[{"data":1,"prerenderedAt":793},["ShallowReactive",2],{"/en-us/blog/automating-boring-git-operations-gitlab-ci":3,"navigation-en-us":39,"banner-en-us":438,"footer-en-us":448,"blog-post-authors-en-us-Kristian Larsson":689,"blog-related-posts-en-us-automating-boring-git-operations-gitlab-ci":703,"assessment-promotions-en-us":744,"next-steps-en-us":783},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":26,"isFeatured":12,"meta":27,"navigation":28,"path":29,"publishedDate":20,"seo":30,"stem":34,"tagSlugs":35,"__hash__":38},"blogPosts/en-us/blog/automating-boring-git-operations-gitlab-ci.yml","Automating Boring Git Operations Gitlab Ci",[7],"kristian-larsson",null,"engineering",{"slug":11,"featured":12,"template":13},"automating-boring-git-operations-gitlab-ci",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"GitBot – automating boring Git operations with CI","Guest author Kristian Larsson shares how he automates some common Git operations, like rebase, using GitLab CI.",[18],"Kristian Larsson","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749672374/Blog/Hero%20Images/gitbot-automate-git-operations.jpg","2017-11-02","Git is super useful for anyone doing a bit of development work or just trying to\nkeep track of a bunch of text files. However, as your project grows you might\nfind yourself doing lots of boring repetitive work just around Git itself. At\nleast that’s what happened to me and so I automated some boring Git stuff using our\n[continuous integration (CI) system](/solutions/continuous-integration/).\n\n\u003C!-- more -->\n\nThere are probably all sorts of use cases for automating various Git operations\nbut I’ll talk about a few that I’ve encountered. We’re using GitLab and [GitLab\nCI](/solutions/continuous-integration/) so that’s what my examples\nwill include, but most of the concepts should apply to other systems as well.\n\n## Automatic rebase\n\nWe have some Git repos with source code that we receive from vendors, who we can think\nof as our `upstream`. We don’t actually share a Git repo with the vendor but\nrather we get a tar ball every now and then. The tar ball is extracted into a\nGit repository, on the `master` branch which thus tracks the software as it is\nreceived from upstream. In a perfect world the software we receive would be\nfeature complete and bug free and so we would be done, but that’s usually not\nthe case. We do find bugs and if they are blocking we might decide to implement\na patch to fix them ourselves. The same is true for new features where we might\nnot want to wait for the vendor to implement it.\n\nThe result is that we have some local patches to apply. We commit such patches\nto a separate branch, commonly named `ts` (for TeraStream), to keep them\nseparate from the official software. Whenever a new software version is released,\nwe extract its content to `master` and then rebase our `ts` branch onto `master`\nso we get all the new official features together with our patches. Once we’ve\nimplemented something we usually send it upstream to the vendor for inclusion.\nSometimes they include our patches verbatim so that the next version of the code\nwill include our exact patch, in which case a rebase will simply skip our patch.\nOther times there are slight or major (it might be a completely different design)\nchanges to the patch and then someone typically needs to sort out the patches\nmanually. Mostly though, rebasing works just fine and we don’t end up with conflicts.\n\nNow, this whole rebasing process gets a tad boring and repetitive after a while,\nespecially considering we have a dozen of repositories with the setup described\nabove. What I recently did was to automate this using our CI system.\n\nThe workflow thus looks like:\n\n- human extracts zip file, git add + git commit on master + git push\n- CI runs for `master` branch\n   - clones a copy of itself into a new working directory\n   - checks out `ts` branch (the one with our patches) in working directory\n   - rebases `ts` onto `master`\n   - push `ts` back to `origin`\n- this event will now trigger a CI build for the `ts` branch\n- when CI runs for the `ts` branch, it will compile, test and save the binary output as “build artifacts”, which can be included in other repositories\n- GitLab CI, which is what we use, has a CI_PIPELINE_ID that we use to version built container images or artifacts\n\nTo do this, all you need is a few lines in a .gitlab-ci.yml file, essentially;\n\n```text\nstages:\n  - build\n  - git-robot\n\n... build jobs ...