[{"data":1,"prerenderedAt":814},["ShallowReactive",2],{"/en-us/blog/100-runners-in-less-than-10mins-and-less-than-10-clicks":3,"navigation-en-us":45,"banner-en-us":445,"footer-en-us":455,"blog-post-authors-en-us-Darwin Sanoy|Nupur Sharma":695,"blog-related-posts-en-us-100-runners-in-less-than-10mins-and-less-than-10-clicks":723,"next-steps-en-us":765,"assessment-promotions-en-us":775},{"id":4,"title":5,"authorSlugs":6,"body":9,"categorySlug":10,"config":11,"content":15,"description":9,"extension":29,"isFeatured":13,"meta":30,"navigation":31,"path":32,"publishedDate":22,"seo":33,"stem":38,"tagSlugs":39,"__hash__":44},"blogPosts/en-us/blog/100-runners-in-less-than-10mins-and-less-than-10-clicks.yml","100 Runners In Less Than 10mins And Less Than 10 Clicks",[7,8],"darwin-sanoy","nupur-sharma",null,"engineering",{"slug":12,"featured":13,"template":14},"100-runners-in-less-than-10mins-and-less-than-10-clicks",false,"BlogPost",{"title":16,"description":17,"authors":18,"heroImage":21,"date":22,"body":23,"category":10,"tags":24},"How to provision 100 AWS Graviton GitLab Spot Runners in 10 Minutes for $2/hour","Utilizing the GitLab HA Scaling Runner Vending Machine for AWS Automation to setup 100 GitLab runners on AWS Spot.",[19,20],"Darwin Sanoy","Nupur Sharma","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749669882/Blog/Hero%20Images/hundredgitlabspotrunner.png","2021-08-17","Managing elastically scaled or highly available compute infrastructures is one of the key challenges the cloud was built for. Application scaling concerns can be handled by cloud services that are purpose designed, rigorously tested, and continually improved. This article dives into some specific enablement automation that brings the benefits of AWS Autoscaling Groups (ASG) to runner management. There are benefits to both the largest fleets and single instance runners.\n\nEmbedded in this article is a YouTube video that demonstrates the deployment of 100 GitLab runners on Amazon EC2 Spot compute in less than 10 minutes using less than 10 clicks. The video also shows updating this entire fleet in under 10 minutes to emphasize the time savings of built-in maintenace.\n\nThe information and automation in this article applies to GitLab Private Runners which are deployed on your own compute resources. Self-managed GitLab instances require private runners, but they can also be configured and used with GitLab.com SaaS accounts.\n\n## Well-architected runner management\n\nThere are many different reasons that a customer might need to deploy multiple runners with various characteristics. Some of the more popular ones are:\n\n- Workloads that require large-scale runner fleets.\n- To gain cost savings through Spot compute, uptime scheduling, and ARM architecture.\n- Projects with high demand of CI activity to make sure that the runner is not being held up by jobs on another project.\n- Jobs that have special security requirements, e.g., security credentials, role-based access or managed identities for Continuous Delivery (CD). These security requirements can enable instance-level (AWS IAM Instance Profile) security by allowing runners with sufficient rights to deploy in specific target environments. For example, a CD runner for non-production environments and a different runner for production.\n- Implementing role-based access control rather than user-based. This means users don't have to use secrets to manage security requirements for CI jobs to accomplish their tasks.\n- Development teams can be confident the runner has the same capabilities for CI and CD automation they test through their interactive logins by leveraging a common IAM role.\n\n### The challenges of building production-grade elastic GitLab Runners\n\n[The GitLab Runner](https://docs.gitlab.com/runner/) is the workhorse of GitLab CI and CD capabilities. The runner can handle numerous operating environments and automation functions for a GitLab instance. The GitLab Runner has become very sophisticated due to the broad range of supported environments. In order to successfully configure the GitLab Runner as a set-it-and-forget-it service, the user has to work through many different decisions and considerations. We summarize some of the GitLab Runner-specific considerations that can be challenging:\n\n- There are a lot of configuration options and scenarios to sort through. It can be an iterative process to discover what needs to be done to set up GitLab Runners.\n- Ensuring runners are a production-grade capability requires Infrastructure as Code (IaC) development so that high availability and scaling can be achieved by automatically spawning new instances.\n- Ensuring that runner deregistration happens correctly when GitLab Runners are automatically scaled in.\n- Additional cost-saving configurations, such as Spot compute and scheduled runner uptime, can complicate the automation requirements for AWS Autoscaling Groups (ASGs).\n- Large organizations often want developers to be able to easily self-service deploy runners with various configurations. Service Management Automation (SMA) has been made popular with products like Service Now, AWS Service Catalog, and AWS Control Tower. This automation is compatible with SMA.