[{"data":1,"prerenderedAt":791},["ShallowReactive",2],{"/en-us/blog/how-to-deploy-react-to-amazon-s3":3,"navigation-en-us":38,"banner-en-us":437,"footer-en-us":447,"blog-post-authors-en-us-Jeremy Wagner":686,"blog-related-posts-en-us-how-to-deploy-react-to-amazon-s3":700,"assessment-promotions-en-us":742,"next-steps-en-us":781},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":25,"isFeatured":12,"meta":26,"navigation":27,"path":28,"publishedDate":20,"seo":29,"stem":33,"tagSlugs":34,"__hash__":37},"blogPosts/en-us/blog/how-to-deploy-react-to-amazon-s3.yml","How To Deploy React To Amazon S3",[7],"jeremy-wagner",null,"engineering",{"slug":11,"featured":12,"template":13},"how-to-deploy-react-to-amazon-s3",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"How to deploy a React application to Amazon S3 using GitLab CI/CD","Follow this guide to use OpenID Connect to connect to AWS and deploy a React application to Amazon S3.",[18],"Jeremy Wagner","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749663291/Blog/Hero%20Images/cover1.jpg","2023-03-01","Amazon S3 has a Static Website Hosting feature which allows you to host a static website directly from an S3 bucket. When you\nhost your website on S3, your website content is stored in the S3 bucket and served directly to your users, without the need\nfor additional resources. Combine this with Amazon CloudFront and you will have a cost-effective and scalable solution for\nhosting static websites – making it a popular choice for single-page applications.\n\nIn this post, I will walk you through setting up your Amazon S3 bucket, setting up OpenID Connect ([OIDC](https://openid.net/connect/)) in AWS, and deploying your application\nto your Amazon S3 bucket using a GitLab [CI/CD](/topics/ci-cd/) pipeline.\n\nBy the end of this post, you will have a [CI/CD pipeline](/blog/how-to-keep-up-with-ci-cd-best-practices/) built in GitLab that automatically deploys to your Amazon S3 bucket. Let's dive in.\n\n## Prerequisites\n\nFor this guide you will need the following:\n\n- [Node.js](https://nodejs.org/en/) >= 14.0.0 and npm >= 5.6 installed on your system\n- [Git](https://git-scm.com/) installed on your system\n- A [GitLab](https://gitlab.com/-/trial_registrations/new) account\n- An [AWS](https://aws.amazon.com/free/) account\n\n[A previous tutorial](/blog/how-to-automate-testing-for-a-react-application-with-gitlab/) demonstrated how to create a new React\napplication, run unit tests as part of the CI process in GitLab, and output the test results and code coverage into the pipeline. This post continues where that project left off, so to follow along you can fork [this project](https://gitlab.com/guided-explorations/engineering-tutorials/react-unit-testing) or complete the guide in the linked post.\n\n## Configure your Amazon S3 bucket\n\nYou'll need to configure your Amazon S3 bucket so let's do that first.\n\n### Create your bucket\n\nAfter you log in to your AWS account, search for S3 using the search bar and select the S3 service. This will open the S3 service home page.\n\nRight away, you should see the option to create a bucket. The bucket is where you are going to store your built React application. Click the **Create bucket** button to continue.\n\n![Create S3 bucket](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/create_bucket.png){: .shadow}\n\nGive your bucket a name, select your region, leave the rest of the settings as default (we’ll come back to these later), and continue by\nclicking the **Create bucket** button. When naming your bucket, it’s important to remember that your bucket name must be unique and follow the\nbucket naming rules. I named mine `jw-gl-react`.\n\nAfter creating your bucket, you should be taken to a list of your buckets as shown below.\n\n![S3 bucket list](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/bucket_list.png){: .shadow}\n\n### Configure static website hosting\n\nThe next step is to configure static website hosting. Open your S3 bucket by clicking into the bucket name. Select the **Properties** tab and\nscroll to the bottom to find the static website hosting option.\n\n![static hosting button](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/static_hosting_1.png){: .shadow}\n\nClick **Edit** and then enable static website hosting. For the **Index** and **Error** document, enter `index.html` and then click **Save changes**.\n\n![edit static hosting](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/static_hosting_2.png){: .shadow}\n\n### Set up permissions\n\nNow that you have enabled static website hosting, you need to update your permissions so the public can visit your website. Return to your bucket and select the **Permissions** tab.\n\nUnder **Block public access (bucket settings)**, click **Edit** and uncheck **Block all public access** and continue to **Save changes**.\n\n![block public access](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/block_access_1.png){: .shadow}\n\nYour page should now look this this:\n\n![saved blocked public access](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/block_access_2.png){: .shadow}\n\nNow, you need to edit the Bucket Policy. Click the **Edit** button in the **Bucket Policy** section. Paste the following code into your new policy:\n\n```javascript\n{\n \"Version\": \"2012-10-17\",\n \"Statement\": [\n {\n \"Sid\": \"PublicReadGetObject\",\n \"Effect\": \"Allow\",\n \"Principal\": \"*\",\n \"Action\": \"s3:GetObject\",\n \"Resource\": \"arn:aws:s3:::jw-gl-react/*\"\n }\n ]\n}\n```\n\nReplace `jw-gl-react` on the resource property with the name of your bucket and **Save changes**.