[{"data":1,"prerenderedAt":793},["ShallowReactive",2],{"/en-us/blog/autoscale-ci-runners":3,"navigation-en-us":38,"banner-en-us":437,"footer-en-us":447,"blog-post-authors-en-us-Max Woolf":688,"blog-related-posts-en-us-autoscale-ci-runners":702,"assessment-promotions-en-us":744,"next-steps-en-us":783},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":25,"isFeatured":12,"meta":26,"navigation":27,"path":28,"publishedDate":20,"seo":29,"stem":33,"tagSlugs":34,"__hash__":37},"blogPosts/en-us/blog/autoscale-ci-runners.yml","Autoscale Ci Runners",[7],"max-woolf",null,"engineering",{"slug":11,"featured":12,"template":13},"autoscale-ci-runners",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"Autoscale GitLab CI/CD runners and save 90% on EC2 costs","Guest author Max Woolf shows how his team makes big savings with an autoscaling cluster of GitLab CI/CD runners.",[18],"Max Woolf","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749680305/Blog/Hero%20Images/autoscale-gitlab-ci-runners.jpg","2017-11-23","At [Substrakt Health](https://substrakthealth.com/), we use continuous integration workers to test our software every time new code is written and pushed, but that computing capacity can be expensive and hard to predict. This tutorial shows you how to set up an autoscaling [cluster of GitLab CI/CD](/topics/ci-cd/) runners using docker-machine and AWS.\n\n\u003C!-- more -->\n\nCode quality is **always** a top priority for us. We want to know that our code works every time and when it stops working we want to know immediately. We use [GitLab CI/CD](/solutions/continuous-integration/) to run our tests every time we push new code and before every deployment. GitLab CI/CD lets us split this work across multiple servers and scale up and down capacity as required to keep costs down for us. This tutorial will show you how to set up an autoscaling CI/CD cluster for GitLab and save up to 90 percent on costs using AWS EC2 Spot Instances.\n\nGitLab CI/CD allows us to split our jobs across multiple machines. By default, each new worker node requires some setup work to provision and attach it to our GitLab instance, but we can also use the autoscaling mode to provision a single machine and let that machine decide how much capacity is required and then spin up or down further instances as required.\n\n>**A warning**: This tutorial will not be covered entirely by the AWS free usage tier. It’s going to cost money to try this out.\n\n## Creating the spawner\n\nFirst off, we need a spawner machine. This runs 24/7 and checks that GitLab CI/CD has enough capacity to run the jobs currently in the queue. **It doesn’t run any jobs itself.**\n\nWe use Ubuntu 16.04 LTS for our internal tooling, so just create an EC2 instance (*t2.micro* is enough and is included in the free tier.) Setting up VPCs and related subnets is out of the scope of this article, we’ll assume that you’re working in the default VPC. Then we need to install a bunch of software on our machine to set it up.\n\n## Installing gitlab-runner\n\ngitlab-runner is the main software we need to complete this task. Installing it on Ubuntu is really easy.\n\n```shell\ncurl -L https://packages.gitlab.com/install/repositories/runner/gitlab-ci-multi-runner/script.deb.sh | sudo bash\n```\n\n```shell\nsudo apt-get install gitlab-ci-multi-runner\n```\n\n\u003Cimg src=\"https://about.gitlab.com/images/blogimages/auto-scale-ci-runners-gif.gif\" alt=\"Installing gitlab-runner\" style=\"width: 700px;\"/>\n\nOnce you’ve done that, register the runner on your GitLab instance. Do this as you normally would with any other GitLab CI/CD runner but choose **docker+machine** as the runner. Docker Machine is the software required to spin up new virtual machines and install Docker on them.\n\n## Installing Docker Machine\n\nDocker Machine is a handy bit of software that allows one host running Docker to spin up and provision other machines running Docker. Installing it is even easier:\n\n```shell\ncurl -L https://github.com/docker/machine/releases/download/v0.12.2/docker-machine-`uname -s`-`uname -m` >/tmp/docker-machine &&\nchmod +x /tmp/docker-machine &&\nsudo cp /tmp/docker-machine /usr/local/bin/docker-machine\n```\n\nThis will install the docker-machine binary in your PATH.