\n\ngit-rebase-ts:\n  stage: git-robot\n  only:\n    - master\n  allow_failure: true\n  before_script:\n    - 'which ssh-agent || ( apt-get update -y && apt-get install openssh-client -y )'\n    - eval $(ssh-agent -s)\n    - ssh-add \u003C(echo \"$GIT_SSH_PRIV_KEY\")\n    - git config --global user.email \"kll@dev.terastrm.net\"\n    - git config --global user.name \"Mr. Robot\"\n    - mkdir -p ~/.ssh\n    - cat gitlab-known-hosts >> ~/.ssh/known_hosts\n  script:\n    - git clone git@gitlab.dev.terastrm.net:${CI_PROJECT_PATH}.git\n    - cd ${CI_PROJECT_NAME}\n    - git checkout ts\n    - git rebase master\n    - git push --force origin ts\n  ```\n\nWe’ll go through the Yaml file a few lines at a time. Some basic knowledge about GitLab CI is assumed.\n\nThis first part lists the stages of our pipeline.\n```yaml\nstages:\n  - build\n  - git-robot\n  ```\n\nWe have two stages, first the `build` stage, which does whatever you want it to\ndo (ours compiles stuff, runs a few unit tests and packages it all up), then the\n`git-robot` stage which is where we perform the rebase.\n\nThen there’s:\n\n```yaml\ngit-rebase-ts:\n  stage: git-robot\n  only:\n    - master\n  allow_failure: true\n  ```\n\nWe define the stage in which we run followed by the only statement which limits\nCI jobs to run only on the specified branch(es), in this case `master`.\n\n`allow_failure` simply allows the CI job to fail but still passing the pipeline.\n\nSince we are going to clone a copy of ourselves (the repository checked out in\nCI) we need SSH and SSH keys set up. We’ll use ssh-agent with a password-less key\nto authenticate. Generate a key using ssh-keygen, for example:\n```text\nssh-keygen\n\nkll@machine ~ $ ssh-keygen -f foo\nGenerating public/private rsa key pair.\nEnter passphrase (empty for no passphrase):\nEnter same passphrase again:\nYour identification has been saved in foo.\nYour public key has been saved in foo.pub.\nThe key fingerprint is:\nSHA256:6s15MZJ1/kUsDU/PF2WwRGA963m6ZSwHvEJJdsRzmaA kll@machine\nThe key's randomart image is:\n+---[RSA 2048]----+\n|            o**.*|\n|           ..o**o|\n|           Eo o%o|\n|          .o.+o O|\n|        So oo.o+.|\n|       .o o.. o+o|\n|      .  . o..o+=|\n|     . o ..  .o= |\n|      . +.    .. |\n+----[SHA256]-----+\nkll@machine ~ $\n```\nAdd the public key as a deploy key under Project Settings\n\u003Ci class=\"fas fa-arrow-right\" aria-hidden=\"true\">\u003C/i> Repository \u003Ci class=\"fas fa-arrow-right\" aria-hidden=\"true\">\u003C/i>\nDeploy Keys. Make sure you enable write access or you won’t be able to have your\nGit robot push commits. We then need to hand over the private key so that it can\nbe accessed from within the CI job. We’ll use a secret environment variable for\nthat, which you can define under Project Settings\n\u003Ci class=\"fas fa-arrow-right\" aria-hidden=\"true\">\u003C/i> Pipelines \u003Ci class=\"fas fa-arrow-right\" aria-hidden=\"true\">\u003C/i>\nEnvironment variables). I’ll use the environment variable GIT_SSH_PRIV_KEY for this.\n\nNext part is the before_script:\n```markdown\n  before_script:\n    - 'which ssh-agent || ( apt-get update -y && apt-get install openssh-client -y )'\n    - eval $(ssh-agent -s)\n    - ssh-add \u003C(echo \"$GIT_SSH_PRIV_KEY\")\n    - git config --global user.email \"kll@dev.terastrm.net\"\n    - git config --global user.name \"Mr. Robot\"\n    - mkdir -p ~/.ssh\n    - cat gitlab-known-hosts >> ~/.ssh/known_hosts\n  ```\n\nFirst ssh-agent is installed if it isn’t already. We then start up ssh-agent and\nadd the key stored in the environment variable GIT_SSH_PRIV_KEY (which we set up\npreviously). The Git user information is set and we finally create .ssh and add\nthe known host information about our GitLab server to our known_hosts file. You\ncan generate the gitlab-known-hosts file using the following command:\n\n```text\nssh-keyscan my-gitlab-machine >> gitlab-known-hosts\n```\n\nAs the name implies, the before_script is run before the main `script` part and\nthe ssh-agent we started in the before_script will also continue to run for the\nduration of the job. The ssh-agent information is stored in some environment\nvariables which are carried across from the before_script into the main script,\nenabling it to work. It’s also possible to put this SSH setup in the main script,\nI just thought it looked cleaner splitting it up between before_script and script.\nNote however that it appears that after_script behaves differently so while it’s\npossible to pass environment vars from before_script to script, they do not\nappear to be passed to after_script. Thus, if you want to do Git magic in the\nafter_script you also need to perform the SSH setup in the after_script.