\n\nYour bucket should now look like this:\n\n![publicly accessible bucket](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/block_access_3.png){: .shadow}\n\n## Manually upload your React application\n\nNow, let’s build your React application and manually publish it to your S3 bucket.\n\nTo build the application, make sure your project is cloned to your local machine and run the following command in your terminal inside of your\nrepository directory:\n\n```shell\nnpm run build\n```\n\nThis will create a build folder inside of your repository directory.\n\nInside of your bucket, click the **Upload** button.\n\n![manual bucket upload](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/upload_1.png){: .shadow}\n\nDrag the contents of your newly created build folder (not the folder itself) into the upload area. This will\nupload the contents of your application into your S3 bucket. Make sure to click **Upload** at the bottom of the page to start the upload.\n\nNow return to your bucket **Properties** tab and scroll to the bottom to find the URL of your static website.\n\n![static website url](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/upload_2.png){: .shadow}\n\nClick the link and you should see your built React application open in your browser.\n\n![deployed app](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/manual_deploy.png){: .shadow}\n\n## Set up OpenID Connect in AWS\n\nTo deploy to your S3 Bucket from GitLab, we’re going to use a GitLab CI/CD job to receive temporary credentials\nfrom AWS without needing to store secrets. To do this, we’re going to configure OIDC for ID federation\nbetween GitLab and AWS. We’ll be following the [related GitLab documentation](https://docs.gitlab.com/ee/ci/cloud_services/aws/).\n\n### Add the identity provider\n\nThe first step is going to be adding GitLab as an identity and access management (IAM) OIDC provider in AWS. AWS has instructions located [here](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_providers_create_oidc.html),\nbut I will walk through it step by step.\n\nOpen the IAM console inside of AWS.\n\n![iam search](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/iam_1.png){: .shadow}\n\nOn the left navigation pane, under **Access management** choose **Identity providers** and then choose **Add provider**.\nFor provider type, select **OpenID Connect**.\n\nFor **Provider URL**, enter the address of your GitLab instance, such as `https://gitlab.com` or `https://gitlab.example.com`.\n\nFor **Audience**, enter something that is generic and specific to your application. In my case, I'm going to\nenter `react_s3_gl`. To prevent confused deputy attacks, it's best to make this something that is not easy to guess. Take a note of\nthis value, you will use it to set the `ID_TOKEN` in your `.gitlab-ci.yml` file.\n\nAfter entering the **Provider URL**, click **Get thumbprint** to verify the server certificate of your IdP. After this, go\nahead and choose **Add provider** to finish up.\n\n### Create the permissions policy\n\nAfter you create the identity provider, you need to create a permissions policy.\n\nFrom the IAM dashboard, under **Access management** select **Policies** and then **Create policy**.\nSelect the JSON tab and paste the following policy replacing `jw-gl-react` on the resource line with your bucket name.\n\n```javascript\n{\n \"Version\": \"2012-10-17\",\n \"Statement\": [\n {\n \"Effect\": \"Allow\",\n \"Action\": [\"s3:ListBucket\"],\n \"Resource\": [\"arn:aws:s3:::jw-gl-react\"]\n },\n {\n \"Effect\": \"Allow\",\n \"Action\": [\n \"s3:PutObject\",\n \"s3:GetObject\",\n \"s3:DeleteObject\"\n ],\n \"Resource\": [\"arn:aws:s3:::jw-gl-react/*\"]\n }\n ]\n}\n```\n\nSelect the **Next: Tags** button, add any tags you want, and then select the **Next: Review** button.\nEnter a name for your policy and finish up by creating the policy.\n\n### Configure the role\n\nNow it’s time to add the role. From the IAM dashboard, under **Access management** select **Roles**\nand then select **Create role**. Select **Web identity**.\n\nIn the **Web identity** section, select the identity provider you created earlier. For the\n**Audience**, select the audience you created earlier. Select the **Next** button to continue.\n\nIf you wanted to limit authorization to a specific group, project, branch, or tag, you could create a **Custom trust policy**\ninstead of a **Web identity**. Since I will be deleting these resources after the tutorial, I'm going to keep it simple. For a\nfull list of supported filterting types, see the [GitLab documentation](https://docs.gitlab.com/ee/ci/cloud_services/index.html#configure-a-conditional-role-with-oidc-claims).\n\n![web identity](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/iam_2.png){: .shadow}\n\nDuring the **Add permissions** step, select the policy you created and select **Next** to continue. Give your role a name and click **Create role**.\n\nOpen the Role you just created. In the summary section, find the Amazon Resource Name (ARN) and save it somewhere secure. You will use this in your pipeline.