\n\n## Configuring gitlab-runner\n\nBy default, gitlab-runner will not work in the autoscaling mode we want. It’ll just run a job by default and then stop. We want to configure this machine to no longer run tests but to spin up new Docker Machines as and when necessary. Open your gitlab-runner config file, usually found in `/etc/gitlab-runner/config.toml` and make some changes. This is our example (with sensitive information removed). Let’s go through some of the important lines.\n\n```text\nconcurrent = 12\ncheck_interval = 0\n\n[[runners]]\n  name = \"aws-gitlab-runner-spawner\"\n  limit = 6\n  url = \"https://git.substrakt.com/ci\"\n  token = \"xxxxx\"\n  executor = \"docker+machine\"\n  [runners.docker]\n    tls_verify = false\n    image = \"ruby:2.3.1\"\n    privileged = true\n    disable_cache = false\n    volumes = [\"/cache\"]\n    shm_size = 0\n  [runners.machine]\n    IdleCount = 0\n    MachineDriver = \"amazonec2\"\n    MachineName = \"runner-%s\"\n    MachineOptions = [\"amazonec2-access-key=XXXX\", \"amazonec2-secret-key=XXXX\", \"amazonec2-ssh-user=ubuntu\", \"amazonec2-region=eu-west-2\", \"amazonec2-instance-type=m4.xlarge\", \"amazonec2-ami=ami-996372fd\", \"amazonec2-vpc-id=vpc-xxxxx\", \"amazonec2-subnet-id=subnet-xxxxx\", \"amazonec2-zone=a\", \"amazonec2-root-size=32\", \"amazonec2-request-spot-instance=true\", \"amazonec2-spot-price=0.03\"]\n    IdleTime = 1800\n\n```\n\n```text\nconcurrent = 12\n```\n\nThis tells GitLab CI/CD that in total, it should attempt to run 12 jobs simultaneously across all child workers.\n\n```text\nlimit = 6\n```\n\nThis tells GitLab CI/CD that in total, it should use for running jobs a maximum of six worker nodes. You’ll need to tweak this value depending on the resources your jobs need and the resources of your child nodes. There’s no right answer here but generally we found it wasn’t a good idea to have more than the number of CPUs – 1 of jobs running per node but again this is a bit of a ‘finger-in-the-air’ calculation as it really depends on your tech stack.\n\n```text\nIdleCount = 0\n```\n\nThis tells GitLab CI/CD not to run any machines constantly (whilst idle). This means when nobody is running a job, or no jobs are queued to spin down all of the worker nodes after an amount of time (IdleTime at the bottom of the file). We power our nodes down after half an hour of no use. This does have the consequence of there being a short wait when we start our day, but it saves us money as we’re not using computing power when it’s not required.\n\nIf you're interested in more about how `concurrent`, `limit` and `IdleCount` are defining the maximum number of jobs and nodes that will be used, you can find a more detailed description in Runner's autoscale configuration document: [Autoscaling algorithm and parameters](https://docs.gitlab.com/runner/configuration/autoscale.html#autoscaling-algorithm-and-parameters), [How parameters generate the upper limit of running machines](https://docs.gitlab.com/runner/configuration/autoscale.html#how-concurrent-limit-and-idlecount-generate-the-upper-limit-of-running-machines).\n\n```text\nMachineOptions = [\"amazonec2-access-key=XXXX\", \"amazonec2-secret-key=XXXX\", \"amazonec2-ssh-user=ubuntu\", \"amazonec2-region=eu-west-2\", \"amazonec2-instance-type=m4.xlarge\", \"amazonec2-ami=ami-996372fd\", \"amazonec2-vpc-id=vpc-xxxxx\", \"amazonec2-subnet-id=subnet-xxxxx\", \"amazonec2-zone=a\", \"amazonec2-root-size=32\", \"amazonec2-request-spot-instance=true\", \"amazonec2-spot-price=0.03\"]\n```\n\nThis is where the magic happens. This is where we set our options for Docker Machine. It defines the size, type and price of our runners. I’ll run through each of the non-obvious options.\n\n```text\namazonec2-vpc-id=vpc-xxxxx & amazonec2-subnet-id=subnet-xxxxx\n```\n\nThis is the VPC and associated subnet ID. Generally, you’d want this in your default VPC in a public subnet. We run our jobs in a private VPC with internal peering connections to other VPCs due to regulatory constraints.