[{"data":1,"prerenderedAt":790},["ShallowReactive",2],{"/en-us/blog/fast-and-natural-continuous-integration-with-gitlab-ci":3,"navigation-en-us":33,"banner-en-us":433,"footer-en-us":443,"blog-post-authors-en-us-Samuel Alfageme":685,"blog-related-posts-en-us-fast-and-natural-continuous-integration-with-gitlab-ci":699,"assessment-promotions-en-us":741,"next-steps-en-us":780},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":22,"isFeatured":12,"meta":23,"navigation":24,"path":25,"publishedDate":20,"seo":26,"stem":30,"tagSlugs":31,"__hash__":32},"blogPosts/en-us/blog/fast-and-natural-continuous-integration-with-gitlab-ci.yml","Fast And Natural Continuous Integration With Gitlab Ci",[7],"samuel-alfageme",null,"engineering",{"slug":11,"featured":12,"template":13},"fast-and-natural-continuous-integration-with-gitlab-ci",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9},"Fast and natural continuous integration with GitLab CI","An overview of GitLab Continuous Integration and Delivery, and the main features of the tool.",[18],"Samuel Alfageme","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749684106/Blog/Hero%20Images/fast-and-natural-continuous-integration-with-gitlab-ci.jpg","2017-05-22","\nDo you use GitLab to store your repos? Have you ever stopped to check what some of those tabs on top of your repositories do? Well, you can either disable those in your project settings, or you can keep reading to discover some ways in which they can help you power up your development speed.\n\n\u003C!-- more -->\n\n![what do these tabs do?](https://about.gitlab.com/images/blogimages/fast-and-natural-continuous-integration-with-gitlab-ci/your-awesome-project.png){: .shadow}\u003Cbr>\n\nThis post aims to offer a high-level overview of how GitLab has interpreted the main concepts of Continuous Integration/Delivery and introduce the main features of the tool as well as their naming conventions, as it can sound more overwhelming than it actually is.\n\nThe product’s growth has made it present on many companies’ tech stacks. Part of this popularity comes from being indeed a great open-source project to follow, its release cycle is blazing fast and it’s delivering new features every month on the 22nd. One of the most important factors of this equation is the fact that it’s not only a self-managed solution that enables you to have all your projects under control, but also a pretty solid one. Just ask your reference ops for his opinion on how even the community (non-commercial) edition brings many stuff to the table, that were incredibly expensive or even lacking on many other SaaS products before.\n\n![integrated development tools](https://about.gitlab.com/images/blogimages/fast-and-natural-continuous-integration-with-gitlab-ci/idea-to-production-graphics.png){: .shadow}\u003Cbr>\n\nIt sometimes happens that we simply stick to well-known tools for us and won’t notice or research alternatives that may improve our everyday work. I believe this to be the case with some of the GitLab’s lesser-known features. The software is much more than a traditional VCS server. In fact, last year they came up with the idea of their so-called “masterplan” to extend the product to be more like a “suite” and cover every step of the development cycle, or in their words: go from [idea to production](/blog/continuous-integration-delivery-and-deployment-with-gitlab/#from-idea-to-production-with-gitlab). And in both previous and [future](/direction/) releases, they are bundling some really cool additional integrations worth checking (e.g. Mattermost ChatOps or Prometheus monitoring).\n\n### Differences with other continuous integration tools\n\nLet’s start getting the full picture of the features that make it so powerful. First of all, its model is based on a lightweight YAML configuration file stored in each repository’s root. This has some pros worth to mention along with the rest:\n\n1. Tightly coupled systems (both Continuous Integration and VCS are a single product).\n2. The Continuous Integration configuration becomes versioned:\n * Enforcing different branches with different configurations.\n * Allowing contributors to also collaborate in the integration setup.\n3. Docker integration out of the box, including private docker registry per project.\n4. Artifacts browser that allows to access the stages output the same way you’d do locally.\n5. No nightmare maintenance time of the CI server.\n\nOf course, from the user’s point of view, it also comes with some drawbacks compared to other Continuous Integration systems, since it embraces a “convention over configuration” model, which means you get a pretty powerful tool without having to spend your time configuring it while you stick to its way of doing things. The lack of plug-ins and integrations we are used to seeing in other tools to fine-grain configure some aspects of the project is one of them (e.g. creating jobs that require multiple repositories becomes non-trivial). On the other hand, most use-cases are covered enough and features like configurable email alerts, history browser or programmable builds, you have them all.\n\nBut let’s be clear, they neither have invented the wheel nor are the only ones using it. Many other Continuous Integration software solutions also lay in similar paradigms (.travis.yml, Jenkinsfiles…). This is all a matter of taste. The strongest feeling you get after using different solutions is that GitLab’s is easier to configure plus it allows having most details under control in the same browser tab. They took some of the best features of every tool and bundled them into this solution. It makes complete sense.\n\n### Main features\n\nLet’s try to briefly illustrate the main features of this tool and demonstrate how easy it is just to get started with it even without any sysadmin experience or without bothering your DevOps. As said, everything spins around the .gitlab_ci.yml file containing the definition of the different stages (steps) that have to be completed in whole, in order to get the project successfully delivered. The [file structure](/direction/) is natural to be read and once you have seen a couple of examples, you’ll start writing your own without much effort.