Hardware Requirements Document

Hardware Requirements Document Template | Sample Customer Service
  • Ubuntu
  • Debian
  • CentOS
  • Red Hat Enterprise Linux (please use the CentOS packages and instructions)
  • Scientific Linux (please use the CentOS packages and instructions)
  • Oracle Linux (please use the CentOS packages and instructions)

Unsupported Unix distributions

  • Arch Linux
  • Fedora
  • FreeBSD
  • Gentoo
  • macOS

On the above unsupported distributions is still possible to install GitLab yourself. Please see the installation from source guide and the installation guides for more information.

Non-Unix operating systems such as Windows

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.

Ruby versions

GitLab requires Ruby (MRI) 2.3. Support for Ruby versions below 2.3 (2.1, 2.2) will stop with GitLab 8.13.

You will have to use the standard MRI implementation of Ruby. We love JRuby and Rubinius but GitLab needs several Gems that have native extensions.

Storage

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.

CPU

  • 1 core supports up to 100 users but the application can be a bit slower due to having all workers and background jobs running on the same core
  • 2 cores is the recommended number of cores and supports up to 500 users
  • 4 cores supports up to 2, 000 users
  • 8 cores supports up to 5, 000 users
  • 16 cores supports up to 10, 000 users
  • 32 cores supports up to 20, 000 users
  • 64 cores supports up to 40, 000 users

Memory

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.

  • 1GB RAM + 3GB of swap is the absolute minimum but we strongly advise against this amount of memory. See the unicorn worker section below for more advice.
  • 2GB RAM + 2GB swap supports up to 100 users but it will be very slow
  • 4GB RAM is the recommended memory size for all installations and supports up to 100 users
  • 8GB RAM supports up to 1, 000 users
  • 16GB RAM supports up to 2, 000 users
  • 32GB RAM supports up to 4, 000 users
  • 64GB RAM supports up to 8, 000 users
  • 128GB RAM supports up to 16, 000 users
  • 256GB RAM supports up to 32, 000 users

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.

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.

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