[{"data":1,"prerenderedAt":794},["ShallowReactive",2],{"/en-us/blog/gitlab-eks-integration-how-to":3,"navigation-en-us":37,"banner-en-us":437,"footer-en-us":447,"blog-post-authors-en-us-Abubakar Siddiq Ango":689,"blog-related-posts-en-us-gitlab-eks-integration-how-to":703,"assessment-promotions-en-us":745,"next-steps-en-us":784},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":26,"isFeatured":12,"meta":27,"navigation":28,"path":29,"publishedDate":20,"seo":30,"stem":34,"tagSlugs":35,"__hash__":36},"blogPosts/en-us/blog/gitlab-eks-integration-how-to.yml","Gitlab Eks Integration How To",[7],"abubakar-siddiq-ango",null,"engineering",{"slug":11,"featured":12,"template":13},"gitlab-eks-integration-how-to",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"How to create a Kubernetes cluster on Amazon EKS in GitLab","A Kubernetes tutorial: Create clusters in a few clicks with GitLab and Amazon EKS.",[18],"Abubakar Siddiq Ango","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749666959/Blog/Hero%20Images/gitlab-aws-cover.png","2020-03-09","Kubernetes has created a whole new world for running infrastructure at scale. With the right setup, an application can go from serving a few users to millions effortlessly. Setting up Kubernetes can be tasking and can require a lot of expertise to put all the pieces together. You’ll need to set up virtual or bare metal machines to use as nodes and manage SSL certificates, networking, load balancers, and many other moving parts.\n\nThe introduction of Amazon Elastic Kubernetes Service (EKS) was widely applauded as it streamlines the abstraction of the complexities in an environment most organizations are already familiar with and on a provider they already trust. Amazon EKS makes creating and managing Kubernetes clusters easier with more granular controls around security and straightforward policies of how resources are used.\n\nGitLab strives to increase developer productivity by automating repetitive tasks and allowing developers to focus on business logic. We recently introduced support for auto-creating Kubernetes clusters on Amazon EKS. In a few clicks with the right permissions, you’ll have a fully functional Kubernetes cluster on Amazon EKS. It doesn’t stop there however – GitLab also gives you the power to achieve the following use cases and more :\n\n* [Highly scalable CI/CD system using GitLab Runner](https://docs.gitlab.com/runner/): There are times like holidays when little to no changes to code are pushed to production, so why keep resources tied down? With the Amazon EKS integration with GitLab, you can install GitLab Runner with just a click and your CI/CD will run effortlessly without worrying about running out of resources.\n* Shared Cluster: Maintaining multiple Kubernetes clusters can be a pain and capital intensive. With Amazon EKS, GitLab allows you to setup a cluster at [Instance](https://docs.gitlab.com/ee/user/instance/clusters/index.html), [Group](https://docs.gitlab.com/ee/user/group/clusters/index.html) and [Project](https://docs.gitlab.com/ee/user/project/clusters/) levels. Kubernetes Namespaces are created for each GitLab project when the Amazon EKS is integrated at Instance and Project level, allowing isolation and ensuring security.\n* [Review Apps](https://docs.gitlab.com/ee/ci/review_apps/index.html): Reviewing changes to code or design can be tricky, you’ll need to check out your branch and run the code in a test environment. GitLab integrated with Amazon EKS deploys your app with new changes to a dynamic environment and all you need to do is click on a “View App“ button to review changes.\n* [AutoDevOps](https://docs.gitlab.com/ee/topics/autodevops/cloud_deployments/auto_devops_with_gke.html) takes DevOps to a whole new level. AutoDevOps detects, builds, tests, deploys, and monitors your applications, leveraging the Amazon EKS integration. All you have to do is push your code and the magic happens. In this tutorial, we will deploy a sample application to the Amazon EKS cluster we will be creating using AutoDevOps.\n\nTo show you how easy it is to create an Amazon EKS cluster from GitLab, the rest of this tutorial will walk you through the steps of the integration, starting with a one-time setup of necessary resources on AWS.\n\n## One-time setup on AWS to access resources\n\nFirst, we need to create a “provision\" role and a “service” role on AWS to grant GitLab access to your AWS resources and set up the necessary permissions to create and manage EKS clusters. You only need to perform these steps once and you can reuse them anytime you want to perform another integration or create more clusters.