[{"data":1,"prerenderedAt":795},["ShallowReactive",2],{"/en-us/blog/moving-to-headless-chrome":3,"navigation-en-us":38,"banner-en-us":438,"footer-en-us":448,"blog-post-authors-en-us-Mike Greiling":690,"blog-related-posts-en-us-moving-to-headless-chrome":704,"assessment-promotions-en-us":746,"next-steps-en-us":785},{"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__":37},"blogPosts/en-us/blog/moving-to-headless-chrome.yml","Moving To Headless Chrome",[7],"mike-greiling",null,"engineering",{"slug":11,"featured":12,"template":13},"moving-to-headless-chrome",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"How GitLab switched to Headless Chrome for testing","A detailed explanation with examples of how GitLab made the switch to headless Chrome.",[18],"Mike Greiling","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749680270/Blog/Hero%20Images/headless-chrome-cover.jpg","2017-12-19","GitLab recently switched from PhantomJS to headless Chrome for both our\nfrontend tests and our RSpec feature tests. In this post we will detail the\nreasons we made this transition, the challenges we faced, and the solutions we\ndeveloped. We hope this will benefit others making the switch.\n\n\u003C!-- more -->\n\nWe now have a truly accurate way to test GitLab within a real, modern browser.\nThe switch has improved our ability to write tests and debug them while running\nthem directly in Chrome. Plus the change forced us to confront and clean up a\nnumber of hacks we had been using in our tests.\n\n## Switching to headless Chrome from PhantomJS: background\n\n[PhantomJS](http://phantomjs.org) has been a part of GitLab's test framework\n[for almost five years](https://gitlab.com/gitlab-org/gitlab-ce/commit/ba25b2dc84cc25e66d6fa1450fee39c9bac002c5).\nIt has been an immensely useful tool for running browser integration tests in a\nheadless environment at a time when few options were available. However, it\nhad some shortcomings:\n\nThe most recent version of PhantomJS (v2.1.1) is compiled with a three-year-old\nversion of [QtWebKit](https://trac.webkit.org/wiki/QtWebKit) (a fork of WebKit\nv538.1 according to the user-agent string). This puts it on par with something\nlike Safari 7 on macOS 10.9. It resembles a real modern browser, but it's not\nquite there. It has a different JavaScript engine, an older rendering engine,\nand a host of missing features and quirks.\n\nAt this time, GitLab supports [the current and previous major\nrelease](https://docs.gitlab.com/ee/install/requirements.html#supported-web-browsers) of\nFirefox, Chrome, Safari, and Microsoft Edge/IE. This puts PhantomJS and its\ncapabilities somewhere near or below our lowest common denominator. Many modern\nbrowser features either [do not work](http://phantomjs.org/supported-web-standards.html),\nor [require vendor prefixes](http://phantomjs.org/tips-and-tricks.html) and\npolyfills that none of our supported browsers require. We could selectively\nadd these polyfills, prefixes, and other workarounds just within our test\nenvironment, but doing so would increase technical debt, cause confusion, and\nmake the tests less representative of a true production environment. In most\ncases we had opted to simply omit them or hack around them (more on this\n[later](#trigger-method)).\n\nHere's a screenshot of the way PhantomJS renders a page from GitLab, followed\nby the same page rendered in Google Chrome:\n\n![Page Rendered by PhantomJS](https://about.gitlab.com/images/blogimages/moving-to-headless-chrome/render-phantomjs.png){: .shadow.center}\n\n![Page Rendered by Google Chrome](https://about.gitlab.com/images/blogimages/moving-to-headless-chrome/render-chrome.png){: .shadow.center}\n\nYou can see in PhantomJS the filter tabs are rendered horizontally, the icons\nin the sidebar render on their own lines, the global search field is\noverflowing off the navbar, etc.\n\nWhile it looks ugly, in most cases we could still use this to run functional\ntests, so long as elements of the page remain visible and clickable, but this\ndisparity with the way GitLab rendered in a real browser did introduce several\nedge cases.\n\n## What is headless Chrome\n\nIn April of this year, [news spread](https://news.ycombinator.com/item?id=14101233)\nthat Chrome 59 would support a [native, cross-platform headless\nmode](https://www.chromestatus.com/features/5678767817097216). It was\npreviously possible to simulate a headless Chrome browser in CI/CD [using\nvirtual frame buffer](https://gist.github.com/addyosmani/5336747), but this\nrequired a lot of memory and extra complexities. A native headless mode is a\ngame changer. It is now possible to run integration tests in a headless\nenvironment on a real, modern web browser that our users actually use!