Understanding Unicorn and unicorn-worker-killer Unicorn
We just wrote some new documentation on how Gitlab uses Unicorn and unicorn-worker-killer, available on doc.gitlab.com but also included below. We would love to hear from the community if you have other questions so we can improve this documentation resource!
Update 19:29 CEST: made link to doc.gitlab.com more specific.
Understanding Unicorn and unicorn-worker-killer
Unicorn
GitLab uses Unicorn, a pre-forking Ruby web server, to handle web requests (web browsers and Git HTTP clients). Unicorn is a daemon written in Ruby and C that can load and run a Ruby on Rails application; in our case the Rails application is GitLab Community Edition or GitLab Enterprise Edition.
Unicorn has a multi-process architecture to make better use of available CPU cores (processes can run on different cores) and to have stronger fault tolerance (most failures stay isolated in only one process and cannot take down GitLab entirely). On startup, the Unicorn 'master' process loads a clean Ruby environment with the GitLab application code, and then spawns 'workers' which inherit this clean initial environment. The 'master' never handles any requests, that is left to the workers. The operating system network stack queues incoming requests and distributes them among the workers.
In a perfect world, the master would spawn its pool of workers once, and then the workers handle incoming web requests one after another until the end of time. In reality, worker processes can crash or time out: if the master notices that a worker takes too long to handle a request it will terminate the worker process with SIGKILL ('kill -9'). No matter how the worker process ended, the master process will replace it with a new 'clean' process again. Unicorn is designed to be able to replace 'crashed' workers without dropping user requests.
This is what a Unicorn worker timeout looks like in unicorn_stderr.log. The master process has PID 56227 below.
[2015-06-05T10:58:08.660325 #56227] ERROR -- : worker=10 PID:53009 timeout (61s > 60s), killing
[2015-06-05T10:58:08.699360 #56227] ERROR -- : reaped #<Process::Status: pid 53009 SIGKILL (signal 9)> worker=10
[2015-06-05T10:58:08.708141 #62538] INFO -- : worker=10 spawned pid=62538
[2015-06-05T10:58:08.708824 #62538] INFO -- : worker=10 ready
Tunables
The main tunables for Unicorn are the number of worker processes and the request timeout after which the Unicorn master terminates a worker process. See the omnibus-gitlab Unicorn settings documentation if you want to adjust these settings.
unicorn-worker-killer
GitLab has memory leaks. These memory leaks manifest themselves in long-running processes, such as Unicorn workers. (The Unicorn master process is not known to leak memory, probably because it does not handle user requests.)
To make these memory leaks manageable, GitLab comes with the unicorn-worker-killer gem. This gem monkey-patches the Unicorn workers to do a memory self-check after every 16 requests. If the memory of the Unicorn worker exceeds a pre-set limit then the worker process exits. The Unicorn master then automatically replaces the worker process.
This is a robust way to handle memory leaks: Unicorn is designed to handle workers that 'crash' so no user requests will be dropped. The unicorn-worker-killer gem is designed to only terminate a worker process in between requests, so no user requests are affected.
This is what a Unicorn worker memory restart looks like in unicorn_stderr.log. You see that worker 4 (PID 125918) is inspecting itself and decides to exit. The threshold memory value was 254802235 bytes, about 250MB. With GitLab this threshold is a random value between 200 and 250 MB. The master process (PID 117565) then reaps the worker process and spawns a new 'worker 4' with PID 127549.
[2015-06-05T12:07:41.828374 #125918] WARN -- : #<Unicorn::HttpServer:0x00000002734770>: worker (pid: 125918) exceeds memory limit (256413696 bytes > 254802235 bytes)
[2015-06-05T12:07:41.828472 #125918] WARN -- : Unicorn::WorkerKiller send SIGQUIT (pid: 125918) alive: 23 sec (trial 1)
[2015-06-05T12:07:42.025916 #117565] INFO -- : reaped #<Process::Status: pid 125918 exit 0> worker=4
[2015-06-05T12:07:42.034527 #127549] INFO -- : worker=4 spawned pid=127549
[2015-06-05T12:07:42.035217 #127549] INFO -- : worker=4 ready
One other thing that stands out in the log snippet above, taken from Gitlab.com, is that 'worker 4' was serving requests for only 23 seconds. This is a normal value for our current GitLab.com setup and traffic.