\n\nHead first for GitLab’s [CI docs](https://docs.gitlab.com/ee/ci/yaml/) for lots of info about how to translate the specific needs of your project into their conventions. But to summarize a review of the Continuous Integration capabilities every project has enabled by default:\n\n#### CI/CD settings\n\nThe settings page gives an overview on just how easy it is to configure everything related to what’s needed for the creation of the continuous integration magic, i.e.:\n\n#### Runners\n\nWhat if I tell you can finally forget about configuring and managing slave machines, the way they speak with the CI server through SSH, how to balance the workload between all the build machines, and many other stuff that is both tedious and often difficult? Meet the runners! [Setup](https://docs.gitlab.com/runner/install/) becomes just as easy as it is to follow the three steps described in the CI/CD settings (settings/ci_cd) on your project: install the right binary for your OS, set the URL endpoint and the registration token provided in the settings page and you are done. Also, you can tag the runners based on their capabilities (e.g. docker, databases, etc.) to select them for specific jobs when they are required.\n\nRunners can implement many executors, i.e. ways of running your build scripts/code in them; from the most basic ssh executor, through a container host and right to the biggest kubernetes cluster you can think of, supporting even Powershell/Batch in Windows systems.\n\nIn their self-managed solution, [gitlab.com](https://gitlab.com/), they also provide \"shared runners\": VMs free of charge, dynamically allocated to build your project, extremely useful for those open source projects with limited resources.\n\n#### Secrets management\n\nIn the microservices era, where your project might be integrated and talk with dozens of APIs that require tokens, secrets, passwords, and many other ways to authorize that dialog, a way to handle this complexity in an elegant manner becomes a priority. A really bad smell [seen in many projects](https://gitleaks.com/) is to store all these in config files on a remote machine or even hang around in some piece of code. To stress the importance of this, just consider how many [services](https://www.vaultproject.io/) and [projects](https://docs.docker.com/engine/swarm/secrets/) are popping up to handle this issue. GitLab projects provide a simple keystore in their Continuous Integration settings that can be accessed from the integration scripts, to help project members handle and configure all these secrets.\n\n#### Pipelines\n\nThis is the core feature of any Continuous Integration system and yet a really simple concept, that translates to all the steps you’ll follow from the moment you are facing your source code to the point in which you are about to deploy your application. In between, you can include everything you would consider to make sure your code looks right (linting), can be built, works right (testing), integrates with other systems and anything you can come up with to take the last steps and ship your code.\n\n\n![this is the core feature of any Continuous Integration system](https://about.gitlab.com/images/blogimages/fast-and-natural-continuous-integration-with-gitlab-ci/pipelines-are-a-core-feature.png){: .shadow}\u003Cbr>\n\n#### Container registry\n\nImagine having your own private Docker hub, where you can store your project’s images and update them whenever it’s needed without having to expose them to the public, and being able to pull them login from anywhere into the registry. You can have an image ready for every stage of the road and pulling them from your runners is blazing fast. This becomes super handy to avoid initializing the environment and therefore speeding up the total time the pipeline takes to run: faster builds = happier devs.\n\n#### Environments and Review Apps\n\nEveryone loves [gitflow](http://nvie.com/posts/a-successful-git-branching-model/), right? There are some good reasons for that. It’s built on the premise that if every branch is developed isolated, new features don’t interfere with each other or the stable version until they are merged back in the master branch. This helps with both developing new functionalities and testing them.\n\nWhen containers came into our lives it was obvious how the process of deploying different, independent environments with individual settings per feature could be eased and improved. It’s fair to say we now use containers as standard de facto for environment templates. Most mainstream Continuous Integration solutions were released way before the first container was even created, so they were not built with Docker in mind, but for GitLab CI it’s the other way around: they embrace containers as the way to go, based on the many benefits it brings to the workflow.\n\n![GitLab embraces containers as the way to go, based on the many benefits it brings to the workflow.](https://about.gitlab.com/images/blogimages/fast-and-natural-continuous-integration-with-gitlab-ci/environments-and-review-apps.png){: .shadow}\u003Cbr>\n\nImagine a very common scenario in the workflow: you are about to merge a feature branch that has to be tested out by the QA team, which introduces some new libraries and a new service (e.g. Redis, mongoDB…) to be deployed. Just update your Dockerfile to include the new layer(s) that manage those new dependencies and push the image to your local registry. Also, append the line to include the new service via docker hub to .gitlab_ci.yml. The feature branch, when pushed on the remote, will have everything in place to be deployed to the testing environment.\n\n![The feature branch, when pushed on the remote, will have everything in place to be deployed to the testing environment](https://about.gitlab.com/images/blogimages/fast-and-natural-continuous-integration-with-gitlab-ci/production-and-staging.png){: .shadow}\u003Cbr>\n\nThis is where [Review Apps](https://docs.gitlab.com/ee/ci/review_apps/) come into action, it’s just a posh way to call dynamic, per-branch environments created to verify changes and see them live. Every branch gets instant deploy support when pushed to the repo. This process can speed up with tools such as [dpl](https://github.com/travis-ci/dpl), that abstract many of the details for major deploy services, or go freestyle and call your custom deployment script from there. It also integrates an interactive terminal in-browser to introspect on builds to debug and troubleshoot if needed. You no longer have to go over the Jenkins’ mantra to clone a configured job, rename it, adjust the branch in the configuration… and 10 or 15 tedious steps before deploying an ephemeral test environment.\n\nAnother major feature you are going to love is the [history browser](https://docs.gitlab.com/ee/ci/environments/index.html#viewing-the-deployment-history-of-an-environment). Imagine you deployed some changes to a demo environment and 10 minutes before going live, you detect it contains a major bug that would be nasty if displayed on camera. No worries; it’s super easy to access the history of what was deployed on every environment and perform rollbacks or redeploy on-demand to any previous reproducible state. Just awesome.