亚洲国产日韩欧美一区二区三区,精品亚洲国产成人av在线,国产99视频精品免视看7,99国产精品久久久久久久成人热,欧美日韩亚洲国产综合乱

Table of Contents
1. Choose the Right Process Manager (pm)
2. Set pm.max_children Based on Available Memory
3. Tune Request Handling and Timeout Settings
4. Optimize I/O and Concurrency
5. Monitor and Iterate
Bonus: Use Opcache
Home Backend Development PHP Tutorial Optimizing PHP-FPM Configuration for Maximum Throughput

Optimizing PHP-FPM Configuration for Maximum Throughput

Jul 24, 2025 pm 05:42 PM
php-fpm Performance optimization

Use dynamic process manager for most cases, static for steady high traffic, and avoid ondemand for high throughput; 2. Set pm.max_children based on available RAM divided by average PHP process memory, leaving headroom to prevent swapping; 3. Configure pm.max_requests to recycle workers and prevent memory leaks, set request_terminate_timeout to kill long-running requests, enable slowlog to track bottlenecks; 4. Use Unix sockets for lower I/O overhead, adjust listen.backlog to match web server settings, increase rlimit_files if needed; 5. Continuously monitor FPM status, upstream response times, and system metrics using tools like htop or Grafana; additionally, enable Opcache with appropriate settings to reduce script parsing overhead and significantly boost performance, as even well-tuned PHP-FPM will underperform without it.

Optimizing PHP-FPM Configuration for Maximum Throughput

Optimizing PHP-FPM for maximum throughput isn’t about cranking every setting to the max — it’s about aligning configuration with your application’s behavior, server resources, and traffic patterns. Poorly tuned PHP-FPM can lead to slow response times, high memory usage, or even 502 errors under load. Here’s how to get the most out of it.

Optimizing PHP-FPM Configuration for Maximum Throughput

1. Choose the Right Process Manager (pm)

PHP-FPM supports three process managers: static, dynamic, and ondemand. Your choice directly affects performance and resource use.

  • dynamic (Recommended for most cases)
    Balances performance and memory. Keeps a pool of child processes that can grow or shrink based on demand.

    Optimizing PHP-FPM Configuration for Maximum Throughput
    pm = dynamic
    pm.max_children = 50
    pm.start_servers = 10
    pm.min_spare_servers = 5
    pm.max_spare_servers = 15
  • static
    All child processes are spawned at startup. Best for high, consistent traffic when you can afford the memory.

    pm = static
    pm.max_children = 30
  • ondemand
    Spawns children only when requests arrive. Saves memory but increases latency during traffic spikes — not ideal for high-throughput scenarios.

    Optimizing PHP-FPM Configuration for Maximum Throughput

? Rule of thumb: Use dynamic unless you have predictable, steady traffic and want to minimize process management overhead.


2. Set pm.max_children Based on Available Memory

This is the most critical setting. Too high = memory exhaustion. Too low = request queuing.

Estimate max_children:

max_children = Total RAM dedicated to PHP-FPM / Average memory per PHP process

For example:

  • You allocate 2GB RAM to PHP-FPM
  • Average PHP process uses ~64MB
  • 2048 MB / 64 MB = 32

So set pm.max_children = 32 (leave some headroom for system overhead).

You can check memory per process using:

ps --no-headers -o "rss,cmd" -C php-fpm | awk '{sum =$1} END {print int(sum/NR/1024)" MB"}'

?? Avoid overcommitting memory — swapping kills performance.


3. Tune Request Handling and Timeout Settings

Long-running or stuck requests can exhaust the worker pool.

pm.max_requests = 500        ; Restart workers after 500 requests (helps prevent memory leaks)
pm.process_idle_timeout = 10s ; For 'ondemand' only
request_terminate_timeout = 30s ; Kill requests taking longer than 30s
request_slowlog_timeout = 5s  ; Log slow requests (pair with slowlog)
catch_workers_output = yes    ; Capture stdout/stderr
  • pm.max_requests helps mitigate memory leaks in long-running scripts (e.g., legacy code).
  • request_terminate_timeout prevents hanging requests from blocking workers.
  • Enable slowlog to identify bottlenecks:
    slowlog = /var/log/php-fpm-slow.log

4. Optimize I/O and Concurrency

PHP-FPM works best when it doesn’t become the bottleneck. Pair it with a fast web server (like Nginx) and optimize request flow.

  • Use socket connections instead of TCP (if on same host):

    listen = /run/php/php8.1-fpm.sock
    listen.owner = www-data
    listen.group = www-data
    listen.mode = 0660

    Unix sockets have lower overhead than 127.0.0.1:9000.

  • Adjust listen.backlog if you see connection rejections:

    listen.backlog = 511

    Set this close to the web server’s backlog (e.g., Nginx listen ... backlog=511).

  • Increase rlimit_files if hitting file descriptor limits:

    rlimit_files = 65535

5. Monitor and Iterate

Tuning is not one-time. Monitor key metrics:

  • FPM status page (enable in pool config):

    pm.status_path = /status

    Access via web server to see active/idle processes, queue length, etc.

  • Nginx upstream response times — long waits may indicate FPM saturation.

  • System metrics: CPU, memory, swap, and load average.

Use tools like htop, sysdig, or Prometheus Grafana for deeper insight.


