[{"data":1,"prerenderedAt":810},["ShallowReactive",2],{"/en-us/blog/ci-deployment-and-environments":3,"navigation-en-us":42,"banner-en-us":442,"footer-en-us":452,"blog-post-authors-en-us-Ivan Nemytchenko|Cesar Saavedra":694,"blog-related-posts-en-us-ci-deployment-and-environments":720,"assessment-promotions-en-us":761,"next-steps-en-us":800},{"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__":41},"blogPosts/en-us/blog/ci-deployment-and-environments.yml","Ci Deployment And Environments",[7,8],"ivan-nemytchenko","cesar-saavedra",null,"engineering",{"slug":12,"featured":13,"template":14},"ci-deployment-and-environments",false,"BlogPost",{"title":16,"description":17,"authors":18,"heroImage":21,"date":22,"body":23,"category":10,"tags":24,"updatedDate":28},"How to use GitLab CI to deploy to multiple environments","We walk you through different scenarios to demonstrate the versatility and power of GitLab CI.",[19,20],"Ivan Nemytchenko","Cesar Saavedra","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749662033/Blog/Hero%20Images/intro.jpg","2021-02-05","This post is a success story of one imaginary news portal, and you're the happy\nowner, the editor, and the only developer. Luckily, you already host your project\ncode on GitLab.com and know that you can\n[run tests with GitLab CI/CD](https://docs.gitlab.com/ee/ci/testing/).\nNow you’re curious if it can be [used for deployment](/blog/how-to-keep-up-with-ci-cd-best-practices/), and how far can you go with it.\n\nTo keep our story technology stack-agnostic, let's assume that the app is just a\nset of HTML files. No server-side code, no fancy JS assets compilation.\n\nDestination platform is also simplistic – we will use [Amazon S3](https://aws.amazon.com/s3/).\n\nThe goal of the article is not to give you a bunch of copy-pasteable snippets.\nThe goal is to show the principles and features of [GitLab CI](/solutions/continuous-integration/) so that you can easily apply them to your technology stack.\n\n\nLet’s start from the beginning. There's no continuous integration (CI) in our story yet.\n\n## At the starting line\n\n**Deployment**: In your case, it means that a bunch of HTML files should appear on your\nS3 bucket (which is already configured for\n[static website hosting](http://docs.aws.amazon.com/AmazonS3/latest/dev/HowDoIWebsiteConfiguration.html?shortFooter=true)).\n\nThere are a million ways to do it. We’ll use the\n[awscli](http://docs.aws.amazon.com/cli/latest/reference/s3/cp.html#examples) library,\nprovided by Amazon.\n\nThe full command looks like this:\n\n```shell\naws s3 cp ./ s3://yourbucket/ --recursive --exclude \"*\" --include \"*.html\"\n```\n\n![Manual deployment](https://about.gitlab.com/images/blogimages/ci-deployment-and-environments/13.jpg){: .center}\nPushing code to repository and deploying are separate processes.\n\n\nImportant detail: The command\n[expects you](http://docs.aws.amazon.com/cli/latest/userguide/cli-chap-getting-started.html#config-settings-and-precedence)\nto provide `AWS_ACCESS_KEY_ID` and  `AWS_SECRET_ACCESS_KEY` environment\nvariables. Also you might need to specify `AWS_DEFAULT_REGION`.\n\n\nLet’s try to automate it using [GitLab CI](/solutions/continuous-integration/).\n\n## The first automated deployment\n\nWith GitLab, there's no difference on what commands to run.\nYou can set up GitLab CI in a way that tailors to your specific needs, as if it was your local terminal on your computer. As long as you execute commands there, you can tell CI to do the same for you in GitLab.\nPut your script to `.gitlab-ci.yml` and push your code – that’s it: CI triggers\na _job_ and your commands are executed.\n\nNow, let's add some context to our story: Our website is small, there is 20-30 daily\nvisitors and the code repository has only one default branch: `main`.\n\nLet's start by specifying a _job_ with the command from above in the `.gitlab-ci.yml` file:\n\n```yaml\ndeploy:\n  script: aws s3 cp ./ s3://yourbucket/ --recursive --exclude \"*\" --include \"*.html\"\n\n```\n\nNo luck:\n![Failed command](https://about.gitlab.com/images/blogimages/ci-deployment-and-environments/fail1.png){: .shadow}\n\nIt is our _job_ to ensure that there is an `aws` executable.\nTo install `awscli` we need `pip`, which is a tool for Python packages installation.