What Is GitLab and How Does It Work for DevOps Teams

GitLab started as an open-source project for Git-based version control but evolved into a comprehensive solution covering the full software development lifecycle. Unlike traditional approaches where you might use GitHub for code storage, Jenkins for automation, Docker Hub for containers and separate tools for security scanning, GitLab consolidates these functions under one roof. This all-in-one design means your team works within a single interface rather than switching between disconnected services.

The platform handles everything from initial code commits through testing, security analysis and final deployment to your web server. Think of GitLab as having a complete workshop where all your tools live in one place instead of visiting separate shops for different equipment. This integration streamlines your workflow because data flows naturally between stages without manual handoffs or complex integrations.

Enterprise adoption demonstrates GitLab’s maturity. As of August 2025, 20,863 verified companies use the platform, contributing to GitLab’s FY2025 revenue of $759.2 million with 31% year-on-year growth. Gartner recognised GitLab as a Leader in its 2025 Magic Quadrant for DevOps Platforms for the third consecutive year, reflecting the platform’s comprehensive capabilities and market position.

At its foundation, GitLab provides Git-based version control for storing and tracking changes to your website code. Git is the industry-standard system that records every modification, allowing you to revert mistakes, compare versions and understand who changed what and when. GitLab’s interface presents your repositories with visual tools for reviewing code changes, managing branches for different features and collaborating with team members through merge requests.

For a practical example, imagine you’re updating your website’s checkout process. You create a branch to work on the changes without affecting the live site. Team members review your code through GitLab’s interface, suggest improvements and approve the merge once everything looks correct. This structured approach prevents accidental breaks to your production website whilst maintaining a complete history of every change.

Continuous integration and continuous deployment represent GitLab’s most powerful feature for hosting customers. When you commit code changes, GitLab automatically runs tests, checks for errors and deploys updates to your web server without manual intervention. You define these automated workflows in YAML files that specify each step, from running security scans to copying files to your hosting environment.

The process works like this: you push updated code to GitLab, which triggers a pipeline that builds your application, runs automated tests, scans for security vulnerabilities and deploys to your staging server for review. Once approved, the same pipeline deploys to your production hosting environment. This automation eliminates repetitive manual deployment tasks and reduces human error. GitLab’s Auto DevOps feature can even generate these pipelines automatically for common deployment scenarios to cloud providers like AWS and Google Cloud Platform.

The free tier includes CI/CD capabilities but limits the minutes available for running pipelines each month. Teams with frequent deployments may need to optimise their pipeline efficiency or upgrade to paid tiers for additional capacity. Similar to how cronjobs automate scheduled tasks on traditional hosting, GitLab pipelines automate your entire deployment workflow on every code change.

GitLab includes a Docker container registry directly within the platform, eliminating the need for external services like Docker Hub. Containers package your web application with all its dependencies into standardised units that run consistently across different hosting environments. This matters for modern hosting approaches where you might deploy to VPS servers, cloud platforms or Kubernetes clusters.

When your CI/CD pipeline builds a container image of your application, GitLab stores it in the integrated registry. Your deployment process then pulls this image and runs it on your hosting infrastructure. This tight integration means your code, build process and container storage all live in one system, simplifying your workflow and reducing external dependencies.

GitLab builds security scanning directly into the platform rather than requiring separate paid tools. The security features include:

• Static Application Security Testing (SAST) that analyses your code for vulnerabilities before deployment
• Dynamic Application Security Testing (DAST) that tests your running application for security weaknesses
• Dependency scanning that checks third-party libraries for known vulnerabilities
• Container scanning for Docker images to identify security issues in your deployment packages
• Secret detection that prevents accidental commits of passwords or API keys

GitLab 18.6 introduced enhanced security capabilities including static reachability analysis and improved secret checks. These tools run automatically in your CI/CD pipelines, catching security problems before they reach your production hosting environment. For regulated industries, GitLab provides compliance frameworks that help you meet requirements like GDPR or industry-specific standards.