\n\n![role](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/iam_3.png){: .shadow}\n\n## Deploy to your Amazon S3 bucket using a GitLab CI/CD pipeline\n\nInside of your project, create two [CI/CD variables](https://docs.gitlab.com/ee/ci/variables/#define-a-cicd-variable-in-the-ui). The first variable should be named `ROLE_ARN`. For the value, paste the ARN of the\nrole you just created. The second variable should be named `S3_BUCKET`. For the value, paste the name of the S3 bucket you created\nearlier in this post.\n\nI have chosen to mask my variables for an extra layer of security.\n\n### Retrieve your temporary credentials\n\nInside of your `.gitlab-ci.yml` file, paste the following code:\n\n```text\n.assume_role: &assume_role\n - >\n STS=($(aws sts assume-role-with-web-identity\n --role-arn ${ROLE_ARN}\n --role-session-name \"GitLabRunner-${CI_PROJECT_ID}-${CI_PIPELINE_ID}\"\n --web-identity-token $ID_TOKEN\n --duration-seconds 3600\n --query 'Credentials.[AccessKeyId,SecretAccessKey,SessionToken]'\n --output text))\n - export AWS_ACCESS_KEY_ID=\"${STS[0]}\"\n - export AWS_SECRET_ACCESS_KEY=\"${STS[1]}\"\n - export AWS_SESSION_TOKEN=\"${STS[2]}\"\n\n```\n\nThis is going to use the the AWS Security Token Service to generate temporary (_3,600 seconds_) credentials utilizing the OIDC role you created earlier.\n\n### Create the deploy job\n\nNow, let's add a build and deploy job to build your application and deploy it to your S3 bucket.\n\nFirst, update the stages in your `.gitlab-ci.yml` file to include a `build` and `deploy` stage as shown below:\n\n```yaml\nstages:\n - build\n - test\n - deploy\n\n```\n\nNext, let's add a job to build your application. Paste the following code in your `.gitlab-ci.yml` file:\n\n```yaml\nbuild artifact:\n stage: build\n image: node:latest\n before_script:\n - npm install\n script:\n - npm run build\n artifacts:\n paths:\n - build/\n when: always\n rules:\n - if: '$CI_COMMIT_REF_NAME == \"main\"'\n when: always\n\n```\n\nThis is going to run `npm run build` if the change occurs on the `main` branch and upload the build directory as an\nartifact to be used during the next step.\n\nNext, let's add a job to actually deploy to your S3 bucket. Paste the following code in your `.gitlab-ci.yml` file:\n\n```yaml\ndeploy s3:\n stage: deploy\n image:\n name: amazon/aws-cli:latest\n entrypoint:\n - '/usr/bin/env'\n id_tokens:\n ID_TOKEN:\n aud: react_s3_gl\n script:\n - *assume_role\n - aws s3 sync build/ s3://$S3_BUCKET\n rules:\n - if: '$CI_COMMIT_REF_NAME == \"main\"'\n when: always\n\n```\n\nThis uses [YAML anchors](https://docs.gitlab.com/ee/ci/yaml/yaml_optimization.html#yaml-anchors-for-scripts) to run the `assume_role` script,\nand then uses the `aws cli` to upload your build artifact to the bucket you defined as a variable. This job also only runs if the change occurs\non the `main` branch.\n\nMake sure the `aud` value matches the value you entered for your audience when you setup the identity provider. In my case, I entered `react-s3_gl`.\n\nYour complete `.gitlab-ci.yml` file should look like this:\n\n```text\nstages:\n - build\n - test\n - deploy\n\n.assume_role: &assume_role\n - >\n STS=($(aws sts assume-role-with-web-identity\n --role-arn ${ROLE_ARN}\n --role-session-name \"GitLabRunner-${CI_PROJECT_ID}-${CI_PIPELINE_ID}\"\n --web-identity-token $ID_TOKEN\n --duration-seconds 3600\n --query 'Credentials.[AccessKeyId,SecretAccessKey,SessionToken]'\n --output text))\n - export AWS_ACCESS_KEY_ID=\"${STS[0]}\"\n - export AWS_SECRET_ACCESS_KEY=\"${STS[1]}\"\n - export AWS_SESSION_TOKEN=\"${STS[2]}\"\n\nunit test:\n image: node:latest\n stage: test\n before_script:\n - npm install\n script:\n - npm run test:ci\n coverage: /All files[^|]*\\|[^|]*\\s+([\\d\\.]+)/\n artifacts:\n paths:\n - coverage/\n when: always\n reports:\n junit:\n - junit.xml\n\nbuild artifact:\n stage: build\n image: node:latest\n before_script:\n - npm install\n script:\n - npm run build\n artifacts:\n paths:\n - build/\n when: always\n rules:\n - if: '$CI_COMMIT_REF_NAME == \"main\"'\n when: always\n\n\ndeploy s3:\n stage: deploy\n image:\n name: amazon/aws-cli:latest\n entrypoint:\n - '/usr/bin/env'\n id_tokens:\n ID_TOKEN:\n aud: react_s3_gl\n script:\n - *assume_role\n - aws s3 sync build/ s3://$S3_BUCKET\n rules:\n - if: '$CI_COMMIT_REF_NAME == \"main\"'\n when: always\n\n```\n\n### Make a change and test your pipeline\n\nTo test your pipeline, inside of `App.js`, change this line `Edit \u003Ccode>src/App.js\u003C/code> and save to reload.` to\n`This was deployed from GitLab!` and commit your changes to the `main` branch. The pipeline should kick off and when\nit finishes successfully you should see your updated application at the URL of your static website.\n\n![updated app](https://about.gitlab.com/images/blogimages/2023-02-10-how-to-deploy-react-to-amazon-s3/auto_deploy.png){: .shadow}\n\nYou now have a CI/CD pipeline built in GitLab that receives temporary credentials from AWS using OIDC and\nautomatically deploys to your Amazon S3 bucket. To take it a step further, you can [secure your application](https://docs.gitlab.com/ee/user/application_security/secure_your_application.html)\nwith GitLab's built-in security tools.\n\nAll code for this project can be found [here](https://gitlab.com/guided-explorations/engineering-tutorials/react-s3).\n\nCover image by [Lucas van Oor](https://unsplash.com/@switch_dtp_fotografie?