This tutorial walks through configuring an enterprise WeChat robot, linking it to Hermes' message gateway, building a skill that runs CPU and memory checks, scheduling periodic inspections, and automatically sending the results to the WeChat robot for hands‑free server performance monitoring.
This article introduces a lightweight Bash script that, with one curl command, automatically gathers CPU, memory, disk, and network information from a Linux server and outputs a formatted, color‑coded report in seconds, dramatically simplifying routine ops tasks.
When a Linux server spikes to 90% CPU, memory pressure grows, and database connections exhaust, this guide walks you through a systematic methodology, essential tools, real‑world case studies, and practical optimizations to quickly locate and resolve performance bottlenecks.
This comprehensive guide walks you through identifying CPU, memory, disk I/O, and network bottlenecks on high‑load Linux servers, presenting essential diagnostic tools, real‑world case studies, and practical optimization techniques to quickly resolve performance issues.
This guide explains why every server must monitor CPU, memory, disk and network usage, shows how to clean disks and analyze traffic using command‑line utilities such as df, du, iotop, iostat, iftop, lsof and tcpdump, and provides real‑world case studies for troubleshooting disk space exhaustion, port conflicts and abnormal outbound traffic.
This guide explains NGINX's access and error logs, their purpose, key fields, configuration directives, custom formats, file locations, and how to enable, view, or disable them for effective server monitoring and troubleshooting.
Sampler is a Linux visual monitoring tool that runs from a single binary, uses simple YAML files to define widgets such as sparklines and bar charts, and displays real‑time CPU, memory, network, Docker container statistics and other metrics, while being easily extensible to services like MySQL, MongoDB and Kafka.
This article introduces the Sampler visual monitoring tool, explains how to install it on Linux, and provides step‑by‑step YAML configuration examples for tracking CPU, memory, Docker containers, network activity, and system time, enabling quick, intuitive server status checks.
This guide explains why disk I/O matters for server performance and walks through using the Linux dd command to create a test file, run read/write benchmarks, interpret the results from /proc/diskstats, and automate regular checks with a cron script.
This guide explains how to identify and resolve common server monitoring alerts—including CPU, memory, disk space, disk I/O, and TCP connection issues—using Linux commands such as top, df, du, iotop, and netstat, and provides practical remediation steps.
Real‑time monitoring of CPU, memory, disk I/O and network bandwidth during performance testing helps identify bottlenecks, prevent crashes, collect actionable data, ensure accurate results, and meet SLA requirements, and a Python script can automate data collection and storage in MySQL.
This article outlines key strategies and Python tools for server monitoring, including defining metrics, utilizing libraries like psutil and requests, log analysis, load testing with Locust and PyTest, and implementing automated alerts for high availability.
This guide presents a comprehensive collection of Bash one‑liners—using awk, grep, sort, uniq, netstat, and other utilities—to count unique IPs, rank page visits, filter bots, analyze traffic by time windows, compute bandwidth, and monitor connection states from Apache or Nginx access logs.
This article describes a Python‑based solution that monitors CPU, memory, disk usage and network traffic on a server and multiple client machines, stores alerts in MySQL, and sends notifications via email and an Enterprise WeChat robot when predefined thresholds are exceeded.
This article presents Python scripts for server‑side and client‑side resource monitoring, automatically checking CPU, memory, disk usage and network traffic, storing alerts in MySQL and optionally sending notifications via email or Enterprise WeChat, with deployment instructions and cron scheduling.
A comprehensive collection of practical Linux one‑liners—using awk, grep, sort, uniq, and netstat—to count unique IPs, track page visits, rank URLs, monitor connection states, and measure traffic from Apache access logs for effective server operations.
This guide compiles a comprehensive set of Linux command‑line techniques—using awk, grep, netstat, and other tools—to help you count unique IPs, track page visits, identify heavy‑traffic files, monitor connection states, and extract performance metrics from Apache and other web server logs.
This guide compiles a comprehensive set of Linux shell commands for analyzing Apache access logs, helping you count unique IPs, identify popular pages, detect suspicious traffic, monitor connection states, measure bandwidth, and extract detailed usage statistics for effective server operations.
This guide presents a comprehensive collection of Linux command‑line techniques—including awk, grep, and netstat—to help you analyze web server logs, identify unique visitors, track page popularity, monitor connection states, and detect performance bottlenecks in a systematic way.
This step‑by‑step guide shows how to install Ruby, add the Scout_Realtime gem, start its daemon, configure firewall access, view real‑time metrics in a web browser, and manage logs, stopping or uninstalling the tool on Linux servers.
This guide explains what Linux Load Average represents, how to read each field of the top command output—including CPU, memory, and process details—and offers practical tips for diagnosing server performance issues using additional tools like vmstat and iostat.
