debian-mirror-gitlab/doc/install/requirements.md
2021-09-30 23:02:18 +05:30

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Installation requirements (FREE SELF)

This page includes useful information on the supported Operating Systems as well as the hardware requirements that are needed to install and use GitLab.

Operating Systems

Supported Linux distributions

  • Ubuntu (16.04/18.04/20.04)
  • Debian (9/10)
  • CentOS (7/8)
  • openSUSE Leap (15.2)
  • SUSE Linux Enterprise Server (12 SP2/12 SP5)
  • 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)

For the installation options, see the main installation page.

Unsupported Linux distributions and Unix-like operating systems

  • Arch Linux
  • Fedora
  • FreeBSD
  • Gentoo
  • macOS

Installation of GitLab on these operating systems is possible, but not supported. Please see the installation from source guide and the installation guides for more information.

Please see OS versions that are no longer supported for Omnibus installs page for a list of supported and unsupported OS versions as well as the last support GitLab version for that OS.

Microsoft Windows

GitLab is developed for Linux-based operating systems. It does not run on Microsoft Windows, and we have no plans to support it in the near future. For the latest development status view this issue. Please consider using a virtual machine to run GitLab.

Software requirements

Redis versions

GitLab 13.0 and later requires Redis version 4.0 or higher.

Redis version 6.0 or higher is recommended, as this is what ships with Omnibus GitLab packages starting with GitLab 13.9.

Hardware requirements

Storage

The necessary hard drive space largely depends on the size of the repositories you want to store in GitLab but as a rule of thumb you should have at least as much free space as all your repositories combined take up.

If you want to be flexible about growing your hard drive space in the future consider mounting it using logical volume management (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 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) improves the responsiveness of GitLab.

NOTE: Since file system performance may affect the overall performance of GitLab, we don't recommend using cloud-based file systems for storage.

NOTE: NFS for Git repository storage is deprecated. See our official Statement of Support for further information.

CPU

CPU requirements are dependent on the number of users and expected workload. Your exact needs may be more, depending on your workload. Your workload is influenced by factors such as - but not limited to - how active your users are, how much automation you use, mirroring, and repository/change size.

The following is the recommended minimum CPU hardware guidance for a handful of example GitLab user base sizes.

  • 4 cores is the recommended minimum number of cores and supports up to 500 users
  • 8 cores supports up to 1000 users
  • More users? Consult the reference architectures page

Memory

Memory requirements are dependent on the number of users and expected workload. Your exact needs may be more, depending on your workload. Your workload is influenced by factors such as - but not limited to - how active your users are, how much automation you use, mirroring, and repository/change size.

The following is the recommended minimum Memory hardware guidance for a handful of example GitLab user base sizes.

  • 4GB RAM is the required minimum memory size and supports up to 500 users
    • Our Memory Team is working to reduce the memory requirement.
  • 8GB RAM supports up to 1000 users
  • More users? Consult the reference architectures page

In addition to the above, we generally recommend having at least 2GB of swap on your server, even if you currently have enough available RAM. Having swap helps to reduce the chance of errors occurring if your available memory changes. We also recommend configuring the kernel's swappiness setting to a low value like 10 to make the most of your RAM while still having the swap available when needed.

Database

PostgreSQL is the only supported database, which is bundled with the Omnibus GitLab package. You can also use an external PostgreSQL database. Support for MySQL was removed in GitLab 12.1. Existing users using GitLab with MySQL/MariaDB are advised to migrate to PostgreSQL before upgrading.

PostgreSQL Requirements

The server running PostgreSQL should have at least 5-10 GB of storage available, though the exact requirements depend on the number of users.

We highly recommend using the minimum PostgreSQL versions (as specified in the following table) as these were used for development and testing:

GitLab version Minimum PostgreSQL version
10.0 9.6
13.0 11
14.0 12

You must also ensure the following extensions are loaded into every GitLab database. Read more about this requirement, and troubleshooting.

Extension Minimum GitLab version
pg_trgm 8.6
btree_gist 13.1
plpgsql 11.7

NOTE: Support for PostgreSQL 9.6 and 10 was removed in GitLab 13.0 so that GitLab can benefit from PostgreSQL 11 improvements, such as partitioning. For the schedule of transitioning to PostgreSQL 12, see the related epic.

Additional requirements for GitLab Geo

If you're using GitLab Geo, we strongly recommend running Omnibus GitLab-managed instances, as we actively develop and test based on those. We try to be compatible with most external (not managed by Omnibus GitLab) databases (for example, AWS Relational Database Service (RDS)), but we can't guarantee compatibility.

