2016-11-03 12:29:30 +05:30
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# Understanding Unicorn and unicorn-worker-killer
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2020-05-24 23:13:21 +05:30
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NOTE: **Note:**
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Starting with GitLab 13.0, Puma is the default web server used in GitLab
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all-in-one package based installations as well as GitLab Helm chart deployments.
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2016-11-03 12:29:30 +05:30
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## Unicorn
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2020-04-22 19:07:51 +05:30
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GitLab uses [Unicorn](https://yhbt.net/unicorn/), a pre-forking Ruby web
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server, to handle web requests (web browsers and Git HTTP clients). Unicorn is
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a daemon written in Ruby and C that can load and run a Ruby on Rails
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application; in our case the Rails application is GitLab Community Edition or
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GitLab Enterprise Edition.
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Unicorn has a multi-process architecture to make better use of available CPU
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cores (processes can run on different cores) and to have stronger fault
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tolerance (most failures stay isolated in only one process and cannot take down
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GitLab entirely). On startup, the Unicorn 'master' process loads a clean Ruby
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environment with the GitLab application code, and then spawns 'workers' which
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inherit this clean initial environment. The 'master' never handles any
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requests, that is left to the workers. The operating system network stack
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queues incoming requests and distributes them among the workers.
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In a perfect world, the master would spawn its pool of workers once, and then
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the workers handle incoming web requests one after another until the end of
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time. In reality, worker processes can crash or time out: if the master notices
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that a worker takes too long to handle a request it will terminate the worker
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process with SIGKILL ('kill -9'). No matter how the worker process ended, the
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master process will replace it with a new 'clean' process again. Unicorn is
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designed to be able to replace 'crashed' workers without dropping user
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requests.
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This is what a Unicorn worker timeout looks like in `unicorn_stderr.log`. The
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master process has PID 56227 below.
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2020-03-13 15:44:24 +05:30
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```plaintext
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[2015-06-05T10:58:08.660325 #56227] ERROR -- : worker=10 PID:53009 timeout (61s > 60s), killing
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[2015-06-05T10:58:08.699360 #56227] ERROR -- : reaped #<Process::Status: pid 53009 SIGKILL (signal 9)> worker=10
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[2015-06-05T10:58:08.708141 #62538] INFO -- : worker=10 spawned pid=62538
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[2015-06-05T10:58:08.708824 #62538] INFO -- : worker=10 ready
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```
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2020-06-23 00:09:42 +05:30
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### Tunable options
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2020-06-23 00:09:42 +05:30
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The main tunable options for Unicorn are the number of worker processes and the
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2016-11-03 12:29:30 +05:30
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request timeout after which the Unicorn master terminates a worker process.
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2019-12-21 20:55:43 +05:30
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See the [Omnibus GitLab Unicorn settings
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documentation](https://gitlab.com/gitlab-org/omnibus-gitlab/blob/master/doc/settings/unicorn.md)
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if you want to adjust these settings.
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## unicorn-worker-killer
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GitLab has memory leaks. These memory leaks manifest themselves in long-running
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processes, such as Unicorn workers. (The Unicorn master process is not known to
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leak memory, probably because it does not handle user requests.)
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To make these memory leaks manageable, GitLab comes with the
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[unicorn-worker-killer gem](https://github.com/kzk/unicorn-worker-killer). This
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gem [monkey-patches](https://en.wikipedia.org/wiki/Monkey_patch) the Unicorn
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workers to do a memory self-check after every 16 requests. If the memory of the
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Unicorn worker exceeds a pre-set limit then the worker process exits. The
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Unicorn master then automatically replaces the worker process.
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This is a robust way to handle memory leaks: Unicorn is designed to handle
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workers that 'crash' so no user requests will be dropped. The
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unicorn-worker-killer gem is designed to only terminate a worker process _in
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2019-03-02 22:35:43 +05:30
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between requests_, so no user requests are affected. You can set the minimum and
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maximum memory threshold (in bytes) for the Unicorn worker killer by
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setting the following values `/etc/gitlab/gitlab.rb`:
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2020-04-08 14:13:33 +05:30
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- For GitLab **12.7** and newer:
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```ruby
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unicorn['worker_memory_limit_min'] = "1024 * 1 << 20"
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unicorn['worker_memory_limit_max'] = "1280 * 1 << 20"
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```
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- For GitLab **12.6** and older:
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2020-04-08 14:13:33 +05:30
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```ruby
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unicorn['worker_memory_limit_min'] = "400 * 1 << 20"
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unicorn['worker_memory_limit_max'] = "650 * 1 << 20"
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```
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2020-03-13 15:44:24 +05:30
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2019-10-12 21:52:04 +05:30
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Otherwise, you can set the `GITLAB_UNICORN_MEMORY_MIN` and `GITLAB_UNICORN_MEMORY_MAX`
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[environment variables](../environment_variables.md).
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This is what a Unicorn worker memory restart looks like in unicorn_stderr.log.
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You see that worker 4 (PID 125918) is inspecting itself and decides to exit.
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The threshold memory value was 254802235 bytes, about 250MB. With GitLab this
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threshold is a random value between 200 and 250 MB. The master process (PID
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117565) then reaps the worker process and spawns a new 'worker 4' with PID
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127549.
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2020-03-13 15:44:24 +05:30
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```plaintext
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[2015-06-05T12:07:41.828374 #125918] WARN -- : #<Unicorn::HttpServer:0x00000002734770>: worker (pid: 125918) exceeds memory limit (256413696 bytes > 254802235 bytes)
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[2015-06-05T12:07:41.828472 #125918] WARN -- : Unicorn::WorkerKiller send SIGQUIT (pid: 125918) alive: 23 sec (trial 1)
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[2015-06-05T12:07:42.025916 #117565] INFO -- : reaped #<Process::Status: pid 125918 exit 0> worker=4
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[2015-06-05T12:07:42.034527 #127549] INFO -- : worker=4 spawned pid=127549
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[2015-06-05T12:07:42.035217 #127549] INFO -- : worker=4 ready
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```
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One other thing that stands out in the log snippet above, taken from
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GitLab.com, is that 'worker 4' was serving requests for only 23 seconds. This
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is a normal value for our current GitLab.com setup and traffic.
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The high frequency of Unicorn memory restarts on some GitLab sites can be a
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source of confusion for administrators. Usually they are a [red
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herring](https://en.wikipedia.org/wiki/Red_herring).
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