Microsoft’s new Low‑Latency Profile for Windows 11 claims up to a 40% speed‑up on entry‑level PCs, but real‑world tests show mixed results: noticeable performance gains alongside higher CPU spikes, fan noise, and a wave of user criticism.
This guide explains how to design a high‑performance Nginx architecture that can handle up to half a million concurrent requests, covering horizontal scaling, OS and hardware tuning, critical Nginx directives, and complementary optimization techniques.
Learn how to identify and resolve common high‑concurrency bottlenecks for Nginx by optimizing OS limits, network stack, Nginx configuration, logging, reverse‑proxy settings, backend services, and hardware resources, with concrete commands, parameter values, and step‑by‑step troubleshooting procedures.
Netflix processes over 5 PB of logs daily, handling millions of events per second, and by layering hot and cold storage, using a custom lexer for fingerprinting, native protocol serialization, and sharded tag maps, they reduced query latency from seconds to sub‑second levels with ClickHouse.
Learn how to transform Nginx into a high‑concurrency powerhouse by addressing common 502/504 errors, optimizing worker processes, event and HTTP settings, fine‑tuning OS kernel parameters, implementing caching, rate‑limiting, load‑balancing, and monitoring scripts, with practical code examples and checklists.
This article presents a step‑by‑step, production‑tested guide for tuning Nginx from 100 k QPS to over a million requests per second, covering worker process settings, TCP tweaks, kernel parameters, caching, compression, SSL optimization, monitoring, and extreme‑case techniques such as DPDK and LuaJIT.
This comprehensive guide explains how to identify and resolve common Linux performance bottlenecks—covering key metrics, hardware upgrades, kernel parameter tuning, process and memory management, and network optimization—while providing practical commands, code examples, and step‑by‑step troubleshooting techniques to keep servers and desktops running smoothly.
This comprehensive guide walks Linux administrators through advanced command usage, performance metric tuning, real‑world troubleshooting cases, and a practical checklist, empowering readers to move from reactive firefighting to proactive system optimization and reliability.
This guide presents a collection of advanced Linux performance optimizations—including kernel parameter tweaks, filesystem and I/O settings, CPU affinity, memory management, network tuning, and automated monitoring scripts—demonstrated with a real‑world e‑commerce case study that boosted QPS from 2 000 to 12 000 and reduced latency by 75%.
This comprehensive guide walks you through Linux system performance monitoring, covering essential tools such as top, htop, vmstat, iostat, and sar, and provides detailed explanations, command examples, scripts, and practical optimization strategies for CPU, memory, disk, and network resources.
This comprehensive guide explains how to identify and resolve Linux server performance bottlenecks by adjusting kernel parameters, optimizing CPU, memory, disk, and network settings, and using monitoring tools such as vmstat, mpstat, iostat, sar, top, ps, htop, pidstat, and strace to ensure stable and efficient operation.
This article explains what page faults are, why frequent faults degrade performance, how to measure them with Linux tools like perf, vmstat, and ftrace, and provides practical solutions ranging from memory upgrades to kernel parameter tuning.
Huawei's Pangu Ultra introduces a 135‑billion‑parameter dense language model trained entirely on Ascend NPUs, detailing novel stability architectures, a domain‑aware tokenizer, multi‑stage pre‑training, extensive system optimizations, and benchmark results that surpass leading models such as Llama 405B and DeepSeek‑R1.
The article introduces Linux’s built‑in performance analysis tool perf, explains its event‑driven sampling, tracing and profiling capabilities, shows how to install it on various distributions, demonstrates common commands with real code examples, and discusses practical scenarios for locating and optimizing kernel and application performance issues.
This curriculum outlines a 25‑week advanced Java engineering program covering performance optimization, JVM internals, concurrency, distributed storage, MySQL and NoSQL databases, Docker, Kubernetes, microservices, Spring framework deep dives, Nginx, Elasticsearch, Redis, messaging systems, CI/CD tools, and hands‑on project implementation to build high‑performance, scalable backend systems.
Migrating a Java computing layer to Rust yielded dramatic performance gains—30% lower CPU usage, 70% less memory—and greater stability, as the authors explain how Rust’s ownership, borrowing, lifetimes, and concurrency, combined with optimized data handling, FFI integration, Tokio async, Docker deployment, and monitoring, outweigh the steep learning curve and ecosystem gaps.
The paper describes transforming a tightly coupled, multi‑stage video search ranking pipeline into a modular, end‑to‑end large‑model architecture that decouples recall, employs a graph‑engine parallel framework and elastic compute allocation, thereby boosting performance, flexibility, personalization and lowering long‑term operational costs.