GitLab Duo brings artificial intelligence into your development workflow through code completion, AI agents and automated problem-solving. The system suggests code as you type, similar to predictive text on your phone but understanding programming languages and your project’s context. GitLab 18.4 introduced custom AI agents that can perform tasks like generating test cases or explaining complex code sections.

The Knowledge Graph feature helps you navigate large codebases by understanding relationships between different parts of your application. Auto-fix pipelines can even suggest corrections when your CI/CD pipeline encounters errors. Gartner named GitLab a Leader in its 2025 Magic Quadrant for AI Code Assistants for the second consecutive year, recognising these capabilities. GitLab’s AI Catalog supports multiple models including Claude and OpenAI, giving you flexibility in choosing the AI capabilities that suit your development needs.

GitLab offers three main tiers that balance features against cost. The Free tier, which includes the open-source Community Edition for self-hosting and the free GitLab.com cloud service, supports up to 5 users per group. This tier provides core Git repositories, basic CI/CD pipelines, issue tracking and the integrated container registry. For small teams managing straightforward websites, the free tier often provides sufficient functionality to automate deployments and collaborate effectively.

Premium tier adds advanced features like code quality analysis, priority support and enhanced security scanning. This level suits growing teams that need more sophisticated workflows and faster response times when problems arise. Ultimate tier includes everything from Premium plus additional security tools, compliance features and advanced AI capabilities through GitLab Duo. Enterprises with strict regulatory requirements or complex security needs typically choose Ultimate.

GitLab shifted to a hybrid seat and usage pricing model in 2025, meaning you pay based on both the number of users and your consumption of resources like CI/CD minutes and storage. The specific quotas change periodically, so check current limits when planning your budget. Self-hosted Community Edition remains free but requires you to manage your own infrastructure and maintenance.

Some hosting providers offer GitLab installation services or VPS configurations optimised for self-hosting, which can simplify the technical setup if you choose to run your own instance. The decision between cloud-hosted GitLab.com and self-hosting depends on your team’s technical expertise, budget and control requirements.

GitHub and GitLab both provide Git-based version control, but their approaches differ significantly. GitHub built its reputation on community and open-source collaboration, offering a simpler interface that many developers find more approachable. GitLab positions itself as a complete DevOps platform with more integrated tools built directly into the core product rather than relying on third-party additions.

The most significant difference appears in CI/CD capabilities. GitLab includes native continuous integration and deployment pipelines that you configure with YAML files stored alongside your code. GitHub offers GitHub Actions for similar automation, but this came later and works somewhat differently. Teams that prioritise deployment automation often find GitLab’s approach more comprehensive and easier to manage within a single system.

Security features show another divergence. GitLab integrates security scanning, vulnerability detection and compliance tools in the platform itself, with many features available on free tiers. GitHub typically requires third-party integrations or paid GitHub Advanced Security for comparable capabilities. This matters for web projects where security scanning should run automatically on every code change before deployment to your hosting environment.

GitHub maintains advantages in community size and third-party integrations. More developers use GitHub, meaning more open-source projects live there and more tools integrate with it. For teams focused primarily on code storage and collaboration with minimal automation needs, GitHub’s simplicity may prove more practical. However, teams managing web hosting deployments with automated testing and security requirements often benefit from GitLab’s integrated approach that handles the full journey from code to production server.

Research describes GitLab as a one-stop shop for Git repositories, CI/CD pipelines, wikis and container management. This consolidation reduces the number of separate services you need to configure and maintain, though it does mean learning a more complex system upfront.

Running GitLab on your own infrastructure requires careful attention to server specifications because the platform handles multiple functions simultaneously. A Linux server forms the foundation, with Ubuntu being the most commonly used distribution for GitLab installations. The resource requirements scale significantly based on your team size and how heavily you use CI/CD pipelines.