\n\n![it’s super easy to access the history of what was deployed on every environment](https://about.gitlab.com/images/blogimages/fast-and-natural-continuous-integration-with-gitlab-ci/history-browser.png){: .shadow}\u003Cbr>\n\nI hope after this post, the central concepts of GitLab’s Continuous Integration make good sense to you and your projects.\n\n_This post was originally published on [solidgeargroup.com](https://solidgeargroup.com/gitlab_countinuous_integration_intro)._\n\n\u003Cp class=\"alert alert-orange\" style=\"background-color: rgba(252,163,38,.3); border-color: rgba(252,163,38,.3); color: rgb(226,67,41) !important; text-align: center;\">Sign up for a   \u003Ci class=\"fab fa-gitlab\" style=\"color:rgb(107,79,187); font-size:.85em\" aria-hidden=\"true\">\u003C/i>   \u003Cstrong>GitLab EE Trial\u003C/strong>   \u003Ci class=\"fab fa-gitlab\" style=\"color:rgb(107,79,187); font-size:.85em\" aria-hidden=\"true\">\u003C/i>   \u003Ca style=\"color: 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statement",{"items":675},[676,679,682],{"text":677,"config":678},"Terms",{"href":503,"dataGaName":504,"dataGaLocation":451},{"text":680,"config":681},"Cookies",{"dataGaName":513,"dataGaLocation":451,"id":514,"isOneTrustButton":24},{"text":683,"config":684},"Privacy",{"href":508,"dataGaName":509,"dataGaLocation":451},[686],{"id":687,"title":18,"body":8,"config":688,"content":690,"description":8,"extension":22,"meta":694,"navigation":24,"path":695,"seo":696,"stem":697,"__hash__":698},"blogAuthors/en-us/blog/authors/samuel-alfageme.yml",{"template":689},"BlogAuthor",{"name":18,"config":691},{"headshot":692,"ctfId":693},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749659488/Blog/Author%20Headshots/gitlab-logo-extra-whitespace.png","Samuel-Alfageme",{},"/en-us/blog/authors/samuel-alfageme",{},"en-us/blog/authors/samuel-alfageme","WQ3KtyBI2Ym-i3OPD5_erB5PNbJSCSgvzU7PxLZQ2xU",[700,713,725],{"content":701,"config":711},{"title":702,"description":703,"authors":704,"heroImage":706,"date":707,"category":9,"tags":708,"body":710},"How IIT Bombay students are coding the future with GitLab","At GitLab, we often talk about how software accelerates innovation. But sometimes, you have to step away from the Zoom calls and stand in a crowded university hall to remember why we do this.",[705],"Nick Veenhof","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099013/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2814%29_6VTUA8mUhOZNDaRVNPeKwl_1750099012960.png","2026-01-08",[255,607,709],"open source","The GitLab team recently had the privilege of judging the **iHack Hackathon** at **IIT Bombay's E-Summit**. The energy was electric, the coffee was flowing, and the talent was undeniable. But what struck us most wasn't just the code — it was the sheer determination of students to solve real-world problems, often overcoming significant logistical and financial hurdles to simply be in the room.\n\n\nThrough our [GitLab for Education program](https://about.gitlab.com/solutions/education/), we aim to empower the next generation of developers with tools and opportunity. Here is a look at what the students built, and how they used GitLab to bridge the gap between idea and reality.\n\n## The challenge: Build faster, build securely\n\nThe premise for the GitLab track of the hackathon was simple: Don't just show us a product; show us how you built it. We wanted to see how students utilized GitLab's platform — from Issue Boards to CI/CD pipelines — to accelerate the development lifecycle.\n\nThe results were inspiring.\n\n## The winners\n\n### 1st place: Team Decode — Democratizing Scientific Research\n\n**Project:** FIRE (Fast Integrated Research Environment)\n\nTeam Decode took home the top prize with a solution that warms a developer's heart: a local-first, blazing-fast data processing tool built with [Rust](https://about.gitlab.com/blog/secure-rust-development-with-gitlab/) and Tauri. They identified a massive pain point for data science students: existing tools are fragmented, slow, and expensive.\n\nTheir solution, FIRE, allows researchers to visualize complex formats (like NetCDF) instantly. What impressed the judges most was their \"hacker\" ethos. They didn't just build a tool; they built it to be open and accessible.\n\n**How they used GitLab:** Since the team lived far apart, asynchronous communication was key. They utilized **GitLab Issue Boards** and **Milestones** to track progress and integrated their repo with Telegram to get real-time push notifications. As one team member noted, \"Coordinating all these technologies was really difficult, and what helped us was GitLab... the Issue Board really helped us track who was doing what.\"\n\n![Team Decode](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380253/epqazj1jc5c7zkgqun9h.jpg)\n\n### 2nd place: Team BichdeHueDost — Reuniting to Solve Payments\n\n**Project:** SemiPay (RFID Cashless Payment for Schools)\n\nThe team name, BichdeHueDost, translates to \"Friends who have been set apart.\" It's a fitting name for a group of friends who went to different colleges but reunited to build this project. They tackled a unique problem: handling cash in schools for young children. Their solution used RFID cards backed by a blockchain ledger to ensure secure, cashless transactions for students.\n\n**How they used GitLab:** They utilized [GitLab CI/CD](https://about.gitlab.com/topics/ci-cd/) to automate the build process for their Flutter application (APK), ensuring that every commit resulted in a testable artifact. This allowed them to iterate quickly despite the \"flaky\" nature of cross-platform mobile development.\n\n![Team BichdeHueDost](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380253/pkukrjgx2miukb6nrj5g.jpg)\n\n### 3rd place: Team ZenYukti — Agentic Repository Intelligence\n\n**Project:** RepoInsight AI (AI-powered, GitLab-native intelligence platform)\n\nTeam ZenYukti impressed us with a solution that tackles a universal developer pain point: understanding unfamiliar codebases. What stood out to the judges was the tool's practical approach to onboarding and code comprehension: RepoInsight-AI automatically generates documentation, visualizes repository structure, and even helps identify bugs, all while maintaining context about the entire codebase.