GitLab

GitLab CI/CD

Built-in CI/CD for GitLab: pipelines defined in .gitlab-ci.yml, runners on Linux, macOS, and Windows, and Auto DevOps for opinionated deploys. GitLab Duo brings AI code suggestions, vulnerability explanations, root cause analysis on failed jobs, and chat-based incident triage. The single-application platform sell remains its differentiator vs GitHub plus add-ons.

Deploy Secure

Visit website

Last reviewedMay 15, 2026

How we review

Overview

GitLab CI/CD is the pipeline engine integrated into the GitLab platform, configured via a .gitlab-ci.yml file stored in the repository. Pipelines are tightly coupled to the GitLab merge request lifecycle: they run against MR branches, post results as MR annotations, and enforce pass/fail requirements on merge.

Runners execute jobs on Linux, Windows, macOS, Docker, Kubernetes, and custom executor environments. Runners register outbound to the GitLab instance and accept jobs without inbound firewall rules; the self-managed runner model gives operators full control over compute, network, and credential handling.

Auto DevOps detects the application runtime and generates a working pipeline configuration without a manually authored .gitlab-ci.yml, covering build, test, and Kubernetes deployment. Built-in security scanning templates (SAST, DAST, dependency scanning, container scanning, secret detection) run as native pipeline jobs. GitLab Duo AI explains failed job logs and suggests fixes, running on the GitLab-hosted AI backend. Pricing: Free, Premium ($29/user/month), Ultimate ($99/user/month); self-managed available on all tiers.

Key Features

.gitlab-ci.yml pipeline config tightly integrated with the GitLab merge request lifecycle — pipelines run against MR branches and block merge on failure without separate webhook configuration
Auto DevOps: zero-configuration pipeline detection for common language stacks — detects the runtime, builds a container image, runs tests, and deploys to Kubernetes without a manually authored .gitlab-ci.yml
Self-managed runner support on any infrastructure: Linux, Windows, macOS, Docker, Kubernetes, and custom executors — runners register with the GitLab instance and accept jobs without inbound firewall rules
Built-in security scanning templates: SAST, DAST, dependency scanning, container scanning, and secret detection are GitLab-native pipeline jobs that produce merge request annotations and a security dashboard
Pipeline DAG visualizer: graphical view of job dependencies and execution order — surfaces which jobs are blocking which and where parallelism can be increased in a complex pipeline
GitLab Duo AI pipeline assistance: explains CI failure logs in plain language, suggests root cause, and proposes YAML fixes — runs on the GitLab-hosted AI backend without sending code to third-party LLMs

Integrations

10 total

scm

GitLab

ci / cd

TerraformOpenTofuAnsibleHelm

cloud

AWSGCPAzure

orchestration

Kubernetes

messaging

Slack

Pricing

No pricing data on file.

Compare with similar tools

1 comparison

GitLab CI/CD vs GitHub Actions

Compliance

5 / 6 attested

SOC 2

HIPAA

GDPR

FedRAMP

PCI DSS

ISO 27001

Freshness

Heartbeatverified · 4d ago

Listings are re-verified on a recurring sweep. If the website 200s and pricing hasn't shifted since the last check, the heartbeat stays green.

UpdatedJun 18, 2026

What does AI Adjacent mean?

AI maturity is an independent editorial rating assigned by infraplz.dev — not a vendor self-claim. We assess how meaningfully each tool actually uses AI in production workflows, cutting through marketing copy.

AI NativeAI is the core product — the tool wouldn't exist without it.
AI EnhancedAI is a first-class feature that materially changes the workflow.
AI AdjacentAI features exist but are superficial or bolt-on additions.
AI MinimalNo meaningful AI features; listed as a critical platform engineering tool.

AboutSubmit a tool