[{"data":1,"prerenderedAt":798},["ShallowReactive",2],{"/en-us/blog/cicd-tunnel-impersonation":3,"navigation-en-us":41,"banner-en-us":441,"footer-en-us":451,"blog-post-authors-en-us-Cesar Saavedra":693,"blog-related-posts-en-us-cicd-tunnel-impersonation":707,"assessment-promotions-en-us":749,"next-steps-en-us":788},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":27,"isFeatured":12,"meta":28,"navigation":29,"path":30,"publishedDate":20,"seo":31,"stem":36,"tagSlugs":37,"__hash__":40},"blogPosts/en-us/blog/cicd-tunnel-impersonation.yml","Cicd Tunnel Impersonation",[7],"cesar-saavedra",null,"engineering",{"slug":11,"featured":12,"template":13},"cicd-tunnel-impersonation",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"How to use fine-grained permissions via generic impersonation in CI/CD Tunnel","Learn how to use use fine-grained permissions via generic impersonation in CI/CD Tunnel",[18],"Cesar Saavedra","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749667435/Blog/Hero%20Images/tunnel.jpg","2022-02-01","\nThe [CI/CD Tunnel](https://docs.gitlab.com/ee/user/clusters/agent/ci_cd_workflow.html), which leverages the [GitLab Agent for Kubernetes](https://docs.gitlab.com/ee/user/clusters/agent/), enables users to access Kubernetes clusters from GitLab CI/CD jobs. In this blog post, we review how you can securely access your clusters from your CI/CD pipelines by using generic impersonation. In addition, we will briefly cover the activity list of the GitLab Agent for Kubernetes, a capability recently introduced by GitLab, that can help you detect and troubleshoot faulty events.\n\n## Using impersonation with your CI/CD tunnel\n\nThe CI/CD Tunnel leverages the GitLab Agent for Kubernetes, which permits the secure connectivity between GitLab and your Kubernetes cluster without the need to expose your cluster to the internet and outside your firewall. The CI/CD Tunnel allows you to connect to your Kubernetes cluster from your CI/CD jobs/pipelines.\n\nBy default, the CI/CD Tunnel inherits all the permissions from the service account used to install the Agent in the cluster. However, fine-grained permissions can be used in conjunction with the CI/CD Tunnel to restrict and manage access to your cluster resources.\n\nFine-grained permissions control with the CI/CD tunnel via impersonation:\n\n- Allows you to leverage your K8s authorization capabilities to limit the permissions of what can be done with the CI/CD tunnel on your running cluster\n\n- Lowers the risk of providing unlimited access to your K8s cluster with the CI/CD tunnel\n\n- Segments fine-grained permissions with the CI/CD tunnel at the project or group level\n\n- Controls permissions with the CI/CD tunnel at the username or service account\n\nTo restrict access to your cluster, you can use impersonation. To specify impersonations, use the access_as attribute in your Agent's configuration file and use Kubernetes RBAC rules to manage impersonated account permissions.\n\nYou can impersonate:\n- The Agent itself (default)\n= The CI job that accesses the cluster\n- A specific user or system account defined within the cluster\n\n## Steps to exercise impersonation with the CI/CD Tunnel\n\nLet's go through the steps on how you can exercise impersonation with the CI/CD Tunnel.\n\n### Creating your Kubernetes cluster\n\nIn order to exercise the capabilities described above, we need a Kubernetes cluster. Although, you can use any Kubernetes distribution, for this example, we create a GKE Standard Kubernetes cluster and name it \"csaavedra-ga4k-cluster\". We select the zone and version 1.21 of Kubernetes and ensure that our cluster will have three nodes. We leave the security and metadata screens with their defaulted values and click on the create button:\n\n![Creating a GKE cluster](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/0-gke-creation.png){: .shadow.medium.center.wrap-text}\nCreating a GKE cluster\n\n\n### Sample projects to be used\n\nLet's proceed now to this [top-level group](https://gitlab.com/tech-marketing/sandbox/gl-14-5-cs-demos), which contains three projects, which we will use to show impersonation with the CI/CD tunnel. You can do this at the project or group level. In this example, we will show setting impersonation at the project level:\n\n![Project structure in GitLab](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/1-project-struct.png){: .shadow.medium.center.wrap-text}\nProject structure in GitLab\n\n\nProject \"ga4k\" will configure the GitLab Agent for Kubernetes and also set impersonations with the CI/CD tunnel. Project \"sample-application\" will use the CI/CD tunnel, managed by the agent, to connect to the Kubernetes cluster and execute a pipeline using different impersonations. Project \"cluster-management\" will also use the CI/CD tunnel to connect to the cluster and install the Ingress application on it.\n\nNot only does the CI/CD tunnel streamline the deployment, management, and monitoring of Kubernetes-native applications, but it also does it securely and safely by using impersonations that leverage your Kubernetes cluster's RBAC rules.