Apache server is a powerful web server software that acts as a bridge between browsers and website servers. 1. It handles HTTP requests and returns web page content based on requests; 2. Modular design allows extended functions, such as support for SSL encryption and dynamic web pages; 3. Configuration files (such as virtual host configurations) need to be carefully set to avoid security vulnerabilities, and optimize performance parameters, such as thread count and timeout time, in order to build high-performance and secure web applications.

When developing websites using CraftCMS, you often encounter resource file caching problems, especially when you frequently update CSS and JavaScript files, old versions of files may still be cached by the browser, causing users to not see the latest changes in time. This problem not only affects the user experience, but also increases the difficulty of development and debugging. Recently, I encountered similar troubles in my project, and after some exploration, I found the plugin wiejeben/craft-laravel-mix, which perfectly solved my caching problem.

The Installation, Configuration and Optimization Guide for HDFS File System under CentOS System This article will guide you how to install, configure and optimize Hadoop Distributed File System (HDFS) on CentOS System. HDFS installation and configuration Java environment installation: First, make sure that the appropriate Java environment is installed. Edit /etc/profile file, add the following, and replace /usr/lib/java-1.8.0/jdk1.8.0_144 with your actual Java installation path: exportJAVA_HOME=/usr/lib/java-1.8.0/jdk1.8.0_144exportPATH=$J

Nginx performance monitoring and troubleshooting are mainly carried out through the following steps: 1. Use nginx-V to view version information, and enable the stub_status module to monitor the number of active connections, requests and cache hit rate; 2. Use top command to monitor system resource occupation, iostat and vmstat monitor disk I/O and memory usage respectively; 3. Use tcpdump to capture packets to analyze network traffic and troubleshoot network connection problems; 4. Properly configure the number of worker processes to avoid insufficient concurrent processing capabilities or excessive process context switching overhead; 5. Correctly configure Nginx cache to avoid improper cache size settings; 6. By analyzing Nginx logs, such as using awk and grep commands or ELK

To view the thread status in the Tomcat log, you can use the following methods: TomcatManagerWeb interface: Enter the management address of Tomcat (usually http://localhost:8080/manager) in the browser, and you can view the status of the thread pool after logging in. JMX Monitoring: Use JMX monitoring tools (such as JConsole) to connect to Tomcat's MBean server to view the status of Tomcat's thread pool. Select in JConsole

There are many ways to monitor the status of HDFS (Hadoop Distributed File System) on CentOS systems. This article will introduce several commonly used methods to help you choose the most suitable solution. 1. Use Hadoop’s own WebUI, Hadoop’s own Web interface to provide cluster status monitoring function. Steps: Make sure the Hadoop cluster is up and running. Access the WebUI: Enter http://:50070 (Hadoop2.x) or http://:9870 (Hadoop3.x) in your browser. The default username and password are usually hdfs/hdfs. 2. Command line tool monitoring Hadoop provides a series of command line tools to facilitate monitoring

Configuring an HTTPS server on a Debian system involves several steps, including installing the necessary software, generating an SSL certificate, and configuring a web server (such as Apache or Nginx) to use an SSL certificate. Here is a basic guide, assuming you are using an ApacheWeb server. 1. Install the necessary software First, make sure your system is up to date and install Apache and OpenSSL: sudoaptupdatesudoaptupgradesudoaptinsta

This article describes how to analyze Nginx logs to improve website performance and user experience. 1. Understand the Nginx log format, such as timestamps, IP addresses, status codes, etc.; 2. Use tools such as awk to parse logs and count indicators such as visits, error rates, etc.; 3. Write more complex scripts according to needs or use more advanced tools, such as goaccess, to analyze data from different dimensions; 4. For massive logs, consider using distributed frameworks such as Hadoop or Spark. By analyzing logs, you can identify website access patterns, improve content strategies, and ultimately optimize website performance and user experience.