[{"data":1,"prerenderedAt":806},["ShallowReactive",2],{"/en-us/blog/can-chatgpt-resolve-gitlab-issues":3,"navigation-en-us":41,"banner-en-us":440,"footer-en-us":450,"blog-post-authors-en-us-John Coghlan|Fatima Sarah Khalid":690,"blog-related-posts-en-us-can-chatgpt-resolve-gitlab-issues":716,"assessment-promotions-en-us":757,"next-steps-en-us":796},{"id":4,"title":5,"authorSlugs":6,"body":9,"categorySlug":10,"config":11,"content":15,"description":9,"extension":29,"isFeatured":13,"meta":30,"navigation":31,"path":32,"publishedDate":22,"seo":33,"stem":37,"tagSlugs":38,"__hash__":40},"blogPosts/en-us/blog/can-chatgpt-resolve-gitlab-issues.yml","Can Chatgpt Resolve Gitlab Issues",[7,8],"john-coghlan","fatima-sarah-khalid",null,"engineering",{"slug":12,"featured":13,"template":14},"can-chatgpt-resolve-gitlab-issues",false,"BlogPost",{"title":16,"description":17,"authors":18,"heroImage":21,"date":22,"body":23,"category":10,"tags":24},"Testing ChatGPT: Can it solve a GitLab issue?","We put ChatGPT to the test to see if it could contribute to GitLab. Here's what we learned.",[19,20],"John Coghlan","Fatima Sarah Khalid","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749670171/Blog/Hero%20Images/akshay-nanavati-Zq6HerrBPEs-unsplash.jpg","2022-12-15","\nChatGPT has taken the tech world by storm since its [launch on November 30](https://openai.com/blog/chatgpt/). Media coverage, front page posts on Hacker News, Twitter threads, and videos - everywhere you look, there is another story.\n\nThe [GitLab Slack](https://handbook.gitlab.com/handbook/communication/#slack) was no different. In threads across Slack channels, including those for developer evangelism, UX, the CEO, random news, and every space in between, our team was chatting about this exciting new tool.\n\nAs we got more familiar with the tool, we started to learn about numerous things it can do. Here are a few that we found:\n\n- It can write poetry about GitLab features.\n- It can write blog posts.\n- It can write unit tests.\n- It gives advice on how to use certain features of GitLab.\n- It conducts competitive analysis.\n\nThere’s quite a bit more out there, including [inventing a new language](https://maximumeffort.substack.com/p/i-taught-chatgpt-to-invent-a-language) and [building a virtual machine](https://www.engraved.blog/building-a-virtual-machine-inside/). We can’t recall any technology that has generated more excitement in such a short time.\n\nWe acknowledge there are ethical and licensing concerns around using AI-generated code. For the purpose of this blog post, we will focus strictly on the capabilities of ChatGPT.\n\n## Testing ChatGPT\n\nAs members of GitLab’s [Developer Relations team](https://handbook.gitlab.com/handbook/marketing/developer-relations/), where we’re focused on growing our community of contributors and evangelists, our first reaction was to think of how this tool can help our contributors. The responses to questions like “How can I get started contributing to GitLab?” were cool but didn’t move the needle. So then we asked ourselves: Can we use ChatGPT to make a contribution to GitLab?\n\nHaving already been testing the tool, we knew we’d need to look for a very specific type of issue. We started to fine-tune our search. Here are the steps we took to find a potential issue:\n\n- Visited [https://gitlab.com/gitlab-org](https://gitlab.com/gitlab-org) and pulled up all the open issues by clicking on `Issues` in the left side nav.\n- Searched for all issues with the [“good for new contributors” label](https://gitlab.com/gitlab-org/gitlab/-/issues/?sort=updated_desc&state=opened&label_name%5B%5D=good%20for%20new%20contributors&first_page_size=20). This returned 482 issues at the time of writing.\n- Set [`“Assignee = None”`](https://gitlab.com/gitlab-org/gitlab/-/issues/?sort=updated_desc&state=opened&label_name%5B%5D=good%20for%20new%20contributors&assignee_id=None&first_page_size=20) to filter out issues that have already been assigned to someone. This trimmed things down even more.