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText) on [Unsplash](https://unsplash.com/s/photos/bucket?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText)\n\n\n## Related posts and documentation\n- [How to automate testing for a React application with GitLab](/blog/how-to-automate-testing-for-a-react-application-with-gitlab/)\n- [How to deploy AWS with GitLab](/blog/deploy-aws/)\n- [Deploy to AWS from GitLab CI/CD](https://docs.gitlab.com/ee/ci/cloud_deployment/)\n- [Configure OpenID Connect in AWS to retrieve temporary credentials](https://docs.gitlab.com/ee/ci/cloud_services/aws/)\n- [Secure GitLab CI/CD workflows using OIDC JWT on a DevSecOps platform](https://about.gitlab.com/blog/oidc/)\n",[23,24],"DevOps","CI/CD","yml",{},true,"/en-us/blog/how-to-deploy-react-to-amazon-s3",{"title":15,"description":16,"ogTitle":15,"ogDescription":16,"noIndex":12,"ogImage":19,"ogUrl":30,"ogSiteName":31,"ogType":32,"canonicalUrls":30},"https://about.gitlab.com/blog/how-to-deploy-react-to-amazon-s3","https://about.gitlab.com","article","en-us/blog/how-to-deploy-react-to-amazon-s3",[35,36],"devops","cicd","Cj2t6yYPOdYhS2PIP2lLvssSsCZl9X6EG7Vzp0KwwE0",{"data":39},{"logo":40,"freeTrial":45,"sales":50,"login":55,"items":60,"search":367,"minimal":398,"duo":417,"pricingDeployment":427},{"config":41},{"href":42,"dataGaName":43,"dataGaLocation":44},"/","gitlab logo","header",{"text":46,"config":47},"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.",[706],"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",[259,608,710],"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":713,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":715,"config":724},{"title":716,"description":717,"authors":718,"heroImage":719,"date":720,"category":9,"tags":721,"body":723},"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.",[706],"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",[608,259,722],"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":725,"featured":27,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":727,"config":740},{"category":9,"tags":728,"body":731,"date":732,"updatedDate":733,"heroImage":734,"authors":735,"title":738,"description":739},[729,730,24],"tutorial","git","\nEnterprise teams are increasingly migrating from Azure DevOps to GitLab to gain strategic advantages and accelerate secure software delivery. \n\n\n- GitLab comes with integrated controls, policies, and [compliance frameworks](https://docs.gitlab.com/user/compliance/compliance_frameworks/) that allow organizations to implement software delivery standards at scale. This is especially important for regulated industries.\n\n- [Security testing](https://docs.gitlab.com/user/application_security/) is embedded in the pipeline and results show in the developer workflow, including static application security testing (SAST), source code analysis (SCA), dynamic application security testing (DAST), infrastructure-as-code scanning (IaC), container scanning, and API scanning.\n\n- [AI capabilities](https://about.gitlab.com/gitlab-duo-agent-platform/) across the full software delivery lifecycle include advanced agent orchestration and customizable flows to support how your organizational teams work.\n\n\nGitLab's open-source, open-core approach, flexible deployment options such as single-tenant dedicated and self-managed, and truly unified platform eliminate integration complexity and security gaps. \n\n\nFor teams facing mounting pressure to accelerate delivery while strengthening security posture and maintaining regulatory compliance, GitLab represents not just a migration but a platform evolution.\n\n\nMigrating from Azure DevOps to GitLab can seem like a daunting task, but with the right approach and tools, it can be a smooth and efficient process. This guide will walk you through the steps needed to successfully migrate your projects, repositories, and pipelines from Azure DevOps to GitLab.\n\n\n## Overview\n\nGitLab provides both [Congregate](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/) (maintained by [GitLab Professional Services](https://about.gitlab.com/professional-services/) organization) and [a built-in Git repository import](https://docs.gitlab.com/user/project/import/repo_by_url/) for migrating projects from Azure DevOps (ADO). These options support repository-by-repository or bulk migration and preserve git commit history, branches, and tags. With Congregate and professional services tools, we support additional assets such as wikis, work items, CI/CD variables, container images, packages, pipelines, and more (see this [feature matrix](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/-/blob/master/customer/ado-migration-features-matrix.md)). Use this guide to plan and execute your migration and complete post-migration follow-up tasks.\n\n\nEnterprises migrating from ADO to GitLab commonly follow a multi-phase approach:\n\n\n- Migrate repositories from ADO to GitLab using Congregate or GitLab's built-in repository migration.\n\n- Migrate pipelines from Azure Pipelines to GitLab CI/CD.\n\n- Migrate remaining assets such as boards, work items, and artifacts to GitLab Issues, Epics, and the Package and Container Registries.