\n\n```text\namazonec2-region=eu-west-2\n```\n\nThis is the AWS region. We run all of our infrastructure in the EU (London) region.\n\n```text\namazonec2-instance-type=m4.xlarge\n```\n\nThis is the size of the instance we want for each of our runners. This setting can have massive implications on cost and it can be a tricky balancing act. Choose too small and your jobs take forever to run due to a lack of resources (more time = more money) but choose too large and you have unused compute capacity which costs you money you don’t need to spend. Again, there’s no right answer here, it’s about what works for your workload. We found m4.xlarge works for us.\n\n## Save up to 90 percent on EC2 costs using Spot Instances\n\nSpot Instances are magic. They allow us to bid for unused capacity in the AWS infrastructure and often can mean that EC2 costs can be dramatically lower. We’re currently seeing discounts of around 85 percent on our EC2 bills due to using Spot Instances. Setting them up for use on GitLab CI/CD is really easy too. There is (of course) a downside. If our bid price for VMs is exceeded, then our instances shut down with only a few minutes notice. But as long as our bid is high enough, this isn’t an issue. Pricing in the spot market is insanely complex but in eu-west-2 at least, prices for m4.large and xlarge instances appear to have been static for months so a bid 10-20 percent higher than the current spot price appears to be a safe bet. Just keep your eyes peeled. The current spot price for an m4.xlarge instance is $0.026. We’ve set our maximum price at $0.03 to give us some wiggle room. At time of writing, the on-demand price is $0.232. The numbers speak for themselves.\n\n>Note: Spot pricing can vary significantly between instance sizes, regions and even availability zones in the same region. This guide assumes that spot pricing won’t vary massively or that you’ve set a good buffer above the current spot price to avoid outages.\n\n```text\namazonec2-request-spot-instance=true & amazonec2-spot-price=0.03\n```\n\nThis tells GitLab CI/CD that instead of just spawning new EC2 instances at full price, that it should request Spot Instances at the current spot price, setting a maximum bid that it should not exceed per hour, in USD (regardless of what currency you’re billed in. We’re billed in GBP, but Spot Instances are still calculated in USD.) The maximum bid is whatever you’re comfortable paying. We tend to set it close to the on-demand price because we’re looking for any discount. As long as we’re not paying more than we otherwise would, it’s fine with us. Your financial constraints may affect your decisions differently.\n\n>Update: From October, AWS will charge in seconds, rather than hours used, making the potential savings even higher for unused partial hours.\n\nWe’d love to see how you get along with this so please let us know. You can contact me max [at] substrakthealth [dot] com. For us, it’s saved us time and money and that’s never a bad thing.\n\n## About the Guest Author\n\nMax Woolf is a Senior Developer at Substrakt Health. Based in the UK, they use innovative technology to transform how primary care providers organize and deliver care to patients in a sustainable NHS.\n\n_[Autoscale GitLab CI runners and save 90% on EC2 costs](https://substrakthealth.com/autoscale-gitlab-ci-runners-and-save-90-on-ec2-costs/) was originally published on Substrakt Health's blog._\n\nCover image by [Sebastien Gabriel](https://unsplash.com/@sgabriel) on Unsplash\n",[23,24],"user stories","CI/CD","yml",{},true,"/en-us/blog/autoscale-ci-runners",{"title":15,"description":16,"ogTitle":15,"ogDescription":16,"noIndex":12,"ogImage":19,"ogUrl":30,"ogSiteName":31,"ogType":32,"canonicalUrls":30},"https://about.gitlab.com/blog/autoscale-ci-runners","https://about.gitlab.com","article","en-us/blog/autoscale-ci-runners",[35,36],"user-stories","cicd","FfevhkNhWcU_LqxWkjuiBCdyOwM7MnvxIsPVZMKKoXI",{"data":39},{"logo":40,"freeTrial":45,"sales":50,"login":55,"items":60,"search":367,"minimal":398,"duo":417,"pricingDeployment":427},{"config":41},{"href":42,"dataGaName":43,"dataGaLocation":44},"/","gitlab