\n- It can be difficult to map runners to AWS and map AWS to runners in large organizations with numerous runners and AWS accounts.\n\n### Introducing the GitLab HA Scaling Runner Vending Machine for AWS\n\nAn effective way to handle multiple design considerations is to make a reusable tool. To help you with best practice runner deployments on AWS, we created the [GitLab HA Scaling Runner Vending Machine for AWS](https://gitlab.com/guided-explorations/aws/gitlab-runner-autoscaling-aws-asg/) (\"The GitLab Runner Vending Machine\"). It is created in AWS’ Infrastructure as Code, known as CloudFormation.\n\n> **Designed with AWS Well Architected:** This automation has many features beyond the scope of this blog post. The primary focus of this blog post is on managing costs. See the [full list of features here](https://gitlab.com/guided-explorations/aws/gitlab-runner-autoscaling-aws-asg/-/blob/main/FEATURES.md).\n\nThe GitLab Runner Vending Machine has the following cost management and scaling management benefits, exposed as a variety of parameters:\n\n- The ability to leverage Spot compute instances. This is important because it leaves CI/CD pipeline developers in charge of whether specific Gitlab CI/CD jobs run on Spot compute or not.\n- ASG-scheduled scaling so that a runner or runner fleet can be completely shutdown when not in use.\n- The GitLab Runner Vending Machine can leverage ARM compute for Linux - which runs faster and costs less.\n- It can also use ASG to update all runners in a fleet with the latest machine images and GitLab Runner version (or a specific version). When maintenance is not built-in, the labor cost of keeping things up-to-date can be significant.\n- Runner naming and tagging in AWS and GitLab, which eases the burden of locating runner instances and managing orphaned runners registrations, whether it is manual or automated.\n\n### How to save money with The GitLab Runner Vending Machine\n\nSignificant savings are possible with this IaC, whether your team wants to save on a single runner or a fleet of them.\n\nThe savings calculations below are for a single runner and should be linear for a given workload. To calculate your savings for more runners, simply multiply the final result by the number of runner instances. The available \"Runner Minutes\" per hour is calculated as the runner's job concurrency setting multiplied by the minutes in an hour. For this exercise, we'll use job concurrency of \"10\". This number should be changed depending on the instance types you are using and the load testing of your typical CI/CD workloads.\n\nJust like most performance analysis, we are assuming that hardware resource utilization is optimal and consistent. If a runner cluster can sustain respectable performance with 80% CPU loading, this calculation assumes that would be maintained regardless of the size of the cluster.\n\n#### AWS Graviton ARM and Spot savings\n\nThe GitLab Runner engineering team has completed performance testing that demonstrates performance gains of more than 30% on some AWS Graviton (ARM-based) instance types. Assuming that runners are performance-managed for optimized utilization, this gain is a direct cost savings. Just recently, we shared [how deploying GitLab on Arm-based AWS Graviton2 resulted in cost savings of 23% and 36% performance gains](/blog/achieving-23-cost-savings-and-36-performance-gain-using-gitlab-and-gitlab-runner-on-arm-neoverse-based-aws-graviton2-processor/).\n\n![ARM Efficiency Test Results For GitLab Runner](https://about.gitlab.com/images/blogimages/hundred-runners/hundredrunners-image1.png)\nGitLab Runner testing results for ARM-efficiency gains.\n\n\n#### Scheduling savings\n\nThe savings can be dramatic when teams are able to turn off runners when not in use. For instance: Scheduling a runner to operate for 40-hours per week saves 76% when compared to the cost of running it for 168 hours. Runners that are just in use for 10 hours per week saves 94%.\n\n#### Combining scheduling, Spot, and ARM to save 97%\n\nJust for fun, let's see what savings are possible by comparing a standard runner scenario with deploying runners in customized, stand-alone instances to the maximum savings automation can deliver.\n\nImagine I am a developer who set up a custom GitLab Runner on an m5.xlarge instance, which is x86 the architecture, for a development team that works for 40 hours on the same time zone. Since there is no automation, the GitLab Runner runs 24/7. We will assume a job concurrency of 10, which gives 600 \"runner minutes\" per hour of run time. Scheduling uptime, running on Spot, and leveraging ARM can all be achieved quickly by redeploying the runner with The GitLab Runner Vending Machine.\n\nHere is the calculation to run the configuration described above, for one week: On Demand, x86, Always On: 1 x m5.xlarge = .192/hr x 168 hrs/week = **$32/week or $1664/year**\n\nHere are the savings that come from running Spot, ARM, and scheduling the Runner to be up just 40hrs/week: 1 x m6g.large Spot = .0419 x 40hrs/week x 64% (36% better performance) = **$1/week**\n\n$1/$32 x 100 = 3.125% of the original cost for the same work. In other words, **we just saved 97%** without ever impacting the ability to get the job done.