\nLet's specify Docker image with preinstalled Python, which should contain `pip` as well:\n\n```yaml\ndeploy:\n  image: python:latest\n  script:\n  - pip install awscli\n  - aws s3 cp ./ s3://yourbucket/ --recursive --exclude \"*\" --include \"*.html\"\n\n```\n\n![Automated deployment](https://about.gitlab.com/images/blogimages/ci-deployment-and-environments/14.jpg){: .center}\nYou push your code to GitLab, and it is automatically deployed by CI.\nThe installation of `awscli` extends the job execution time, but that is not a big\ndeal for now. If you need to speed up the process, you can always [look for\na Docker image](https://hub.docker.com/explore/) with preinstalled `awscli`,\nor create an image by yourself.\n\n\nAlso, let’s not forget about these environment variables, which you've just grabbed\nfrom [AWS Console](https://console.aws.amazon.com/):\n\n```yaml\nvariables:\n  AWS_ACCESS_KEY_ID: \"AKIAIOSFODNN7EXAMPLE\"\n  AWS_SECRET_ACCESS_KEY: \"wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY\"\ndeploy:\n  image: python:latest\n  script:\n  - pip install awscli\n  - aws s3 cp ./ s3://yourbucket/ --recursive --exclude \"*\" --include \"*.html\"\n\n```\nIt should work, but keeping secret keys open, even in a private repository,\nis not a good idea. Let's see how to deal with this situation.\n\n### Keeping secret things secret\n\nGitLab has a special place for secret variables: **Settings > CI/CD > Variables**\n\n![Picture of Variables page](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674076/Blog/Content%20Images/add-variable-updated.png)\n\nWhatever you put there will be turned into **environment variables**.\nChecking the \"Mask variable\" checkbox will obfuscate the variable in job logs. Also, checking the \"Protect variable\" checkbox will export the variable to only pipelines running on protected branches and tags. Users with Owner or Maintainer permissions to a project will have access to this section.\n\nWe could remove `variables` section from our CI configuration. However, let’s use it for another purpose.\n\n### How to specify and use variables that are not secret\n\nWhen your configuration gets bigger, it is convenient to keep some of the\nparameters as variables at the beginning of your configuration. Especially if you\nuse them in more than one place. Although it is not the case in our situation yet,\nlet's set the S3 bucket name as a [**variable**](https://docs.gitlab.com/ee/ci/variables/) for the purpose of this demonstration:\n\n```yaml\nvariables:\n  S3_BUCKET_NAME: \"yourbucket\"\ndeploy:\n  image: python:latest\n  script:\n  - pip install awscli\n  - aws s3 cp ./ s3://$S3_BUCKET_NAME/ --recursive --exclude \"*\" --include \"*.html\"\n\n```\n\nSo far so good:\n\n![Successful build](https://about.gitlab.com/images/blogimages/ci-deployment-and-environments/build.png){: .shadow.medium.center}\n\nIn our hypothetical scenario, the audience of your website has grown, so you've hired a developer to help you.\nNow you have a team. Let's see how teamwork changes the GitLab CI workflow.\n\n## How to use GitLab CI with a team\n\nNow, that there are two users working in the same repository, it is no longer convenient\nto use the `main` branch for development. You decide to use separate branches\nfor both new features and new articles and merge them into `main` when they are ready.\n\nThe problem is that your current CI config doesn’t care about branches at all.\nWhenever you push anything to GitLab, it will be deployed to S3.\n\nPreventing this problem is straightforward. Just add `only: main` to your `deploy` job.\n\n![Automated deployment of main branch](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674076/Blog/Content%20Images/15-updated.png){: .center}\nYou don't want to deploy every branch to the production website but it would also be nice to preview your changes from feature-branches somehow.\n\n\n### How to set up a separate place for testing code\n\nThe person you recently hired, let's call him Patrick, reminds you that there is a featured called\n[GitLab Pages](https://docs.gitlab.com/ee/user/project/pages/). It looks like a perfect candidate for\na place to preview your work in progress.