\n\n### Step 1 - Create Provision Role\n\nTo grant GitLab access to your AWS resources, a “provision role” is required. Let’s create one:\n\n1. Access GitLab Kubernetes Integration Page by clicking on the ”Kubernetes” menu for groups and Operations > Kubernetes menu for projects and click the “Add Kubernetes Cluster” button.\n2. Select “Amazon EKS” in the options provided under the “Create new cluster on EKS” tab.\n3. You are provided with an Account and External ID to use for authentication. Make note of these values to be used in a later step.\n\n ![Gitlab EKS Integration Page](https://about.gitlab.com/images/blogimages/gitlab-eks-integration/gitlab_eks_integration_page.png)\n\n4. Open IAM Management Console in another tab and click on “Create Role”\n5. Click on the “Another AWS account” tab and provide the Account and External ID obtained from GitLab and click Next to set permissions as shown below:\n\n ![AWS Provision Role](https://about.gitlab.com/images/blogimages/gitlab-eks-integration/provision_role.png)\n\n6. On the permissions page, click on “Create policy.” This will open a new tab where you can set either of the permissions below using JSON:\n\n ```json\n {\n \"Version\": \"2012-10-17\",\n \"Statement\": [\n {\n \"Effect\": \"Allow\",\n \"Action\": [\n \"autoscaling:*\",\n \"cloudformation:*\",\n \"ec2:*\",\n \"eks:*\",\n \"iam:*\",\n \"ssm:*\"\n ],\n \"Resource\": \"*\"\n }\n ]\n }\n ```\n\n This gives GitLab full access to create and manage resources, as seen in the image below:\n\n ![AWS Role Policy](https://about.gitlab.com/images/blogimages/gitlab-eks-integration/create_role_policy.png)\n\n If you prefer limited permission, you can give GitLab the ability to create resources, but not delete them with the JSON snippet below. The drawback here is if an error is encountered during the creation process, changes will not be rolled back and you must remove resources manually. You can do this by deleting the relevant CloudFormation stack.\n\n ```json\n {\n \"Version\": \"2012-10-17\",\n \"Statement\": [\n {\n \"Effect\": \"Allow\",\n \"Action\": [\n \"autoscaling:CreateAutoScalingGroup\",\n \"autoscaling:DescribeAutoScalingGroups\",\n \"autoscaling:DescribeScalingActivities\",\n \"autoscaling:UpdateAutoScalingGroup\",\n \"autoscaling:CreateLaunchConfiguration\",\n \"autoscaling:DescribeLaunchConfigurations\",\n \"cloudformation:CreateStack\",\n \"cloudformation:DescribeStacks\",\n \"ec2:AuthorizeSecurityGroupEgress\",\n \"ec2:AuthorizeSecurityGroupIngress\",\n \"ec2:RevokeSecurityGroupEgress\",\n \"ec2:RevokeSecurityGroupIngress\",\n \"ec2:CreateSecurityGroup\",\n \"ec2:createTags\",\n \"ec2:DescribeImages\",\n \"ec2:DescribeKeyPairs\",\n \"ec2:DescribeRegions\",\n \"ec2:DescribeSecurityGroups\",\n \"ec2:DescribeSubnets\",\n \"ec2:DescribeVpcs\",\n \"eks:CreateCluster\",\n \"eks:DescribeCluster\",\n \"iam:AddRoleToInstanceProfile\",\n \"iam:AttachRolePolicy\",\n \"iam:CreateRole\",\n \"iam:CreateInstanceProfile\",\n \"iam:CreateServiceLinkedRole\",\n \"iam:GetRole\",\n \"iam:ListRoles\",\n \"iam:PassRole\",\n \"ssm:GetParameters\"\n ],\n \"Resource\": \"*\"\n }\n ]\n }\n ```\n\n The image below visualizes what permissions are granted:\n\n ![Limited Role Policy](https://about.gitlab.com/images/blogimages/gitlab-eks-integration/limited_role_policy.png)\n\n7. Once the policy is created, return to the “Create Role” browser tab and refresh to see the policy we created listed. Select the policy and click “Next.”\n8. In the Tags section, we don’t need to set any Tags, except if it’s required in your organization. Let’s proceed to Review.\n9. Specify a Name for your new Role. You will see the policy we created listed under policies and click “Create Role” to complete the process.\n10. Click on the new Role you created in the list of Roles to view its details. You may have to search for it in the list of Roles if it’s not listed in the first view. Copy the Role ARN provided – we will need it on the GitLab Kubernetes Integration page.\n\n### Step 2 - Create Service Role\n\nThe Service Role is required to allow Amazon EKS and the Kubernetes control plane to manage AWS resources on your behalf.\n\n1. In the IAM Management Console, click on “Create Role” and select the “AWS service” tab.