\n\nIn short, The GitLab Runner Vending Machine intends to bring the many cost saving mechanisms of AWS Cloud computing to your GitLab Runner fleets.\n\nYou can save costs by using ARM/Graviton instances, Spot compute, or by scheduling uptime. In many cases, you can combine all three savings mechanisms for maximum impact.\n\n### Special pipeline building concerns for Spot Runners\n\nSpot instances can disappear with as little as two minutes of warning. This inevitably means some runners will be terminated while jobs are still in progress. CI/CD pipeline developers must take into account whether a job ought to run on compute resources that can disappear with short notice (so short as to be considered \"no notice\"). This comes down to deciding what jobs are OK to run on Spot and what jobs should instead run on AWS' persistent compute known as \"On-Demand\".\n\nThe GitLab Runner Vending Machine accounts for these constraints by tagging runner instances in GitLab with `computetype-spot` or `computetype-ondemand` – indicating in the \"tags\" segment of GitLab CI/CD jobs if a job should run on Spot compute.\n\nSome types of CI workloads, e.g., mass performance testing or large unit testing suites, may already have work queues and work tracking that make it ideal for Spot compute. Other activities, e.g., polling another system for a deployment status, could suffer a material discrepancy if terminated permaturely. Others, such as building the application, are sort of in the middle. Usually, restarting the build is sufficient.\n\n### Job configuration for Spot\n\nIf you need to reschedule terminated work, it is helpful to configure GitLab’s job `retry:` keyword. When working with a dispatching engine or work queue that automatically accounts for incompleted work by processing agents, the retry configuration is unnecessary.\n\nHere is an example that implements both of these concepts:\n\n```yaml\nmy-scaled-test-suite:\n  parallel: 100\n  tags:\n  - computetype-Spot\n  retry:\n    max: 2\n    when:\n      - runner_system_failure\n      - unknown_failure\n\n```\n\nThe usage and limitations of `retry:` are discussed in greater detail in the [GitLab CI documentation on retry](https://docs.gitlab.com/ee/ci/yaml/#retry).\n\n### How to get started\n\nThe CloudFormation templates for the [GitLab Runner Vending Machine are managed in a public project on GitLab.com](https://gitlab.com/guided-explorations/aws/gitlab-runner-autoscaling-aws-asg/). There is a lot of information in the project about how the solution works and what problems it aims to solve, and will be useful for very experienced AWS builders.\n\nBut to keep it simple for users who want the quickest path to creating runners of all sizes, it also has an \"easy button\" page that has a table that looks like this:\n\n![Easy Button Page Sample](https://about.gitlab.com/images/blogimages/hundred-runners/hundredrunners-image2.png)\nThe easy buttons launch a CloudFormation Quick Create that only requires filling in a few fields.\n\n\nKeep in mind that easy buttons intentionally hide the high degree of customization that is possible with this automation by setting the parameters for the most common scenarios in advance. Advanced AWS users should read more of the documentation in the repository to understand that the GitLab Runner Vending Machine is also capable of creating sophisticated runner fleets.\n\nFirst, click the CloudFormation icons to launch the Easy Button template directly into the CloudFormation Quick Create console. The Quick Create console is designed for simplicity to enable you to complete the prompts and then click one button to launch the stack.\n\n![CloudFormation Quick Create Example](https://about.gitlab.com/images/blogimages/hundred-runners/hundredrunners-image3.png){: .shadow.medium.center}\nThis is a typical Quick Create form for the GitLab Vending Machine easy buttons.\n\n\nNext, select the deploy region by using the drop down menu in the upper right of the console (where the screenshot says \"Oregon\").\n\nIn most cases, you will only need to add your GitLab instance URL (GitLab.com is fine if that is where your repositories are), and the runner token, which you retrieve from the group level or project you wish to attach the runners to. If you are registering against a self-managed instance, you can use the instance-level tokens from the administrator console to register the runner for use across the entire instance. Read on for [instructions for finding Runner Registration Tokens](https://docs.gitlab.com/runner/register/#requirements).\n\nA few other customization parameters are available for your convenience.\n\nNote that the automation attempts to use the default VPC of the region in which you deploy and the default security group for the VPC. In some organizations, default VPCs and/or their security groups are locked. You can deploy to custom VPCs by using the full template instead of an easy button. On the easy button page look for the footnote \"Not any easy button person?\"\" to find a link to the full template.