\n\nAfter poking through a few issues, this one caught our attention: an issue that is a request to [de-depulicate identical dropdown functionality from two Vue components into a shared component](https://gitlab.com/gitlab-org/gitlab/-/issues/221293).\n\n### Getting started\n\nWe opened up a ChatGPT thread via [https://chat.openai.com/chat](https://chat.openai.com/chat). If you don’t already have an account, you’ll need to register with OpenAI.\n\nThen we started a thread with Assistant (that’s what is returned when you ask ChatGPT what is its name). We asked Assistant to create a shared Vue component called `SharedDropdownFilter` from the duplicate code in `GroupsDropdownFilter` and `ProjectsDropdownFilter` and passed the scripts of both components.\n\nChatGPT replied with:\n\n>You can create a new `SharedDropdownFilter` component that contains the duplicate code and use it in both `GroupsDropdownFilter` and `ProjectsDropdownFilter`:\n\nand provided a template to describe the use. The template provided wasn’t quite what we were looking for.\n\n```xml\n\u003Ctemplate>\n  \u003CGlDropdown\n    :aria-label=\"label\"\n    :class=\"{ disabled: loading }\"\n    :disabled=\"loading\"\n    :selected=\"selectedProjectsLabel\"\n    :variant=\"multiSelect ? 'inline' : 'single-line'\"\n  >\n    \u003Ctemplate v-slot:menu>\n      \u003Cdiv class=\"py-4\">\n        \u003CGlSearchBoxByType\n          autofocus\n          class=\"search-box\"\n          :placeholder=\"searchPlaceholder\"\n          :type=\"searchType\"\n          v-model=\"searchTerm\"\n        />\n\n        \u003CGlDropdownHeader\n          v-if=\"selectedProjects.length && multiSelect\"\n          :class=\"{ 'd-none': !searchTerm }\"\n          class=\"js-dropdown-header\"\n        >\n          \u003Cspan>\n            {{ selectedProjectsLabel }}\n          \u003C/span>\n\n          \u003Cbutton\n\n```\n\nSo we tried again, this time being more specific and asking ChatGPT to “Create a shared Vue component that combines the two components `ProjectsDropdownFilter` and  `GroupsDropdownFilter`”. We passed in the full component files, including the templates.\n\nChatGPT responded with instructions, a sample Vue component, and an explanation of the functionality:\n\n> Here is a sample implementation of a shared Vue component that combines the two components `ProjectsDropdownFilter` and `GroupsDropdownFilter`:\n\n```vue\n\u003Ctemplate>\n  \u003Cdiv>\n    \u003CProjectsDropdownFilter\n      :groupId=\"groupId\"\n      :multiSelect=\"multiSelect\"\n      :label=\"label\"\n      :queryParams=\"queryParams\"\n      :defaultProjects=\"defaultProjects\"\n      @selected=\"onProjectsSelected\"\n    />\n    \u003CGroupsDropdownFilter\n      :multiSelect=\"multiSelect\"\n      :label=\"label\"\n      :queryParams=\"queryParams\"\n      :defaultGroups=\"defaultGroups\"\n      @selected=\"onGroupsSelected\"\n    />\n  \u003C/div>\n\u003C/template>\n\n\u003Cscript>\nimport { ProjectsDropdownFilter } from './ProjectsDropdownFilter.vue';\nimport { GroupsDropdownFilter } from './GroupsDropdownFilter.vue';\n\nexport default {\n  name: 'SharedDropdownFilter',\n  components: {\n    ProjectsDropdownFilter,\n    GroupsDropdownFilter,\n  },\n  props: {\n    groupId: {\n      type: Number,\n      required: true,\n    },\n    multiSelect: {\n      type: Boolean,\n      required: false,\n      default: false,\n    },\n    label: {\n      type: String,\n      required: false,\n      default: 'Dropdown filter',\n    },\n    queryParams: {\n      type: Object,\n      required: false,\n      default: () => ({}),\n    },\n    defaultProjects: {\n      type: Array,\n      required: false,\n      default: () => [],\n    },\n    defaultGroups: {\n      type: Array,\n      required: false,\n      default: () => [],\n    },\n  },\n  data() {\n    return {\n      selectedProjects: this.defaultProjects || [],\n      selectedGroups: this.defaultGroups || [],\n    };\n  },\n  methods: {\n    onProjectsSelected(selectedProjects) {\n      this.selectedProjects = selectedProjects;\n      this.$emit('selected', this.selectedProjects, this.selectedGroups);\n    },\n    onGroupsSelected(selectedGroups) {\n      this.selectedGroups = selectedGroups;\n      this.