\n\nThis brings us to the main script. In GitLab CI we already have a checked-out\nclone of our project but that was automatically checked out by the CI system\nthrough the use of magic (it actually happens in a container previous to the one\nwe are operating in, that has some special credentials) so we can’t really use\nit, besides, checking out other branches and stuff would be really weird as it\ndisrupts the code we are using to do this, since that’s available in the Git\nrepository that’s checked out. It’s all rather meta.\n\nAnyway, we’ll be checking out a new Git repository where we’ll do our work, then\nchange the current directory to the newly checked-out repository, after which\nwe’ll check out the `ts` branch, do the rebase and push it back to the origin remote.\n\n```markdown\n\n    - git clone git@gitlab.dev.terastrm.net:${CI_PROJECT_PATH}.git\n    - cd ${CI_PROJECT_NAME}\n    - git checkout ts\n    - git rebase master\n    - git push --force origin ts\n  ```\n\n… and that’s it. We’ve now automated the rebasing of a branch in our config file. Occasionally it\nwill fail due to problems rebasing (most commonly merge conflicts) but then you\ncan just step in and do the above steps manually and be interactively prompted\non how to handle conflicts.\n\n## Automatic merge requests\n\nAll the repositories I mentioned in the previous section are NEDs, a form of\ndriver for how to communicate with a certain type of device, for Cisco NSO (a\nnetwork orchestration system). We package up Cisco NSO, together with these NEDs\nand our own service code, in a container image. The build of that image is\nperformed in CI and we use a repository called `nso-ts` to control that work.\n\nThe NEDs are compiled in CI from their own repository and the binaries are saved\nas build artifacts. Those artifacts can then be pulled in the CI build of `nso-ts`.\nThe reference to which artifact to include is the name of the NED as well as the\nbuild version. The version number of the NED is nothing more than the pipeline\nid (which you’ll access in CI as ${CI_PIPELINE_ID}) and by including a specific\nversion of the NED, rather than just use “latest” we gain a much more consistent\nand reproducible build.\n\nWhenever a NED is updated a new build is run that produces new binary artifacts.\nWe probably want to use the new version but not before we test it out in CI. The\nactual versions of NEDs to use is stored in a file in the `nso-ts` repository and\nfollows a simple format, like this:\n```text\nned-iosxr-yang=1234\nned-junos-yang=4567\n...\n```\nThus, updating the version to use is a simple job to just rewrite this text file\nand replace the version number with a given CI_PIPELINE_ID version number. Again,\nwhile NED updates are more seldom than updates to `nso-ts`, they do occur and\nhandling it is bloody boring. Enter automation!\n```text\ngit-open-mr:\n  image: gitlab.dev.terastrm.net:4567/terastream/cisco-nso/ci-cisco-nso:4.2.3\n  stage: git-robot\n  only:\n    - ts\n  tags:\n    - no-docker\n  allow_failure: true\n  before_script:\n    - 'which ssh-agent || ( apt-get update -y && apt-get install openssh-client -y )'\n    - eval $(ssh-agent -s)\n    - ssh-add \u003C(echo \"$GIT_SSH_PRIV_KEY\")\n    - git config --global user.email \"kll@dev.terastrm.net\"\n    - git config --global user.name \"Mr. Robot\"\n    - mkdir -p ~/.ssh\n    - cat gitlab-known-hosts >> ~/.ssh/known_hosts\n  script:\n    - git clone git@gitlab.dev.terastrm.net:TeraStream/nso-ts.git\n    - cd nso-ts\n    - git checkout -b robot-update-${CI_PROJECT_NAME}-${CI_PIPELINE_ID}\n    - for LIST_FILE in $(ls ../ned-package-list.* | xargs -n1 basename); do NED_BUILD=$(cat ../${LIST_FILE}); sed -i packages/${LIST_FILE} -e \"s/^${CI_PROJECT_NAME}.*/${CI_PROJECT_NAME}=${NED_BUILD}/\"; done\n    - git diff\n    - git commit -a -m \"Use ${CI_PROJECT_NAME} artifacts from pipeline ${CI_PIPELINE_ID}\"\n    - git push origin robot-update-${CI_PROJECT_NAME}-${CI_PIPELINE_ID}\n    - HOST=${CI_PROJECT_URL} CI_COMMIT_REF_NAME=robot-update-${CI_PROJECT_NAME}-${CI_PIPELINE_ID} CI_PROJECT_NAME=TeraStream/nso-ts GITLAB_USER_ID=${GITLAB_USER_ID} PRIVATE_TOKEN=${PRIVATE_TOKEN} ../open-mr.sh\n```\n\nSo this time around we check out a Git repository into a separate working\ndirectory again, it’s just that it’s not the same Git repository as we are\nrunning on simply because we are trying to do changes to a repository that is\nusing the output of the repository we are running on. It doesn’t make much of a\ndifference in terms of our process. At the end, once we’ve modified the files we\nare interested in, we also open up a merge request on the target repository.