\n\n**How they used GitLab:** The team built a comprehensive CI/CD pipeline that showcased GitLab's security and DevOps capabilities. They integrated [GitLab's Security Templates](https://gitlab.com/gitlab-org/gitlab/-/tree/master/lib/gitlab/ci/templates/Security) (SAST, Dependency Scanning, and Secret Detection), and utilized [GitLab Container Registry](https://docs.gitlab.com/user/packages/container_registry/) to manage their Docker images for backend and frontend components. They created an AI auto-review bot that runs on merge requests, demonstrating an \"agentic workflow\" where AI assists in the development process itself.\n\n![Team ZenYukti](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380253/ymlzqoruv5al1secatba.jpg)\n\n## Beyond the code: A lesson in inclusion\n\nWhile the code was impressive, the most powerful moment of the event happened away from the keyboard.\n\nDuring the feedback session, we learned about the journey Team ZenYukti took to get to Mumbai. They traveled over 24 hours, covering nearly 1,800 kilometers. Because flights were too expensive and trains were booked, they traveled in the \"General Coach,\" a non-reserved, severely overcrowded carriage.\n\nAs one student described it:\n\n*\"You cannot even imagine something like this... there are no seats... people sit on the top of the train. This is what we have endured.\"*\n\nThis hit home. [Diversity, Inclusion, and Belonging](https://handbook.gitlab.com/handbook/company/culture/inclusion/) are core values at GitLab. We realized that for these students, the barrier to entry wasn't intellect or skill, it was access.\n\nIn that moment, we decided to break that barrier. We committed to reimbursing the travel expenses for the participants who struggled to get there. It's a small step, but it underlines a massive truth: **talent is distributed equally, but opportunity is not.**\n\n![hackathon class together](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380252/o5aqmboquz8ehusxvgom.jpg)\n\n### The future is bright (and automated)\n\nWe also saw incredible potential in teams like Prometheus, who attempted to build an autonomous patch remediation tool (DevGuardian), and Team Arrakis, who built a voice-first job portal for blue-collar workers using [GitLab Duo](https://about.gitlab.com/gitlab-duo/) to troubleshoot their pipelines.\n\nTo all the students who participated: You are the future. Through [GitLab for Education](https://about.gitlab.com/solutions/education/), we are committed to providing you with the top-tier tools (like GitLab Ultimate) you need to learn, collaborate, and change the world — whether you are coding from a dorm room, a lab, or a train carriage. **Keep shipping.**\n\n> :bulb: Learn more about the [GitLab for Education program](https://about.gitlab.com/solutions/education/).\n",{"slug":712,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":714,"config":723},{"title":715,"description":716,"authors":717,"heroImage":718,"date":719,"category":9,"tags":720,"body":722},"Artois University elevates research and curriculum with GitLab Ultimate for Education","Artois University's CRIL leveraged the GitLab for Education program to gain free access to Ultimate, transforming advanced research and computer science curricula.",[705],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099203/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2820%29_2bJGC5ZP3WheoqzlLT05C5_1750099203484.png","2025-12-10",[607,255,721],"product","Leading academic institutions face a critical challenge: how to provide thousands of students and researchers with industry-standard, **full-featured DevSecOps tools** without compromising institutional control. Many start with basic version control, but the modern curriculum demands integrated capabilities for planning, security, and advanced CI/CD.\n\nThe **GitLab for Education program** is designed to solve this by providing access to **GitLab Ultimate** for qualifying institutions, allowing them to scale their operations and elevate their academic offerings. \n\nThis article showcases a powerful success story from the **Centre de Recherche en Informatique de Lens (CRIL)**, a joint laboratory of **Artois University** and CNRS in France. After years of relying solely on GitLab Community Edition (CE), the university's move to GitLab Ultimate through the GitLab for Education program immediately unlocked advanced capabilities, transforming their teaching, research, and contribution workflows virtually overnight. This story demonstrates why GitLab Ultimate is essential for institutions seeking to deliver advanced computer science and research curricula.\n\n## GitLab Ultimate unlocked: Managing scale and driving academic value\n\n**Artois University's** self-managed GitLab instance is a large-scale operation, supporting nearly **3,000 users** across approximately **19,000 projects**, primarily serving computer science students and researchers. While GitLab Community Edition was robust, the upgrade to GitLab Ultimate provided the sophisticated tooling necessary for managing this scale and facilitating advanced university-level work.\n\n***\"We can see the difference,\" says Daniel Le Berre, head of research at CRIL and the instance maintainer. \"It's a completely different product. Each week reveals new features that directly enhance our productivity and teaching.\"***\n\nThe institution joined the GitLab for Education program specifically because it covers both **instructional and non-commercial research use cases** and offers full access to Ultimate's features, removing significant cost barriers.\n\n### Key GitLab Ultimate benefits for students and researchers\n\n* **Advanced project management at scale:** Master's students now benefit from **GitLab Ultimate's project planning features**. This enables them to structure, track, and manage complex, long-term research projects using professional methodologies like portfolio management and advanced issue tracking that seamlessly roll up across their thousands of projects.\n\n* **Enhanced visibility:** Features like improved dashboards and code previews directly in Markdown files dramatically streamline tracking and documentation review, reducing administrative friction for both instructors and students managing large project loads.\n\n## Comprehensive curriculum: From concepts to continuous delivery\n\nGitLab Ultimate is deeply integrated into the computer science curriculum, moving students beyond simple `git` commands to practical **DevSecOps implementation**.\n\n* **Git fundamentals:** Students begin by visualizing concepts using open-source tools to master Git concepts.\n\n* **Full CI/CD implementation:** Students use GitLab CI for rigorous **Test-Driven Development (TDD)** in their software projects. They learn to build, test, and perform quality assurance using unit and integration testing pipelines—core competency made seamless by the integrated platform.