\n\nProject \"ga4k\" contains and manages the configuration for the GitLab Agent for K8s called \"csaavedra-agentk\". Looking at its \"config.yaml\" file, we see that the agent points to itself for manifest projects, but most importantly, it provides CI/CD tunnel access to two projects: \"sample-application\" and \"cluster-management\". This means that these two projects' CI/CD pipelines will have access to the K8s cluster that the agent is securely connected to:\n\n![The GitLab Agent for K8s configuration](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/2-agent-config.png){: .shadow.medium.center.wrap-text}\nThe GitLab Agent for K8s configuration\n\n\nProject \"sample-application\" has a pipeline, which we will later execute under different impersonations. And project \"cluster-management\" has a pipeline that will install only the Ingress application on the Kubernetes cluster, as configured in its helmfile.yaml file:\n\n![Deployable applications in cluster-management project](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/3-cluster-mgmt-helmfile.png){: .shadow.medium.center.wrap-text}\nDeployable applications in cluster-management project\n\n\n### Connecting the Agent to your Kubernetes cluster\n\nLet's head back to project \"ga4k\" and connect to the Kubernetes cluster via the agent. We select agent \"csaavedra-agentk\" to register with GitLab:\n\n![List of defined agents](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/4-agents-popdown.png){: .shadow.medium.center.wrap-text}\nList of defined agents\n\n\nThis step generates a token that we can use to install the agent on the cluster. We copy the Docker command to our local desktop for later use. Notice that the command includes the generated token, which you can also copy:\n\n![Docker command to deploy agent to your K8s cluster](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/5-docker-cmd.png){: .shadow.medium.center.wrap-text}\nDocker command to deploy agent to your K8s cluster\n\n\nFrom a local command window, we ensure that our connectivity parameters to GCP are correct:\n\n![Checking your GCP connectivity parameters](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/6-gcp-connectivity.png){: .shadow.medium.center.wrap-text}\nChecking your GCP connectivity parameters\n\n\nWe then add the credentials to our kubeconfig file to connect to our newly created Kubernetes cluster \"csaavedra-ga4k-cluster\" and verify that our context is set to it:\n\n![Adding your cluster credentials to your kubeconfig](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/7-adding-creds.png){: .shadow.medium.center.wrap-text}\nAdding the credentials of your cluster to your kubeconfig\n\n\nOnce this is done, we can list all the pods that are up and running on the cluster by entering `kubectl get pods –all-namespaces`:\n\n![Listing the pods in your running cluster](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/8-listing-pods.png){: .shadow.medium.center.wrap-text}\nListing the pods in your running cluster\n\n\nFinally, we paste the docker command that will install the GitLab Agent for Kubernetes to this cluster making sure that its namespace is \"ga4k-agent\":\n\n![Deploying the agent to your K8s cluster](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/9-pasted-docker-cmd.png){: .shadow.medium.center.wrap-text}\nDeploying the agent to your K8s cluster\n\n\nWe list the pods one more time to check that the agent pod is up and running on the cluster:\n\n![Agent up and running on your K8s cluster](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/10-agent-up.png){: .shadow.medium.center.wrap-text}\nAgent up and running on your K8s cluster\n\n\nThe screen will refresh and show our Kubernetes cluster connected via the agent:\n\n![Agent connected to your K8s cluster](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/11-agent-connected.png){: .shadow.large.center.wrap-text}\nAgent connected to your K8s cluster\n\n\n### The Agent's Activity Information page\n\nClicking on the agent name takes us to the Agent's Activity Information page, which lists agent events in real time. This information can help monitor your cluster's activity and detect and troubleshoot faulty events from your cluster. Connection and token information is currently listed with more events coming in future releases:\n\n![Agent activity information page](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/12-agent-activity.png){: .shadow.small.center.wrap-text}\nAgent activity information page\n\n\n### Deploying Ingress to your Kubernetes cluster using default impersonation\n\nBy default, the CI/CD Tunnel inherits all the permissions from the service account used to install the agent in the cluster. Per the agent's configuration, the CI/CD pipelines of the \"cluster-management\" project will have access to the K8s cluster that the agent is securely connected to. Let's leverage this connectivity to deploy the Ingress