\n\nTo [host websites on GitLab Pages](/blog/gitlab-pages-setup/) your CI configuration file should satisfy three simple rules:\n\n- The _job_ should be named `pages`\n- There should be an `artifacts` section with folder `public` in it\n- Everything you want to host should be in this `public` folder\n\nThe contents of the public folder will be hosted at `http://\u003Cusername>.gitlab.io/\u003Cprojectname>/`\n\n\nAfter applying the [example config for plain-html websites](https://gitlab.com/pages/plain-html/blob/master/.gitlab-ci.yml),\nthe full CI configuration looks like this:\n\n```yaml\nvariables:\n  S3_BUCKET_NAME: \"yourbucket\"\n\ndeploy:\n  image: python:latest\n  script:\n  - pip install awscli\n  - aws s3 cp ./ s3://$S3_BUCKET_NAME/ --recursive --exclude \"*\" --include \"*.html\"\n  only:\n  - main\n\npages:\n  image: alpine:latest\n  script:\n  - mkdir -p ./public\n  - cp ./*.html ./public/\n  artifacts:\n    paths:\n    - public\n  except:\n  - main\n\n```\n\nWe specified two jobs. One job deploys the website for your customers to S3 (`deploy`).\nThe other one (`pages`) deploys the website to GitLab Pages.\nWe can name them \"Production environment\" and \"Staging environment\", respectively.\n\n![Deployment to two places](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674076/Blog/Content%20Images/16-updated.png){: .center}\nAll branches, except main, will be deployed to GitLab Pages.\n\n\n## Introducing environments\n\nGitLab offers\n [support for environments](https://docs.gitlab.com/ee/ci/environments/) (including dynamic environments and static environments),\n and all you need to do it to specify the corresponding environment for each deployment *job*:\n\n```yaml\nvariables:\n  S3_BUCKET_NAME: \"yourbucket\"\n\ndeploy to production:\n  environment: production\n  image: python:latest\n  script:\n  - pip install awscli\n  - aws s3 cp ./ s3://$S3_BUCKET_NAME/ --recursive --exclude \"*\" --include \"*.html\"\n  only:\n  - main\n\npages:\n  image: alpine:latest\n  environment: staging\n  script:\n  - mkdir -p ./public\n  - cp ./*.html ./public/\n  artifacts:\n    paths:\n    - public\n  except:\n  - main\n\n```\n\nGitLab keeps track of your deployments, so you always know what is currently being deployed on your servers:\n\n![List of environments](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674076/Blog/Content%20Images/envs-updated.png){: .shadow.center}\n\nGitLab provides full history of your deployments for each of your current environments:\n\n![List of deployments to staging environment](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674077/Blog/Content%20Images/staging-env-detail-updated.png){: .shadow.center}\n\n![Environments](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674077/Blog/Content%20Images/17-updated.png){: .center}\n\nNow, with everything automated and set up, we’re ready for the new challenges that are just around the corner.\n\n## How to troubleshoot deployments\n\nIt has just happened again.\nYou've pushed your feature-branch to preview it on staging and a minute later Patrick pushed\nhis branch, so the staging environment was rewritten with his work. Aargh!! It was the third time today!\n\nIdea! \u003Ci class=\"far fa-lightbulb\" style=\"color:#FFD900; font-size:.85em\" aria-hidden=\"true\">\u003C/i> Let's use Slack to notify us of deployments, so that people will not push their stuff if another one has been just deployed!\n\n> Learn how to [integrate GitLab with Slack](https://docs.gitlab.com/ee/user/project/integrations/gitlab_slack_application.html).\n\n## Teamwork at scale\n\nAs the time passed, your website became really popular, and your team has grown from two people to eight people.\nPeople develop in parallel, so the situation when people wait for each other to\npreview something on Staging has become pretty common. \"Deploy every branch to staging\" stopped working.\n\n![Queue of branches for review on Staging](https://about.gitlab.com/images/blogimages/ci-deployment-and-environments/queue.jpg){: .center}\n\nIt's time to modify the process one more time. You and your team agreed that if\nsomeone wants to see their changes on the staging\nserver, they should first merge the changes to the \"staging\" branch.