\n\nSoon after this was revealed, Vitaly Slobodin, PhantomJS's chief developer,\nannounced that the project [would no longer be\nmaintained](https://github.com/ariya/phantomjs/issues/15105#issuecomment-322850178):\n\n\u003Cdiv class=\"center\">\n\n\u003Cblockquote class=\"twitter-tweet\" data-cards=\"hidden\" data-lang=\"en\">\u003Cp lang=\"en\" dir=\"ltr\">This is the end - \u003Ca href=\"https://t.co/GVmimAyRB5\">https://t.co/GVmimAyRB5\u003C/a>\u003Ca href=\"https://twitter.com/hashtag/phantomjs?src=hash&ref_src=twsrc%5Etfw\">#phantomjs\u003C/a> 2.5 will not be released. Sorry, guys!\u003C/p>— Vitaly Slobodin (@Vitalliumm) \u003Ca href=\"https://twitter.com/Vitalliumm/status/852450027318464513?ref_src=twsrc%5Etfw\">April 13, 2017\u003C/a>\u003C/blockquote>\n\u003Cscript async src=\"https://platform.twitter.com/widgets.js\" charset=\"utf-8\">\u003C/script>\n\n\u003C/div>\n\nIt became clear that we would need to make the transition away from PhantomJS at\nsome point, so we [opened up an issue](https://gitlab.com/gitlab-org/gitlab-ce/issues/30876),\ndownloaded the Chrome 59 beta, and started looking at options.\n\n### Frontend tests (Karma)\n\nOur frontend test suite utilizes the [Karma](http://karma-runner.github.io/)\ntest runner, and updating this to work with Google Chrome was surprisingly\nsimple ([here's the merge request](https://gitlab.com/gitlab-org/gitlab-ce/merge_requests/12036)).\nThe [karma-chrome-launcher](https://github.com/karma-runner/karma-chrome-launcher)\nplugin was very quickly updated to support headless mode starting from\n[version 2.1.0](https://github.com/karma-runner/karma-chrome-launcher/releases/tag/v2.1.0),\nand it was essentially a drop-in replacement for the PhantomJS launcher. Once\nwe [re-built our CI/CD build images](https://gitlab.com/gitlab-org/gitlab-build-images/merge_requests/41)\nto include Google Chrome 59 (and fiddled around with some pesky timeout\nsettings), it worked!  We were also able to remove some rather ugly\nPhantomJS-specific hacks that Jasmine required to spy on some built-in browser\nfunctions.\n\n### Backend feature tests (RSpec + Capybara)\n\nOur feature tests use RSpec and [Capybara](https://github.com/teamcapybara/capybara)\nto perform full end-to-end integration testing of database, backend, and\nfrontend interactions. Before switching to headless Chrome, we had used\n[Poltergeist](https://github.com/teampoltergeist/poltergeist) which is a\nPhantomJS driver for Capybara. It would spin up a PhantomJS browser instance\nand direct it to browse, fill out forms, and click around on pages to verify\nthat everything behaved as it should.\n\nSwitching from PhantomJS to Google Chrome required a change in drivers from\nPoltergeist to Selenium and [ChromeDriver](https://sites.google.com/a/chromium.org/chromedriver/).\nSetting this up was pretty straightforward. You can install ChromeDriver on\nmacOS with `brew install chromedriver` and the process is similar on any given\npackage manager in Linux. After this we added the `selenium-webdriver` gem to\nour test dependencies and configured Capybara like so:\n\n```ruby\nrequire 'selenium-webdriver'\n\nCapybara.register_driver :chrome do |app|\n  options = Selenium::WebDriver::Chrome::Options.new(\n    args: %w[headless disable-gpu no-sandbox]\n  )\n  Capybara::Selenium::Driver.new(app, browser: :chrome, options: options)\nend\n\nCapybara.javascript_driver = :chrome\n```\n\nGoogle says the [`disable-gpu` option is necessary for the time\nbeing](https://developers.google.com/web/updates/2017/04/headless-chrome#cli)\nuntil some bugs are resolved. The `no-sandbox` option also appears to be\nnecessary to get Chrome running inside a Docker container for [GitLab's CI/CD\nenvironment](/topics/ci-cd/). Google provides a [useful guide for working with headless Chrome\nand Selenium](https://developers.google.com/web/updates/2017/04/headless-chrome).\n\nIn our final implementation we changed this to conditionally add the `headless`\noption unless you have `CHROME_HEADLESS=false` in your environment. This makes\nit easy to disable headless mode while debugging or writing tests. It's also\npretty fun to watch tests execute on the browser window in real time:\n\n```shell\nexport CHROME_HEADLESS=false\nbundle exec rspec spec/features/merge_requests/filter_merge_requests_spec.rb\n```\n\n![Tests Executing in Chrome](https://about.gitlab.com/images/blogimages/moving-to-headless-chrome/headlessless-chrome-tests.gif){: .shadow.center}\n\n### What is the differences between Poltergeist and Selenium?