\n\n\nHigh-level migration phases:\n\n\n```mermaid\ngraph LR\n subgraph Prerequisites\n direction TB\n A[\"Set up identity provider (IdP) and\u003Cbr/>provision users\"]\n A --> B[\"Set up runners and\u003Cbr/>third-party integrations\"]\n B --> I[\"Users enablement and\u003Cbr/>change management\"]\n end\n \n subgraph MigrationPhase[\"Migration phase\"]\n direction TB\n C[\"Migrate source code\"]\n C --> D[\"Preserve contributions and\u003Cbr/> format history\"]\n D --> E[\"Migrate work items and\u003Cbr/>map to \u003Ca href=\"https://docs.gitlab.com/topics/plan_and_track/\">GitLab Plan \u003Cbr/>and track work\"]\n end\n \n subgraph PostMigration[\"Post-migration steps\"]\n direction TB\n F[\"Create or translate \u003Cbr/>ADO pipelines to GitLab CI\"]\n F --> G[\"Migrate other assets\u003Cbr/>packages and container images\"]\n G --> H[\"Introduce \u003Ca href=\"https://docs.gitlab.com/user/application_security/secure_your_application/\">security\u003C/a> and\u003Cbr/>SDLC improvements\"]\n end\n \n Prerequisites --> MigrationPhase\n MigrationPhase --> PostMigration\n\n style A fill:#FC6D26\n style B fill:#FC6D26\n style I fill:#FC6D26\n style C fill:#8C929D\n style D fill:#8C929D\n style E fill:#8C929D\n style F fill:#FFA500\n style G fill:#FFA500\n style H fill:#FFA500\n```\n\n\n## Planning your migration\n\n\n**To plan your migration, ask these questions:**\n\n\n- How soon do we need to complete the migration?\n\n- Do we understand what will be migrated?\n\n- Who will run the migration?\n\n- What organizational structure do we want in GitLab?\n\n- Are there any constraints, limitations, or pitfalls that need to be taken into account?\n\n\nDetermine your timeline, as it will largely dictate your migration approach. Identify champions or groups familiar with both ADO and GitLab platforms (such as early adopters) to help drive adoption and provide guidance.\n\n\n**Inventory what you need to migrate:**\n\n\n- The number of repositories, pull requests, and contributors\n\n- The number and complexity of work items and pipelines\n\n- Repository sizes and dependency relationships\n\n- Critical integrations and runner requirements (agent pools with specific capabilities)\n\n\nUse GitLab Professional Services's [Evaluate](https://gitlab.com/gitlab-org/professional-services-automation/tools/utilities/evaluate#beta-azure-devops) tool to produce a complete inventory of your entire Azure DevOps organization, including repositories, PR counts, contributor lists, number of pipelines, work items, CI/CD variables and more. If you're working with the GitLab Professional Services team, share this report with your engagement manager or technical architect to help plan the migration.\n\n\nMigration timing is primarily driven by pull request count, repository size, and amount of contributions (e.g. comments in PR, work items, etc). For example, 1,000 small repositories with few PRs and limited contributors can migrate much faster than a smaller set of repositories containing tens of thousands of PRs and thousands of contributors. Use your inventory data to estimate effort and plan test runs before proceeding with production migrations.\n\n\nCompare inventory against your desired timeline and decide whether to migrate all repositories at once or in batches. If teams cannot migrate simultaneously, batch and stagger migrations to align with team schedules. For example, in Professional Services engagements, we organize migrations into waves of 200-300 projects to manage complexity and respect API rate limits, both in [GitLab](https://docs.gitlab.com/security/rate_limits/) and [ADO](https://learn.microsoft.com/en-us/azure/devops/integrate/concepts/rate-limits?view=azure-devops).\n\n\nGitLab's built-in [repository importer](https://docs.gitlab.com/user/project/import/repo_by_url/) migrates Git repositories (commits, branches, and tags) one-by-one. Congregate is designed to preserve pull requests (known in GitLab as merge requests), comments, and related metadata where possible; the simple built-in repository import focuses only on the Git data (history, branches, and tags).\n\n\n**Items that typically require separate migration or manual recreation:**\n\n\n- Azure Pipelines - create equivalent GitLab CI/CD pipelines (consult with [CI/CD YAML](https://docs.gitlab.com/ci/yaml/) and/or with [CI/CD components](https://docs.gitlab.com/ci/components/)). Alternatively, consider using AI-based pipeline conversion available in Congregate.\n\n- Work items and boards - map to GitLab Issues, Epics, and Issue Boards.\n\n- Artifacts, container images (ACR) - migrate to GitLab Package Registry or Container Registry.\n\n- Service hooks and external integrations - recreate in GitLab.\n\n- [Permissions models](https://docs.gitlab.com/user/permissions/) differ between ADO and GitLab; review and plan permissions mapping rather than assuming exact preservation.\n\n\nReview what each tool (Congregate vs. built-in import) will migrate and choose the one that fits your needs. Make a list of any data or integrations that must be migrated or recreated manually.\n\n\n**Who will run the migration?**\n\n\nMigrations are typically run by a GitLab group owner or instance administrator, or by a designated migrator who has been granted the necessary permissions on the destination group/project. Congregate and the GitLab import APIs require valid authentication tokens for both Azure DevOps and GitLab.\n\n\n- Decide whether a group owner/admin will perform the migrations or whether you will grant a specific team/person delegated access.