\n2. Select EKS in the list of services and Use Cases as shown below and click Next.\n\n ![Service Role](https://about.gitlab.com/images/blogimages/gitlab-eks-integration/service_role.png)\n\n3. You will notice the “AmazonEKSClusterPolicy” and “AmazonEKSServicePolicy” permissions are selected; these are all we need. Click through the Tags step and create if necessary, then click Next to get to the Review step. Click “Create Role” to complete the process.\n\n ![Role Summary](https://about.gitlab.com/images/blogimages/gitlab-eks-integration/role_summary.png)\n\n## GitLab EKS Integration\n\nThis is the easy part! As mentioned earlier, you only need to create the Provision and Service role once if you don’t already have them in your organization’s AWS setup. You can reuse the roles for other integrations or cluster creations.\n\n1. Return to the GitLab Kubernetes Integration page and provide the Role ARN of the Provision Role we created earlier and click “Authenticate with AWS.”\n\n ![Gitlab EKS Integration Page](https://about.gitlab.com/images/blogimages/gitlab-eks-integration/gitlab_eks_integration_page.png)\n\n2. Once authenticated, you’ll have a page to set the parameters needed to set up your cluster as shown in the image below and click on “Create Kubernetes Cluster” to let GitLab do its magic!\n\n The parameters you’ll need to provide are:\n * **Kubernetes cluster name** - The name you wish to give the cluster.\n * **Environment scope** - The [GitLab environment](https://docs.gitlab.com/ee/user/project/clusters/index.html#setting-the-environment-scope) associated with this cluster; `*` denotes the cluster will be used for deployments to all environments.\n * **Kubernetes version** - The Kubernetes version to use. Currently, the only version supported is 1.14.\n * **Role name** - The service role we created earlier.\n * **Region** - The [AWS region](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-regions-availability-zones.html) in which the cluster will be created.\n * **Key pair name** - Select the [key pair](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-key-pairs.html) that you can use to connect to your worker nodes if required.\n * **VPC** - Select a [VPC](https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html) to use for your EKS Cluster resources.\n * **Subnets** - Choose the [subnets](https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html) in your VPC where your worker nodes will run.\n * **Security group** - Choose the [security group](https://docs.aws.amazon.com/vpc/latest/userguide/VPC_SecurityGroups.html) to apply to the EKS-managed Elastic Network Interfaces that are created in your worker node subnets. AWS provides a default group, which can be used for the purpose of this guide. However, you are advised to setup up the right rules required for your resources.\n * **Instance type** - The AWS [instance type](https://aws.amazon.com/ec2/instance-types/) of your worker nodes.\n * **Node count** - The number of worker nodes.\n * **GitLab-managed cluster** - Leave this checked if you want [GitLab to manage namespaces and service accounts](https://docs.gitlab.com/ee/user/project/clusters/index.html#gitlab-managed-clusters) for this cluster.\n\n ![Gitlab EKS Integration Page](https://about.gitlab.com/images/blogimages/gitlab-eks-integration/gitlab_eks_integration_post_auth.png)\n\n3. The cluster creation process will take approximately 10 minutes. Once done you can proceed to install some predefined applications. At the very least, you need to install the following:\n - **Helm Tiller**: This is required to install the other applications.\n - **Ingress**: This provides SSL termination, load balancing and name-based virtual hosting you your applications. It acts as a web proxy for your application, which is useful when using AutoDevOps or deploying your own apps.\n - **Cert Manager**: This is a native Kubernetes certificate management controller, which helps in issuing certificates using Let’s Encrypt. You don’t need this if you want to use a custom Certificate issuer.\n - **Prometheus**: GitLab uses the Prometheus integration for automatic monitoring of your applications to collect metrics from Kubernetes containers allowing you to understand what is going on from within the GitLab UI.