\nHere we can see the MR (which is merged already) to use a new version of the\nNED `ned-snabbaftr-yang`.\n\n\u003Cimg src=\"https://about.gitlab.com/images/blogimages/gitbot-ned-update-mr.png\" alt=\"MR using new version of NED\" style=\"width: 700px;\"/>\n\nWhat we end up with is that whenever there is a new version of a NED, a single merge\nrequest is opened on our `nso-ts` repository to start using the new NED. That\nmerge request is using changes on a new branch and CI will obviously run for\n`nso-ts` on this new branch, which will then test all of our code using the new\nversion of the NED. We get a form of version pinning, with the form of explicit\nchanges that it entails, yet it’s a rather convenient and non-cumbersome\nenvironment to work with thanks to all the automation.\n\n## Getting fancy\n\nWhile automatically opening an MR is sweet… we can do ~~better~~fancier. Our `nso-ts`\nrepository is based on Cisco NSO (Tail-F NCS), or actually the `nso-ts` Docker\nimage is based on a `cisco-nso` Docker image that we build in a separate\nrepository. We put the version of NSO as the tag of the `cisco-nso` Docker\nimage, so `cisco-nso:4.2.3` means Cisco NSO 4.2.3. This is what the `nso-ts`\nDockerfile will use in its `FROM` line.\n\nUpgrading to a new version of NCS is thus just a matter of rewriting the tag…\nbut what version of NCS should we use? There’s 4.2.4, 4.3.3, 4.4.2 and 4.4.3\navailable and I’m sure there’s some other version that will pop up its evil\nhead soon enough. How do I know which version to pick? And will our current code\nwork with the new version?\n\nTo help myself in the choice of NCS version I implemented a script that gets the\nREADME file of a new NCS version and cross references the list of fixed issues\nwith the issues that we currently have open in the Tail-F issue tracker. The\noutput of this is included in the merge request description so when I look at\nthe merge request I immediately know what bugs are fixed or new features are\nimplemented by moving to a specific version. Having this automatically generated\nfor us is… well, it’s just damn convenient. Together with actually testing our\ncode with the new version of NCS gives us confidence that an upgrade will be smooth.\n\nHere are the merge requests currently opened by our GitBot:\n\n\u003Cimg src=\"https://about.gitlab.com/images/blogimages/automate-git-merge-requests.png\" alt=\"Merge requests automated by Git bot\" style=\"width: 700px;\"/>\n\nWe can see how the system have generated MRs to move to all the different\nversions of NSO currently available. As we are currently on NSO v4.2.3 there’s\nno underlying branch for that one leading to an errored build. For the other\nversions though, there is a branch per version that executes the CI pipeline to\nmake sure all our code runs with this version of NSO.\n\nAs there have been a few commits today, these branches are behind by six commits\nbut will be rebased this night so we get an up-to-date picture if they work or\nnot with our latest code.\n\n\u003Cimg src=\"https://about.gitlab.com/images/blogimages/automate-git-commits.png\" alt=\"Commits\" style=\"width: 700px;\"/>\n\nIf we go back and look at one of these merge requests, we can see how the\ndescription includes information about what issues that we currently have open\nwith Cisco / Tail-F would be solved by moving to this version.\n\n\u003Cimg src=\"https://about.gitlab.com/images/blogimages/automate-git-mr-description.png\" alt=\"Merge request descriptions\" style=\"width: 700px;\"/>\n\nThis is from v4.2.4 and as we are currently on v4.2.3 we can see that there are\nonly a few fixed issues.\n\nIf we instead look at v4.4.3 we can see that the list is significantly longer.\n\n\u003Cimg src=\"https://about.gitlab.com/images/blogimages/automate-git-mr-description-list.png\" alt=\"Merge request descriptions\" style=\"width: 700px;\"/>\n\nPretty sweet, huh? :)\n\nAs this involves a bit more code I’ve put the relevant files in a [GitHub gist](https://gist.github.com/plajjan/42592665afd5ae045ee36220e19919aa).\n\n## This is the end\n\nIf you are reading this, chances are you already have your reasons for why you\nwant to automate some Git operations. Hopefully I’ve provided some inspiration\nfor how to do it.\n\nIf not or if you just want to discuss the topic in general or have more specific\nquestions about our setup, please do reach out to me on [Twitter](https://twitter.com/plajjan).