\n\n- Ensure the migrator has correctly configured personal access tokens (Azure DevOps and GitLab) with the scopes required by your chosen migration tool (for example, api/read_repository scopes and any tool-specific requirements). \n\n- Test tokens and permissions with a small pilot migration.\n\n**Note:** Congregate leverages file-based import functionality for ADO migrations and requires instance administrator permissions to run ([see our documentation](https://docs.gitlab.com/user/project/settings/import_export/#migrate-projects-by-uploading-an-export-file)). If you are migrating to GitLab.com, consider engaging Professional Services. For more information, see the [Professional Services Full Catalog](https://about.gitlab.com/professional-services/catalog/). Non-admin account cannot preserve contribution attribution!\n\n\n**What organizational structure do we want in GitLab?**\n\nWhile it's possible to map ADO structure directly to GitLab structure, it's recommended to rationalize and simplify the structure during migration. Consider how teams will work in GitLab and design the structure to facilitate collaboration and access management. Here is a way to think about mapping ADO structure to GitLab structure:\n\n\n```mermaid\ngraph TD\n subgraph GitLab\n direction TB\n A[\"Top-level Group\"]\n B[\"Subgroup (optional)\"]\n C[\"Projects\"]\n A --> B\n A --> C\n B --> C\n end\n\n subgraph AzureDevOps[\"Azure DevOps\"]\n direction TB\n F[\"Organizations\"]\n G[\"Projects\"]\n H[\"Repositories\"]\n F --> G\n G --> H\n end\n\n style A fill:#FC6D26\n style B fill:#FC6D26\n style C fill:#FC6D26\n style F fill:#8C929D\n style G fill:#8C929D\n style H fill:#8C929D\n```\n\nRecommended approach:\n\n\n- Map each ADO organization to a GitLab group (or a small set of groups), not to many small groups. Avoid creating a GitLab group for every ADO team project. Use migration as an opportunity to rationalize your GitLab structure.\n\n- Use subgroups and project-level permissions to group related repositories.\n\n- Manage access to sets of projects by using GitLab groups and group membership (groups and subgroups) rather than one group per team project.\n\n- Review GitLab [permissions](https://docs.gitlab.com/ee/user/permissions.html) and consider [SAML Group Links](https://docs.gitlab.com/user/group/saml_sso/group_sync/) to implement an enterprise RBAC model for your GitLab instance (or a GitLab.com namespace).\n\n\n**ADO Boards and work items: State of migration**\n\n\nIt's important to understand how work items migrate from ADO into GitLab Plan (issues, epics, and boards).\n\n\n- ADO Boards and work items map to GitLab Issues, Epics, and Issue Boards. Plan how your workflows and board configurations will translate.\n\n- ADO Epics and Features become GitLab Epics.\n\n- Other work item types (e.g., user stories, tasks, bugs) become project-scoped issues.\n\n- Most standard fields are preserved; selected custom fields can be migrated when supported.\n\n- Parent-child relationships are retained so Epics reference all related issues.\n\n- Links to pull requests are converted to merge request links to maintain development traceability.\n\n\nExample: Migration of an individual work item to a GitLab Issue, including field accuracy and relationships:\n\n\n![Example: Migration of an individual work item to a GitLab Issue](https://res.cloudinary.com/about-gitlab-com/image/upload/v1764769188/ztesjnxxfbwmfmtckyga.png)\n\n\nBatching guidance:\n\n\n- If you need to run migrations in batches, use your new group/subgroup structure to define batches (for example, by ADO organization or by product area).\n\n- Use inventory reports to drive batch selection and test each batch with a pilot migration before scaling.\n\n\n**Pipelines migration**\n\n\nCongregate [recently introduced](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/-/merge_requests/1298) AI-powered conversion for multi-stage YAML pipelines from Azure DevOps to GitLab CI/CD. This automated conversion works best for simple, single-file pipelines and is designed to provide a working starting point rather than a production-ready `.gitlab-ci.yml` file. The tool generates a functionally equivalent GitLab pipeline that you can then refine and optimize for your specific needs.\n\n\n- Converts Azure Pipelines YAML to `.gitlab-ci.yml` format automatically.\n\n- Best suited for straightforward, single-file pipeline configurations.\n\n- Provides a boilerplate to accelerate migration, not a final production artifact.\n\n- Requires review and adjustment for complex scenarios, custom tasks, or enterprise requirements.\n\n- Does not support Azure DevOps classic release pipelines — [convert these to multi-stage YAML](https://learn.microsoft.com/en-us/azure/devops/pipelines/release/from-classic-pipelines?view=azure-devops) first.\n\n\nRepository owners should review the [GitLab CI/CD documentation](https://docs.gitlab.com/ci/) to further optimize and enhance their pipelines after the initial conversion.