Xiaohongshu’s team unveiled a self‑developed RLHF system that trains multimodal large language models using heterogeneous and homogeneous network architectures, extensive PPO optimizations, and Medusa speculative sampling, achieving over 50% throughput gains, reduced hardware needs, and 5‑20% performance improvements on zero‑shot benchmarks.
This article presents a comprehensive framework for optimizing system components such as databases, caches, message queues, and search engines, covering environment configuration, data structure organization, client‑side usage, and inter‑component collaboration, illustrated with MySQL, Redis, Kafka, and Elasticsearch examples.
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.
Learn 25 practical Linux performance tuning techniques—from adjusting kernel parameters like swappiness and ulimit to optimizing I/O schedulers, network buffers, and enabling HugePages—each with clear commands and step‑by‑step instructions to help you maximize system responsiveness and throughput.
To prevent audit pipelines from choking during traffic surges, the article proposes augmenting the classic Chain of Responsibility with a sliding‑window anomaly detector, a statistically‑driven dynamic detector, a rule‑based backflow mechanism, and AI‑powered traffic forecasting, enabling adaptive routing and proactive scaling.
Learn practical ways to enhance a system’s concurrent handling capacity, including traffic distribution via load balancers, database sharding and clustering, message queues, caching layers, CDNs, code and database optimizations, and scaling hardware resources such as servers, CPUs, and memory.
This article analyzes the rising compute demand in modern deep‑learning‑driven search systems, proposes a micro‑ and macro‑level adaptive power‑allocation framework, models the optimization problem with cost, time, and feasibility constraints, and details an elastic cascading architecture that dynamically balances resource usage, system state, and traffic value to achieve higher ROI and stability.
This article explains why Linux performance issues arise, examines hardware, OS, network and application factors, outlines RAID choices, details OS and kernel tuning, describes the roles of ops staff, architects and developers, and provides a step‑by‑step troubleshooting workflow to improve system responsiveness and stability.
The article explains how automated performance testing using Alibaba Cloud PTS—integrated with VPC‑based Kubernetes clusters, GitLab CI/CD pipelines, and cloud APIs—overcomes the inaccuracy, coordination delays, and resource waste of manual testing by providing on‑demand, scalable load generation, scenario orchestration, real‑time metrics, and cost‑effective reporting.
This article explains how to identify and resolve Linux performance bottlenecks by examining hardware resources, operating‑system settings, storage configurations, network bandwidth, and application behavior, and it outlines a systematic troubleshooting workflow for administrators, architects, and developers.
This article reviews Tencent's research on large‑scale graph neural networks, covering three memory/computation paradigms, the SAGA extension of the GAS model, various system optimizations such as graph partitioning and feature transmission, and future challenges including non‑message‑passing models and geometric information.
This guide outlines eight practical Linux performance‑tuning methods—including kernel parameter tweaks, filesystem and network optimizations, process priority adjustments, memory management, scheduler configuration, software bloat removal, and log cleanup—while showcasing key tools and visual diagrams for effective system optimization.
Linux performance hinges on the interplay of hardware resources, OS configuration, and application efficiency; this guide outlines key factors such as CPU, memory, disk I/O, RAID, network bandwidth, kernel tuning, and the roles of ops, architects, and developers in systematic performance optimization.
The article explains Linux I/O optimization through zero‑copy techniques—such as mmap + write, sendfile, and splice—detailing memory hierarchy, the benefits of reducing user‑kernel copies, the suitability of async + direct I/O for large file transfers, real‑world uses like Kafka and Nginx, and inherent platform limitations.
This article explains the concept of feed streams, compares push and pull implementation models, discusses storage options such as MySQL, Redis SortedSet and Cassandra, and presents optimization techniques including online‑push/offline‑pull strategies, pagination methods, and deep‑paging solutions for large‑scale systems.
By streamlining packet capture, cutting Goroutine count, employing Sync.Pool for object reuse, and filtering empty packets, the database audit tool’s CPU usage dropped from six cores to one, object allocation fell 90%, packet processing halved, and data loss was reduced 60%, achieving near‑zero loss with minimal performance impact.
This article details how Vivo's push notification platform leverages Redis for massive message throughput, identifies bottlenecks encountered during peak traffic, and outlines a series of capacity, clustering, hot‑key, and client‑side optimizations that reduced load by up to 15% and improved response times dramatically.
This article outlines a comprehensive process for analyzing, diagnosing, and optimizing performance issues in production business systems, covering hardware, database, middleware, JVM tuning, code-level problems, testing limitations, scaling considerations, and the role of APM monitoring.