\n\nWatch the video below to see the deployment of provisioning 100 GitLab Spot Runners on AWS in less than 10 minutes and in less than 10 clicks for just $5 per hour.\n\n\u003C!-- blank line -->\n\u003Cfigure class=\"video_container\">\n  \u003Ciframe src=\"https://www.youtube-nocookie.com/embed/EW4RJv5zW4U\" frameborder=\"0\" allowfullscreen=\"true\"> \u003C/iframe>\n\u003C/figure>\n\u003C!-- blank line -->\n\nCheck out the YouTube playlist for more relevant videos about [GitLab and AWS](https://youtube.com/playlist?list=PL05JrBw4t0Ko30Bkf8bAvR-8E441Fy2G9)\n\n### This automation does much, much more\n\nWhile this article focused how much you can saving while using Spot for scaled runners, the underlying automation is capable of many other scenarios. Below is a summary of the additional features and benefits covered in the documentation.\n\n- Scaled runners that are persistent (not Spot) ([see more easy buttons here](https://gitlab.com/guided-explorations/aws/gitlab-runner-autoscaling-aws-asg/-/blob/main/easybuttons.md)).\n- Supports small, single runner setups and scaled ones.\n- Supports GitLab.com SaaS or self-managed instances.\n- Automates OS patching and Runner version upgrading.\n- Supports Windows and Linux.\n- Can be reused with Amazon provisioning services such as Service Catalog and Control Tower.\n- Implements least privilege security throughout.\n- Supports deregistering runners on scale-in or Spot termination.\n\nA full feature list is in the document [Features of GitLab HA Scaling Runner Vending Machine for AWS](https://gitlab.com/guided-explorations/aws/gitlab-runner-autoscaling-aws-asg/-/blob/main/FEATURES.md)\n\n### Easy running\n\nWe hope that this automation will make deployment of runners of all sizes simple for you. We are open to your feedback, suggestions and contributions in the GitLab project.\n",[25,26,27,28],"CI","CD","DevOps","AWS","yml",{},true,"/en-us/blog/100-runners-in-less-than-10mins-and-less-than-10-clicks",{"title":34,"description":17,"ogTitle":34,"ogDescription":17,"noIndex":13,"ogImage":21,"ogUrl":35,"ogSiteName":36,"ogType":37,"canonicalUrls":35},"Setting up 100 AWS Graviton Spot Runners for GitLab","https://about.gitlab.com/blog/100-runners-in-less-than-10mins-and-less-than-10-clicks","https://about.gitlab.com","article","en-us/blog/100-runners-in-less-than-10mins-and-less-than-10-clicks",[40,41,42,43],"ci","cd","devops","aws","NmGzAfPVvEyrn-p13LzOVJFDPc3CQ3QYwy3V3SwdyLE",{"data":46},{"logo":47,"freeTrial":52,"sales":57,"login":62,"items":67,"search":375,"minimal":406,"duo":425,"pricingDeployment":435},{"config":48},{"href":49,"dataGaName":50,"dataGaLocation":51},"/","gitlab logo","header",{"text":53,"config":54},"Get free trial",{"href":55,"dataGaName":56,"dataGaLocation":51},"https://gitlab.com/-/trial_registrations/new?glm_source=about.gitlab.com&glm_content=default-saas-trial/","free trial",{"text":58,"config":59},"Talk to sales",{"href":60,"dataGaName":61,"dataGaLocation":51},"/sales/","sales",{"text":63,"config":64},"Sign in",{"href":65,"dataGaName":66,"dataGaLocation":51},"https://gitlab.com/users/sign_in/","sign in",[68,95,190,195,296,356],{"text":69,"config":70,"cards":72},"Platform",{"dataNavLevelOne":71},"platform",[73,79,87],{"title":69,"description":74,"link":75},"The intelligent orchestration platform for DevSecOps",{"text":76,"config":77},"Explore our Platform",{"href":78,"dataGaName":71,"dataGaLocation":51},"/platform/",{"title":80,"description":81,"link":82},"GitLab Duo Agent Platform","Agentic AI for the entire software lifecycle",{"text":83,"config":84},"Meet GitLab Duo",{"href":85,"dataGaName":86,"dataGaLocation":51},"/gitlab-duo-agent-platform/","gitlab duo agent platform",{"title":88,"description":89,"link":90},"Why GitLab","See the top reasons enterprises choose GitLab",{"text":91,"config":92},"Learn more",{"href":93,"dataGaName":94,"dataGaLocation":51},"/why-gitlab/","why gitlab",{"text":96,"left":31,"config":97,"link":99,"lists":103,"footer":172},"Product",{"dataNavLevelOne":98},"solutions",{"text":100,"config":101},"View all Solutions",{"href":102,"dataGaName":98,"dataGaLocation":51},"/solutions/",[104,128,151],{"title":105,"description":106,"link":107,"items":112},"Automation","CI/CD and automation to accelerate deployment",{"config":108},{"icon":109,"href":110,"dataGaName":111,"dataGaLocation":51},"AutomatedCodeAlt","/solutions/delivery-automation/","automated software delivery",[113,117,120,124],{"text":114,"config":115},"CI/CD",{"href":116,"dataGaLocation":51,"dataGaName":114},"/solutions/continuous-integration/",{"text":80,"config":118},{"href":85,"dataGaLocation":51,"dataGaName":119},"gitlab duo agent platform - product menu",{"text":121,"config":122},"Source Code Management",{"href":123,"dataGaLocation":51,"dataGaName":121},"/solutions/source-code-management/",{"text":125,"config":126},"Automated Software Delivery",{"href":110,"dataGaLocation":51,"dataGaName":127},"Automated software delivery",{"title":129,"description":130,"link":131,"items":136},"Security","Deliver code faster without compromising security",{"config":132},{"href":133,"dataGaName":134,"dataGaLocation":51,"icon":135},"/solutions/application-security-testing/","security and compliance","ShieldCheckLight",[137,141,146],{"text":138,"config":139},"Application