Commit 3cf51236 authored by Grzegorz Bizon's avatar Grzegorz Bizon

Add notice about GitLab Runner to requirements docs

This is related to !14589, and problems that may stem from running
GitLab Runner on same machine user installed GitLab web app on.
parent 438e0ce8
...@@ -79,6 +79,16 @@ With less memory GitLab will give strange errors during the reconfigure run and ...@@ -79,6 +79,16 @@ With less memory GitLab will give strange errors during the reconfigure run and
Notice: The 25 workers of Sidekiq will show up as separate processes in your process overview (such as top or htop) but they share the same RAM allocation since Sidekiq is a multithreaded application. Please see the section below about Unicorn workers for information about many you need of those. Notice: The 25 workers of Sidekiq will show up as separate processes in your process overview (such as top or htop) but they share the same RAM allocation since Sidekiq is a multithreaded application. Please see the section below about Unicorn workers for information about many you need of those.
## Gitlab Runner
We strongly advise against installing GitLab Runner on the same machine you plan to install GitLab on. Depending on how you decide to configure GitLab Runner and what tools you use to exercise your application in the CI environment, GitLab Runner can consume significant amount of available memory.
Memory consumption calculations, that are available above, will not be valid if you decide to run GitLab Runner and GitLab web application on the same machine.
It is also not safe to install everything on a single machine, because of the security reasons - especially when you plan to use shell executor with GitLab Runner.
We recommend using a separate machine for each GitLab Runner, if you plan to use CI features.
## Unicorn Workers ## Unicorn Workers
It's possible to increase the amount of unicorn workers and this will usually help for to reduce the response time of the applications and increase the ability to handle parallel requests. It's possible to increase the amount of unicorn workers and this will usually help for to reduce the response time of the applications and increase the ability to handle parallel requests.
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