines common timeout problems in microservice architectures, identifies root causes such as connection and socket timeouts, and presents ten practical optimization techniques—including setting appropriate timeouts, rate limiting, cache improvements, thread‑pool tuning, GC and JIT adjustments, NIO async programming, host migration, and network checks—to enhance system stability and performance.
This article explains the fundamentals of cache systems, describes the evolution from no‑cache to distributed and local caches, analyzes common challenges such as consistency, hot‑key detection, and cache avalanche, and provides practical guidelines and real‑world lessons for designing effective backend caching solutions.
This article summarizes practical techniques for reducing API latency, including batch processing, asynchronous execution, caching, pre‑processing, pooling, parallelization, indexing, transaction size control, program structure refactoring, deep pagination handling, SQL tuning, and proper lock granularity.
This article presents a comprehensive set of backend API optimization strategies—including batch processing, asynchronous execution, caching, pre‑processing, pooling, parallelization, indexing, transaction management, code restructuring, deep pagination, SQL tuning, and lock granularity—to dramatically reduce response times and improve system efficiency.
This article details the systematic reduction of memory consumption for Ctrip's hotel query service by halving container memory, evaluating and tuning modern garbage collectors, diagnosing off‑heap leaks, and ultimately replacing the default ptmalloc allocator with jemalloc to achieve stable performance and lower resource costs.
This article explains the concept of distributed link tracing, its importance for visualizing microservice call chains, introduces the OpenTracing standard, and details how SkyWalking implements automatic span collection, context propagation, unique trace IDs, sampling strategies, and performance advantages over other tracing tools.
This article explains the key performance metrics of backend systems—including QPS, TPS, response time, concurrency, and throughput—provides their definitions, relationships, practical calculation examples, and guidance on optimal thread counts for achieving balanced performance.