\n\n* **DevSecOps for research and documentation:** The university teaches students that DevSecOps principles are vital for all collaborative work. Inspired by earlier work in Delft, students manage and produce critical research documentation (PDFs from Markdown files) using GitLab, incorporating quality checks like linters and spell checks directly in the CI pipeline. This ensures high-quality, reproducible research output.\n\n* **Future-proofing security skills:** The GitLab Ultimate platform immediately positions the institution to incorporate advanced DevSecOps features like SAST and DAST scanning as their research and development code projects grow, ensuring students are prepared for industry security standards.\n\n## Accelerating open source contributions with GitLab Duo\n\nAccess to the full GitLab platform, including our AI capabilities, has empowered students to make impactful contributions to the wider open source community faster than ever before.\n\nTwo Master's students recently completed direct contributions to the GitLab product, adding the **ORCID identifier** into user profiles. Working on GitLab.com, they leveraged **GitLab Duo's AI chat and code suggestions** to navigate the codebase efficiently.\n\n***\"This would not have been possible without GitLab Duo,\" Daniel Le Berre notes. \"The AI features helped students, who might have lacked deep codebase knowledge, deliver meaningful contributions in just two weeks.\"***\n\nThis demonstrates how providing students with cutting-edge tools **accelerates their learning and impact**, allowing them to translate classroom knowledge into real-world contributions immediately.\n\n## Empowering open research and institutional control\n\nThe stability of the self-managed instance at Artois University is key to its success. This model guarantees **institutional control and stability** — a critical factor for long-term research preservation.\n\nThe institution's expertise in this area was recently highlighted in a major 2024 study led by CRIL, titled: \"[Higher Education and Research Forges in France - Definition, uses, limitations encountered and needs analysis](https://hal.science/hal-04208924v4)\" ([Project on GitLab](https://gitlab.in2p3.fr/coso-college-codes-sources-et-logiciels/forges-esr-en)). The research found that the vast majority of public forges in French Higher Education and Research relied on **GitLab**. This finding underscores the consensus among academic leaders that self-hosted solutions are essential for **data control and longevity**, especially when compared to relying on external, commercial forges.\n\n## Unlock GitLab Ultimate for your institution today\n\nThe success story of **Artois University's CRIL** proves the transformative power of the GitLab for Education program. By providing **free access to GitLab Ultimate**, we enable large-scale institutions to:\n\n1. **Deliver a modern, integrated DevSecOps curriculum.**\n\n2. **Support advanced, collaborative research projects with Ultimate planning features.**\n\n3. **Empower students to make AI-assisted open source contributions.**\n\n4. **Maintain institutional control and data longevity.**\n\nIf your academic institution is ready to equip its students and researchers with the complete DevSecOps platform and its most advanced features, we invite you to join the program.\n\nThe program provides **free access to GitLab Ultimate** for qualifying instructional and non-commercial research use cases.\n\n**Apply now [online](https://about.gitlab.com/solutions/education/join/).**\n",{"slug":724,"featured":24,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":726,"config":739},{"category":9,"tags":727,"body":730,"date":731,"updatedDate":732,"heroImage":733,"authors":734,"title":737,"description":738},[728,729,102],"tutorial","git","\nEnterprise teams are increasingly migrating from Azure DevOps to GitLab to gain strategic advantages and accelerate secure software delivery. \n\n\n- GitLab comes with integrated controls, policies, and [compliance frameworks](https://docs.gitlab.com/user/compliance/compliance_frameworks/) that allow organizations to implement software delivery standards at scale. This is especially important for regulated industries.\n\n- [Security testing](https://docs.gitlab.com/user/application_security/) is embedded in the pipeline and results show in the developer workflow, including static application security testing (SAST), source code analysis (SCA), dynamic application security testing (DAST), infrastructure-as-code scanning (IaC), container scanning, and API scanning.\n\n- [AI capabilities](https://about.gitlab.com/gitlab-duo-agent-platform/) across the full software delivery lifecycle include advanced agent orchestration and customizable flows to support how your organizational teams work.\n\n\nGitLab's open-source, open-core approach, flexible deployment options such as single-tenant dedicated and self-managed, and truly unified platform eliminate integration complexity and security gaps. \n\n\nFor teams facing mounting pressure to accelerate delivery while strengthening security posture and maintaining regulatory compliance, GitLab represents not just a migration but a platform evolution.\n\n\nMigrating from Azure DevOps to GitLab can seem like a daunting task, but with the right approach and tools, it can be a smooth and efficient process. This guide will walk you through the steps needed to successfully migrate your projects, repositories, and pipelines from Azure DevOps to GitLab.\n\n\n## Overview\n\nGitLab provides both [Congregate](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/) (maintained by [GitLab Professional Services](https://about.gitlab.com/professional-services/) organization) and [a built-in Git repository import](https://docs.gitlab.com/user/project/import/repo_by_url/) for migrating projects from Azure DevOps (ADO). These options support repository-by-repository or bulk migration and preserve git commit history, branches, and tags. With Congregate and professional services tools, we support additional assets such as wikis, work items, CI/CD variables, container images, packages, pipelines, and more (see this [feature matrix](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/-/blob/master/customer/ado-migration-features-matrix.md)). Use this guide to plan and execute your migration and complete post-migration follow-up tasks.\n\n\nEnterprises migrating from ADO to GitLab commonly follow a multi-phase approach:\n\n\n- Migrate repositories from ADO to GitLab using Congregate or GitLab's built-in repository migration.