For the installations options please see the installation page on the GitLab website.
GitLab is developed for Unix operating systems. GitLab does not run on Windows and we have no plans of supporting it in the near future. Please consider using a virtual machine to run GitLab.
GitLab requires Ruby (MRI) 2.3. Support for Ruby versions below 2.3 (2.1, 2.2) will stop with GitLab 8.13.
The necessary hard drive space largely depends on the size of the repos you want to store in GitLab but as a rule of thumb you should have at least as much free space as all your repos combined take up.
If you want to be flexible about growing your hard drive space in the future consider mounting it using LVM so you can add more hard drives when you need them.
Apart from a local hard drive you can also mount a volume that supports the network file system (NFS) protocol. This volume might be located on a file server, a network attached storage (NAS) device, a storage area network (SAN) or on an Amazon Web Services (AWS) Elastic Block Store (EBS) volume.
If you have enough RAM memory and a recent CPU the speed of GitLab is mainly limited by hard drive seek times. Having a fast drive (7200 RPM and up) or a solid state drive (SSD) will improve the responsiveness of GitLab.
You need at least 4GB of addressable memory (RAM + swap) to install and use GitLab! The operating system and any other running applications will also be using memory so keep in mind that you need at least 4GB available before running GitLab. With less memory GitLab will give strange errors during the reconfigure run and 500 errors during usage.
We recommend having at least 2GB of swap on your server, even if you currently have enough available RAM. Having swap will help reduce the chance of errors occurring if your available memory changes.
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.
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 the GitLab Rails 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 the CI features.
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.
For most instances we recommend using: CPU cores + 1 = unicorn workers. So for a machine with 2 cores, 3 unicorn workers is ideal.
For all machines that have 2GB and up we recommend a minimum of three unicorn workers. If you have a 1GB machine we recommend to configure only two Unicorn workers to prevent excessive swapping.
To change the Unicorn workers when you have the Omnibus package please see the Unicorn settings in the Omnibus GitLab documentation.
If you want to run the database separately expect a size of about 1 MB per user.
Users using PostgreSQL must ensure the
pg_trgm extension is loaded into every GitLab database. This extension can be enabled (using a PostgreSQL super user) by running the following query for every database:
CREATE EXTENSION pg_trgm;
On some systems you may need to install an additional package (e.g.
postgresql-contrib) for this extension to become available.
Redis stores all user sessions and the background task queue. The storage requirements for Redis are minimal, about 25kB per user. Sidekiq processes the background jobs with a multithreaded process. This process starts with the entire Rails stack (200MB+) but it can grow over time due to memory leaks. On a very active server (10,000 active users) the Sidekiq process can use 1GB+ of memory.
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