Security Testing",{"href":133,"dataGaName":140,"dataGaLocation":51},"Application security testing",{"text":142,"config":143},"Software Supply Chain Security",{"href":144,"dataGaLocation":51,"dataGaName":145},"/solutions/supply-chain/","Software supply chain security",{"text":147,"config":148},"Software Compliance",{"href":149,"dataGaName":150,"dataGaLocation":51},"/solutions/software-compliance/","software compliance",{"title":152,"link":153,"items":158},"Measurement",{"config":154},{"icon":155,"href":156,"dataGaName":157,"dataGaLocation":51},"DigitalTransformation","/solutions/visibility-measurement/","visibility and measurement",[159,163,167],{"text":160,"config":161},"Visibility & Measurement",{"href":156,"dataGaLocation":51,"dataGaName":162},"Visibility and Measurement",{"text":164,"config":165},"Value Stream Management",{"href":166,"dataGaLocation":51,"dataGaName":164},"/solutions/value-stream-management/",{"text":168,"config":169},"Analytics & Insights",{"href":170,"dataGaLocation":51,"dataGaName":171},"/solutions/analytics-and-insights/","Analytics and insights",{"title":173,"items":174},"GitLab for",[175,180,185],{"text":176,"config":177},"Enterprise",{"href":178,"dataGaLocation":51,"dataGaName":179},"/enterprise/","enterprise",{"text":181,"config":182},"Small Business",{"href":183,"dataGaLocation":51,"dataGaName":184},"/small-business/","small business",{"text":186,"config":187},"Public Sector",{"href":188,"dataGaLocation":51,"dataGaName":189},"/solutions/public-sector/","public sector",{"text":191,"config":192},"Pricing",{"href":193,"dataGaName":194,"dataGaLocation":51,"dataNavLevelOne":194},"/pricing/","pricing",{"text":196,"config":197,"link":199,"lists":203,"feature":283},"Resources",{"dataNavLevelOne":198},"resources",{"text":200,"config":201},"View all resources",{"href":202,"dataGaName":198,"dataGaLocation":51},"/resources/",[204,237,255],{"title":205,"items":206},"Getting started",[207,212,217,222,227,232],{"text":208,"config":209},"Install",{"href":210,"dataGaName":211,"dataGaLocation":51},"/install/","install",{"text":213,"config":214},"Quick start guides",{"href":215,"dataGaName":216,"dataGaLocation":51},"/get-started/","quick setup checklists",{"text":218,"config":219},"Learn",{"href":220,"dataGaLocation":51,"dataGaName":221},"https://university.gitlab.com/","learn",{"text":223,"config":224},"Product documentation",{"href":225,"dataGaName":226,"dataGaLocation":51},"https://docs.gitlab.com/","product documentation",{"text":228,"config":229},"Best practice videos",{"href":230,"dataGaName":231,"dataGaLocation":51},"/getting-started-videos/","best practice videos",{"text":233,"config":234},"Integrations",{"href":235,"dataGaName":236,"dataGaLocation":51},"/integrations/","integrations",{"title":238,"items":239},"Discover",[240,245,250],{"text":241,"config":242},"Customer success stories",{"href":243,"dataGaName":244,"dataGaLocation":51},"/customers/","customer success stories",{"text":246,"config":247},"Blog",{"href":248,"dataGaName":249,"dataGaLocation":51},"/blog/","blog",{"text":251,"config":252},"Remote",{"href":253,"dataGaName":254,"dataGaLocation":51},"https://handbook.gitlab.com/handbook/company/culture/all-remote/","remote",{"title":256,"items":257},"Connect",[258,263,268,273,278],{"text":259,"config":260},"GitLab Services",{"href":261,"dataGaName":262,"dataGaLocation":51},"/services/","services",{"text":264,"config":265},"Community",{"href":266,"dataGaName":267,"dataGaLocation":51},"/community/","community",{"text":269,"config":270},"Forum",{"href":271,"dataGaName":272,"dataGaLocation":51},"https://forum.gitlab.com/","forum",{"text":274,"config":275},"Events",{"href":276,"dataGaName":277,"dataGaLocation":51},"/events/","events",{"text":279,"config":280},"Partners",{"href":281,"dataGaName":282,"dataGaLocation":51},"/partners/","partners",{"backgroundColor":284,"textColor":285,"text":286,"image":287,"link":291},"#2f2a6b","#fff","Insights for the future of software development",{"altText":288,"config":289},"the source promo card",{"src":290},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1758208064/dzl0dbift9xdizyelkk4.svg",{"text":292,"config":293},"Read the latest",{"href":294,"dataGaName":295,"dataGaLocation":51},"/the-source/","the source",{"text":297,"config":298,"lists":300},"Company",{"dataNavLevelOne":299},"company",[301],{"items":302},[303,308,314,316,321,326,331,336,341,346,351],{"text":304,"config":305},"About",{"href":306,"dataGaName":307,"dataGaLocation":51},"/company/","about",{"text":309,"config":310,"footerGa":313},"Jobs",{"href":311,"dataGaName":312,"dataGaLocation":51},"/jobs/","jobs",{"dataGaName":312},{"text":274,"config":315},{"href":276,"dataGaName":277,"dataGaLocation":51},{"text":317,"config":318},"Leadership",{"href":319,"dataGaName":320,"dataGaLocation":51},"/company/team/e-group/","leadership",{"text":322,"config":323},"Team",{"href":324,"dataGaName":325,"dataGaLocation":51},"/company/team/","team",{"text":327,"config":328},"Handbook",{"href":329,"dataGaName":330,"dataGaLocation":51},"https://handbook.gitlab.com/","handbook",{"text":332,"config":333},"Investor relations",{"href":334,"dataGaName":335,"dataGaLocation":51},"https://ir.gitlab.com/","investor