\n\n ![Gitlab EKS Integration Page](https://about.gitlab.com/images/blogimages/gitlab-eks-integration/gitlab_eks_integration_post_cluster.png)\n\n4. To make use of Auto Review Apps and Auto Deploy stages of [AutoDevOps](https://docs.gitlab.com/ee/topics/autodevops/quick_start_guide.html), you will need to specify a Base Domain name with a wild card DNS pointing to the Ingress Endpoint generated when you Install Ingress in the list of predefined apps.\n\n## Summary\n\nIn this tutorial, we looked at how GitLab integrates with Amazon EKS, allowing Kubernetes clusters to be created easily from the GitLab UI after setting the right permissions. As we’ve seen, developer productivity is greatly improved by no longer having to manually set up clusters. Also, the same cluster can be used for multiple projects when Amazon EKS is integrated with GitLab at the Group and Instance levels, thus making onboarding new projects a breeze. After integration, the possibilities of what developers can achieve is enormous.\n\nIn the next part of this tutorial, we will look at how to deploy your applications on an Amazon EKS cluster using AutoDevOps.\n",[23,24,25],"kubernetes","features","demo","yml",{},true,"/en-us/blog/gitlab-eks-integration-how-to",{"title":15,"description":16,"ogTitle":15,"ogDescription":16,"noIndex":12,"ogImage":19,"ogUrl":31,"ogSiteName":32,"ogType":33,"canonicalUrls":31},"https://about.gitlab.com/blog/gitlab-eks-integration-how-to","https://about.gitlab.com","article","en-us/blog/gitlab-eks-integration-how-to",[23,24,25],"u8gOJw9NJP6usLaBazn96skHXR2MefbH7_On5csRtpA",{"data":38},{"logo":39,"freeTrial":44,"sales":49,"login":54,"items":59,"search":367,"minimal":398,"duo":417,"pricingDeployment":427},{"config":40},{"href":41,"dataGaName":42,"dataGaLocation":43},"/","gitlab logo","header",{"text":45,"config":46},"Get free 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statement",{"items":679},[680,683,686],{"text":681,"config":682},"Terms",{"href":507,"dataGaName":508,"dataGaLocation":455},{"text":684,"config":685},"Cookies",{"dataGaName":517,"dataGaLocation":455,"id":518,"isOneTrustButton":28},{"text":687,"config":688},"Privacy",{"href":512,"dataGaName":513,"dataGaLocation":455},[690],{"id":691,"title":18,"body":8,"config":692,"content":694,"description":8,"extension":26,"meta":698,"navigation":28,"path":699,"seo":700,"stem":701,"__hash__":702},"blogAuthors/en-us/blog/authors/abubakar-siddiq-ango.yml",{"template":693},"BlogAuthor",{"name":18,"config":695},{"headshot":696,"ctfId":697},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749660104/Blog/Author%20Headshots/abuango-headshot.jpg","abuango",{},"/en-us/blog/authors/abubakar-siddiq-ango",{},"en-us/blog/authors/abubakar-siddiq-ango","u5Jv4JxCpfmcGQuXEU4Lr5xVBJP9LAB2NkXRMLeYwPE",[704,717,729],{"content":705,"config":715},{"title":706,"description":707,"authors":708,"heroImage":710,"date":711,"category":9,"tags":712,"body":714},"How IIT Bombay students are coding the future with GitLab","At GitLab, we often talk about how software accelerates innovation. But sometimes, you have to step away from the Zoom calls and stand in a crowded university hall to remember why we do this.",[709],"Nick Veenhof","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099013/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2814%29_6VTUA8mUhOZNDaRVNPeKwl_1750099012960.png","2026-01-08",[259,611,713],"open source","The GitLab team recently had the privilege of judging the **iHack Hackathon** at **IIT Bombay's E-Summit**. The energy was electric, the coffee was flowing, and the talent was undeniable. But what struck us most wasn't just the code — it was the sheer determination of students to solve real-world problems, often overcoming significant logistical and financial hurdles to simply be in the room.\n\n\nThrough our [GitLab for Education program](https://about.gitlab.com/solutions/education/), we aim to empower the next generation of developers with tools and opportunity. Here is a look at what the students built, and how they used GitLab to bridge the gap between idea and reality.\n\n## The challenge: Build faster, build securely\n\nThe premise for the GitLab track of the hackathon was simple: Don't just show us a product; show us how you built it. We wanted to see how students utilized GitLab's platform — from Issue Boards to CI/CD pipelines — to accelerate the development lifecycle.\n\nThe results were inspiring.