Gitaly Cluster database requirements

Read more in the Gitaly Cluster documentation.

Exclusive use of GitLab databases

Databases created or used for GitLab, Geo, Gitaly Cluster, or other components should be for the exclusive use of GitLab. Do not make direct changes to the database, schemas, users, or other properties except when following procedures in the GitLab documentation or following the directions of GitLab Support or other GitLab engineers.

  • The main GitLab application currently uses three schemas:

    • The default public schema
    • gitlab_partitions_static (automatically created)
    • gitlab_partitions_dynamic (automatically created)

    No other schemas should be manually created.

  • GitLab may create new schemas as part of Rails database migrations. This happens when performing a GitLab upgrade. The GitLab database account requires access to do this.

  • GitLab creates and modifies tables during the upgrade process, and also as part of normal operations to manage partitioned tables.

  • You should not modify the GitLab schema (for example, adding triggers or modifying tables). Database migrations are tested against the schema definition in the GitLab code base. GitLab version upgrades may fail if the schema is modified.

Puma settings

The recommended settings for Puma are determined by the infrastructure on which it's running. The GitLab Linux package defaults to the recommended Puma settings. Regardless of installation method, you can tune the Puma settings:

  • If you're using the GitLab Linux package, see Puma settings for instructions on changing the Puma settings.
  • If you're using the GitLab Helm chart, see the webservice chart.

Puma workers

The recommended number of workers is calculated as the highest of the following:

  • 2
  • A combination of CPU and memory resource availability (see how this is configured automatically for the Linux package).

Take for example the following scenarios:

  • A node with 2 cores / 8 GB memory should be configured with 2 Puma workers.

    Calculated as:

    The highest number from
    2
    And 
    [
    the lowest number from
      - number of cores: 2
      - memory limit: (8 - 1.5) = 6
    ]
    

    So, the highest from 2 and 2 is 2.

  • A node with 4 cores / 4 GB memory should be configured with 2 Puma workers.

    The highest number from
    2
    And 
    [
    the lowest number from
      - number of cores: 4
      - memory limit: (4 - 1.5) = 2.5 
    ]
    

    So, the highest from 2 and 2 is 2.

  • A node with 4 cores / 8 GB memory should be configured with 4 Puma workers.

    The highest number from
    2
    And 
    [
    the lowest number from
      - number of cores: 4
      - memory limit: (8 - 1.5) = 6.5
    ]
    

    So, the highest from 2 and 4 is 4.

You can increase the number of Puma workers, provided enough CPU and memory capacity is available. A higher number of Puma workers usually helps to reduce the response time of the application and increase the ability to handle parallel requests. You must perform testing to verify the optimal settings for your infrastructure.

Puma threads

The recommended number of threads is dependent on several factors, including total memory, and use of legacy Rugged code.

  • If the operating system has a maximum 2 GB of memory, the recommended number of threads is 1. A higher value results in excess swapping, and decrease performance.
  • If legacy Rugged code is in use, the recommended number of threads is 1.
  • In all other cases, the recommended number of threads is 4. We don't recommend setting this higher, due to how Ruby MRI multi-threading works.

Redis and Sidekiq

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 multi-threaded 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 billable users) the Sidekiq process can use 1GB+ of memory.

Prometheus and its exporters

As of Omnibus GitLab 9.0, Prometheus and its related exporters are enabled by default, to enable easy and in depth monitoring of GitLab. With default settings, these processes consume approximately 200MB of memory.

If you would like to disable Prometheus and it's exporters or read more information about it, check the Prometheus documentation.

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, won't be valid if you decide to run GitLab Runner and the GitLab Rails application on the same machine.

It's 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. The GitLab Runner server requirements depend on:

  • The type of executor you configured on GitLab Runner.
  • Resources required to run build jobs.
  • Job concurrency settings.

Since the nature of the jobs varies for each use case, you need to experiment by adjusting the job concurrency to get the optimum setting.

For reference, GitLab.com's auto-scaling shared runner is configured so that a single job runs in a single instance with:

  • 1vCPU.
  • 3.75GB of RAM.

Supported web browsers

WARNING: With GitLab 13.0 (May 2020) we have removed official support for Internet Explorer 11.

GitLab supports the following web browsers:

For the listed web browsers, GitLab supports:

  • The current and previous major versions of browsers.
  • The current minor version of a supported major version.

NOTE: We don't support running GitLab with JavaScript disabled in the browser and have no plans of supporting that in the future because we have features such as Issue Boards which require JavaScript extensively.