\n\n_[This post](http://plajjan.github.io/automating-git/) was originally published on [plajjan.github.io](http://plajjan.github.io/)._\n\n## About the Guest Author\n\nKristian Larsson is a network automation systems architect at Deutsche Telekom.\nHe is working on automating virtually all aspects of running TeraStream, the\ndesign for Deutsche Telekom's next generation fixed network, using robust and\nfault tolerant software. He is active in the IETF as well as being a\nrepresenting member in OpenConfig. Previous to joining Deutsche Telekom,\nKristian was the IP & opto network architect for Tele2's international backbone\nnetwork.\n\n\"[BB-8 in action](https://unsplash.com/photos/C8VWyZhcIIU) by [Joseph Chan](https://unsplash.com/@yulokchan) on Unsplash\n",[23,24,25],"CI/CD","user stories","git","yml",{},true,"/en-us/blog/automating-boring-git-operations-gitlab-ci",{"title":15,"description":16,"ogTitle":15,"ogDescription":16,"noIndex":12,"ogImage":19,"ogUrl":31,"ogSiteName":32,"ogType":33,"canonicalUrls":31},"https://about.gitlab.com/blog/automating-boring-git-operations-gitlab-ci","https://about.gitlab.com","article","en-us/blog/automating-boring-git-operations-gitlab-ci",[36,37,25],"cicd","user-stories","Ds45efuEvD4ppSZBUWgNtFtEYz83Gf1uE1MctWUSp20",{"data":40},{"logo":41,"freeTrial":46,"sales":51,"login":56,"items":61,"search":368,"minimal":399,"duo":418,"pricingDeployment":428},{"config":42},{"href":43,"dataGaName":44,"dataGaLocation":45},"/","gitlab 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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.",[709],"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",[260,611,713],"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":716,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":718,"config":727},{"title":719,"description":720,"authors":721,"heroImage":722,"date":723,"category":9,"tags":724,"body":726},"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.",[709],"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",[611,260,725],"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":728,"featured":28,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":730,"config":742},{"category":9,"tags":731,"body":733,"date":734,"updatedDate":735,"heroImage":736,"authors":737,"title":740,"description":741},[732,25,23],"tutorial","\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. Self-managed GitLab may need Elasticsearch/OpenSearch for advanced features.                                                                   |\n","2025-12-03","2026-01-16","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749658924/Blog/Hero%20Images/securitylifecycle-light.png",[738,739],"Evgeny Rudinsky","Michael Leopard","Guide: Migrate from Azure DevOps to GitLab","Learn how to carry out the full migration from Azure DevOps to GitLab using GitLab Professional Services migration tools — from planning and execution to post-migration follow-up tasks.",{"featured":28,"template":13,"slug":743},"migration-from-azure-devops-to-gitlab",{"promotions":745},[746,760,771],{"id":747,"categories":748,"header":750,"text":751,"button":752,"image":757},"ai-modernization",[749],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":753,"config":754},"Get your AI maturity score",{"href":755,"dataGaName":756,"dataGaLocation":242},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":758},{"src":759},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":761,"categories":762,"header":763,"text":751,"button":764,"image":768},"devops-modernization",[725,557],"Are you just managing tools or shipping innovation?",{"text":765,"config":766},"Get your DevOps maturity score",{"href":767,"dataGaName":756,"dataGaLocation":242},"/assessments/devops-modernization-assessment/",{"config":769},{"src":770},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":772,"categories":773,"header":775,"text":751,"button":776,"image":780},"security-modernization",[774],"security","Are you trading speed for security?",{"text":777,"config":778},"Get your security maturity score",{"href":779,"dataGaName":756,"dataGaLocation":242},"/assessments/security-modernization-assessment/",{"config":781},{"src":782},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":784,"blurb":785,"button":786,"secondaryButton":791},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":787,"config":788},"Get your free trial",{"href":789,"dataGaName":50,"dataGaLocation":790},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":494,"config":792},{"href":54,"dataGaName":55,"dataGaLocation":790},1772652079452]