The article outlines a comprehensive process for diagnosing and optimizing performance problems in production business systems, covering causes such as high concurrency, data growth, hardware constraints, and detailing analysis of hardware, OS, database, middleware, JVM settings, code inefficiencies, and the role of monitoring and APM tools.
This article outlines a comprehensive process for analyzing, diagnosing, and optimizing performance issues in production business systems, covering hardware, OS, database, middleware, JVM tuning, and APM monitoring to identify root causes and implement effective solutions.
This article outlines a comprehensive approach to diagnosing and optimizing performance problems in production business systems, covering analysis processes, hardware, OS, database, middleware, JVM tuning, code inefficiencies, and monitoring techniques to identify root causes and improve system reliability.
This article details Baidu's multimodal retrieval architecture, explaining the separation of online and offline services, the design of the Imazon image processing and ingestion platform, its technical indicators, large‑scale streaming and batch pipelines, optimization practices for high throughput, and the underlying content‑relationship engine.
This article reviews the development history, technical routes, and recent breakthroughs of pre‑ranking (coarse ranking) in large‑scale advertising systems, focusing on Alibaba's COLD (Computing‑power‑cost‑aware Online and Lightweight Deep) framework, its model design, engineering optimizations, experimental results, and future research directions.
The article details Qunar's in‑house instant messaging platform, covering its purpose, protocol choices (XMPP with protocol‑buffer optimization), architecture based on ejabberd, message flow, reliability mechanisms, extensions such as bots and HTTP APIs, as well as extensive system‑level tuning for high‑concurrency TCP connections.
This article outlines a comprehensive process for diagnosing and optimizing performance problems in production business systems, covering hardware, OS, database, middleware, JVM tuning, code inefficiencies, monitoring tools, and the limitations of pre‑release testing, with practical guidelines and visual references.
This article outlines a step‑by‑step approach for identifying root causes of performance bottlenecks in production business systems, covering common scenarios such as high concurrency, data growth, hardware limits, database and middleware tuning, code inefficiencies, and the role of monitoring and APM tools.
The article presents Alibaba's display‑advertising team’s three‑stage computing‑power efficiency evolution, introduces the DCAF personalized power‑allocation algorithm with its Lagrangian formulation, and describes the AllSpark dynamic‑control framework that together enable a flexible, resource‑aware Transformers engine achieving significant business gains during high‑traffic events.
This article details the design and implementation of 58.com’s intelligent voice robot backend, covering its four‑layer architecture, SIP/SDP/RTP protocols, connection setup, multi‑turn voice interaction flow, DTMF handling, common troubleshooting issues, algorithm service modularization, SIP scheduling optimizations, and Java thread‑pool system tuning.
This article provides a comprehensive guide to improving Elasticsearch performance and stability by covering configuration file tweaks, system‑level settings, and usage‑level optimizations such as hot‑thread analysis, pending tasks, field storage, translog handling, refresh intervals, shard management, and best practices for routing and alias usage.
This article describes how 58.com applied deep‑learning techniques—including feature engineering, sample construction, model evolution from Wide&Deep to DIN/DIEN and multi‑task learning—and system‑level optimizations to improve CTR/CPM performance in its large‑scale commercial ranking platform.
This article details the end‑to‑end deep‑learning workflow for click‑through‑rate (CTR) prediction in 58.com’s commercial ranking system, covering system architecture, feature engineering, sample construction, model evolution from Wide&Deep to DIN/DIEN, and engineering optimizations that together yielded significant CPM and CVR improvements.
The article details JD.com's advertising division's comprehensive backend engineering efforts—including traffic handling, data pipeline upgrades, memory optimization, and disaster‑recovery designs—to ensure system stability and performance during the high‑traffic 618 sales event.
This article presents a comprehensive guide to Linux performance analysis, covering CPU, memory, disk I/O, network, system load, flame‑graph techniques, and a real‑world Nginx case study, enabling engineers to quickly locate and resolve bottlenecks.
This article examines the challenges of handling massive log data in large‑scale e‑commerce platforms, outlines a baseline ELK‑based architecture, discusses real‑time versus near‑real‑time requirements, and presents four optimization strategies—including basic tuning, platform scaling, data partitioning, and system degradation—to improve performance, resource utilization, and reliability.
This guide details comprehensive Nginx performance optimization, covering worker process sizing, CPU affinity, file descriptor limits, event model settings, HTTP directives, fastcgi parameters, gzip compression, expires caching, anti‑hotlinking, and essential Linux kernel tweaks for high‑traffic servers.