\n\n\nExample of converted pipelines:\n\n\n```yml \n\n# azure-pipelines.yml\n\ntrigger:\n - main\n\nvariables:\n imageName: myapp\n\nstages:\n - stage: Build\n jobs:\n - job: Build\n pool:\n vmImage: 'ubuntu-latest'\n steps:\n - checkout: self\n\n - task: Docker@2\n displayName: Build Docker image\n inputs:\n command: build\n repository: $(imageName)\n Dockerfile: '**/Dockerfile'\n tags: |\n $(Build.BuildId)\n\n - stage: Test\n jobs:\n - job: Test\n pool:\n vmImage: 'ubuntu-latest'\n steps:\n - checkout: self\n\n # Example: run tests inside the container\n - script: |\n docker run --rm $(imageName):$(Build.BuildId) npm test\n displayName: Run tests\n\n - stage: Push\n jobs:\n - job: Push\n pool:\n vmImage: 'ubuntu-latest'\n steps:\n - checkout: self\n\n - task: Docker@2\n displayName: Login to ACR\n inputs:\n command: login\n containerRegistry: '\u003Cyour-acr-service-connection>'\n\n - task: Docker@2\n displayName: Push image to ACR\n inputs:\n command: push\n repository: $(imageName)\n tags: |\n $(Build.BuildId)\n\n```\n\n```yaml\n\n# .gitlab-ci.yml\n\nvariables:\n imageName: myapp\n\nstages:\n - build\n - test\n - push\n\nbuild:\n stage: build\n image: docker:latest\n services:\n - docker:dind\n script:\n - docker build -t $imageName:$CI_PIPELINE_ID -f $(find . -name Dockerfile) .\n only:\n - main\n\ntest:\n stage: test\n image: docker:latest\n services:\n - docker:dind\n script:\n - docker run --rm $imageName:$CI_PIPELINE_ID npm test\n only:\n - main\n\npush:\n stage: push\n image: docker:latest\n services:\n - docker:dind\n before_script:\n - docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY\n script:\n - docker tag $imageName:$CI_PIPELINE_ID $CI_REGISTRY/$CI_PROJECT_PATH/$imageName:$CI_PIPELINE_ID\n - docker push $CI_REGISTRY/$CI_PROJECT_PATH/$imageName:$CI_PIPELINE_ID\n only:\n - main\n\n```\n\n**Final checklist:**\n\n\n- Decide timeline and batch strategy.\n\n- Produce a full inventory of repositories, PRs, and contributors.\n\n- Choose Congregate or the built-in import based on scope (PRs and metadata vs. Git data only).\n\n- Decide who will run migrations and ensure tokens/permissions are configured.\n\n- Identify assets that must be migrated separately (pipelines, work items, artifacts, and hooks) and plan those efforts.\n\n- Run pilot migrations, validate results, then scale according to your plan.\n\n\n## Running your migrations\n\n\nAfter planning, execute migrations in stages, starting with trial runs. Trial migrations help surface org-specific issues early and let you measure duration, validate outcomes, and fine-tune your approach before production.\n\n\nWhat trial migrations validate:\n\n\n- Whether a given repository and related assets migrate successfully (history, branches, tags; plus MRs/comments if using Congregate)\n\n- Whether the destination is usable immediately (permissions, runners, CI/CD variables, integrations)\n\n- How long each batch takes, to set schedules and stakeholder expectations\n\n\nDowntime guidance:\n\n\n- GitLab's built-in Git import and Congregate do not inherently require downtime.\n\n- For production waves, freeze changes in ADO (branch protections or read-only) to avoid missed commits, PR updates, or work items created mid-migration.\n\n- Trial runs do not require freezes and can be run anytime.\n\n\nBatching guidance:\n\n\n- Run trial batches back-to-back to shorten elapsed time; let teams validate results asynchronously.\n\n- Use your planned group/subgroup structure to define batches and respect API rate limits.\n\n\nRecommended steps:\n\n\n1. Create a test destination in GitLab for trials:\n\n\n - GitLab.com: create a dedicated group/namespace (for example, my-org-sandbox)\n\n - Self-managed: create a top-level group or a separate test instance if needed\n\n\n2. Prepare authentication:\n\n\n - Azure DevOps PAT with required scopes.\n\n - GitLab Personal Access Token with api and read_repository (plus admin access for file-based imports used by Congregate).\n\n\n3. Run trial migrations:\n\n\n - Repos only: use GitLab's built-in import (Repo by URL)\n\n - Repos + PRs/MRs and additional assets: use Congregate\n\n\n4. Post-trial follow-up:\n\n\n - Verify repo history, branches, tags; merge requests (if migrated), issues/epics (if migrated), labels, and relationships.\n\n - Check permissions/roles, protected branches, required approvals, runners/tags, variables/secrets, integrations/webhooks.\n\n - Validate pipelines (`.gitlab-ci.yml`) or converted pipelines where applicable.\n\n\n5. Ask users to validate functionality and data fidelity.\n\n6. Resolve issues uncovered during trials and update your runbooks.\n\n7. Network and security:\n\n\n - If your destination uses IP allow lists, add the IPs of your migration host and any required runners/integrations so imports can succeed.\n\n\n8. Run production migrations in waves:\n\n\n - Enforce change freezes in ADO during each wave.\n\n - Monitor progress and logs; retry or adjust batch sizes if you hit rate limits.\n\n\n9. Optional: remove the sandbox group or archive it after you finish.