\n\nThe change of `.gitlab-ci.yml` is minimal:\n\n```yaml\nexcept:\n- main\n```\n\nis now changed to\n\n```yaml\nonly:\n- staging\n```\n\n![Staging branch](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674077/Blog/Content%20Images/18-updated.png){: .center}\nPeople have to merge their feature branches before preview on the staging server.\n\n\nOf course, it requires additional time and effort for merging, but everybody agreed that it is better than waiting.\n\n### How to handle emergencies\n\nYou can't control everything, so sometimes things go wrong. Someone merged branches incorrectly and\npushed the result straight to production exactly when your site was on top of HackerNews.\nThousands of people saw your completely broken layout instead of your shiny main page.\n\nLuckily, someone found the **Rollback** button, so the\nwebsite was fixed a minute after the problem was discovered.\n\n![List of environments](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674077/Blog/Content%20Images/prod-env-rollback-arrow-updated.png){: .shadow.center}\nRollback relaunches the previous job with the previous commit\n\n\nAnyway, you felt that you needed to react to the problem and decided to turn off\nauto-deployment to Production and switch to manual deployment.\nTo do that, you needed to add `when: manual` to your _job_.\n\nAs you expected, there will be no automatic deployment to Production after that.\nTo deploy manually go to **CI/CD > Pipelines**, and click the button:\n\n![Skipped job is available for manual launch](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674076/Blog/Content%20Images/manual-pipeline-arrow-updated.png){: .shadow.center}\n\nFast forward in time. Finally, your company has turned into a corporation. Now, you have hundreds of people working on the website,\nso all the previous compromises no longer work.\n\n### Time to start using Review Apps\n\nThe next logical step is to boot up a temporary instance of the application per feature branch for review.\n\nIn our case, we set up another bucket on S3 for that. The only difference is that\nwe copy the contents of our website to a \"folder\" with the name of the\nthe development branch, so that the URL looks like this:\n\n`http://\u003CREVIEW_S3_BUCKET_NAME>.s3-website-us-east-1.amazonaws.com/\u003Cbranchname>/`\n\nHere's the replacement for the `pages` _job_ we used before:\n\n```yaml\nreview apps:\n  variables:\n    S3_BUCKET_NAME: \"reviewbucket\"\n  image: python:latest\n  environment: review\n  script:\n  - pip install awscli\n  - mkdir -p ./$CI_BUILD_REF_NAME\n  - cp ./*.html ./$CI_BUILD_REF_NAME/\n  - aws s3 cp ./ s3://$S3_BUCKET_NAME/ --recursive --exclude \"*\" --include \"*.html\"\n\n```\n\nThe interesting thing is where we got this `$CI_BUILD_REF_NAME` variable from.\nGitLab predefines [many environment variables](https://docs.gitlab.com/ee/ci/variables/predefined_variables.html) so that you can use them in your jobs.\n\nNote that we defined the `S3_BUCKET_NAME` variable inside the *job*. You can do this to rewrite top-level definitions.\n\n\nVisual representation of this configuration:\n![Review apps]![How to use GitLab CI - update - 19 - updated](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674077/Blog/Content%20Images/19-updated.png){: .illustration}\n\nThe details of the Review Apps implementation varies widely, depending upon your real technology\nstack and on your deployment process, which is outside the scope of this blog post.\n\nIt will not be that straightforward, as it is with our static HTML website.\nFor example, you had to make these instances temporary, and booting up these instances\nwith all required software and services automatically on the fly is not a trivial task.\nHowever, it is doable, especially if you use Docker containers, or at least Chef or Ansible.\n\nWe'll cover deployment with Docker in a future blog post.\nI feel a bit guilty for simplifying the deployment process to a simple HTML files copying, and not\nadding some hardcore scenarios. If you need some right now, I recommend you read the article [\"Building an Elixir Release into a Docker image using GitLab CI.\"](/blog/building-an-elixir-release-into-docker-image-using-gitlab-ci-part-1/)\n\nFor now, let's talk about one final thing.\n\n### Deploying to different platforms\n\nIn real life, we are not limited to S3 and GitLab Pages. We host, and therefore,\ndeploy our apps and packages to various services.