For a small team of up to 10 users with light CI/CD usage, you need at minimum 4GB of RAM and 2 CPU cores. This handles basic Git operations and occasional pipeline runs. Medium-sized teams of 100 users typically require 16GB RAM and 8 CPU cores to maintain responsive performance. Enterprise deployments with hundreds of users and constant CI/CD activity may need 32GB RAM or more, along with dedicated storage for repositories and build artifacts.

Storage needs depend on your repository sizes and how long you retain CI/CD build artifacts. Fast SSD storage improves performance significantly compared to traditional hard drives. You can check RAM usage on your server to verify it meets GitLab’s requirements and monitor resource consumption as your usage grows.

Several hosting providers offer VPS plans specifically configured for GitLab or provide managed GitLab hosting that handles the technical setup and maintenance for you.

GitLab Community Edition is open-source and free to self-host on your own infrastructure. The installation typically uses package managers that handle dependencies and configuration automatically. For Ubuntu servers, you add GitLab’s package repository and install via apt commands. Docker-based installation offers an alternative approach that packages GitLab and its dependencies in containers, which some teams find easier to manage and update.

The installation requires SSH access to your server with root or sudo privileges. You’ll configure basic settings like the domain name where GitLab will be accessible, email settings for notifications and initial administrator credentials. The process involves setting up a database (PostgreSQL), web server (Nginx) and background job processor (Sidekiq), though package installations handle these components automatically.

GitLab’s official documentation provides detailed step-by-step guides, as specific commands vary by Linux distribution and GitLab version. The installation typically takes 30 minutes to an hour for someone familiar with Linux server administration, longer if you’re learning as you go.

Self-hosting GitLab means you’re responsible for ongoing maintenance, security updates and backups. GitLab releases new versions monthly with security patches and feature updates. You need to apply these updates regularly to keep your installation secure and stable. The update process usually involves running package manager commands, though you should always back up your data first in case something goes wrong.

Regular backups are essential because your GitLab instance contains your entire code repository, CI/CD configurations and project history. Most teams automate daily backups to separate storage, either on-site or to cloud storage services. You’ll also need to monitor server resources to ensure GitLab has sufficient capacity as your usage grows.

The trade-offs between self-hosting and cloud-hosted GitLab.com become clear when considering maintenance:

• Self-hosting pros: Complete control over data location, customisation options, no external service dependencies, suitable for strict compliance requirements
• Self-hosting cons: Requires technical expertise, ongoing maintenance burden, you handle security updates, infrastructure costs, need backup strategy
• Cloud hosting pros: GitLab handles all maintenance and updates, automatic backups, no infrastructure management, easier to scale
• Cloud hosting cons: Data stored on GitLab’s servers, less customisation, ongoing subscription costs, dependent on external service

Teams with strong Linux administration skills and compliance requirements that mandate on-premise data storage often choose self-hosting. Teams wanting to focus on development rather than infrastructure management typically prefer GitLab.com’s cloud service.

GitLab’s CI/CD pipelines can automate deployment to traditional shared hosting or VPS environments through several methods. The most common approach uses FTP, SFTP or SSH to transfer files from your GitLab repository to your web server after successful testing. You define this workflow in a .gitlab-ci.yml file stored in your repository, which specifies the deployment steps.

A typical pipeline for a website might include stages for testing, building and deployment. When you commit code changes, GitLab runs your tests to verify nothing broke. If tests pass, the build stage compiles assets like CSS and JavaScript. Finally, the deployment stage connects to your web server and uploads the updated files. This happens automatically on every commit to your main branch, or you can configure manual approval steps for production deployments.

The deployment stage typically uses copying files via SSH for secure transfer to your hosting environment. You store your server credentials as protected variables in GitLab’s settings, keeping them secure rather than exposing them in your code. The pipeline script then uses these credentials to authenticate and transfer files.