\n\n- Migrate pipelines from Azure Pipelines to GitLab CI/CD.\n\n- Migrate remaining assets such as boards, work items, and artifacts to GitLab Issues, Epics, and the Package and Container Registries.\n\n\nHigh-level migration phases:\n\n\n```mermaid\ngraph LR\n subgraph Prerequisites\n direction TB\n A[\"Set up identity provider (IdP) and\u003Cbr/>provision users\"]\n A --> B[\"Set up runners and\u003Cbr/>third-party integrations\"]\n B --> I[\"Users enablement and\u003Cbr/>change management\"]\n end\n \n subgraph MigrationPhase[\"Migration phase\"]\n direction TB\n C[\"Migrate source code\"]\n C --> D[\"Preserve contributions and\u003Cbr/> format history\"]\n D --> E[\"Migrate work items and\u003Cbr/>map to \u003Ca href=\"https://docs.gitlab.com/topics/plan_and_track/\">GitLab Plan \u003Cbr/>and track work\"]\n end\n \n subgraph PostMigration[\"Post-migration steps\"]\n direction TB\n F[\"Create or translate \u003Cbr/>ADO pipelines to GitLab CI\"]\n F --> G[\"Migrate other assets\u003Cbr/>packages and container images\"]\n G --> H[\"Introduce \u003Ca href=\"https://docs.gitlab.com/user/application_security/secure_your_application/\">security\u003C/a> and\u003Cbr/>SDLC improvements\"]\n end\n \n Prerequisites --> MigrationPhase\n MigrationPhase --> PostMigration\n\n style A fill:#FC6D26\n style B fill:#FC6D26\n style I fill:#FC6D26\n style C fill:#8C929D\n style D fill:#8C929D\n style E fill:#8C929D\n style F fill:#FFA500\n style G fill:#FFA500\n style H fill:#FFA500\n```\n\n\n## Planning your migration\n\n\n**To plan your migration, ask these questions:**\n\n\n- How soon do we need to complete the migration?\n\n- Do we understand what will be migrated?\n\n- Who will run the migration?\n\n- What organizational structure do we want in GitLab?\n\n- Are there any constraints, limitations, or pitfalls that need to be taken into account?\n\n\nDetermine your timeline, as it will largely dictate your migration approach. Identify champions or groups familiar with both ADO and GitLab platforms (such as early adopters) to help drive adoption and provide guidance.\n\n\n**Inventory what you need to migrate:**\n\n\n- The number of repositories, pull requests, and contributors\n\n- The number and complexity of work items and pipelines\n\n- Repository sizes and dependency relationships\n\n- Critical integrations and runner requirements (agent pools with specific capabilities)\n\n\nUse GitLab Professional Services's [Evaluate](https://gitlab.com/gitlab-org/professional-services-automation/tools/utilities/evaluate#beta-azure-devops) tool to produce a complete inventory of your entire Azure DevOps organization, including repositories, PR counts, contributor lists, number of pipelines, work items, CI/CD variables and more. If you're working with the GitLab Professional Services team, share this report with your engagement manager or technical architect to help plan the migration.\n\n\nMigration timing is primarily driven by pull request count, repository size, and amount of contributions (e.g. comments in PR, work items, etc). For example, 1,000 small repositories with few PRs and limited contributors can migrate much faster than a smaller set of repositories containing tens of thousands of PRs and thousands of contributors. Use your inventory data to estimate effort and plan test runs before proceeding with production migrations.\n\n\nCompare inventory against your desired timeline and decide whether to migrate all repositories at once or in batches. If teams cannot migrate simultaneously, batch and stagger migrations to align with team schedules. For example, in Professional Services engagements, we organize migrations into waves of 200-300 projects to manage complexity and respect API rate limits, both in [GitLab](https://docs.gitlab.com/security/rate_limits/) and [ADO](https://learn.microsoft.com/en-us/azure/devops/integrate/concepts/rate-limits?view=azure-devops).\n\n\nGitLab's built-in [repository importer](https://docs.gitlab.com/user/project/import/repo_by_url/) migrates Git repositories (commits, branches, and tags) one-by-one. Congregate is designed to preserve pull requests (known in GitLab as merge requests), comments, and related metadata where possible; the simple built-in repository import focuses only on the Git data (history, branches, and tags).\n\n\n**Items that typically require separate migration or manual recreation:**\n\n\n- Azure Pipelines - create equivalent GitLab CI/CD pipelines (consult with [CI/CD YAML](https://docs.gitlab.com/ci/yaml/) and/or with [CI/CD components](https://docs.gitlab.com/ci/components/)). Alternatively, consider using AI-based pipeline conversion available in Congregate.\n\n- Work items and boards - map to GitLab Issues, Epics, and Issue Boards.\n\n- Artifacts, container images (ACR) - migrate to GitLab Package Registry or Container Registry.\n\n- Service hooks and external integrations - recreate in GitLab.\n\n- [Permissions models](https://docs.gitlab.com/user/permissions/) differ between ADO and GitLab; review and plan permissions mapping rather than assuming exact preservation.\n\n\nReview what each tool (Congregate vs. built-in import) will migrate and choose the one that fits your needs. Make a list of any data or integrations that must be migrated or recreated manually.\n\n\n**Who will run the migration?**\n\n\nMigrations are typically run by a GitLab group owner or instance administrator, or by a designated migrator who has been granted the necessary permissions on the destination group/project. Congregate and the GitLab import APIs require valid authentication tokens for both Azure DevOps and GitLab.\n\n\n- Decide whether a group owner/admin will perform the migrations or whether you will grant a specific team/person delegated access.\n\n- Ensure the migrator has correctly configured personal access tokens (Azure DevOps and GitLab) with the scopes required by your chosen migration tool (for example, api/read_repository scopes and any tool-specific requirements). \n\n- Test tokens and permissions with a small pilot migration.\n\n**Note:** Congregate leverages file-based import functionality for ADO migrations and requires instance administrator permissions to run ([see our documentation](https://docs.gitlab.com/user/project/settings/import_export/#migrate-projects-by-uploading-an-export-file)). If you are migrating to GitLab.com, consider engaging Professional Services. For more information, see the [Professional Services Full Catalog](https://about.gitlab.com/professional-services/catalog/). Non-admin account cannot preserve contribution attribution!\n\n\n**What organizational structure do we want in GitLab?