\n\nMoreover, at some point, you could decide to move to a new platform and will need to rewrite all your deployment scripts.\nYou can use a gem called `dpl` to minimize the damage.\n\nIn the examples above we used `awscli` as a tool to deliver code to an example\nservice (Amazon S3).\nHowever, no matter what tool and what destination system you use, the principle is the same:\nYou run a command with some parameters and somehow pass a secret key for authentication purposes.\n\nThe `dpl` deployment tool utilizes this principle and provides a\nunified interface for [this list of providers](https://github.com/travis-ci/dpl#supported-providers).\n\nHere's how a production deployment _job_ would look if we use `dpl`:\n\n```yaml\nvariables:\n  S3_BUCKET_NAME: \"yourbucket\"\n\ndeploy to production:\n  environment: production\n  image: ruby:latest\n  script:\n  - gem install dpl\n  - dpl --provider=s3 --bucket=$S3_BUCKET_NAME\n  only:\n  - main\n\n```\n\nIf you deploy to different systems or change destination platform frequently, consider\nusing `dpl` to make your deployment scripts look uniform.\n\n## Five key takeaways\n\n1. Deployment is just a command (or a set of commands) that is regularly executed. Therefore it can run inside GitLab CI.\n2. Most times you'll need to provide some secret key(s) to the command you execute. Store these secret keys in **Settings > CI/CD > Variables**.\n3. With GitLab CI, you can flexibly specify which branches to deploy to.\n4. If you deploy to multiple environments, GitLab will conserve the history of deployments,\nwhich allows you to rollback to any previous version.\n5. 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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.",[726],"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",[264,616,730],"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":733,"featured":13,"template":14},"how-iit-bombay-students-code-future-with-gitlab",{"content":735,"config":744},{"title":736,"description":737,"authors":738,"heroImage":739,"date":740,"category":10,"tags":741,"body":743},"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.",[726],"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",[616,264,742],"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":745,"featured":31,"template":14},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":747,"config":759},{"category":10,"tags":748,"body":750,"date":751,"updatedDate":752,"heroImage":753,"authors":754,"title":757,"description":758},[27,749,111],"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",[755,756],"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":760},"migration-from-azure-devops-to-gitlab",{"promotions":762},[763,777,788],{"id":764,"categories":765,"header":767,"text":768,"button":769,"image":774},"ai-modernization",[766],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":770,"config":771},"Get your AI maturity score",{"href":772,"dataGaName":773,"dataGaLocation":246},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":775},{"src":776},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":778,"categories":779,"header":780,"text":768,"button":781,"image":785},"devops-modernization",[742,562],"Are you just managing tools or shipping innovation?",{"text":782,"config":783},"Get your DevOps maturity score",{"href":784,"dataGaName":773,"dataGaLocation":246},"/assessments/devops-modernization-assessment/",{"config":786},{"src":787},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":789,"categories":790,"header":792,"text":768,"button":793,"image":797},"security-modernization",[791],"security","Are you trading speed for security?",{"text":794,"config":795},"Get your security maturity score",{"href":796,"dataGaName":773,"dataGaLocation":246},"/assessments/security-modernization-assessment/",{"config":798},{"src":799},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":801,"blurb":802,"button":803,"secondaryButton":808},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":804,"config":805},"Get your free trial",{"href":806,"dataGaName":53,"dataGaLocation":807},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":498,"config":809},{"href":57,"dataGaName":58,"dataGaLocation":807},1772652067533]