For example, a WordPress site deployment might look like this: you update a theme file in your local development environment, commit the change to GitLab, which triggers a pipeline that runs PHP syntax checks, optimises images, then connects via SSH to your hosting account and copies the updated files to the correct directory. Your website updates within minutes of committing the code, with no manual file uploads or FTP client needed.

Modern hosting approaches using cloud platforms like AWS, Google Cloud or Azure integrate naturally with GitLab’s container-focused features. Your CI/CD pipeline builds a Docker container image of your application, stores it in GitLab’s integrated registry, then deploys that container to your cloud infrastructure. This approach ensures your application runs identically across development, staging and production environments because the container packages everything needed.

GitLab’s Auto DevOps feature can automatically generate deployment pipelines for major cloud providers, detecting your application type and configuring appropriate build and deployment steps. Nasdaq’s case study demonstrates this capability, where they achieved their 100% cloud vision at DevOps speed using GitLab’s integrated approach to cloud deployments.

For teams using Kubernetes to orchestrate containers across multiple servers, GitLab provides built-in Kubernetes integration. Your pipeline can deploy to Kubernetes clusters, manage rolling updates and handle rollbacks if deployments fail. Infrastructure-as-code tools like Terraform integrate with GitLab to manage your hosting infrastructure itself through code, meaning you can version control not just your application code but also the server configurations, network settings and cloud resources that run your website.

Professional web development typically involves multiple environments: development for active coding, staging for testing before release and production for your live website. GitLab manages deployments to these different environments through its pipeline configuration and environment-specific variables.

You define separate deployment stages in your pipeline, each targeting a different server. Development deployments might happen automatically on every commit, giving developers immediate feedback. Staging deployments could trigger when you merge code into a release branch, allowing quality assurance testing before production. Production deployments might require manual approval from a team lead, adding a safety check before changes reach your live website.

Environment-specific variables let you use different database credentials, API keys or server addresses for each environment whilst keeping the pipeline configuration itself consistent. This prevents accidentally deploying development code with test credentials to your production hosting environment. GitLab’s interface shows the current state of each environment, which Git commit is deployed where and provides buttons to manually trigger deployments or rollbacks when needed.

Beginning with GitLab involves several practical decisions and setup steps. First, choose between GitLab.com’s cloud service and self-hosting. For most small teams starting out, GitLab.com makes sense because you can begin immediately without server setup. The free tier supports 5 users per group, which suffices for small website projects whilst you learn the platform.

Create your account on GitLab.com and set up your first project repository. This involves giving your project a name, choosing visibility settings (private, internal or public) and optionally initialising with a README file. Import existing code from your local machine using Git commands, or start fresh if this is a new project. The GitLab interface provides clear instructions for connecting your local development environment to the remote repository.

Next, invite team members by adding their email addresses or GitLab usernames to your project. Set appropriate permission levels so developers can push code whilst restricting who can approve merges or modify settings. This access control prevents accidental changes to critical configurations.

Configuring your first CI/CD pipeline represents the most valuable step for hosting customers. Start simple rather than trying to implement complex workflows immediately. A basic pipeline might just run syntax checks and deploy to a staging server. Create a .gitlab-ci.yml file in your repository root with straightforward stages. Many teams over-complicate their initial pipeline configuration, which creates frustration. Begin with one or two stages, verify they work correctly, then gradually add more sophisticated testing and deployment steps.

Connect GitLab to your hosting environment by adding server credentials as protected variables in your project settings. Test your deployment pipeline to a staging server first, never directly to production. This lets you identify and fix configuration issues without risking your live website. Once the staging deployment works reliably, duplicate the configuration for production with appropriate approval requirements.

GitLab 18.6 introduced improvements to the glab command-line interface, which some developers prefer for interacting with GitLab from their terminal rather than the web interface. This is optional but worth exploring once you’re comfortable with the basics. Some hosting providers offer GitLab integration guides specific to their platforms or provide one-click deployment configurations that simplify connecting GitLab pipelines to your hosting account.

