The article explains how Linux’s page cache bridges memory and disk, detailing its read/write mechanisms, dirty page handling, pre‑read optimization, kernel parameters, and practical tuning tips for static file serving, databases, and logging, showing why mastering it is essential for performance.
This comprehensive guide walks you through Linux system performance monitoring using tools like top, htop, vmstat, iostat, sar, netstat, ps, and free, explains each metric, provides practical shell scripts for real‑time analysis, alerts, and detailed tuning strategies for CPU, memory, disk, and network.
This guide explains the exact prerequisites, anti‑patterns, system‑level tuning, Nginx configuration template, performance testing, monitoring, and rollback procedures required to reliably handle over one million concurrent connections on modern Linux servers.
This article explains the Linux kernel parameters that limit the number of open files and TCP connections, shows how to adjust them, estimates realistic connection counts based on memory, and discusses client‑side port constraints and related practical issues.
This article walks ops engineers through a real production incident, explains why deep Linux kernel knowledge is crucial, presents typical high‑traffic, log‑burst, and DB‑slow‑query scenarios, and shares a three‑step practical tuning methodology with code snippets, monitoring scripts, and future‑proof tips such as eBPF and AIOps.
This article explains the practical limits on how many TCP connections a Linux server or client can support, covering file‑descriptor parameters, memory consumption per socket, kernel tuning examples, and scaling calculations for large‑scale long‑connection services.
Linux treats everything as a file, so the maximum number of open files and TCP connections a server can support depends on kernel parameters like fs.file-max, soft/hard nofile, and fs.nr_open, as well as memory size, port limits, and proper configuration to avoid 'too many open files' errors.
This guide lists 44 essential Linux kernel and sysctl parameters, providing their default values and recommended settings to improve memory management, networking, file handling, and overall system stability for production environments and reliability.
This article explains the Linux parameters that limit the maximum number of open files and TCP connections on a server, shows how to adjust those limits with configuration examples, and discusses practical constraints such as memory, port ranges, and real‑world scaling scenarios.
This article analyzes a Kubernetes‑Docker environment where Java pods encounter “fork: Resource temporarily unavailable” errors, tracing the issue through kernel event logs, ulimit settings, PID limits, and related sysctl parameters, and provides detailed recommendations for kernel and user‑level configuration to prevent such failures.
The article explains why the free command reports more memory than the available column, describes how the kernel calculates MemAvailable using min_free_kbytes and watermarks, and provides practical guidance on tuning min_free_kbytes to meet OceanBase's memory requirements.
This article examines common TCP handshake anomalies in backend systems, detailing how client port exhaustion and server-side connection queue overflows cause packet loss and latency spikes, while providing kernel-level insights and practical configuration strategies to optimize network performance and ensure reliable service availability.
This guide explains how to tune Linux for high‑concurrency workloads by disabling unnecessary iptables, raising the per‑process file descriptor limit, modifying kernel TCP parameters via sysctl, and choosing appropriate I/O event mechanisms such as epoll or AIO.
This guide explains how to configure Linux for high‑concurrency workloads by increasing the maximum open files limit, adjusting kernel TCP parameters, and selecting appropriate I/O event mechanisms such as epoll or AIO.
This article provides a comprehensive, step‑by‑step guide to MySQL performance tuning, covering the underlying query process, optimization philosophy, practical tools, system‑level diagnostics, hardware and OS recommendations, as well as detailed configuration parameters for both the server and storage engine.
This article presents a comprehensive guide to Nginx performance tuning, covering methodology, request lifecycle, application‑level tweaks, and system‑level optimizations to achieve higher concurrency, lower latency, and better resource utilization.
This guide details high‑concurrency system performance metrics, testing methodologies using Tsung, and practical Linux and Erlang configuration tweaks—including kernel parameters, file descriptor limits, port ranges, and VM settings—to improve throughput, reduce latency, and effectively identify bottlenecks in production environments.
This article explains how to monitor CPU usage on Linux using tools like top, vmstat, and gstat, analyzes common causes of high user and system CPU time, and provides practical tuning methods such as adjusting process priority, using ulimit, and configuring program‑specific CPU settings.
This guide explains what hardware interrupts are, how SMP IRQ affinity works, and provides step‑by‑step Linux commands to assign specific device IRQs—such as network or disk—to individual CPU cores, improving multi‑core server performance and throughput.
This guide explains how to increase Linux's per-process file descriptor limits, adjust kernel TCP parameters, and adopt high-performance I/O models such as epoll or AIO to support tens of thousands of concurrent TCP connections.
This guide compiles essential Linux kernel sysctl settings, Nginx performance tweaks, MySQL configuration for 8 GB RAM, Tomcat connector optimizations, and hardware load monitoring commands to help you fine‑tune a production server for maximum throughput and stability.
This guide explains how to install and use the tuned and tuned‑adm tools on RHEL/CentOS 6.3+, lists the built‑in optimization profiles such as laptop‑battery‑powersave and virtual‑host, shows how to apply them, and demonstrates creating custom profiles for specific workloads.