relations",{"text":337,"config":338},"Trust Center",{"href":339,"dataGaName":340,"dataGaLocation":51},"/security/","trust center",{"text":342,"config":343},"AI Transparency Center",{"href":344,"dataGaName":345,"dataGaLocation":51},"/ai-transparency-center/","ai transparency center",{"text":347,"config":348},"Newsletter",{"href":349,"dataGaName":350,"dataGaLocation":51},"/company/contact/#contact-forms","newsletter",{"text":352,"config":353},"Press",{"href":354,"dataGaName":355,"dataGaLocation":51},"/press/","press",{"text":357,"config":358,"lists":359},"Contact us",{"dataNavLevelOne":299},[360],{"items":361},[362,365,370],{"text":58,"config":363},{"href":60,"dataGaName":364,"dataGaLocation":51},"talk to sales",{"text":366,"config":367},"Support portal",{"href":368,"dataGaName":369,"dataGaLocation":51},"https://support.gitlab.com","support portal",{"text":371,"config":372},"Customer portal",{"href":373,"dataGaName":374,"dataGaLocation":51},"https://customers.gitlab.com/customers/sign_in/","customer portal",{"close":376,"login":377,"suggestions":384},"Close",{"text":378,"link":379},"To search repositories and projects, login to",{"text":380,"config":381},"gitlab.com",{"href":65,"dataGaName":382,"dataGaLocation":383},"search login","search",{"text":385,"default":386},"Suggestions",[387,389,393,395,399,403],{"text":80,"config":388},{"href":85,"dataGaName":80,"dataGaLocation":383},{"text":390,"config":391},"Code Suggestions (AI)",{"href":392,"dataGaName":390,"dataGaLocation":383},"/solutions/code-suggestions/",{"text":114,"config":394},{"href":116,"dataGaName":114,"dataGaLocation":383},{"text":396,"config":397},"GitLab on AWS",{"href":398,"dataGaName":396,"dataGaLocation":383},"/partners/technology-partners/aws/",{"text":400,"config":401},"GitLab on Google Cloud",{"href":402,"dataGaName":400,"dataGaLocation":383},"/partners/technology-partners/google-cloud-platform/",{"text":404,"config":405},"Why GitLab?",{"href":93,"dataGaName":404,"dataGaLocation":383},{"freeTrial":407,"mobileIcon":412,"desktopIcon":417,"secondaryButton":420},{"text":408,"config":409},"Start free trial",{"href":410,"dataGaName":56,"dataGaLocation":411},"https://gitlab.com/-/trials/new/","nav",{"altText":413,"config":414},"Gitlab Icon",{"src":415,"dataGaName":416,"dataGaLocation":411},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1758203874/jypbw1jx72aexsoohd7x.svg","gitlab icon",{"altText":413,"config":418},{"src":419,"dataGaName":416,"dataGaLocation":411},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1758203875/gs4c8p8opsgvflgkswz9.svg",{"text":421,"config":422},"Get Started",{"href":423,"dataGaName":424,"dataGaLocation":411},"https://gitlab.com/-/trial_registrations/new?glm_source=about.gitlab.com/compare/gitlab-vs-github/","get started",{"freeTrial":426,"mobileIcon":431,"desktopIcon":433},{"text":427,"config":428},"Learn more about GitLab Duo",{"href":429,"dataGaName":430,"dataGaLocation":411},"/gitlab-duo/","gitlab duo",{"altText":413,"config":432},{"src":415,"dataGaName":416,"dataGaLocation":411},{"altText":413,"config":434},{"src":419,"dataGaName":416,"dataGaLocation":411},{"freeTrial":436,"mobileIcon":441,"desktopIcon":443},{"text":437,"config":438},"Back to pricing",{"href":193,"dataGaName":439,"dataGaLocation":411,"icon":440},"back to pricing","GoBack",{"altText":413,"config":442},{"src":415,"dataGaName":416,"dataGaLocation":411},{"altText":413,"config":444},{"src":419,"dataGaName":416,"dataGaLocation":411},{"title":446,"button":447,"config":452},"See how agentic AI transforms software delivery",{"text":448,"config":449},"Watch GitLab Transcend now",{"href":450,"dataGaName":451,"dataGaLocation":51},"/events/transcend/virtual/","transcend event",{"layout":453,"icon":454},"release","AiStar",{"data":456},{"text":457,"source":458,"edit":464,"contribute":469,"config":474,"items":479,"minimal":684},"Git is a trademark of Software Freedom Conservancy and our use of 'GitLab' is under license",{"text":459,"config":460},"View page source",{"href":461,"dataGaName":462,"dataGaLocation":463},"https://gitlab.com/gitlab-com/marketing/digital-experience/about-gitlab-com/","page source","footer",{"text":465,"config":466},"Edit this page",{"href":467,"dataGaName":468,"dataGaLocation":463},"https://gitlab.com/gitlab-com/marketing/digital-experience/about-gitlab-com/-/blob/main/content/","web ide",{"text":470,"config":471},"Please contribute",{"href":472,"dataGaName":473,"dataGaLocation":463},"https://gitlab.com/gitlab-com/marketing/digital-experience/about-gitlab-com/-/blob/main/CONTRIBUTING.md/","please contribute",{"twitter":475,"facebook":476,"youtube":477,"linkedin":478},"https://twitter.com/gitlab","https://www.facebook.com/gitlab","https://www.youtube.com/channel/UCnMGQ8QHMAnVIsI3xJrihhg","https://www.linkedin.com/company/gitlab-com",[480,527,579,623,650],{"title":191,"links":481,"subMenu":496},[482,486,491],{"text":483,"config":484},"View plans",{"href":193,"dataGaName":485,"dataGaLocation":463},"view plans",{"text":487,"config":488},"Why Premium?",{"href":489,"dataGaName":490,"dataGaLocation":463},"/pricing/premium/","why premium",{"text":492,"config":493},"Why Ultimate?",{"href":494,"dataGaName":495,"dataGaLocation":463},"/pricing/ultimate/","why