logo","header",{"text":46,"config":47},"Get free trial",{"href":48,"dataGaName":49,"dataGaLocation":44},"https://gitlab.com/-/trial_registrations/new?glm_source=about.gitlab.com&glm_content=default-saas-trial/","free trial",{"text":51,"config":52},"Talk to sales",{"href":53,"dataGaName":54,"dataGaLocation":44},"/sales/","sales",{"text":56,"config":57},"Sign in",{"href":58,"dataGaName":59,"dataGaLocation":44},"https://gitlab.com/users/sign_in/","sign in",[61,88,182,187,288,348],{"text":62,"config":63,"cards":65},"Platform",{"dataNavLevelOne":64},"platform",[66,72,80],{"title":62,"description":67,"link":68},"The intelligent orchestration platform for DevSecOps",{"text":69,"config":70},"Explore our Platform",{"href":71,"dataGaName":64,"dataGaLocation":44},"/platform/",{"title":73,"description":74,"link":75},"GitLab Duo Agent Platform","Agentic AI for the entire software lifecycle",{"text":76,"config":77},"Meet GitLab Duo",{"href":78,"dataGaName":79,"dataGaLocation":44},"/gitlab-duo-agent-platform/","gitlab duo agent platform",{"title":81,"description":82,"link":83},"Why GitLab","See the top reasons enterprises choose GitLab",{"text":84,"config":85},"Learn more",{"href":86,"dataGaName":87,"dataGaLocation":44},"/why-gitlab/","why gitlab",{"text":89,"left":27,"config":90,"link":92,"lists":96,"footer":164},"Product",{"dataNavLevelOne":91},"solutions",{"text":93,"config":94},"View all Solutions",{"href":95,"dataGaName":91,"dataGaLocation":44},"/solutions/",[97,120,143],{"title":98,"description":99,"link":100,"items":105},"Automation","CI/CD and automation to accelerate deployment",{"config":101},{"icon":102,"href":103,"dataGaName":104,"dataGaLocation":44},"AutomatedCodeAlt","/solutions/delivery-automation/","automated software delivery",[106,109,112,116],{"text":24,"config":107},{"href":108,"dataGaLocation":44,"dataGaName":24},"/solutions/continuous-integration/",{"text":73,"config":110},{"href":78,"dataGaLocation":44,"dataGaName":111},"gitlab duo agent platform - product menu",{"text":113,"config":114},"Source Code Management",{"href":115,"dataGaLocation":44,"dataGaName":113},"/solutions/source-code-management/",{"text":117,"config":118},"Automated Software Delivery",{"href":103,"dataGaLocation":44,"dataGaName":119},"Automated software delivery",{"title":121,"description":122,"link":123,"items":128},"Security","Deliver code faster without compromising security",{"config":124},{"href":125,"dataGaName":126,"dataGaLocation":44,"icon":127},"/solutions/application-security-testing/","security and compliance","ShieldCheckLight",[129,133,138],{"text":130,"config":131},"Application Security Testing",{"href":125,"dataGaName":132,"dataGaLocation":44},"Application security testing",{"text":134,"config":135},"Software Supply Chain Security",{"href":136,"dataGaLocation":44,"dataGaName":137},"/solutions/supply-chain/","Software supply chain security",{"text":139,"config":140},"Software Compliance",{"href":141,"dataGaName":142,"dataGaLocation":44},"/solutions/software-compliance/","software compliance",{"title":144,"link":145,"items":150},"Measurement",{"config":146},{"icon":147,"href":148,"dataGaName":149,"dataGaLocation":44},"DigitalTransformation","/solutions/visibility-measurement/","visibility and measurement",[151,155,159],{"text":152,"config":153},"Visibility & Measurement",{"href":148,"dataGaLocation":44,"dataGaName":154},"Visibility and Measurement",{"text":156,"config":157},"Value Stream Management",{"href":158,"dataGaLocation":44,"dataGaName":156},"/solutions/value-stream-management/",{"text":160,"config":161},"Analytics & Insights",{"href":162,"dataGaLocation":44,"dataGaName":163},"/solutions/analytics-and-insights/","Analytics and insights",{"title":165,"items":166},"GitLab for",[167,172,177],{"text":168,"config":169},"Enterprise",{"href":170,"dataGaLocation":44,"dataGaName":171},"/enterprise/","enterprise",{"text":173,"config":174},"Small Business",{"href":175,"dataGaLocation":44,"dataGaName":176},"/small-business/","small business",{"text":178,"config":179},"Public Sector",{"href":180,"dataGaLocation":44,"dataGaName":181},"/solutions/public-sector/","public