Manage GitLab configuration as code to make it easily manageable, traceable and reproducible.
When configuring your GitLab instance, part of the settings you put in Omnibus or Helm Chart configuration, and the rest you configure through GitLab UI or API. Due to tons of configuration options in UI, making GitLab work as you intend is a complex process.
We intend to let you automate things you do through now UI in a simple way. The Configuration as Code has been designed to configure GitLab based on human-readable declarative configuration files written in Yaml. Writing such a file should be feasible without being a GitLab expert, just translating into code a configuration process one is used to executing in the web UI.
GCasC offers a functionality to configure:
- appearance
- application settings
- features
- Instance CI/CD variables
- license
- ... more coming soon!
It gives you also a way to:
- include external files or other Yamls using
!include
directive - inject environment variables into configuration using
!env
directive into your Yaml configuration.
Visit our documentation site for detailed information on how to use it.
Configuring your GitLab instance is as simple as this:
appearance:
title: "Your GitLab instance title"
logo: "http:https://path-to-your-logo/logo.png"
settings:
elasticsearch:
url: http:https://elasticsearch.mygitlab.com
username: !env ELASTICSEARCH_USERNAME
password: !env ELASTICSEARCH_PASSWORD
recaptcha_enabled: yes
terms: '# Terms of Service\n\n *GitLab rocks*!!'
plantuml:
enabled: true
url: 'http:https://plantuml.url'
instance_variables:
anotherVariable: 'another value'
MY_VARIABLE:
value: !env MY_VARIABLE
protected: false
masked: true
features:
- name: sourcegraph
value: true
groups:
- mygroup1
projects:
- mygroup2/myproject
users:
- myuser
license:
starts_at: 2019-11-17
expires_at: 2019-12-17
plan: premium
user_limit: 30
data: !include gitlab.lic
Note: GCasC supports only Python 3+. Because Python 2.7 end of life is January 1st, 2020 we do not consider support for Python 2.
Here you will learn how to quickly start with GCasC.
Important! Any execution of GCasC may override properties you define in your Yaml files. Don't try it directly on your production environment.
Visit our documentation site for detailed information on how to use it.
You can configure client in two ways:
- using configuration file:
By default GCasC is trying to find client configuration file in following paths:
[global] url = https://gitlab.yourdomain.com ssl_verify = true timeout = 5 private_token = <personal_access_token> api_version = 4
"/etc/python-gitlab.cfg", "/etc/gitlab.cfg", "~/.python-gitlab.cfg", "~/.gitlab.cfg",
B
You can provide a path to your configuration file in GITLAB_CLIENT_CONFIG_FILE
environment variable.
- using environment variables:
GITLAB_CLIENT_URL=<gitlab_url> # path to GitLab, default: https://gitlab.com GITLAB_CLIENT_API_VERSION=<gitlab_api_version> # GitLab API version, default: 4 GITLAB_CLIENT_TOKEN=<personal_access_token> # GitLab personal access token GITLAB_CLIENT_SSL_VERIFY=<ssl_verify> # Flag if SSL certificate should be verified, default: true
You can combine both methods and configuration settings will be searched in the following order:
- configuration file
- environment variables (due to limitations in
python-gitlab
if using configuration file onlyGITLAB_CLIENT_TOKEN
environment variable will be used)
Personal access token is mandatory in any client configuration approach and you can configure your it by following these instructions
Additionally you can customize HTTP session to enable mutual TLS authentication. To configure this, you should provide two additional environment variables:
GITLAB_CLIENT_CONFIG_FILE=<path_to_client_certificate>
GITLAB_CLIENT_KEY=<path_to_client_key>
GitLab configuration must be defined in Yaml file. You can provide a configuration in a single file, or you can split it into multiple Yaml files and inject them.
For information how to prepare GitLab configuration Yaml file visit our documentation site.
For settings
configuration, which defines Application Settings,
the structure is flexible. For example
settings:
elasticsearch:
url: http:https://elasticsearch.mygitlab.com
username: elastic_user
password: elastic_password
and B
settings:
elasticsearch_url: http:https://elasticsearch.mygitlab.com
elasticsearch_username: elastic_user
elasticsearch_password: elastic_password
are exactly the same and match elasticsearch_url
, elasticsearch_username
and elasticsearch_password
settings.
This means you can flexibly structure your configuration Yaml, where a map child keys are prefixed by parent key (here
elasticsearch
parent key was a prefix for url
, username
and password
keys). You only need to follow available
Application Settings.