\n\nThe process of switching drivers here was not nearly as straightforward as\nit was with the frontend test suite. Dozens of tests started failing as soon\nas we changed our Capybara configuration, and this was due to some major\ndifferences in the way Selenium/ChromeDriver implemented Capybara's driver API\ncompared to Poltergeist/PhantomJS. Here are some of the challenges we ran into:\n\n1.  **JavaScript modals are no longer accepted automatically**\n\n    We often use JavaScript `confirm(\"Are you sure you want to do X?\");` click\n    events when performing a destructive action such as deleting a branch or\n    removing a user from a group. Under Poltergeist a `.click` action would\n    automatically accept modals like `alert()` and `confirm()`, but under\n    Selenium, you now need to wrap these with one of `accept_alert`,\n    `accept_confirm`, or `dismiss_confirm`. e.g.:\n\n    ```ruby\n    # Before\n    page.within('.some-selector') do\n      click_link 'Delete'\n    end\n\n    # After\n    page.within('.some-selector') do\n      accept_confirm { click_link 'Delete' }\n    end\n    ```\n\n1.  **Selenium `Element.visible?` returns false for empty elements**\n\n    If you have an empty `div` or `span` that you want to access in your test,\n    Selenium does not consider these \"visible.\" This is not much of an issue\n    unless you set `Capybara.ignore_hidden_elements = true` as we do in our\n    feature tests. Where `find('.empty-div')` would have worked fine in\n    Poltergeist, we now need to use `visible: :any` to\n    select such elements.\n\n    ```ruby\n    # Before\n    find('.empty-div')\n\n    # After\n    find('.empty-div', visible: :any)\n    # or\n    find('.empty-div', visible: false)\n    ```\n\n    More on [Capybara and hidden elements](https://makandracards.com/makandra/7617-change-how-capybara-sees-or-ignores-hidden-elements).\n\n1.  {:#trigger-method} **Poltergeist's `Element.trigger('click')` method does not exist in Selenium**\n\n    In Capybara, when you use `find('.some-selector').click`, the element you\n    are clicking must be both visible and unobscured by any overlapping\n    element. Situations where links could not be clicked would sometimes occur\n    with Poltergeist/PhantomJS due to its poor CSS support sans-prefixes.\n    Here's one example:\n\n    ![Overlapping elements](https://about.gitlab.com/images/blogimages/moving-to-headless-chrome/overlapping-element.png)\n\n    The broken layout of the search form here was actually placing an invisible\n    element over the top of the \"Update all\" button, making it unclickable.\n    Poltergeist offers a `.trigger('click')` method to work around this.\n    Rather than actually clicking the element, this method would trigger a DOM\n    event to simulate a click. Utilizing this method was a bad practice, but\n    we ran into similar issues so often that many developers formed a habit\n    of using it everywhere. This began to lead to some lazy and sloppy test\n    writing. For instance, someone might use `.trigger` as a shortcut to click\n    on an link that was obscured behind an open dropdown menu, when a properly\n    written test should `.click` somewhere to close the dropdown, and _then_\n    `.click` on the item behind it.\n\n    Selenium does not support the `.trigger` method. Now that we were using a\n    more accurate rendering engine that won't break our layouts, many of these\n    instances could be resolved by simply replacing `.trigger('click')` with\n    `.click`, but due to some of the bad practice uses mentioned above, this\n    didn't always work.\n\n    There are of course some ways to hack a `.trigger` replacement. You could\n    simulate a click by focusing on an element and hitting the \"return\" key,\n    or use JavaScript to trigger a click event, but in most cases we decided to\n    take the time and actually correct these poorly implemented tests so that a\n    normal `.click` could again be used. After all, if our tests are meant to\n    simulate a real user interacting with the page, we should limit ourselves\n    to the actions a real user would be expected to use.\n\n    ```ruby\n    # Before\n    find('.obscured-link').trigger('click')\n\n    # After\n\n    # bad\n    find('.obscured-link').send_keys(:return)\n\n    # bad\n    execute_script(\"document.querySelector('.obscured-link').click();\")\n\n    # good\n    # do something to make link accessible, then\n    find('.link').click\n    ```\n\n1.  **`Element.send_keys` only works on focus-able elements**\n\n    We had a few places in our code where we would test out our keyboard\n    shortcuts using something like `find('.boards-list').native.send_keys('i')`.\n    It turns out Chrome will not allow you to `send_keys` to any element that\n    cannot be \"focused\", e.g. links, form elements, the document body, or\n    presumably anything with a tab index.\n\n    In all of the cases where we were doing this, triggering `send_keys` on the\n    body element would work since that's ultimately where our event handler was\n    listening anyway:\n\n    ```ruby\n    # Before\n    find('.some-div').native.send_keys('i')\n\n    # After\n    find('body').native.send_keys('i')\n    ```\n\n1.  **`Element.send_keys` does not support non-BMP characters (like emoji)**\n\n    In a few tests, we needed to fill out forms with emoji characters. With\n    Poltergeist we would do this like so:\n\n    ```ruby\n    # Before\n    find('#note-body').native.send_keys('@💃username💃')\n    ```\n\n    In Selenium we would get the following error message:\n\n    ```text\n    Selenium::WebDriver::Error::UnknownError:\n        unknown error: ChromeDriver only supports characters in the BMP\n    ```\n\n    To work around this, we added [a JavaScript method to our test bundle that\n    would simulate input and fire off the same DOM events](https://gitlab.com/gitlab-org/gitlab-ce/blob/a8b9852837/app/assets/javascripts/test_utils/simulate_input.js)\n    that an actual keyboard input would generate on every keystroke, then\n    wrapped this with a [ruby helper](https://gitlab.com/gitlab-org/gitlab-ce/blob/a8b9852837/spec/support/input_helper.rb)\n    method that could be called like so:\n\n    ```ruby\n    # After\n    include InputHelper\n\n    simulate_input('#note-body', \"@💃username💃\")\n    ```\n\n1.  **Setting cookies is much more complicated**\n\n    It's quite common to want to set some cookies before `visit`ing a page that\n    you intend to test, whether it's to mock a user session, or toggle a\n    setting. With Poltergeist, this process is really simple. You can use\n    `page.driver.set_cookie`, provide a simple key/value pair, and it will just\n    work as expected, setting a cookie with the correct domain and scope.\n\n    Selenium is quite a bit more strict. The method is now\n    `page.driver.browser.manage.add_cookie`, and it comes with two caveats:\n\n    - You cannot set cookies until you `visit` a page in the domain you intend\n      to scope your cookies to.\n    - Annoyingly, you cannot alter the `path` parameter (or at least we could\n      never get this to work), so it is best to set cookies at the root path.\n\n    Before you `visit` your page, Chrome's url is technically sitting at\n    something like `about:blank;`. When you attempt to set a cookie there, it\n    will refuse because there is no hostname, and you cannot coerce one by\n    providing a domain as an argument. The [Selenium\n    documentation](http://docs.seleniumhq.org/docs/03_webdriver.jsp#cookies)\n    suggests that you do the following:\n\n    > If you are trying to preset cookies before you start interacting with a\n    > site and your homepage is large / takes a while to load, an alternative is\n    > to find a smaller page on the site (typically the 404 page is small, e.g.\n    > `http://example.com/some404page`).\n\n    ```ruby\n    # Before\n    before do\n      page.driver.set_cookie('name', 'value')\n    end\n\n    # After\n    before do\n      visit '/some-root-path'\n      page.driver.browser.manage.add_cookie(name: 'name', value: 'value')\n    end\n    ```\n\n1.  **Page request/response inspection methods are missing**\n\n    Poltergeist very conveniently implemented methods like `page.status_code`\n    and `page.response_headers` which are also present in Capybara's default\n    `RackTest` driver, making it easy to inspect the raw response from the\n    server, in addition to the way that response is rendered by the browser. It\n    also allowed you to inject headers into the requests made to the server,\n    e.g.:\n\n    ```ruby\n    # Before\n    before do\n      page.driver.add_header('Accept', '*/*')\n    end\n\n    it 'returns a 404 page'\n      visit some_path\n\n      expect(page.status_code).to eq(404)\n      expect(page).to have_css('.some-selector')\n    end\n    ```\n\n    Selenium does not implement these methods, and [the