\n\n## The winners\n\n### 1st place: Team Decode — Democratizing Scientific Research\n\n**Project:** FIRE (Fast Integrated Research Environment)\n\nTeam Decode took home the top prize with a solution that warms a developer's heart: a local-first, blazing-fast data processing tool built with [Rust](https://about.gitlab.com/blog/secure-rust-development-with-gitlab/) and Tauri. They identified a massive pain point for data science students: existing tools are fragmented, slow, and expensive.\n\nTheir solution, FIRE, allows researchers to visualize complex formats (like NetCDF) instantly. What impressed the judges most was their \"hacker\" ethos. They didn't just build a tool; they built it to be open and accessible.\n\n**How they used GitLab:** Since the team lived far apart, asynchronous communication was key. They utilized **GitLab Issue Boards** and **Milestones** to track progress and integrated their repo with Telegram to get real-time push notifications. As one team member noted, \"Coordinating all these technologies was really difficult, and what helped us was GitLab... the Issue Board really helped us track who was doing what.\"\n\n![Team Decode](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380253/epqazj1jc5c7zkgqun9h.jpg)\n\n### 2nd place: Team BichdeHueDost — Reuniting to Solve Payments\n\n**Project:** SemiPay (RFID Cashless Payment for Schools)\n\nThe team name, BichdeHueDost, translates to \"Friends who have been set apart.\" It's a fitting name for a group of friends who went to different colleges but reunited to build this project. They tackled a unique problem: handling cash in schools for young children. Their solution used RFID cards backed by a blockchain ledger to ensure secure, cashless transactions for students.\n\n**How they used GitLab:** They utilized [GitLab CI/CD](https://about.gitlab.com/topics/ci-cd/) to automate the build process for their Flutter application (APK), ensuring that every commit resulted in a testable artifact. This allowed them to iterate quickly despite the \"flaky\" nature of cross-platform mobile development.\n\n![Team BichdeHueDost](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380253/pkukrjgx2miukb6nrj5g.jpg)\n\n### 3rd place: Team ZenYukti — Agentic Repository Intelligence\n\n**Project:** RepoInsight AI (AI-powered, GitLab-native intelligence platform)\n\nTeam ZenYukti impressed us with a solution that tackles a universal developer pain point: understanding unfamiliar codebases. What stood out to the judges was the tool's practical approach to onboarding and code comprehension: RepoInsight-AI automatically generates documentation, visualizes repository structure, and even helps identify bugs, all while maintaining context about the entire codebase.\n\n**How they used GitLab:** The team built a comprehensive CI/CD pipeline that showcased GitLab's security and DevOps capabilities. They integrated [GitLab's Security Templates](https://gitlab.com/gitlab-org/gitlab/-/tree/master/lib/gitlab/ci/templates/Security) (SAST, Dependency Scanning, and Secret Detection), and utilized [GitLab Container Registry](https://docs.gitlab.com/user/packages/container_registry/) to manage their Docker images for backend and frontend components. They created an AI auto-review bot that runs on merge requests, demonstrating an \"agentic workflow\" where AI assists in the development process itself.\n\n![Team ZenYukti](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380253/ymlzqoruv5al1secatba.jpg)\n\n## Beyond the code: A lesson in inclusion\n\nWhile the code was impressive, the most powerful moment of the event happened away from the keyboard.\n\nDuring the feedback session, we learned about the journey Team ZenYukti took to get to Mumbai. They traveled over 24 hours, covering nearly 1,800 kilometers. Because flights were too expensive and trains were booked, they traveled in the \"General Coach,\" a non-reserved, severely overcrowded carriage.\n\nAs one student described it:\n\n*\"You cannot even imagine something like this... there are no seats... people sit on the top of the train. This is what we have endured.\"*\n\nThis hit home. [Diversity, Inclusion, and Belonging](https://handbook.gitlab.com/handbook/company/culture/inclusion/) are core values at GitLab. We realized that for these students, the barrier to entry wasn't intellect or skill, it was access.\n\nIn that moment, we decided to break that barrier. We committed to reimbursing the travel expenses for the participants who struggled to get there. It's a small step, but it underlines a massive truth: **talent is distributed equally, but opportunity is not.