$emit('selected', this.selectedProjects, this.selectedGroups);\n    },\n  },\n};\n\u003C/script>\n```\n\n> In this implementation, the `SharedDropdownFilter` component is rendered as a container for the `ProjectsDropdownFilter` and` GroupsDropdownFilter` components. It passes down the `groupId`, `multiSelect`, `label`, `queryParams`, and `defaultProjects` props to the `ProjectsDropdownFilter` component, and the `multiSelect`, `label`, `queryParams`, and `defaultGroups` props to the `GroupsDropdownFilter` component. It also listens to the selected event emitted by the two components and updates its own `selectedProjects` and `selectedGroups` data accordingly. The `SharedDropdownFilter` component emits its own `selected` event with the updated `selectedProjects` and `selectedGroups` data when it receives the selected event from the `ProjectsDropdownFilter` and `GroupsDropdownFilter` components. This allows the parent component of the `SharedDropdownFilter` to be notified whenever the selected projects and groups are updated, so that it can take appropriate action, such as updating the data it displays.\n\nWith ChatGPT’s shared Vue component, we could start an MR for the issue, but would need to manually review the code and run tests in order to make sure the deduplication was done correctly.\n\n### Adjusting the filters\n\nIn hopes of finding an issue that ChatGPT could fully solve, this time we filtered using two labels (`good for new contributors` and `quick win`), Assignee = None, and added the keyword “refactor” to look for issues that required less net new code. At the time of writing, this [query](https://gitlab.com/gitlab-org/gitlab/-/issues/?search=refactor&sort=updated_asc&state=opened&label_name%5B%5D=quick%20win&label_name%5B%5D=good%20for%20new%20contributors&assignee_id=None&first_page_size=20) returned one issue: [a refactor for widget state tests](https://gitlab.com/gitlab-org/gitlab/-/issues/228611).\n\nAfter reviewing the issue, we opened the `/spec/frontend/vue_merge_request_widget/stores/get_state_key_spec.js` file mentioned in the issue description by navigating to that file on GitLab.com SaaS and opening the dropdown on the blue button at the top of the file frame, selecting “Open in Web IDE”, and then clicking the button to open the file in GitLab’s built-in Web IDE.\n\nWe copied the code from the file and asked ChatGPT to refactor these tests into a table of `it.each`. It was interesting to watch the output as ChatGPT provided an example of how we could refactor the tests using `it.each`:\n\n```javascript\nimport getStateKey from '~/vue_merge_request_widget/stores/get_state_key';\n\ndescribe('getStateKey', () => {\n  const context = {\n    mergeStatus: 'checked',\n    autoMergeEnabled: false,\n    canMerge: true,\n    onlyAllowMergeIfPipelineSucceeds: false,\n    isPipelineFailed: false,\n    hasMergeableDiscussionsState: false,\n    isPipelineBlocked: false,\n    canBeMerged: false,\n    projectArchived: false,\n    branchMissing: false,\n    commitsCount: 2,\n    hasConflicts: false,\n    draft: false,\n    detailedMergeStatus: null,\n  };\n\n  it.each([\n    [{}, null],\n    [{detailedMergeStatus: 'MERGEABLE'}, 'readyToMerge'],\n    [{detailedMergeStatus: 'DISCUSSIONS_NOT_RESOLVED'}, 'unresolvedDiscussions'],\n    [{detailedMergeStatus: 'DRAFT_STATUS'}, 'draft'],\n    [{detailedMergeStatus: 'CI_MUST_PASS'}, 'pipelineFailed'],\n    [{shouldBeRebased: true}, 'rebase'],\n    [{hasConflicts: true}, 'conflicts'],\n    [{detailedMergeStatus: 'CHECKING'}, 'checking'],\n    [{commitsCount: 0}, 'nothingToMerge'],\n    [{commitsCount: 1, branchMissing: true}, 'missingBranch'],\n    [{projectArchived: true}, 'archived'],\n  ])('should return \"%s\" when called with %p', (expected, input) => {\n    const bound = getStateKey.bind(Object.assign({}, context, input));\n    expect(bound()).toEqual(expected);\n  });\n\n  it('returns rebased state key', () => {\n    const context = {\n      mergeStatus: 'checked',\n      autoMergeEnabled: false,\n      canMerge: true,\n      onlyAllowMergeIfPipelineSucceeds: true,\n      isPipelineFailed: true,\n      hasMergeableDiscussionsState: false,\n      isPipelineBlocked: false,\n      canBeMerged: false,\n      shouldBeRebased: true,\n      projectArchived: false,\n      branchMissing: false,\n      commitsCount: 2,\n      hasConflicts: false,\n      draft: false,\n    };\n    const bound = getStateKey.bind(context);\n\n    expect(bound()).toEqual('rebase');\n  });\n});\n```\n\nAlong with an explanation of `it.each`:\n\n> Note that `it.each` is a utility provided by Jest that allows you to write the same test with different inputs and expected results. This can make your tests more concise and easier to read.