application to the Kubernetes cluster from project \"cluster-management\". Let's make a small update to the project pipeline to launch it. Once the pipeline launches, we navigate to its detail view to track its completion:\n\n![Project \"cluster-management\" pipeline completed](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/13-cluster-mgmt-pipeline.png){: .shadow.small.center.wrap-text}\nProject \"cluster-management\" pipeline completed\n\n\nand check the log of its **apply** job to verify that it was able to switch to the agent's context and successfully ran all the installation steps:\n\n![Ingress deployed to your cluster via CI/CD Tunnel using default impersonation](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/14-apply-job-log.png){: .shadow.medium.center.wrap-text}\nIngress deployed to your cluster via CI/CD Tunnel using default impersonation\n\n\nFor further verification, we list the pods in the cluster and check that the ingress pods are up and running:\n\n![Ingress pods up and running](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/15-ingress-pods-up.png){: .shadow.medium.center.wrap-text}\nIngress pods up and running on your cluster\n\n\n### Start trailing the agent's log file to watch updates\n\nBefore we start the impersonation use cases, let's start trailing the agent's log file from a command window:\n\n![Trailing agent log from the command line](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/16-trail-agent-log.png){: .shadow.medium.center.wrap-text}\nTrailing agent log from the command line\n\n\nAnd also let's increase its logging to debug:\n\n![Increasing the agent log level to debug](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/17-agent-logging-level.png){: .shadow.medium.center.wrap-text}\nIncreasing the agent log level to debug\n\n\n### Running impersonation using access_as:ci_job\n\nLet's now impersonate the CI job that accesses the cluster. For this, we modify the agent's configuration and add the \"access_as\" attribute with the \"ci_job\" tag under it:\n\n![Impersonating the CI job](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/18-ci-job-impersonation.png){: .shadow.medium.center.wrap-text}\nImpersonating the CI job\n\n\nAs we save the updated configuration, we verify in the log output that the update has taken place in the running agent:\n\n![Agent updated with CI job impersonation](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/19-agent-conf-updated.png){: .shadow.large.center.wrap-text}\nAgent updated with CI job impersonation\n\n\nNotice that the pipeline of the \"sample-application\" project has a test stage and a test job. It sets the variable KUBE_CONTEXT first, loads an image with the version of kubectl that matches the version of the K8s cluster, and executes two kubectl commands that access the remote cluster via the agent:\n\n![Project \"sample-application\" pipeline](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/20-sample-application-pipeline.png){: .shadow.medium.center.wrap-text}\nProject \"sample-application\" pipeline\n\n\nWe manually execute the pipeline of the \"sample-application\" project and verify in the job log output that the context switch was successful and that the kubectl commands executed correctly:\n\n![Job log output with CI impersonation](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/21-ci-impersonation-job-log.png){: .shadow.medium.center.wrap-text}\nJob log output with CI impersonation\n\n\n### Running impersonation using access_as:impersonate:username\n\nThe last use case is the impersonation of a specific user or system account defined within the cluster. I have pre-created a service account called \"jane\" on the Kubernetes cluster under the \"default\" namespace. And \"jane\" has been given the permission to do a \"get\", \"list\", and \"watch\" on the cluster pods as you can see by the output in the command window:\n\n![Jane user with permission to list pods](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/22-jane-and-perms.png){: .shadow.medium.center.wrap-text}\nJane user with permission to list pods\n\n\nRemember that the service account \"gitlab-agent\" under namespace \"ga4k-agent\" was created earlier when we installed the agent by running the Docker command. In order for the agent to be able to impersonate another service account or user, it needs to have the permissions to do so. We do this by creating a clusterrole \"impersonate\" for impersonating users, groups, and service accounts, and then create a clusterrolebinding \"allowimpersonator\" to give these permissions for the \"default\" namespace to the agent \"gitlab-agent\" in the \"ga4k-agent\" namespace:\n\n![Giving impersonation permission to agent](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/23-clusterrole-perm-to-agent.png){: .shadow.large.center.wrap-text}\nGiving impersonation permission to agent\n\n\nWe then edit the agent's configuration and add the \"impersonate\" attribute and provide the service account for \"jane\" as the parameter for