This article provides an in‑depth overview of Java application performance optimization, covering a four‑layer model (application, database, framework, JVM), on‑site and post‑mortem analysis methods, OS and JVM diagnostic tools, common code and GC issues, database deadlock handling, and practical tuning recommendations.
This guide explains how to use a variety of Linux performance tools—including top, perf, sar/ksar, mpstat, uptime, vmstat, pidstat, time, cpustat, htop, atop, glances, nmon, pcp‑gui, collectl and colplot—to monitor CPU, memory, disk, network and process activity with concrete command examples and visualisations.
This guide explains how to use Arthas's trace command to capture Java method call paths, measure execution time for each node, handle class and method patterns, and highlights its limitations with lambda expressions, providing practical code examples and output analysis.
This article presents a thorough overview of Java application performance optimization, covering a four‑layer model (application, database, framework, JVM), practical OS and Java diagnostic tools, JVM and GC tuning, application‑level code improvements, and database deadlock mitigation strategies.
This article introduces the Arthas Java diagnostic tool, explains the powerful ognl command with basic usage examples for inspecting static fields and invoking static methods, and provides a sample Java code snippet illustrating how to apply these techniques in practice.
This article explains the Arthas "sc" (Search‑Class) and "sm" (Search‑Method) commands, showing how they list loaded classes and their methods in a JVM, when they are useful, and why they can often be skipped if source code is available.
This article compiles Arthas video tutorials and explains the four basic commands—JVM, sysprop, sysenv, and vmoption—detailing what they display, their differences from built‑in JVM tools, and where to find further resources for deeper JVM parameter tuning.
The author plans to study Arthas, a highly recommended Java diagnostic tool praised by colleagues for its ability to capture method execution details, thread states, and overall performance dashboards, and intends to share an introductory video on a public platform soon.
This article introduces Arthas, an open‑source Java diagnostic tool, explains its key features, demonstrates four practical troubleshooting scenarios with command examples, and shows how to start using it via an IDE plugin or direct download.
This article demonstrates how to use MySQL's stacked diagnostics and a custom stored procedure to automatically capture and log errors from bulk INSERT statements during Oracle‑to‑MySQL migration, enabling quick identification and correction of problematic rows without manual inspection.
This article explains how to diagnose and manually re‑execute a Spring @Scheduled task that fails to send notifications by using Arthas to obtain the ApplicationContext, invoke the bean method, and reveals that a missing timeout in Hutool caused the original hang.
This article presents a practical guide for Oracle DBAs to quickly diagnose and resolve application‑related database issues by checking OS load, analyzing wait events, querying session and object details, capturing diagnostic dumps, and using scripted commands to kill sessions or restart the database.
The article explains why InnoDB semaphore waits exceeding 600 seconds trigger server crashes, details the lock structures and functions involved, shows how buffer pool pressure and metadata statistics cause contention, and introduces a small DBA utility that parses MySQL error logs to reveal the relationships between threads, locks, and transactions.
The Lingjing system, built by Alibaba Infrastructure, provides an end‑to‑end hardware‑software performance diagnosis platform that collects fine‑grained metrics, visualizes data, automatically detects anomalies, and helps optimize resource utilization across complex data‑center stacks.
This guide shows how to configure a .curlrc file and use cURL’s timing variables to capture DNS lookup, connection, TLS handshake, transfer start, total time, and download size, enabling precise performance analysis of web requests.
This article explains how to choose MySQL storage engines, apply effective table partitioning and indexing, identify common causes of slow queries, adopt practical SQL optimization tips, use diagnostic tools, and handle data loss or bugs with proper recovery procedures.
This article explains how to obtain iOS diagnostics battery data on iOS 10+ and iOS 9 devices, interpret the SQLite tables to measure app power consumption, and provides practical code and performance‑optimization tips for reducing energy usage in iOS applications.
This guide introduces the powerful sysstat suite, explains how to install sar, outlines its key features and statistics, and provides step‑by‑step commands for troubleshooting CPU, memory, I/O, and network problems on Linux servers.
This article explains the various timeout scenarios in SQL Server‑backed web applications—including ASP.NET, IIS, WebService, SSMS, remote login, and linked‑server timeouts—provides diagnostic queries such as the Connectivity Ring Buffer, and offers concrete tuning steps and best‑practice recommendations to resolve and prevent them.
When a Linux server suddenly spikes in load, this guide shows how to pinpoint the root cause within a minute by running ten key commands that reveal CPU, memory, disk I/O, and network metrics.
This article explains a PerRequest‑level problem‑location method for mobile internet, detailing how precise packet loss enumeration and a Supply‑Chain‑based logging approach dramatically improved Sina Weibo image quality by identifying and reducing key error codes.
This guide compiles essential Linux commands for inspecting system details, resources, disks, networks, processes, users, services, and installed programs, providing concise descriptions that help administrators quickly gather kernel, hardware, memory, storage, and runtime information.
This article outlines a comprehensive performance testing workflow, introduces layered and segment diagnostic methods, presents a detailed Apache/Tomcat/Linux/Oracle case study with LoadRunner and Nmon, and discusses monitoring metrics, analysis results, and practical recommendations for optimizing system performance.
Within the first minute of logging into a Linux server, this guide walks you through ten essential command‑line tools—such as uptime, vmstat, mpstat, pidstat, iostat, free, sar, and top—to quickly assess system load, CPU, memory, disk, and network saturation for effective performance troubleshooting.