This article examines the design, deployment, and optimization of massive log systems, comparing architectures, discussing real‑time versus near‑real‑time requirements, and presenting practical improvements such as memory, CPU, network tuning, data partitioning, storage reduction, and component upgrades using ELK, Kafka, Fluentd, and HBase.
This article presents a comprehensive methodology for performance testing and optimization of a new corporate banking system, covering evaluation metrics, monitoring tools, test environment setup, common bottlenecks, detailed troubleshooting steps, and real‑world case studies to achieve higher throughput, lower latency, and better scalability.
This article explains why the traditional %CPU metric can be deceptive, describes how CPU stalls and memory bottlenecks affect perceived utilization, and offers practical guidance on using IPC and performance counters to obtain a more accurate view of system performance.
Meituan’s HULK platform is a custom container‑cluster manager that integrates service governance, deployment and monitoring, while employing kernel patches, enhanced cgroup controls, dynamic CPU/memory isolation, P2P image distribution and in‑container core‑dump handling to overcome stability, performance and resource‑reporting challenges.
The JD Finance technical teams—including Wealth R&D, Consumer Finance, Payment, Middle‑Platform, and Crowdfunding—conducted comprehensive system reviews, performance stress tests, capacity expansions, monitoring enhancements, and emergency downgrade plans to ensure stable, high‑throughput service during the 11.11 shopping festival.
This article provides a comprehensive overview of performance testing, explaining its definition, key metrics such as throughput, response time and concurrent users, the relationship between these indicators, optimal testing timing, a step‑by‑step workflow from requirement analysis to reporting, and practical tips for effective load testing and system optimization.
This article provides a comprehensive, easy‑to‑understand overview of performance tuning, covering what, why, when, where, who, and how to optimize hardware, operating systems, and applications, with practical examples, metrics, tools, and step‑by‑step procedures for both pre‑deployment and post‑deployment optimization.
This comprehensive guide covers Linux operations interview topics, including the definition of ops, game‑ops roles, server management techniques, RAID levels, load‑balancing tools (LVS, Nginx, HAProxy), middleware, MySQL troubleshooting, backup solutions, health‑check configuration, common networking commands, virus removal, TCP/IP model, Nginx modules, log retention, system optimization, and useful command‑line shortcuts, all presented with clear explanations and practical examples.
This guide explains how to maximize system performance by debugging and adjusting kernel parameters using sysctl, detailing command options, key network and security settings, recommended values, and related /proc/sys entries for tuning TCP, UDP, socket buffers, and other kernel behaviors.
This article explains how to measure a system's load capacity, identifies key factors such as bandwidth, hardware, OS and application configurations, and provides practical optimization techniques for Linux, Tomcat, Nginx, MySQL, and Redis to handle high concurrency efficiently.
This guide explains how to assess and improve server performance by understanding key metrics such as CPU utilization, memory management, and disk I/O, introducing fundamental concepts, analysis methodologies like 5W2H and load‑characteristic summarization, and recommending practical Linux tools such as uptime, vmstat, top, perf, and DTrace for comprehensive troubleshooting.
This guide walks you through optimizing Ubuntu by updating sources, removing unwanted packages, installing Unity tweak tools, applying the Flatabulous theme and icons, adding a system load indicator, setting up Microsoft YaHei fonts, configuring Zsh, and recommending essential software and DEB installation tips.
JD.com's R&D team completed a full-linkage pressure test for the 618 promotion, addressing hardware shortages by optimizing existing systems and preparing 24/7 monitoring.
This guide walks through comprehensive Linux server hardening techniques, covering user account management, service minimization, file permission tightening, virtual memory tuning, log handling, and firewall configuration with iptables and ipchains, providing step‑by‑step commands and screenshots to enhance system security and stability.
This article shares a practical template for optimizing web service performance, covering kernel sysctl tweaks, file‑handle limits, and Nginx/PHP‑FPM configuration adjustments to eliminate bottlenecks and maximize throughput under high traffic conditions.
The Meituan Dianping Technology Salon gathered technical experts to discuss logistics architecture, LBS spatial search optimization, and real‑time platform development, highlighting Meituan’s growth from zero to millions of daily orders, high‑concurrency challenges, scalability, DevOps practices, and case studies from both established firms and startups.
This article provides a comprehensive, easy‑to‑understand overview of server performance tuning, covering what it is, why it matters, when to apply it, where to focus, who should be involved, and how to execute systematic optimization across hardware, operating system, and applications.
This guide provides detailed steps and registry tweaks to optimize Windows 7 performance on SSDs, covering BIOS settings, SSD usage principles, disabling unnecessary services, disk space management, and system configuration commands to improve speed and reduce resource consumption.