ultimate",[497],{"title":498,"links":499},"Contact Us",[500,503,505,507,512,517,522],{"text":501,"config":502},"Contact sales",{"href":60,"dataGaName":61,"dataGaLocation":463},{"text":366,"config":504},{"href":368,"dataGaName":369,"dataGaLocation":463},{"text":371,"config":506},{"href":373,"dataGaName":374,"dataGaLocation":463},{"text":508,"config":509},"Status",{"href":510,"dataGaName":511,"dataGaLocation":463},"https://status.gitlab.com/","status",{"text":513,"config":514},"Terms of use",{"href":515,"dataGaName":516,"dataGaLocation":463},"/terms/","terms of use",{"text":518,"config":519},"Privacy statement",{"href":520,"dataGaName":521,"dataGaLocation":463},"/privacy/","privacy statement",{"text":523,"config":524},"Cookie preferences",{"dataGaName":525,"dataGaLocation":463,"id":526,"isOneTrustButton":31},"cookie preferences","ot-sdk-btn",{"title":96,"links":528,"subMenu":537},[529,533],{"text":530,"config":531},"DevSecOps platform",{"href":78,"dataGaName":532,"dataGaLocation":463},"devsecops platform",{"text":534,"config":535},"AI-Assisted Development",{"href":429,"dataGaName":536,"dataGaLocation":463},"ai-assisted development",[538],{"title":539,"links":540},"Topics",[541,546,551,554,559,564,569,574],{"text":542,"config":543},"CICD",{"href":544,"dataGaName":545,"dataGaLocation":463},"/topics/ci-cd/","cicd",{"text":547,"config":548},"GitOps",{"href":549,"dataGaName":550,"dataGaLocation":463},"/topics/gitops/","gitops",{"text":27,"config":552},{"href":553,"dataGaName":42,"dataGaLocation":463},"/topics/devops/",{"text":555,"config":556},"Version Control",{"href":557,"dataGaName":558,"dataGaLocation":463},"/topics/version-control/","version control",{"text":560,"config":561},"DevSecOps",{"href":562,"dataGaName":563,"dataGaLocation":463},"/topics/devsecops/","devsecops",{"text":565,"config":566},"Cloud Native",{"href":567,"dataGaName":568,"dataGaLocation":463},"/topics/cloud-native/","cloud native",{"text":570,"config":571},"AI for Coding",{"href":572,"dataGaName":573,"dataGaLocation":463},"/topics/devops/ai-for-coding/","ai for coding",{"text":575,"config":576},"Agentic AI",{"href":577,"dataGaName":578,"dataGaLocation":463},"/topics/agentic-ai/","agentic ai",{"title":580,"links":581},"Solutions",[582,584,586,591,595,598,602,605,607,610,613,618],{"text":138,"config":583},{"href":133,"dataGaName":138,"dataGaLocation":463},{"text":127,"config":585},{"href":110,"dataGaName":111,"dataGaLocation":463},{"text":587,"config":588},"Agile development",{"href":589,"dataGaName":590,"dataGaLocation":463},"/solutions/agile-delivery/","agile delivery",{"text":592,"config":593},"SCM",{"href":123,"dataGaName":594,"dataGaLocation":463},"source code management",{"text":542,"config":596},{"href":116,"dataGaName":597,"dataGaLocation":463},"continuous integration & delivery",{"text":599,"config":600},"Value stream management",{"href":166,"dataGaName":601,"dataGaLocation":463},"value stream management",{"text":547,"config":603},{"href":604,"dataGaName":550,"dataGaLocation":463},"/solutions/gitops/",{"text":176,"config":606},{"href":178,"dataGaName":179,"dataGaLocation":463},{"text":608,"config":609},"Small business",{"href":183,"dataGaName":184,"dataGaLocation":463},{"text":611,"config":612},"Public sector",{"href":188,"dataGaName":189,"dataGaLocation":463},{"text":614,"config":615},"Education",{"href":616,"dataGaName":617,"dataGaLocation":463},"/solutions/education/","education",{"text":619,"config":620},"Financial services",{"href":621,"dataGaName":622,"dataGaLocation":463},"/solutions/finance/","financial services",{"title":196,"links":624},[625,627,629,631,634,636,638,640,642,644,646,648],{"text":208,"config":626},{"href":210,"dataGaName":211,"dataGaLocation":463},{"text":213,"config":628},{"href":215,"dataGaName":216,"dataGaLocation":463},{"text":218,"config":630},{"href":220,"dataGaName":221,"dataGaLocation":463},{"text":223,"config":632},{"href":225,"dataGaName":633,"dataGaLocation":463},"docs",{"text":246,"config":635},{"href":248,"dataGaName":249,"dataGaLocation":463},{"text":241,"config":637},{"href":243,"dataGaName":244,"dataGaLocation":463},{"text":251,"config":639},{"href":253,"dataGaName":254,"dataGaLocation":463},{"text":259,"config":641},{"href":261,"dataGaName":262,"dataGaLocation":463},{"text":264,"config":643},{"href":266,"dataGaName":267,"dataGaLocation":463},{"text":269,"config":645},{"href":271,"dataGaName":272,"dataGaLocation":463},{"text":274,"config":647},{"href":276,"dataGaName":277,"dataGaLocation":463},{"text":279,"config":649},{"href":281,"dataGaName":282,"dataGaLocation":463},{"title":297,"links":651},[652,654,656,658,660,662,664,668,673,675,677,679],{"text":304,"config":653},{"href":306,"dataGaName":299,"dataGaLocation":463},{"text":309,"config":655},{"href":311,"dataGaName":312,"dataGaLocation":463},{"text":317,"config":657},{"href":319,"dataGaName":320,"dataGaLocation":463},{"text":322,"config":659},{"href":324,"dataGaName":325,"dataGaLocation":463},{"text":327,"config":661},{"href":329,"dataGaName":330,"dataGaLocation":463},{"text":332,"config":663},{"href":334,"dataGaName":335,"dataGaLocation":463},{"text":665,"config":666},"Sustainability",{"href":667,"dataGaName":665,"dataGaLocation":463},"/sustainability/",{"text":669,"config":670},"Diversity, inclusion