To dramatically improve page load speed, first diagnose whether slowness stems from client network, DNS, or server bottlenecks, then apply solutions such as scaling servers, optimizing TCP settings, enabling HTTP/2/QUIC, compressing assets, and most cost-effectively integrating a CDN for global edge caching and compression.
This guide walks through customizing Nginx 404 error pages, enabling and reading the stub_status module, increasing worker processes and connections, adjusting kernel limits, expanding header buffers, and configuring browser caching for static assets to dramatically improve server performance and reliability.
This guide presents a curated set of practical Linux command-line techniques for analyzing web server logs, including counting unique IPs, identifying popular pages, measuring traffic volume, detecting slow or error responses, and monitoring connection states, enabling administrators to efficiently monitor performance and security.
This article explains how the Linux top command provides real‑time server monitoring, details its common options, interprets each line of its output—including CPU, memory, and process information—and shows useful interactive commands and a practical example for tracking a specific process.
This guide walks you through common online failures—from disk full and high CPU on servers to Java Tomcat hangs, MySQL deadlocks, slow queries, Redis memory alerts, and network connection issues—providing step‑by‑step troubleshooting methods and practical commands to quickly locate and resolve problems.
Discover six essential server monitoring tools—including Conky, Glances, Linux Dash, Netdata, Prometheus + Grafana, and Ward—that help system administrators track performance, visualize metrics, and maintain reliable infrastructure across diverse platforms.
This article introduces eleven robust server monitoring solutions, explaining their key features and benefits to help IT professionals ensure server availability, performance, and rapid issue resolution across diverse environments.
This guide walks you through a step‑by‑step method for diagnosing a sluggish production server, covering overall system status with top, CPU usage via vmstat, memory with free, disk space with df, disk I/O using iostat, and network I/O using sar, so you can confidently answer interview questions.
This tutorial demonstrates how to create a full‑stack server‑monitoring web app by setting up a Vue‑based frontend with Element and ECharts, and a Python Flask backend that collects load and disk usage data via Paramiko, stores it in SQLite, and serves it through a JSON API.
This tutorial walks through creating a web‑based server monitoring tool that tracks CPU load and disk usage, using Vue.js with Element UI and Echarts for the frontend and a Python Flask backend with SQLite for data storage and API delivery.
This guide explains how to use Linux commands such as watch, top, and ac to continuously monitor server performance, track user activity, view process resource consumption, and analyze login times, providing practical examples and command options for effective system administration.
This guide compiles a comprehensive set of Linux commands—using awk, grep, netstat, and more—to help you analyze web server logs, track traffic, identify top IPs, monitor connection states, and detect performance bottlenecks on an Alibaba Cloud ECS instance.
The article explains how to achieve precise, real‑time detection of physical server outages, reduce false alarms through heartbeat monitoring, network and special‑case interference filtering, and detailed analysis, ultimately improving detection accuracy and coverage for reliable operations.
This article walks through the design and implementation of a Django‑powered operations management platform, covering request flow, modular app structure, user authentication, asset storage, performance monitoring, batch management with Ansible, and full‑stack front‑end integration, illustrated with diagrams and code snippets.
This guide explains how to set up JMeter’s PerfMon plugins for both GUI and non-GUI server performance monitoring, including required plugin downloads, agent installation, JAR placement, test plan configuration, command-line execution, and result analysis.
This article outlines the motivation, design principles, architecture, component choices, and step‑by‑step implementation of a comprehensive server security audit system, covering server information collection, log gathering, access control checks, local vulnerability detection, abnormal traffic analysis, and integration with ELK, Hadoop, and open‑source tools like Lynis and OSSEC.
After five years as a system administrator, the author shares the five essential Linux commands—w, history, top, df, and netstat—that should be run immediately upon logging into any server to quickly assess uptime, user activity, system load, disk usage, and network status.
This article shares the architecture, design principles, challenges, and performance‑optimizing solutions behind a ten‑hundred‑thousand‑scale server monitoring system, covering data collection agents, distributed pipelines, real‑time alerts, high throughput, multi‑platform support, and practical lessons learned.
This guide introduces three essential Linux server monitoring tools—htop, Glances, and dstat—detailing their key interactive commands, configuration options, and the rich performance metrics they provide to help administrators quickly diagnose and resolve system issues.
This guide walks through identifying MySQL CPU overload caused by excessive temporary tables and thread creation, then details configuration tweaks and SQL optimizations—including adjusting tmp_table_size, thread_cache_size, and join/sort buffers—to restore normal performance.
This article describes how Netflix’s technical operations team built an automatic anomaly‑detection system based on the DBSCAN clustering algorithm to identify subtly failing servers from time‑series error‑rate data, evaluate its effectiveness, and discuss practical deployment considerations.
This guide shows how to configure Nginx and php‑fpm to expose a status page, explains the necessary settings, and provides a sample output to help you monitor PHP request handling and fine‑tune performance parameters.