\n\n\n\u003Cfigure class=\"video_container\">\n \u003Ciframe src=\"https://www.youtube.com/embed/ibIXGfrVbi4?si=ZxOVnXjCF-h4Ne0N\" frameborder=\"0\" allowfullscreen=\"true\">\u003C/iframe>\n\u003C/figure>\n\n\n## Terminology reference for GitLab and Azure DevOps\n\n| GitLab | Azure DevOps | Similarities & Key Differences |\n| ---------------------------------------------------------------- | -------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Group | Organization | Top-level namespace, membership, policies. ADO org contains Projects; GitLab Group contains Subgroups and Projects. |\n| Group or Subgroup | Project | Logical container, permissions boundary. ADO Project holds many repos; GitLab Groups/Subgroups organize many Projects. |\n| Project (includes a Git repo) | Repository (inside a Project) | Git history, branches, tags. In GitLab, a \"Project\" is the repo plus issues, CI/CD, wiki, etc. One repo per Project. |\n| Merge Request (MR) | Pull Request (PR) | Code review, discussions, approvals. MR rules include approvals, required pipelines, code owners. |\n| Protected Branches, MR Approval Rules, Status Checks | Branch Policies | Enforce reviews and checks. GitLab combines protections + approval rules + required status checks. |\n| GitLab CI/CD | Azure Pipelines | YAML pipelines, stages/jobs, logs. ADO also has classic UI pipelines; GitLab centers on .gitlab-ci.yml. |\n| .gitlab-ci.yml | azure-pipelines.yml | Defines stages/jobs/triggers. Syntax/features differ; map jobs, variables, artifacts, and triggers. |\n| Runners (shared/specific) | Agents / Agent Pools | Execute jobs on machines/containers. Target via demands (ADO) vs tags (GitLab). Registration/scoping differs. |\n| CI/CD Variables (project/group/instance), Protected/Masked | Pipeline Variables, Variable Groups, Library | Pass config/secrets to jobs. GitLab supports group inheritance and masking/protection flags. |\n| Integrations, CI/CD Variables, Deploy Keys | Service Connections | External auth to services/clouds. Map to integrations or variables; cloud-specific helpers available. |\n| Environments & Deployments (protected envs) | Environments (with approvals) | Track deploy targets/history. Approvals via protected envs and manual jobs in GitLab. |\n| Releases (tag + notes) | Releases (classic or pipelines) | Versioned notes/artifacts. GitLab Release ties to tags; deployments tracked separately. |\n| Job Artifacts | Pipeline Artifacts | Persist job outputs. Retention/expiry configured per job or project. |\n| Package Registry (NuGet/npm/Maven/PyPI/Composer, etc.) | Azure Artifacts (NuGet/npm/Maven, etc.) | Package hosting. Auth/namespace differ; migrate per package type. |\n| GitLab Container Registry | Azure Container Registry (ACR) or others | OCI images. GitLab provides per-project/group registries. |\n| Issue Boards | Boards | Visualize work by columns. GitLab boards are label-driven; multiple boards per project/group. |\n| Issues (types/labels), Epics | Work Items (User Story/Bug/Task) | Track units of work. Map ADO types/fields to labels/custom fields; epics at group level. |\n| Epics, Parent/Child Issues | Epics/Features | Hierarchy of work. Schema differs; use epics + issue relationships. |\n| Milestones and Iterations | Iteration Paths | Time-boxing. GitLab Iterations (group feature) or Milestones per project/group. |\n| Labels (scoped labels) | Area Paths | Categorization/ownership. Replace hierarchical areas with scoped labels. |\n| Project/Group Wiki | Project Wiki | Markdown wiki. Backed by repos in both; layout/auth differ slightly. |\n| Test reports via CI, Requirements/Test Management, integrations | Test Plans/Cases/Runs | QA evidence/traceability. No 1:1 with ADO Test Plans; often use CI reports + issues/requirements. |\n| Roles (Owner/Maintainer/Developer/Reporter/Guest) + custom roles | Access levels + granular permissions | Control read/write/admin. Models differ; leverage group inheritance and protected resources. |\n| Webhooks | Service Hooks | Event-driven integrations. Event names/payloads differ; reconfigure endpoints. |\n| Advanced Search | Code Search | Full-text repo search. Self-managed GitLab may need Elasticsearch/OpenSearch for advanced features. |\n","2025-12-03","2026-01-16","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749658924/Blog/Hero%20Images/securitylifecycle-light.png",[736,737],"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":27,"template":13,"slug":741},"migration-from-azure-devops-to-gitlab",{"promotions":743},[744,758,769],{"id":745,"categories":746,"header":748,"text":749,"button":750,"image":755},"ai-modernization",[747],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":751,"config":752},"Get your AI maturity score",{"href":753,"dataGaName":754,"dataGaLocation":241},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":756},{"src":757},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":759,"categories":760,"header":761,"text":749,"button":762,"image":766},"devops-modernization",[722,554],"Are you just managing tools or shipping innovation?",{"text":763,"config":764},"Get your DevOps maturity score",{"href":765,"dataGaName":754,"dataGaLocation":241},"/assessments/devops-modernization-assessment/",{"config":767},{"src":768},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":770,"categories":771,"header":773,"text":749,"button":774,"image":778},"security-modernization",[772],"security","Are you trading speed for security?",{"text":775,"config":776},"Get your security maturity score",{"href":777,"dataGaName":754,"dataGaLocation":241},"/assessments/security-modernization-assessment/",{"config":779},{"src":780},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":782,"blurb":783,"button":784,"secondaryButton":789},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":785,"config":786},"Get your free trial",{"href":787,"dataGaName":49,"dataGaLocation":788},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":493,"config":790},{"href":53,"dataGaName":54,"dataGaLocation":788},1772652076891]