and belonging (DIB)",{"href":671,"dataGaName":672,"dataGaLocation":463},"/diversity-inclusion-belonging/","Diversity, inclusion and belonging",{"text":337,"config":674},{"href":339,"dataGaName":340,"dataGaLocation":463},{"text":347,"config":676},{"href":349,"dataGaName":350,"dataGaLocation":463},{"text":352,"config":678},{"href":354,"dataGaName":355,"dataGaLocation":463},{"text":680,"config":681},"Modern Slavery Transparency Statement",{"href":682,"dataGaName":683,"dataGaLocation":463},"https://handbook.gitlab.com/handbook/legal/modern-slavery-act-transparency-statement/","modern slavery transparency statement",{"items":685},[686,689,692],{"text":687,"config":688},"Terms",{"href":515,"dataGaName":516,"dataGaLocation":463},{"text":690,"config":691},"Cookies",{"dataGaName":525,"dataGaLocation":463,"id":526,"isOneTrustButton":31},{"text":693,"config":694},"Privacy",{"href":520,"dataGaName":521,"dataGaLocation":463},[696,711],{"id":697,"title":19,"body":9,"config":698,"content":700,"description":9,"extension":29,"meta":706,"navigation":31,"path":707,"seo":708,"stem":709,"__hash__":710},"blogAuthors/en-us/blog/authors/darwin-sanoy.yml",{"template":699},"BlogAuthor",{"role":701,"name":19,"config":702},"Field Chief Cloud Architect",{"headshot":703,"linkedin":704,"ctfId":705},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749659751/Blog/Author%20Headshots/Darwin-Sanoy-headshot-395-square-gitlab-teampage-avatar.png","https://linkedin.com/in/darwinsanoy","DarwinJS",{},"/en-us/blog/authors/darwin-sanoy",{},"en-us/blog/authors/darwin-sanoy","UkMMwmU5o2e6Y-wBltA9E_z96LvHuB-bG6VW9DsLzIY",{"id":712,"title":20,"body":9,"config":713,"content":714,"description":9,"extension":29,"meta":718,"navigation":31,"path":719,"seo":720,"stem":721,"__hash__":722},"blogAuthors/en-us/blog/authors/nupur-sharma.yml",{"template":699},{"name":20,"config":715},{"headshot":716,"ctfId":717},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749659488/Blog/Author%20Headshots/gitlab-logo-extra-whitespace.png","6p7RQDl0cDWnAxU8yu2vVK",{},"/en-us/blog/authors/nupur-sharma",{},"en-us/blog/authors/nupur-sharma","W1cwk5soVjeBGguklBuk4kAvUCs-8zwbXzCNpD6ju3g",[724,737,749],{"content":725,"config":735},{"title":726,"description":727,"authors":728,"heroImage":730,"date":731,"category":10,"tags":732,"body":734},"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.",[729],"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",[267,617,733],"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":736,"featured":13,"template":14},"how-iit-bombay-students-code-future-with-gitlab",{"content":738,"config":747},{"title":739,"description":740,"authors":741,"heroImage":742,"date":743,"category":10,"tags":744,"body":746},"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.",[729],"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",[617,267,745],"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":748,"featured":31,"template":14},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":750,"config":763},{"category":10,"tags":751,"body":754,"date":755,"updatedDate":756,"heroImage":757,"authors":758,"title":761,"description":762},[752,753,114],"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",[759,760],"Evgeny Rudinsky","Michael Leopard","Guide: Migrate from Azure DevOps to GitLab","Learn how to carry out the full migration from Azure DevOps to GitLab using GitLab Professional Services migration tools — from planning and execution to post-migration follow-up tasks.",{"featured":31,"template":14,"slug":764},"migration-from-azure-devops-to-gitlab",{"header":766,"blurb":767,"button":768,"secondaryButton":773},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":769,"config":770},"Get your free trial",{"href":771,"dataGaName":56,"dataGaLocation":772},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":501,"config":774},{"href":60,"dataGaName":61,"dataGaLocation":772},{"promotions":776},[777,791,802],{"id":778,"categories":779,"header":781,"text":782,"button":783,"image":788},"ai-modernization",[780],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":784,"config":785},"Get your AI maturity score",{"href":786,"dataGaName":787,"dataGaLocation":249},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":789},{"src":790},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":792,"categories":793,"header":794,"text":782,"button":795,"image":799},"devops-modernization",[745,563],"Are you just managing tools or shipping innovation?",{"text":796,"config":797},"Get your DevOps maturity score",{"href":798,"dataGaName":787,"dataGaLocation":249},"/assessments/devops-modernization-assessment/",{"config":800},{"src":801},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":803,"categories":804,"header":806,"text":782,"button":807,"image":811},"security-modernization",[805],"security","Are you trading speed for security?",{"text":808,"config":809},"Get your security maturity score",{"href":810,"dataGaName":787,"dataGaLocation":249},"/assessments/security-modernization-assessment/",{"config":812},{"src":813},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",1772652059356]