**\n\n![hackathon class together](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380252/o5aqmboquz8ehusxvgom.jpg)\n\n### The future is bright (and automated)\n\nWe also saw incredible potential in teams like Prometheus, who attempted to build an autonomous patch remediation tool (DevGuardian), and Team Arrakis, who built a voice-first job portal for blue-collar workers using [GitLab Duo](https://about.gitlab.com/gitlab-duo/) to troubleshoot their pipelines.\n\nTo all the students who participated: You are the future. Through [GitLab for Education](https://about.gitlab.com/solutions/education/), we are committed to providing you with the top-tier tools (like GitLab Ultimate) you need to learn, collaborate, and change the world — whether you are coding from a dorm room, a lab, or a train carriage. **Keep shipping.**\n\n> :bulb: Learn more about the [GitLab for Education program](https://about.gitlab.com/solutions/education/).\n",{"slug":716,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":718,"config":727},{"title":719,"description":720,"authors":721,"heroImage":722,"date":723,"category":9,"tags":724,"body":726},"Artois University elevates research and curriculum with GitLab Ultimate for Education","Artois University's CRIL leveraged the GitLab for Education program to gain free access to Ultimate, transforming advanced research and computer science curricula.",[709],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099203/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2820%29_2bJGC5ZP3WheoqzlLT05C5_1750099203484.png","2025-12-10",[611,259,725],"product","Leading academic institutions face a critical challenge: how to provide thousands of students and researchers with industry-standard, **full-featured DevSecOps tools** without compromising institutional control. Many start with basic version control, but the modern curriculum demands integrated capabilities for planning, security, and advanced CI/CD.\n\nThe **GitLab for Education program** is designed to solve this by providing access to **GitLab Ultimate** for qualifying institutions, allowing them to scale their operations and elevate their academic offerings. \n\nThis article showcases a powerful success story from the **Centre de Recherche en Informatique de Lens (CRIL)**, a joint laboratory of **Artois University** and CNRS in France. After years of relying solely on GitLab Community Edition (CE), the university's move to GitLab Ultimate through the GitLab for Education program immediately unlocked advanced capabilities, transforming their teaching, research, and contribution workflows virtually overnight. This story demonstrates why GitLab Ultimate is essential for institutions seeking to deliver advanced computer science and research curricula.\n\n## GitLab Ultimate unlocked: Managing scale and driving academic value\n\n**Artois University's** self-managed GitLab instance is a large-scale operation, supporting nearly **3,000 users** across approximately **19,000 projects**, primarily serving computer science students and researchers. While GitLab Community Edition was robust, the upgrade to GitLab Ultimate provided the sophisticated tooling necessary for managing this scale and facilitating advanced university-level work.\n\n***\"We can see the difference,\" says Daniel Le Berre, head of research at CRIL and the instance maintainer. \"It's a completely different product. Each week reveals new features that directly enhance our productivity and teaching.\"***\n\nThe institution joined the GitLab for Education program specifically because it covers both **instructional and non-commercial research use cases** and offers full access to Ultimate's features, removing significant cost barriers.\n\n### Key GitLab Ultimate benefits for students and researchers\n\n* **Advanced project management at scale:** Master's students now benefit from **GitLab Ultimate's project planning features**. This enables them to structure, track, and manage complex, long-term research projects using professional methodologies like portfolio management and advanced issue tracking that seamlessly roll up across their thousands of projects.\n\n* **Enhanced visibility:** Features like improved dashboards and code previews directly in Markdown files dramatically streamline tracking and documentation review, reducing administrative friction for both instructors and students managing large project loads.