Bonus: Use Opcache

PHP-FPM handles process management, but Opcache dramatically reduces script parsing overhead.

opcache.enable=1
opcache.memory_consumption=256
opcache.max_accelerated_files=20000
opcache.validate_timestamps=0  ; Disable in production (re-enable for deployments)
opcache.fast_shutdown=1

Without Opcache, even perfectly tuned FPM will underperform.


Basically, optimizing PHP-FPM comes down to: matching max_children to memory, choosing the right process manager, preventing stuck requests, and reducing I/O overhead. Combine that with Opcache and monitoring, and you’ll squeeze the most throughput out of your PHP stack.

The above is the detailed content of Optimizing PHP-FPM Configuration for Maximum Throughput. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undress AI Tool

Undress AI Tool

Undress images for free

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Performance optimization and horizontal expansion technology of Go framework? Performance optimization and horizontal expansion technology of Go framework? Jun 03, 2024 pm 07:27 PM

In order to improve the performance of Go applications, we can take the following optimization measures: Caching: Use caching to reduce the number of accesses to the underlying storage and improve performance. Concurrency: Use goroutines and channels to execute lengthy tasks in parallel. Memory Management: Manually manage memory (using the unsafe package) to further optimize performance. To scale out an application we can implement the following techniques: Horizontal Scaling (Horizontal Scaling): Deploying application instances on multiple servers or nodes. Load balancing: Use a load balancer to distribute requests to multiple application instances. Data sharding: Distribute large data sets across multiple databases or storage nodes to improve query performance and scalability.

Nginx Performance Tuning: Optimizing for Speed and Low Latency Nginx Performance Tuning: Optimizing for Speed and Low Latency Apr 05, 2025 am 12:08 AM

Nginx performance tuning can be achieved by adjusting the number of worker processes, connection pool size, enabling Gzip compression and HTTP/2 protocols, and using cache and load balancing. 1. Adjust the number of worker processes and connection pool size: worker_processesauto; events{worker_connections1024;}. 2. Enable Gzip compression and HTTP/2 protocol: http{gzipon;server{listen443sslhttp2;}}. 3. Use cache optimization: http{proxy_cache_path/path/to/cachelevels=1:2k

Apache Performance Tuning: Optimizing Speed & Efficiency Apache Performance Tuning: Optimizing Speed & Efficiency Apr 04, 2025 am 12:11 AM

Methods to improve Apache performance include: 1. Adjust KeepAlive settings, 2. Optimize multi-process/thread parameters, 3. Use mod_deflate for compression, 4. Implement cache and load balancing, 5. Optimize logging. Through these strategies, the response speed and concurrent processing capabilities of Apache servers can be significantly improved.

Performance optimization in Java microservice architecture Performance optimization in Java microservice architecture Jun 04, 2024 pm 12:43 PM

Performance optimization for Java microservices architecture includes the following techniques: Use JVM tuning tools to identify and adjust performance bottlenecks. Optimize the garbage collector and select and configure a GC strategy that matches your application's needs. Use a caching service such as Memcached or Redis to improve response times and reduce database load. Employ asynchronous programming to improve concurrency and responsiveness. Split microservices, breaking large monolithic applications into smaller services to improve scalability and performance.

Questions and Answers on PHP Performance Optimization Architecture Design Questions and Answers on PHP Performance Optimization Architecture Design Jun 03, 2024 pm 07:15 PM

In order to improve the performance of concurrent, high-traffic PHP applications, it is crucial to implement the following architectural optimizations: 1. Optimize PHP configuration and enable caching; 2. Use frameworks such as Laravel; 3. Optimize code to avoid nested loops; 4. Optimize database, Build index; 5. Use CDN to cache static resources; 6. Monitor and analyze performance, and take measures to solve bottlenecks. For example, website user registration optimization successfully handled a surge in user registrations by fragmenting data tables and enabling caching.

PHP framework performance optimization: Exploration combined with cloud native architecture PHP framework performance optimization: Exploration combined with cloud native architecture Jun 04, 2024 pm 04:11 PM

PHP Framework Performance Optimization: Embracing Cloud-Native Architecture In today’s fast-paced digital world, application performance is crucial. For applications built using PHP frameworks, optimizing performance to provide a seamless user experience is crucial. This article will explore strategies to optimize PHP framework performance by combining cloud-native architecture. Advantages of Cloud Native Architecture Cloud native architecture provides some advantages that can significantly improve the performance of PHP framework applications: Scalability: Cloud native applications can be easily scaled to meet changing load requirements, ensuring that peak periods do not occur bottleneck. Elasticity: The inherent elasticity of cloud services allows applications to recover quickly from failures and maintain availability and responsiveness. Agility: Cloud-native architecture supports continuous integration and continuous delivery

How to consider performance optimization in C++ class design? How to consider performance optimization in C++ class design? Jun 05, 2024 pm 12:28 PM

Tips for improving performance in C++ class design include: avoiding unnecessary copies, optimizing data layout, and using constexpr. Practical case: Use object pool to optimize object creation and destruction.

Scaling XML/RSS Processing: Performance Optimization Techniques Scaling XML/RSS Processing: Performance Optimization Techniques Apr 27, 2025 am 12:28 AM

When processing XML and RSS data, you can optimize performance through the following steps: 1) Use efficient parsers such as lxml to improve parsing speed; 2) Use SAX parsers to reduce memory usage; 3) Use XPath expressions to improve data extraction efficiency; 4) implement multi-process parallel processing to improve processing speed.

See all articles