GitLab’s comprehensive feature set creates a steeper learning curve compared to simpler alternatives like basic GitHub usage. New users often feel overwhelmed by the number of options and settings. The solution is to ignore most features initially and focus only on what you need immediately: repository management and basic CI/CD. You don’t need to understand security scanning, container registries or AI features to get value from GitLab. Add complexity gradually as your needs grow rather than trying to learn everything at once.

CI/CD minute limits on free plans create constraints for teams with frequent deployments or long-running pipelines. Each pipeline execution consumes minutes from your monthly quota, and complex builds can exhaust this quickly. Optimise your pipelines by caching dependencies between runs so they don’t need to download the same files repeatedly. Split long pipelines into smaller stages that only run when relevant code changes. Consider upgrading to a paid tier if your team deploys frequently, as the time saved through automation typically justifies the cost.

YAML syntax for pipeline configuration frustrates developers unfamiliar with the format. YAML is sensitive to indentation and spacing, making it easy to create configuration files that look correct but fail with cryptic errors. Use GitLab’s built-in CI/CD configuration validator to check your YAML before committing. Start with example configurations from GitLab’s documentation and modify them incrementally rather than writing from scratch. Many teams keep a library of working pipeline snippets they can reuse across projects.

The transition from free to paid tiers creates what researchers call funnel friction where teams outgrow free limits but hesitate at the pricing jump. Plan for this by monitoring your usage of CI minutes and storage as your project grows. The free tier works well for learning and small projects, but professional web development typically requires a paid plan eventually. Factor this into your project budget from the start rather than being surprised later.

British businesses evaluating GitLab often prioritise data sovereignty and compliance with UK regulations. Self-hosting GitLab on your own infrastructure or using GitLab Dedicated (a single-tenant cloud option) keeps your code and data within your control, which matters for organisations with strict data location requirements. This approach lets you choose UK-based hosting providers or data centres, ensuring your repositories never leave British jurisdiction.

GDPR compliance affects how you handle code that processes personal data. GitLab’s security scanning helps identify potential data protection issues in your code before deployment. The platform’s audit logs track who accessed what and when, providing the documentation needed for compliance reporting. For regulated industries like finance or healthcare, GitLab Ultimate includes compliance frameworks that map your development processes to regulatory requirements.

UK businesses adopting AI-powered development tools saw significant benefits according to a 2025 report. British firms gained £6.7 billion in business growth from AI software, with 53% reporting revenue growth and 54% experiencing productivity boosts. GitLab Duo’s AI features contribute to these gains by accelerating code writing, automating routine tasks and helping developers understand complex codebases faster.

Integration with UK-based cloud regions matters for latency and data residency. GitLab works with AWS’s London region, Google Cloud’s UK zones and Azure’s British data centres, letting you deploy applications to infrastructure within the UK whilst using GitLab’s CI/CD pipelines for automation. This geographic proximity reduces deployment times and keeps your application data in Britain. Several UK-based hosting providers offer GitLab-optimised infrastructure or managed GitLab hosting services that understand British compliance requirements.

GitLab provides a comprehensive DevSecOps platform that unifies version control, automated pipelines, security scanning and AI-powered development tools in a single application. For web development teams, this consolidation means managing your entire workflow from initial code commits through testing and deployment to your hosting infrastructure without juggling multiple disconnected services. The platform works as either a cloud service through GitLab.com or as a self-hosted solution on your own servers, giving you flexibility based on your team’s technical expertise and control requirements.

The learning curve is real, particularly compared to simpler tools focused only on code storage. However, teams that invest time in learning GitLab typically see faster deployments, fewer manual errors and more reliable releases to their production websites. Start with the free tier to evaluate whether GitLab fits your workflow before committing to paid plans. For hosting customers, the choice between cloud-hosted and self-hosted GitLab depends on your team size, compliance needs and whether you prefer managing infrastructure yourself or letting GitLab handle the technical operations.