The high frequency of Unicorn memory restarts on some GitLab sites can be a source of confusion for administrators. Usually they are a red herring.
https://about.gitlab.com/2015/06/05/how-gitlab-uses-unicorn-and-unicorn-worker-killer/
Understanding Unicorn and unicorn-worker-killer Unicorn的更多相关文章
- different between unicorn / unicorn_rails
$ unicorn_rails -h Usage: unicorn_rails [ruby options] [unicorn_rails options] [rackup config file] ...
- Nginx + unicorn 运行多个Rails应用程序
PS:第一次写的很详细,可惜发布失败,然后全没了,这是第二次,表示只贴代码,剩下的自己领悟好了,这就是所谓的一鼓作气再而衰吧,希望没有第三次. 版本: ruby 2.1.0 rails 4.0.2 n ...
- puma vs passenger vs rainbows! vs unicorn vs thin 适用场景 及 performance
ruby的几个web server,按照开发活跃度.并发方案及要点.适用场景等分析puma vs passenger vs rainbows! vs unicorn vs thin. 1. thin: ...
- Setting up Unicorn with Nginx
gem install unicorn or gem 'unciron' 1 install Nginx yum install ... 2 Configuration vi /etc/nginx/n ...
- MacOS下安装unicorn这个库失败
因为在Mac下安装pwntools,发现安装unicorn库的时候失败了,编译报错如下 make: *** [qemu/config-host.h-timestamp] Error 1 error: ...
- gitlab服务器搭建教程
gitlab服务器搭建教程 ----2016年终总结 三 参考https://bbs.gitlab.cc/topic/35/gitlab-ce-8-7-%E6%BA%90%E7%A0%81%E5%AE ...
- gitlab10.0安装手记
+ +exec chpst -e /opt/gitlab/etc/gitlab-workhorse/env -P \ + -U git \ + -u git \ + /opt/gitlab/embed ...
- Jenkins + Ansible + Gitlab之gitlab篇
前言 持续交付 版本控制器:Gitlab.GitHub 持续集成工具:jenkins 部署工具:ansible 课程安排 Gitlab搭建与流程使用 Ansible环境配置与Playbook编写规范 ...
- ror笔记2
在rails app的 config 文件夹中新建unicorn.rb内容如下 worker_processes 2 working_directory "/home/mage/boleht ...
随机推荐
- mysql数据库编码格式
1.查看数据库编码格式 mysql> show variables like 'character_set_database'; 2.查看数据表的编码格式 mysql> show crea ...
- hdu 5437(优先队列模拟)
Alisha’s Party Time Limit: 3000/2000 MS (Java/Others) Memory Limit: 131072/131072 K (Java/Others) ...
- 微信小程序 使用HMACSHA1和md5为登陆注册报文添加指纹验证签名
对接口请求报文作指纹验证签名相信在开发中经常碰到, 这次在与java后端一起开发小程序时,就碰到需求对登陆注册请求报文添加指纹验证签名来防止信息被修改 先来看下我们与后端定制签名规则 2.4. 签名规 ...
- 海量端口扫描工具masscan
海量端口扫描工具masscan masscan号称是互联网上最快的端口扫描工具,可以6分钟扫描整个互联网,每秒可以发送一百万个数据包.为了提高处理速度,masscan定制了TCP/IP栈,从而不影 ...
- PyTorch学习笔记之CBOW模型实践
import torch from torch import nn, optim from torch.autograd import Variable import torch.nn.functio ...
- Java泛型总结---基本用法,类型限定,通配符,类型擦除
一.基本概念和用法 在Java语言处于还没有出现泛型的版本时,只能通过Object是所有类型的父类和类型强制转换两个特点的配合来实现类型泛化.例如在哈希表的存取中,JDK1.5之前使用HashMap的 ...
- java资源分享、面试题资料、分布式大数据
马士兵大数据_架构师(1) 链接:http://pan.baidu.com/s/1qYTW1m0 密码:lxjd spring Cloud 链接:http://pan.baidu.com/s/1bzG ...
- 解决Gradle执行命令时报Could not determine the dependencies of task ':compileReleaseJava'.
Could not determine the dependencies of task ':compileReleaseJava'. > failed to find target andro ...
- 百科知识 scm文件如何打开
用scplayer打开,目前有效的下载链接将是: http://download.csdn.net/download/kevingao/2686778
- 几种常用的listenner
1.ServletContextListener:监控web容器的启动和关闭 2.HttpSessionListener:监控bs结构中b的session创建和session销毁 3.HttpSess ...