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GitLab Runners – A Complete Guide

If you’re using GitLab SaaS (GitLab Cloud), you have multiple runner options to execute your CI/CD jobs. Each runner source gives you different levels of control, performance, and cost efficiency.

Here’s a complete and up-to-date list of runner sources available to you on GitLab Cloud (GitLab.com) as of version 18.0 (May 2026):


✅ Available Runner Sources in GitLab Cloud

Runner SourceDescriptionUse CaseAvailability
GitLab Shared RunnersProvided and maintained by GitLab. Run on GitLab-managed infrastructure (auto-scaled).Quick start, no setup needed✅ Enabled by default
Project-Specific RunnersInstalled and registered for a single project only.Dedicated pipelines for sensitive repos✅ User-managed
Group RunnersRegistered to a group and available to all projects inside the group.Shared infra across multiple related projects✅ User-managed
Self-Hosted Runners (Custom)Installed on your own infrastructure (Linux, macOS, Windows, Docker, Kubernetes, etc.).Full control over environment & cost✅ GitLab SaaS-compatible
GitLab Kubernetes Executor (Auto DevOps)Auto-provisioned runner inside a connected K8s cluster (via GitLab Agent or legacy cert).Cloud-native CI/CD with GitOps-style delivery✅ Optional setup
GitLab macOS Runners (M1/M2) (beta)Apple Silicon runners for building macOS/iOS apps (Xcode). Currently in Beta for SaaS.iOS/macOS mobile CI/CD🧪 Limited Beta
GitLab Windows Runners (hosted or self)Use Windows executor to build/test .NET, Windows apps.Windows-native software pipelines✅ Self-hosted or BYO
GitLab GPU Runners (beta)GPU-backed runners for AI/ML workloads (uses NVIDIA CUDA).Model training and GPU-based data pipelines🧪 Ultimate / Limited Beta

🔧 Summary of Executors by Runner Type

Executor TypeCompatible with GitLab Cloud?Platform Examples
shell✅ (self-hosted only)Local VMs, bare metal
dockerDocker-in-Docker setups
docker+machine✅ (with autoscaling)AWS/GCP dynamic runners
kubernetesGKE, EKS, AKS
customAny custom automation
sshRemote Linux VMs
virtualbox❌ GitLab SaaS not supportedOnly works self-managed
parallels❌ Deprecated
shell-windowsWindows self-hosted

📌 Special GitLab SaaS-Hosted Runners

Runner TypeLanguage SupportNotes
Linux Shared RunnersDefault Docker executor (Node, Python, etc.)400 CI minutes/month for Free tier
macOS Runners (beta)Swift, Xcode, iOSAvailable via GitLab-hosted pool
GPU Runners (beta)CUDA, TensorFlow, PyTorchUltimate SaaS, usage billed separately
Windows Runners.NET Core, PowerShellUse your own runner for Windows

🎯 When to Use What

Use CaseRecommended Runner
Quick setup for any projectGitLab Shared Runners
Secure or private pipelines (sensitive data)Project/Group-specific runners
Complex environments (Terraform, AI/ML)Self-hosted Docker or Kubernetes
macOS/iOS CI/CDGitLab macOS Runners (Beta)
Windows CI/CDSelf-hosted Windows runner
GPU training / AI workloadsGPU runners (Ultimate only)

✅ How to View/Add Runners in GitLab Cloud

  • Project > Settings > CI/CD > Runners
    • Shows shared runners, and allows adding project-specific ones
  • Group > Settings > CI/CD > Runners
    • For group-level runners
  • Admin Runners Page (for instance-level visibility, GitLab self-managed only)

As of GitLab 18.x, GitLab supports several types of runners to execute CI/CD jobs. Here’s a clear and updated breakdown:


🏃 Types of GitLab Runners in GitLab 18.x

1. Shared Runners

  • Scope: Available to all projects in an instance or group.
  • Managed by: GitLab instance admin (self-hosted or GitLab.com).
  • Use case: Ideal for teams that don’t want to manage infrastructure for builds.
  • Example: GitLab.com provides autoscaling shared runners using Docker Machine.

✅ Pros:

  • Easy to set up
  • Great for small teams and quick pipelines
    ⚠️ Cons:
  • Queues can be long on GitLab.com during peak usage

2. Group Runners

  • Scope: Available to all projects within a group.
  • Managed by: Group owners
  • Use case: For teams managing multiple related projects needing the same CI resources.

✅ Pros:

  • Centralized control at group level
  • Avoids redundancy for project-specific runners

3. Project-specific Runners

  • Scope: Tied to a single project only.
  • Managed by: Project maintainers/owners
  • Use case: When a project needs specialized tools or secure execution.

✅ Pros:

  • Full control
  • Secure, isolated builds
    ⚠️ Cons:
  • More setup and maintenance overhead

🔧 Execution Environments (Runners’ Executor Types)

Each runner (regardless of shared/group/project) uses an executor to determine how jobs are run:

ExecutorDescription
shellUses host shell (e.g., Bash); minimal setup
dockerSpawns Docker containers to run jobs (very popular)
docker+machineScales runners dynamically using Docker Machine
kubernetesRuns jobs as pods inside a Kubernetes cluster
sshExecutes jobs on a remote server over SSH
customDefine your own job executor flow
virtualbox (deprecated)Used VMs (not commonly used now)
parallels (macOS only)Used Parallels for macOS virtualized runners

🧠 Special Note on GitLab SaaS vs Self-Managed

Runner TypeGitLab.com (SaaS)Self-Managed GitLab
Shared Runners✅ Available✅ Can be configured
Group Runners🚫 Not available✅ Available
Project Runners✅ Available✅ Available

GitLab.com (SaaS) does not support Group-level runners for security/resource isolation reasons.


🔄 Registering a Runner

To register a runner in GitLab 18.0, follow these steps:GitLab Docs

  1. Install GitLab Runner: Ensure GitLab Runner is installed on your desired host machine.
  2. Obtain a Registration Token:
    • Instance Runner: Available in the Admin Area under CI/CD > Runners.
    • Group Runner: Found in the group’s Settings > CI/CD > Runners section.
    • Project Runner: Located in the project’s Settings > CI/CD > Runners section.
  3. Register the Runner:

After successful registration, the runner will appear in the GitLab UI under the appropriate scope (instance, group, or project). GitLab Docs

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