authors do not intend\n    to add support for them](https://github.com/seleniumhq/selenium-google-code-issue-archive/issues/141#issuecomment-191404986),\n    so we needed to develop a workaround. Several people have suggested running\n    a proxy alongside ChromeDriver that would intercept all traffic to and from\n    the server, but this seemed to us like overkill. Instead, we opted to\n    create a [lightweight Rack middleware](https://gitlab.com/gitlab-org/gitlab-ce/blob/a8b9852837/lib/gitlab/testing/request_inspector_middleware.rb)\n    and a corresponding [helper class](https://gitlab.com/gitlab-org/gitlab-ce/blob/a8b9852837/spec/support/inspect_requests.rb)\n    that would intercept the traffic for inspection. This is similar to our\n    [RequestBlockerMiddleware](https://gitlab.com/gitlab-org/gitlab-ce/blob/master/lib/gitlab/testing/request_blocker_middleware.rb)\n    that we were already using to intelligently `wait_for_requests` to complete\n    within our tests. It works like this:\n\n    ```ruby\n    # After\n    it 'returns a 404 page'\n      requests = inspect_requests do\n        visit some_path\n      end\n\n      expect(requests.first.status_code).to eq(404)\n      expect(page).to have_css('.some-selector')\n    end\n    ```\n\n    Within the `inspect_requests` block, the Rack middleware will log all\n    requests and responses, and return them as an array for inspection. This\n    will include the page being `visit`ed as well as the subsequent XHR and\n    asset requests, but the initial path request will be the first in the array.\n\n    You can also inject headers using the same helper like so:\n\n    ```ruby\n    # After\n    inspect_requests(inject_headers: { 'Accept' => '*/*' }) do\n      visit some_path\n    end\n    ```\n\n    This middleware should be injected early in the stack to ensure any other\n    middleware that might intercept or modify the request/response will be\n    seen by our tests. We include this line in our test environment config:\n\n    ```ruby\n    config.middleware.insert_before('ActionDispatch::Static', 'Gitlab::Testing::RequestInspectorMiddleware')\n    ```\n\n1.  **Browser console output is no longer output to the terminal**\n\n    Poltergeist would automatically output any `console` messages directly into\n    the terminal in real time as tests were run. If you had a bug in the frontend\n    code that caused a test to fail, this feature would make debugging much\n    easier as you could inspect the terminal output of the test for an error\n    message or a stack trace, or inject your own `console.log()` into the\n    JavaScript to see what is going on. With Selenium this is sadly no longer the\n    case.\n\n    You can, however, collect browser logs by configuring Capybara like so:\n\n    ```ruby\n    capabilities = Selenium::WebDriver::Remote::Capabilities.chrome(\n      loggingPrefs: {\n        browser: \"ALL\",\n        client: \"ALL\",\n        driver: \"ALL\",\n        server: \"ALL\"\n      }\n    )\n\n    # ...\n\n    Capybara::Selenium::Driver.new(\n      app,\n      browser: :chrome,\n      desired_capabilities: capabilities,\n      options: options\n    )\n    ```\n\n    This will allow you to access logs with the following, i.e. in the event of\n    a test failure:\n\n    ```ruby\n    page.driver.manage.get_log(:browser)\n    ```\n\n    This is far more cumbersome than it was in Poltergeist, but it's the best\n    method we've found so far. Thanks to [Larry Reid's blog post](http://technopragmatica.blogspot.com/2017/10/switching-to-headless-chrome-for-rails_31.html)\n    for the tip!\n\n## Results\n\nRegarding performance, we attempted to quantify the change with a\nnon-scientific analysis of 10 full-suite RSpec test runs _before_ this change,\nand 10 more runs from _after_ this change, factoring out any tests that were\nadded or removed between these pipelines. The end result was:\n\n**Before:** 5h 18m 52s\n**After:** 5h 12m 34s\n\nA savings of about six minutes, or roughly 2 percent of the total compute time, is\nstatistically insignificant, so I'm not going to claim we improved our test\nspeed with this change.\n\nWhat we did improve was test accuracy, and we vastly improved the tools at our\ndisposal to write and debug tests. Now, all of the Capybara screenshots\ngenerated when a CI/CD job fails look exactly as they do on your own browser\nrather than resembling the broken PhantomJS screenshot above. Inspecting a\nfailing test locally can now be done interactively by turning off headless\nmode, dropping a `byebug` line into the spec file, and watching the browser\nwindow as you type commands into the prompt. This technique proved extremely\nuseful while working on this project.