the \"username\" tag:\n\n![Impersonating a specific user](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/24-user-impersonation.png){: .shadow.medium.center.wrap-text}\nImpersonating a specific user called jane\n\n\nAs we commit the changes, we check the log output to verify that the update has taken place in the running agent:\n\n![Agent updated with user impersonation](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/25-agent-conf-updated.png){: .shadow.large.center.wrap-text}\nAgent updated with user impersonation\n\n\nSince we know that \"jane\" has the permission to list the running pods in the cluster, let's head to the project \"sample-application\" pipeline and add the command \"kubectl get pods –all-namespaces\" to it:\n\n![Adding get pods command that jane is allowed to run](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/26-adding-get-pods-cmd.png){: .shadow.medium.center.wrap-text}\nAdding get pods command that jane is allowed to run\n\n\nWe commit the update and head over to the running pipeline and drill into the \"test\" job log output to see that the context switch was successful and that the kubectl commands executed correctly, including the listing of the running pods in the cluster:\n\n![Job output for pipeline impersonation jane](https://about.gitlab.com/images/blogimages/cicd-tunnel-impersonate/27-user-impersonation-job-log.png){: .shadow.medium.center.wrap-text}\nJob output for pipeline impersonation jane\n\n\n## Conclusion\n\nIn this blog post, we reviewed how you can securely access your Kubernetes clusters from your CI/CD pipelines by using generic impersonation.  In addition, we showed the activity list of the GitLab Agent for Kubernetes, which can help you detect and troubleshoot faulty events from your cluster.\n\nTo see these capabilities in action, check out the following video:\n\n\u003C!-- blank line -->\n\u003Cfigure class=\"video_container\">\n  \u003Ciframe src=\"https://www.youtube.com/embed/j8SJuHd7Zsw\" frameborder=\"0\" allowfullscreen=\"true\"> \u003C/iframe>\n\u003C/figure>\n\u003C!-- blank line -->\n\nCover image by Jakob Søby on [Unsplash](https://www.unsplash.com)\n",[23,24,25,26],"releases","CI","CD","kubernetes","yml",{},true,"/en-us/blog/cicd-tunnel-impersonation",{"title":32,"description":16,"ogTitle":32,"ogDescription":16,"noIndex":12,"ogImage":19,"ogUrl":33,"ogSiteName":34,"ogType":35,"canonicalUrls":33},"Fine-grained permissions with impersonation in CI/CD 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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.",[713],"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",[263,615,717],"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":720,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":722,"config":731},{"title":723,"description":724,"authors":725,"heroImage":726,"date":727,"category":9,"tags":728,"body":730},"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.",[713],"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",[615,263,729],"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":732,"featured":29,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":734,"config":747},{"category":9,"tags":735,"body":738,"date":739,"updatedDate":740,"heroImage":741,"authors":742,"title":745,"description":746},[736,737,110],"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",[743,744],"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":29,"template":13,"slug":748},"migration-from-azure-devops-to-gitlab",{"promotions":750},[751,765,776],{"id":752,"categories":753,"header":755,"text":756,"button":757,"image":762},"ai-modernization",[754],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":758,"config":759},"Get your AI maturity score",{"href":760,"dataGaName":761,"dataGaLocation":245},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":763},{"src":764},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":766,"categories":767,"header":768,"text":756,"button":769,"image":773},"devops-modernization",[729,561],"Are you just managing tools or shipping innovation?",{"text":770,"config":771},"Get your DevOps maturity score",{"href":772,"dataGaName":761,"dataGaLocation":245},"/assessments/devops-modernization-assessment/",{"config":774},{"src":775},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":777,"categories":778,"header":780,"text":756,"button":781,"image":785},"security-modernization",[779],"security","Are you trading speed for security?",{"text":782,"config":783},"Get your security maturity score",{"href":784,"dataGaName":761,"dataGaLocation":245},"/assessments/security-modernization-assessment/",{"config":786},{"src":787},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":789,"blurb":790,"button":791,"secondaryButton":796},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":792,"config":793},"Get your free trial",{"href":794,"dataGaName":52,"dataGaLocation":795},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":497,"config":797},{"href":56,"dataGaName":57,"dataGaLocation":795},1772652067392]