**\n\nWhile it's possible to map ADO structure directly to GitLab structure, it's recommended to rationalize and simplify the structure during migration. Consider how teams will work in GitLab and design the structure to facilitate collaboration and access management. Here is a way to think about mapping ADO structure to GitLab structure:\n\n\n```mermaid\ngraph TD\n subgraph GitLab\n direction TB\n A[\"Top-level Group\"]\n B[\"Subgroup (optional)\"]\n C[\"Projects\"]\n A --> B\n A --> C\n B --> C\n end\n\n subgraph AzureDevOps[\"Azure DevOps\"]\n direction TB\n F[\"Organizations\"]\n G[\"Projects\"]\n H[\"Repositories\"]\n F --> G\n G --> H\n end\n\n style A fill:#FC6D26\n style B fill:#FC6D26\n style C fill:#FC6D26\n style F fill:#8C929D\n style G fill:#8C929D\n style H fill:#8C929D\n```\n\nRecommended approach:\n\n\n- Map each ADO organization to a GitLab group (or a small set of groups), not to many small groups. Avoid creating a GitLab group for every ADO team project. Use migration as an opportunity to rationalize your GitLab structure.\n\n- Use subgroups and project-level permissions to group related repositories.\n\n- Manage access to sets of projects by using GitLab groups and group membership (groups and subgroups) rather than one group per team project.\n\n- Review GitLab [permissions](https://docs.gitlab.com/ee/user/permissions.html) and consider [SAML Group Links](https://docs.gitlab.com/user/group/saml_sso/group_sync/) to implement an enterprise RBAC model for your GitLab instance (or a GitLab.com namespace).\n\n\n**ADO Boards and work items: State of migration**\n\n\nIt's important to understand how work items migrate from ADO into GitLab Plan (issues, epics, and boards).\n\n\n- ADO Boards and work items map to GitLab Issues, Epics, and Issue Boards. Plan how your workflows and board configurations will translate.\n\n- ADO Epics and Features become GitLab Epics.\n\n- Other work item types (e.g., user stories, tasks, bugs) become project-scoped issues.\n\n- Most standard fields are preserved; selected custom fields can be migrated when supported.\n\n- Parent-child relationships are retained so Epics reference all related issues.\n\n- Links to pull requests are converted to merge request links to maintain development traceability.\n\n\nExample: Migration of an individual work item to a GitLab Issue, including field accuracy and relationships:\n\n\n![Example: Migration of an individual work item to a GitLab Issue](https://res.cloudinary.com/about-gitlab-com/image/upload/v1764769188/ztesjnxxfbwmfmtckyga.png)\n\n\nBatching guidance:\n\n\n- If you need to run migrations in batches, use your new group/subgroup structure to define batches (for example, by ADO organization or by product area).\n\n- Use inventory reports to drive batch selection and test each batch with a pilot migration before scaling.\n\n\n**Pipelines migration**\n\n\nCongregate [recently introduced](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/-/merge_requests/1298) AI-powered conversion for multi-stage YAML pipelines from Azure DevOps to GitLab CI/CD. This automated conversion works best for simple, single-file pipelines and is designed to provide a working starting point rather than a production-ready `.gitlab-ci.yml` file. The tool generates a functionally equivalent GitLab pipeline that you can then refine and optimize for your specific needs.\n\n\n- Converts Azure Pipelines YAML to `.gitlab-ci.yml` format automatically.\n\n- Best suited for straightforward, single-file pipeline configurations.\n\n- Provides a boilerplate to accelerate migration, not a final production artifact.\n\n- Requires review and adjustment for complex scenarios, custom tasks, or enterprise requirements.\n\n- Does not support Azure DevOps classic release pipelines — [convert these to multi-stage YAML](https://learn.microsoft.com/en-us/azure/devops/pipelines/release/from-classic-pipelines?view=azure-devops) first.\n\n\nRepository owners should review the [GitLab CI/CD documentation](https://docs.gitlab.com/ci/) to further optimize and enhance their pipelines after the initial conversion.\n\n\nExample of converted pipelines:\n\n\n```yml \n\n# azure-pipelines.yml\n\ntrigger:\n - main\n\nvariables:\n imageName: myapp\n\nstages:\n - stage: Build\n jobs:\n - job: Build\n pool:\n vmImage: 'ubuntu-latest'\n steps:\n - checkout: self\n\n - task: Docker@2\n displayName: Build Docker image\n inputs:\n command: build\n repository: $(imageName)\n Dockerfile: '**/Dockerfile'\n tags: |\n $(Build.BuildId)\n\n - stage: Test\n jobs:\n - job: Test\n pool:\n vmImage: 'ubuntu-latest'\n steps:\n - checkout: self\n\n # Example: run tests inside the container\n - script: |\n docker run --rm $(imageName):$(Build.BuildId) npm test\n displayName: Run tests\n\n - stage: Push\n jobs:\n - job: Push\n pool:\n vmImage: 'ubuntu-latest'\n steps:\n - checkout: self\n\n - task: Docker@2\n displayName: Login to ACR\n inputs:\n command: login\n containerRegistry: '\u003Cyour-acr-service-connection>'\n\n - task: Docker@2\n displayName: Push image to ACR\n inputs:\n command: push\n repository: $(imageName)\n tags: |\n $(Build.BuildId)\n\n```\n\n```yaml\n\n# .gitlab-ci.yml\n\nvariables:\n imageName: myapp\n\nstages:\n - build\n - test\n - push\n\nbuild:\n stage: build\n image: docker:latest\n services:\n - docker:dind\n script:\n - docker build -t $imageName:$CI_PIPELINE_ID -f $(find . -name Dockerfile) .\n only:\n - main\n\ntest:\n stage: test\n image: docker:latest\n services:\n - docker:dind\n script:\n - docker run --rm $imageName:$CI_PIPELINE_ID npm test\n only:\n - main\n\npush:\n stage: push\n image: docker:latest\n services:\n - docker:dind\n before_script:\n - docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY\n script:\n - docker tag $imageName:$CI_PIPELINE_ID $CI_REGISTRY/$CI_PROJECT_PATH/$imageName:$CI_PIPELINE_ID\n - docker push $CI_REGISTRY/$CI_PROJECT_PATH/$imageName:$CI_PIPELINE_ID\n only:\n - main\n\n```\n\n**Final checklist:**\n\n\n- Decide timeline and batch strategy.\n\n- Produce a full inventory of repositories, PRs, and contributors.\n\n- Choose Congregate or the built-in import based on scope (PRs and metadata vs. Git data only).\n\n- Decide who will run migrations and ensure tokens/permissions are configured.\n\n- Identify assets that must be migrated separately (pipelines, work items, artifacts, and hooks) and plan those efforts.\n\n- Run pilot migrations, validate results, then scale according to your plan.\n\n\n## Running your migrations\n\n\nAfter planning, execute migrations in stages, starting with trial runs. Trial migrations help surface org-specific issues early and let you measure duration, validate outcomes, and fine-tune your approach before production.