\n\nOur next steps were to:\n- Paste the output from ChatGPT into the Web IDE.\n- Click the blue “Commit” button to commit the code.\n- Name the branch.\n- Open a merge request.\n\nAll of this can be done inside [GitLab’s Web IDE](https://docs.gitlab.com/ee/user/project/web_ide/) without leaving the browser.\n\n### Examining the results\n\nOnce we opened the merge request, a CI/CD pipeline was created to test the change. Unfortunately, the pipeline jobs for the Jest tests failed because the tests were returning `null` for each case instead of the expected results. We went back to ChatGPT to see if it could help us understand why the test was returning null for all cases. ChatGPT suggested a few different implementations to check to make sure things are defined currently:\n\n> There are a few reasons why the tests in the `it.each` function might be returning null for every case. Here are a few possibilities:\n>\n> If the `getStateKey` function is not implemented correctly, it might always return null, regardless of the input.\n> If the `getStateKey` function relies on certain variables that are not defined in the test cases, it might return null because those variables are undefined.\n> If the context object passed to the `getStateKey` function is not being merged correctly with the input object in the test cases, the function might not have access to all of the necessary information, and it might return null.\n\nWhile ChatGPT couldn’t solve the issue with the returned value directly, it provided a lot of possibilities to look into and offered suggestions of what variables or functions to debug. The suggestions prompted us to add code changes that logged the variable values onto the [JavaScript debug console](https://www.w3schools.com/js/js_debugging.asp), find the implementation of the `getStateKey` function, and figure out why the return value was null. Whenever we came across something unfamiliar in the code, like syntax in the `it.each` that wasn’t familiar, we asked ChatGPT for clarification or a helpful example. Many times throughout this experiment, working with ChatGPT felt like “rubber duck debugging,” but with an AI with which you have to be very specific about your ask.\n\n## What we learned from ChatGPT\n\nIn the end, we weren’t able to figure out why our tests were returning null, so we asked the front-end team if someone could review the code. Senior Frontend Engineer [Angelo Gulina](https://gitlab.com/agulina) reviewed the MR. He found that the solution was actually quite trivial: The order of parameters was inverted, resulting in a comparison that led to null! In his assessment, ChatGPT wasn’t able to provide a working solution, but would be able to provide solutions and ideas to an engineer with some experience with the codebase. It delivered a clean, organized solution and answered the task of combining the tests into an it.each table. It could not, however, catch the actual error (the inversion of parameters) or correctly guess why the tests were returning null.\n\nLet's circle back to the question that started this experiment: Can we use ChatGPT to contribute to GitLab? At this time, we’d say, \"yes,\" and you will need some understanding of the code to complete your solution. Since ChatGPT is a language model trained by OpenAI, it can only answer questions and provide information addressed in the model, which means answers requiring contextual specificity may fall short of what is needed to resolve an issue. However, it’s a tool that can help you if you’re stuck, need more clarification on a code snippet, or are trying to refactor some code. It was fascinating for us to experiment with ChatGPT and we were excited to see what it was capable of. The code provided, however, lacked some of the valuable insight and industry experience that a community of contributors can provide.