This article walks through Linux performance optimization by explaining core metrics such as throughput and latency, describing how to interpret average load, CPU usage, context switches, memory management, and swap, and showing step‑by‑step usage of tools like vmstat, pidstat, perf, and dstat with concrete command examples and analysis cases.
Learn how Linux memory management works, from virtual memory and user/kernel space to allocation, reclamation, and common bottlenecks, and discover practical tools like free, top, vmstat, valgrind, jstat, and swap configuration techniques to diagnose, monitor, and optimize server memory for stable, high‑performance operation.
Performance testing involves monitoring various metrics to assess system behavior under different conditions, including response time, throughput, CPU usage, memory utilization, and error rates.
This comprehensive guide explains how to diagnose Linux performance issues using systematic 5W2H analysis, essential monitoring tools for CPU, memory, disk I/O, network, and flame‑graph visualizations, and demonstrates the methodology with a detailed nginx case study to quickly locate bottlenecks.
This article reviews the Java HotSpot memory model, explains when JVM tuning is needed, details common OutOfMemoryError scenarios with reproducible code, introduces built‑in monitoring utilities and third‑party tools, and provides practical tuning parameters and case studies for optimizing Java applications.
This guide explains Linux performance optimization by defining key metrics such as throughput and latency, clarifying average load, detailing CPU context switches, describing common performance analysis tools, and providing practical methods for diagnosing and improving CPU, memory, and I/O bottlenecks in production environments.
This article introduces essential JVM performance monitoring and profiling tools—including jps, jstack, jmap, jhat, jstat, and hprof—explaining their syntax, options, and practical usage for diagnosing memory leaks, thread deadlocks, high CPU consumption, and other common Java production issues.
This guide walks through adding Sentry to a frontend project—explaining core concepts, Docker deployment, environment‑specific integration, webpack source‑map uploading, alert rule configuration, ownership assignment, webhook/GitLab extensions, and common pitfalls such as URL prefix handling and HTTPS DSN setup.
This article introduces the most common JVM performance problems in enterprise Java applications and provides a practical guide to using core monitoring and tuning tools such as jps, jstack, jmap, jstat and hprof, complete with command syntax, sample outputs and step‑by‑step troubleshooting examples.
This article explains how to assess and improve system I/O performance by defining I/O models, selecting appropriate evaluation tools for disk and network, monitoring key metrics such as IOPS, bandwidth and latency, and applying host, network, and storage‑side optimization techniques for high‑throughput and low‑latency workloads.
This article explains the essential concepts, philosophy, participants, dimensions, tools, and step‑by‑step procedures for safely and effectively optimizing MySQL databases, covering hardware, system, application, and MySQL‑level tuning together with practical command‑line examples.
This article outlines the philosophy, risks, participants, and step‑by‑step strategies for MySQL optimization, covering query flow, hardware and system tuning, configuration parameters, monitoring tools, and SQL‑level improvements to achieve stable, high‑performance database operations.
This article explains how to assess I/O capabilities, choose appropriate evaluation tools, monitor key performance metrics, and apply targeted optimization techniques for both disk and network I/O to improve system throughput and latency.
This guide explains the three main performance bottlenecks—CPU, network I/O, and disk I/O—on Linux servers, offers concrete optimization techniques for each, and introduces essential diagnostic tools such as top, free, vmstat, strace, tcpdump, and gprof to pinpoint and resolve issues.
Learn how to diagnose and resolve common Java performance issues such as OutOfMemoryError, thread deadlocks, and high CPU usage by using built‑in JVM tools—including jps, jstack, jmap, jhat, jstat, and hprof—through detailed command examples, output explanations, and practical profiling techniques.
This article outlines how the Linux CPU scheduler manages threads and interrupts, explains context switches, run queue length, CPU utilization metrics, typical performance thresholds, and introduces monitoring tools like vmstat and mpstat, followed by real‑world troubleshooting examples.
