How to Centralize GitLab CI/CD Configurations Across Projects, Groups, and Instances

Most developers and DevOps engineers assume that a GitLab CI/CD pipeline is triggered by a .gitlab-ci.yml file placed in the root of each project. As teams grow, maintaining a separate CI configuration for every repository becomes redundant and hard to manage. GitLab, however, offers flexible ways to define CI/CD pipelines at the project, group, and even instance level.

Project level: custom CI/CD configuration file path

The simplest approach is to stop relying on the default path. GitLab allows each project to specify an alternative location for its CI/CD configuration file, which can reside in another directory, another project, or an external URL.

Separate code and CI configuration – keep application source code apart from pipeline logic.

Shared configuration – multiple projects can reference the same file stored in a central "CI config repository".

Configuration steps:

In the project sidebar, go to Settings > CI/CD .

Expand the General pipelines section.

In the CI/CD configuration file field, enter the desired path.

The path format is very flexible:

Other path inside the project – path/to/my-ci-config.yml File in another project – .gitlab-ci.yml@group-name/other-project-name External URL – https://example.com/path/to/ci-config.yml By using this method, a dedicated repository can hold a standard CI template that multiple business projects reference, achieving unified management and updates.

Group level: using include for shared and inherited configurations

When a common CI/CD logic must be applied to a set of projects, specifying a file path for each project is still cumbersome. Combining group-level CI/CD variables with the include keyword enables elegant configuration sharing.

The include keyword imports external YAML content into the current CI/CD file, allowing a concise .gitlab-ci.yml that pulls one or more template files from a central repository.

A typical workflow:

Create a CI template project under a group (e.g., ci-templates).

Define base templates such as build.yml, test.yml, deploy.yml inside that project.

Include templates in business projects by adding an include section to their own .gitlab-ci.yml.

# .gitlab-ci.yml in your application project
include:
  - project: 'your-group/ci-templates'
    ref: main
    file: '/templates/build-and-deploy.yml'

# Your project‑specific jobs can be added here
# They can even extend jobs defined in the included file

This pattern ensures consistent CI/CD processes while still allowing each project to add or extend jobs using job definitions or the extends keyword.

Instance level: setting a default CI/CD template for new projects

For self‑hosted GitLab instances, administrators can define a default CI/CD configuration that all newly created projects inherit, helping enforce organization‑wide DevOps standards.

In Admin Area > Settings > CI/CD , two key options are available:

Default CI/CD configuration file – specify a path (e.g., pointing to an instance‑level template project) that new projects will use instead of a .gitlab-ci.yml in the repository root.

CI/CD templates – configure an "Instance template repository" where vetted, high‑quality CI/CD templates are stored for universal use.

With instance‑level defaults, even brand‑new projects immediately receive a compliant, feature‑complete CI/CD pipeline, dramatically lowering onboarding effort.

Conclusion: From fragmented to centralized CI/CD management

In summary, GitLab’s CI/CD system is far more flexible than a single .gitlab-ci.yml file at the project root. Teams can choose the most suitable strategy based on their scale and needs:

Project level – custom paths separate code from CI configuration.

Group level – use include and template projects to share and inherit configurations, achieving DRY principles.

Instance level – set default configurations and template repositories to establish organization‑wide standards.

These advanced features not only reduce redundancy but also shift CI/CD management from a scattered, project‑driven model to a centralized, platform‑driven approach, making it easier for DevOps teams to propagate best practices, enforce security policies, and adapt pipelines quickly when infrastructure or toolchains evolve.