\n\nAt GitLab, our [community and our open source stewardship](https://handbook.gitlab.com/handbook/company/strategy/#dual-flywheels) are part of our company strategy. Thousands of open source contributors worldwide have helped make GitLab what it is today. We see potential for ChatGPT and similar AI tools, not as a replacement for our community, but a way to make our community more efficient and enable more people to contribute GitLab.\n\n\n\n\n",[25,26,27,28],"tutorial","community","contributors","DevOps","yml",{},true,"/en-us/blog/can-chatgpt-resolve-gitlab-issues",{"title":16,"description":17,"ogTitle":16,"ogDescription":17,"noIndex":13,"ogImage":21,"ogUrl":34,"ogSiteName":35,"ogType":36,"canonicalUrls":34},"https://about.gitlab.com/blog/can-chatgpt-resolve-gitlab-issues","https://about.gitlab.com","article","en-us/blog/can-chatgpt-resolve-gitlab-issues",[25,26,27,39],"devops","vw5IorIWvERshGTFnXUlGbFRMgBjdvB4D1Fiz6PXE3M",{"data":42},{"logo":43,"freeTrial":48,"sales":53,"login":58,"items":63,"search":370,"minimal":401,"duo":420,"pricingDeployment":430},{"config":44},{"href":45,"dataGaName":46,"dataGaLocation":47},"/","gitlab logo","header",{"text":49,"config":50},"Get free 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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.",[722],"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",[26,612,726],"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":729,"featured":13,"template":14},"how-iit-bombay-students-code-future-with-gitlab",{"content":731,"config":740},{"title":732,"description":733,"authors":734,"heroImage":735,"date":736,"category":10,"tags":737,"body":739},"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.",[722],"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",[612,26,738],"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":741,"featured":31,"template":14},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":743,"config":755},{"category":10,"tags":744,"body":746,"date":747,"updatedDate":748,"heroImage":749,"authors":750,"title":753,"description":754},[25,745,110],"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",[751,752],"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":31,"template":14,"slug":756},"migration-from-azure-devops-to-gitlab",{"promotions":758},[759,773,784],{"id":760,"categories":761,"header":763,"text":764,"button":765,"image":770},"ai-modernization",[762],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":766,"config":767},"Get your AI maturity score",{"href":768,"dataGaName":769,"dataGaLocation":245},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":771},{"src":772},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":774,"categories":775,"header":776,"text":764,"button":777,"image":781},"devops-modernization",[738,558],"Are you just managing tools or shipping innovation?",{"text":778,"config":779},"Get your DevOps maturity score",{"href":780,"dataGaName":769,"dataGaLocation":245},"/assessments/devops-modernization-assessment/",{"config":782},{"src":783},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":785,"categories":786,"header":788,"text":764,"button":789,"image":793},"security-modernization",[787],"security","Are you trading speed for security?",{"text":790,"config":791},"Get your security maturity score",{"href":792,"dataGaName":769,"dataGaLocation":245},"/assessments/security-modernization-assessment/",{"config":794},{"src":795},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":797,"blurb":798,"button":799,"secondaryButton":804},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":800,"config":801},"Get your free trial",{"href":802,"dataGaName":52,"dataGaLocation":803},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":496,"config":805},{"href":56,"dataGaName":57,"dataGaLocation":803},1772652056286]