\n\n\nWhat trial migrations validate:\n\n\n- Whether a given repository and related assets migrate successfully (history, branches, tags; plus MRs/comments if using Congregate)\n\n- Whether the destination is usable immediately (permissions, runners, CI/CD variables, integrations)\n\n- How long each batch takes, to set schedules and stakeholder expectations\n\n\nDowntime guidance:\n\n\n- GitLab's built-in Git import and Congregate do not inherently require downtime.\n\n- For production waves, freeze changes in ADO (branch protections or read-only) to avoid missed commits, PR updates, or work items created mid-migration.\n\n- Trial runs do not require freezes and can be run anytime.\n\n\nBatching guidance:\n\n\n- Run trial batches back-to-back to shorten elapsed time; let teams validate results asynchronously.\n\n- Use your planned group/subgroup structure to define batches and respect API rate limits.\n\n\nRecommended steps:\n\n\n1. Create a test destination in GitLab for trials:\n\n\n - GitLab.com: create a dedicated group/namespace (for example, my-org-sandbox)\n\n - Self-managed: create a top-level group or a separate test instance if needed\n\n\n2. Prepare authentication:\n\n\n - Azure DevOps PAT with required scopes.\n\n - GitLab Personal Access Token with api and read_repository (plus admin access for file-based imports used by Congregate).\n\n\n3. Run trial migrations:\n\n\n - Repos only: use GitLab's built-in import (Repo by URL)\n\n - Repos + PRs/MRs and additional assets: use Congregate\n\n\n4. Post-trial follow-up:\n\n\n - Verify repo history, branches, tags; merge requests (if migrated), issues/epics (if migrated), labels, and relationships.\n\n - Check permissions/roles, protected branches, required approvals, runners/tags, variables/secrets, integrations/webhooks.\n\n - Validate pipelines (`.gitlab-ci.yml`) or converted pipelines where applicable.\n\n\n5. Ask users to validate functionality and data fidelity.\n\n6. Resolve issues uncovered during trials and update your runbooks.\n\n7. Network and security:\n\n\n - If your destination uses IP allow lists, add the IPs of your migration host and any required runners/integrations so imports can succeed.\n\n\n8. Run production migrations in waves:\n\n\n - Enforce change freezes in ADO during each wave.\n\n - Monitor progress and logs; retry or adjust batch sizes if you hit rate limits.\n\n\n9. Optional: remove the sandbox group or archive it after you finish.\n\n\n\u003Cfigure class=\"video_container\">\n \u003Ciframe src=\"https://www.youtube.com/embed/ibIXGfrVbi4?si=ZxOVnXjCF-h4Ne0N\" frameborder=\"0\" allowfullscreen=\"true\">\u003C/iframe>\n\u003C/figure>\n\n\n## Terminology reference for GitLab and Azure DevOps\n\n| GitLab | Azure DevOps | Similarities & Key Differences |\n| ---------------------------------------------------------------- | -------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Group | Organization | Top-level namespace, membership, policies. ADO org contains Projects; GitLab Group contains Subgroups and Projects. |\n| Group or Subgroup | Project | Logical container, permissions boundary. ADO Project holds many repos; GitLab Groups/Subgroups organize many Projects. |\n| Project (includes a Git repo) | Repository (inside a Project) | Git history, branches, tags. In GitLab, a \"Project\" is the repo plus issues, CI/CD, wiki, etc. One repo per Project. |\n| Merge Request (MR) | Pull Request (PR) | Code review, discussions, approvals. MR rules include approvals, required pipelines, code owners. |\n| Protected Branches, MR Approval Rules, Status Checks | Branch Policies | Enforce reviews and checks. GitLab combines protections + approval rules + required status checks. |\n| GitLab CI/CD | Azure Pipelines | YAML pipelines, stages/jobs, logs. ADO also has classic UI pipelines; GitLab centers on .gitlab-ci.yml. |\n| .gitlab-ci.yml | azure-pipelines.yml | Defines stages/jobs/triggers. Syntax/features differ; map jobs, variables, artifacts, and triggers. |\n| Runners (shared/specific) | Agents / Agent Pools | Execute jobs on machines/containers. Target via demands (ADO) vs tags (GitLab). Registration/scoping differs. |\n| CI/CD Variables (project/group/instance), Protected/Masked | Pipeline Variables, Variable Groups, Library | Pass config/secrets to jobs. GitLab supports group inheritance and masking/protection flags. |\n| Integrations, CI/CD Variables, Deploy Keys | Service Connections | External auth to services/clouds. Map to integrations or variables; cloud-specific helpers available. |\n| Environments & Deployments (protected envs) | Environments (with approvals) | Track deploy targets/history. Approvals via protected envs and manual jobs in GitLab. |\n| Releases (tag + notes) | Releases (classic or pipelines) | Versioned notes/artifacts. GitLab Release ties to tags; deployments tracked separately. |\n| Job Artifacts | Pipeline Artifacts | Persist job outputs. Retention/expiry configured per job or project. |\n| Package Registry (NuGet/npm/Maven/PyPI/Composer, etc.) | Azure Artifacts (NuGet/npm/Maven, etc.) | Package hosting. Auth/namespace differ; migrate per package type. |\n| GitLab Container Registry | Azure Container Registry (ACR) or others | OCI images. GitLab provides per-project/group registries. |\n| Issue Boards | Boards | Visualize work by columns. GitLab boards are label-driven; multiple boards per project/group. |\n| Issues (types/labels), Epics | Work Items (User Story/Bug/Task) | Track units of work. Map ADO types/fields to labels/custom fields; epics at group level. |\n| Epics, Parent/Child Issues | Epics/Features | Hierarchy of work. Schema differs; use epics + issue relationships. |\n| Milestones and Iterations | Iteration Paths | Time-boxing. GitLab Iterations (group feature) or Milestones per project/group. |\n| Labels (scoped labels) | Area Paths | Categorization/ownership. Replace hierarchical areas with scoped labels. |\n| Project/Group Wiki | Project Wiki | Markdown wiki. Backed by repos in both; layout/auth differ slightly. |\n| Test reports via CI, Requirements/Test Management, integrations | Test Plans/Cases/Runs | QA evidence/traceability. No 1:1 with ADO Test Plans; often use CI reports + issues/requirements. |\n| Roles (Owner/Maintainer/Developer/Reporter/Guest) + custom roles | Access levels + granular permissions | Control read/write/admin. Models differ; leverage group inheritance and protected resources. |\n| Webhooks | Service Hooks | Event-driven integrations. Event names/payloads differ; reconfigure endpoints. |\n| Advanced Search | Code Search | Full-text repo search. 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