\n\nYou can find all of the changes we made in [the original merge request page\non GitLab.com](https://gitlab.com/gitlab-org/gitlab-ce/merge_requests/12244).\n\n## What are some additional uses for headless Chrome?\n\nWe have also been utilizing headless Chrome to analyze frontend performance, and have found it to be useful in detecting issues.\n\nWe'd like to make it easier for other companies to embrace as well, so as part of the upcoming 10.3 release of GitLab we are releasing [Browser Performance Testing](https://docs.gitlab.com/ee/user/project/merge_requests/browser_performance_testing.html). Leveraging [GitLab CI/CD](/solutions/continuous-integration/), headless Chrome is launched against a set of pages and an overall performance score is calculated. Then for each merge request the scores are compared between the source and target branches, making it easier detect performance regressions prior to merge.\n\n## Acknowledgements\n\nI sincerely hope this information will prove useful to anybody else looking to\nmake the switch from PhantomJS to headless Chrome for their Rails application.\n\nThanks to the Google team for their very helpful documentation, thanks to the\nmany bloggers out there who shared their own experiences with hacking headless\nChrome in the early days of its availability, and special thanks to Vitaly\nSlobodin and the rest of the contributors to PhantomJS who provided us with an\nextremely useful tool that served us for many years. 🙇‍\n\n\u003Cstyle>\n\n.center {\n  text-align: center;\n  display: block;\n  margin-right: auto;\n  margin-left: auto;\n}\n\ncode, kbd {\n  font-size: 80%;\n}\n\n\u003C/style>\n",[23,24,25],"inside 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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.",[710],"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",[260,612,714],"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. 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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":717,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":719,"config":728},{"title":720,"description":721,"authors":722,"heroImage":723,"date":724,"category":9,"tags":725,"body":727},"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.",[710],"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",[612,260,726],"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":729,"featured":28,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":731,"config":744},{"category":9,"tags":732,"body":735,"date":736,"updatedDate":737,"heroImage":738,"authors":739,"title":742,"description":743},[733,734,107],"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. 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",[740,741],"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":745},"migration-from-azure-devops-to-gitlab",{"promotions":747},[748,762,773],{"id":749,"categories":750,"header":752,"text":753,"button":754,"image":759},"ai-modernization",[751],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":755,"config":756},"Get your AI maturity score",{"href":757,"dataGaName":758,"dataGaLocation":242},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":760},{"src":761},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":763,"categories":764,"header":765,"text":753,"button":766,"image":770},"devops-modernization",[726,558],"Are you just managing tools or shipping innovation?",{"text":767,"config":768},"Get your DevOps maturity score",{"href":769,"dataGaName":758,"dataGaLocation":242},"/assessments/devops-modernization-assessment/",{"config":771},{"src":772},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":774,"categories":775,"header":777,"text":753,"button":778,"image":782},"security-modernization",[776],"security","Are you trading speed for security?",{"text":779,"config":780},"Get your security maturity score",{"href":781,"dataGaName":758,"dataGaLocation":242},"/assessments/security-modernization-assessment/",{"config":783},{"src":784},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":786,"blurb":787,"button":788,"secondaryButton":793},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":789,"config":790},"Get your free trial",{"href":791,"dataGaName":49,"dataGaLocation":792},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":494,"config":794},{"href":53,"dataGaName":54,"dataGaLocation":792},1772652077556]