\n\n## Comprehensive curriculum: From concepts to continuous delivery\n\nGitLab Ultimate is deeply integrated into the computer science curriculum, moving students beyond simple `git` commands to practical **DevSecOps implementation**.\n\n* **Git fundamentals:** Students begin by visualizing concepts using open-source tools to master Git concepts.\n\n* **Full CI/CD implementation:** Students use GitLab CI for rigorous **Test-Driven Development (TDD)** in their software projects. They learn to build, test, and perform quality assurance using unit and integration testing pipelines—core competency made seamless by the integrated platform.\n\n* **DevSecOps for research and documentation:** The university teaches students that DevSecOps principles are vital for all collaborative work. Inspired by earlier work in Delft, students manage and produce critical research documentation (PDFs from Markdown files) using GitLab, incorporating quality checks like linters and spell checks directly in the CI pipeline. This ensures high-quality, reproducible research output.\n\n* **Future-proofing security skills:** The GitLab Ultimate platform immediately positions the institution to incorporate advanced DevSecOps features like SAST and DAST scanning as their research and development code projects grow, ensuring students are prepared for industry security standards.\n\n## Accelerating open source contributions with GitLab Duo\n\nAccess to the full GitLab platform, including our AI capabilities, has empowered students to make impactful contributions to the wider open source community faster than ever before.\n\nTwo Master's students recently completed direct contributions to the GitLab product, adding the **ORCID identifier** into user profiles. Working on GitLab.com, they leveraged **GitLab Duo's AI chat and code suggestions** to navigate the codebase efficiently.\n\n***\"This would not have been possible without GitLab Duo,\" Daniel Le Berre notes. \"The AI features helped students, who might have lacked deep codebase knowledge, deliver meaningful contributions in just two weeks.\"***\n\nThis demonstrates how providing students with cutting-edge tools **accelerates their learning and impact**, allowing them to translate classroom knowledge into real-world contributions immediately.\n\n## Empowering open research and institutional control\n\nThe stability of the self-managed instance at Artois University is key to its success. This model guarantees **institutional control and stability** — a critical factor for long-term research preservation.\n\nThe institution's expertise in this area was recently highlighted in a major 2024 study led by CRIL, titled: \"[Higher Education and Research Forges in France - Definition, uses, limitations encountered and needs analysis](https://hal.science/hal-04208924v4)\" ([Project on GitLab](https://gitlab.in2p3.fr/coso-college-codes-sources-et-logiciels/forges-esr-en)). The research found that the vast majority of public forges in French Higher Education and Research relied on **GitLab**. This finding underscores the consensus among academic leaders that self-hosted solutions are essential for **data control and longevity**, especially when compared to relying on external, commercial forges.\n\n## Unlock GitLab Ultimate for your institution today\n\nThe success story of **Artois University's CRIL** proves the transformative power of the GitLab for Education program. By providing **free access to GitLab Ultimate**, we enable large-scale institutions to:\n\n1. **Deliver a modern, integrated DevSecOps curriculum.**\n\n2. **Support advanced, collaborative research projects with Ultimate planning features.**\n\n3. **Empower students to make AI-assisted open source contributions.**\n\n4. **Maintain institutional control and data longevity.**\n\nIf your academic institution is ready to equip its students and researchers with the complete DevSecOps platform and its most advanced features, we invite you to join the program.\n\nThe program provides **free access to GitLab Ultimate** for qualifying instructional and non-commercial research use cases.\n\n**Apply now [online](https://about.gitlab.com/solutions/education/join/).**\n",{"slug":728,"featured":28,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":730,"config":743},{"category":9,"tags":731,"body":734,"date":735,"updatedDate":736,"heroImage":737,"authors":738,"title":741,"description":742},[732,733,106],"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. 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