You can adjust your Yamls by splitting them into multiple or injecting environment variables into certain values using
!include
or !env
directives respectively. Example is shown below:
settings:
elasticsearch:
url: http:https://elasticsearch.mygitlab.com
username: !env ELASTICSEARCH_USERNAME
password: !env ELASTICSEARCH_PASSWORD
terms: !include tos.md
license: !include license.yml
where:
-
settings.elasticsearch.username
andsettings.elasticsearch.password
are injected from environment variablesELASTICSEARCH_USERNAME
andELASTICSEARCH_PASSWORD
respectively -
settings.terms
andlicense
are injected fromtos.md
plain text file andlicense.yml
Yaml file respectively. In this scenario, yourlicense.yml
may look like this:
starts_at: 2019-11-17
expires_at: 2019-12-17
plan: premium
user_limit: 30
data: !include gitlab.lic
To run GCasC you can leverage CLI or Docker image. Docker image is a preferred way, because it is simple and does not require from you installing any additional libraries. Also, Docker image was designed that it can be easily used in your CI/CD pipelines.
When running locally, you may benefit from running GCasC in TEST mode (default mode is APPLY
), where no changes
will be applied, but validation will be performed and differences will be logged. Just set GITLAB_MODE
environment variable to TEST
.
export GITLAB_MODE=TEST
GCasC library is available in PyPI.
To install CLI run pip install gitlab-configuration-as-code
. Then you can simply execute
gcasc
//TODO add more information on CLI usage
Currently, CLI is limited and does not support passing any arguments to it, but behavior can only be configured using environment variables. Support for CLI arguments may appear in future releases.
Image is available in Docker Hub.
GCasC Docker image working directory is /workspace
. Thus you can quickly launch gcasc
with:
docker run -v $(pwd):/workspace hoffmannlaroche/gcasc
It will try to find both GitLab client configuration and GitLab configuration in /workspace
directory. You can modify
the behavior by passing environment variables:
GITLAB_CLIENT_CONFIG_FILE
to provide path to GitLab client configuration fileGITLAB_CONFIG_FILE
to provide a path to GitLab configuration file
docker run -e GITLAB_CLIENT_CONFIG_FILE=/gitlab/client.cfg -e GITLAB_CONFIG_FILE=/gitlab/config.yml
-v $(pwd):/gitlab hoffmannlaroche/gcasc
You can also configure a GitLab client using environment variables. More details about the configuration of GitLab client are available in this documentation.
We provide a few examples to give you a quick starting place to use GCasC. They can be found in examples
directory.
gitlab.cfg
is example GitLab client file configuration.basic
is an example GitLab configuration using a single configuration file.environment_variables
shows how environment variables can be injected into GitLab configuration file using!env
directive.modularized
shows how you can split single GitLab configuration file into smaller and inject files containing static text using!include
directive.
Use make
to build a basic Docker image quickly.
make docker-build
When using make
you can additionally pass DOCKER_IMAGE_NAME
to change default gcasc:latest
to another image name:
make docker-build DOCKER_IMAGE_NAME=mygcasc:1.0
To get more control over builds you can use docker build
directly:
docker builds -t gcasc[:TAG] .
Dockerfile comes with two build arguments you may use to customize your image by providing --build-arg
parameter
to docker build
command:
GCASC_PATH
defines the path where GCasC library will be copied. Defaults to/opt/gcasc
.WORKSPACE
defines a working directory when you run GCasC image. Defaults to/workspace
.
Use make
to build source distribution (sdist), Wheel binary distribution and Sphinx documentation.
make build
Both source and Wheel distributions will be placed in dist
directory. Documentation page will be placed
in build/docs
directory.
Remember to run tests before building your distribution!
Before submitting a pull request make sure that the tests still succeed with your change. Unit tests run using Github Actions and passing tests are mandatory to get merge requests accepted.
You need to install tox
to run unit tests locally:
# run the unit tests for python 3, python 2, and the flake8 tests:
tox
# run tests in one environment only:
tox -e py37
# run flake8 linter and black code formatter
tox -e flake
# run black code formatter
tox -e black
Instead of using tox
directly, it is recommended to use make
:
# run tests
make test
# run flake8 linter and black code formatter
make lint
Everyone is warm welcome to contribute!
Please make sure to read the Contributing Guide and Code of Conduct before making a pull request.
Mateusz |
Benj Fassbind |
Mariusz Kozakowski |
Project is released under Apache License, Version 2.0 license.