sector",{"text":183,"config":184},"Pricing",{"href":185,"dataGaName":186,"dataGaLocation":44,"dataNavLevelOne":186},"/pricing/","pricing",{"text":188,"config":189,"link":191,"lists":195,"feature":275},"Resources",{"dataNavLevelOne":190},"resources",{"text":192,"config":193},"View all resources",{"href":194,"dataGaName":190,"dataGaLocation":44},"/resources/",[196,229,247],{"title":197,"items":198},"Getting started",[199,204,209,214,219,224],{"text":200,"config":201},"Install",{"href":202,"dataGaName":203,"dataGaLocation":44},"/install/","install",{"text":205,"config":206},"Quick start guides",{"href":207,"dataGaName":208,"dataGaLocation":44},"/get-started/","quick setup checklists",{"text":210,"config":211},"Learn",{"href":212,"dataGaLocation":44,"dataGaName":213},"https://university.gitlab.com/","learn",{"text":215,"config":216},"Product documentation",{"href":217,"dataGaName":218,"dataGaLocation":44},"https://docs.gitlab.com/","product documentation",{"text":220,"config":221},"Best practice videos",{"href":222,"dataGaName":223,"dataGaLocation":44},"/getting-started-videos/","best practice videos",{"text":225,"config":226},"Integrations",{"href":227,"dataGaName":228,"dataGaLocation":44},"/integrations/","integrations",{"title":230,"items":231},"Discover",[232,237,242],{"text":233,"config":234},"Customer success stories",{"href":235,"dataGaName":236,"dataGaLocation":44},"/customers/","customer success stories",{"text":238,"config":239},"Blog",{"href":240,"dataGaName":241,"dataGaLocation":44},"/blog/","blog",{"text":243,"config":244},"Remote",{"href":245,"dataGaName":246,"dataGaLocation":44},"https://handbook.gitlab.com/handbook/company/culture/all-remote/","remote",{"title":248,"items":249},"Connect",[250,255,260,265,270],{"text":251,"config":252},"GitLab Services",{"href":253,"dataGaName":254,"dataGaLocation":44},"/services/","services",{"text":256,"config":257},"Community",{"href":258,"dataGaName":259,"dataGaLocation":44},"/community/","community",{"text":261,"config":262},"Forum",{"href":263,"dataGaName":264,"dataGaLocation":44},"https://forum.gitlab.com/","forum",{"text":266,"config":267},"Events",{"href":268,"dataGaName":269,"dataGaLocation":44},"/events/","events",{"text":271,"config":272},"Partners",{"href":273,"dataGaName":274,"dataGaLocation":44},"/partners/","partners",{"backgroundColor":276,"textColor":277,"text":278,"image":279,"link":283},"#2f2a6b","#fff","Insights for the future of software development",{"altText":280,"config":281},"the source promo card",{"src":282},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1758208064/dzl0dbift9xdizyelkk4.svg",{"text":284,"config":285},"Read the latest",{"href":286,"dataGaName":287,"dataGaLocation":44},"/the-source/","the source",{"text":289,"config":290,"lists":292},"Company",{"dataNavLevelOne":291},"company",[293],{"items":294},[295,300,306,308,313,318,323,328,333,338,343],{"text":296,"config":297},"About",{"href":298,"dataGaName":299,"dataGaLocation":44},"/company/","about",{"text":301,"config":302,"footerGa":305},"Jobs",{"href":303,"dataGaName":304,"dataGaLocation":44},"/jobs/","jobs",{"dataGaName":304},{"text":266,"config":307},{"href":268,"dataGaName":269,"dataGaLocation":44},{"text":309,"config":310},"Leadership",{"href":311,"dataGaName":312,"dataGaLocation":44},"/company/team/e-group/","leadership",{"text":314,"config":315},"Team",{"href":316,"dataGaName":317,"dataGaLocation":44},"/company/team/","team",{"text":319,"config":320},"Handbook",{"href":321,"dataGaName":322,"dataGaLocation":44},"https://handbook.gitlab.com/","handbook",{"text":324,"config":325},"Investor relations",{"href":326,"dataGaName":327,"dataGaLocation":44},"https://ir.gitlab.com/","investor relations",{"text":329,"config":330},"Trust Center",{"href":331,"dataGaName":332,"dataGaLocation":44},"/security/","trust center",{"text":334,"config":335},"AI Transparency Center",{"href":336,"dataGaName":337,"dataGaLocation":44},"/ai-transparency-center/","ai transparency center",{"text":339,"config":340},"Newsletter",{"href":341,"dataGaName":342,"dataGaLocation":44},"/company/contact/#contact-forms","newsletter",{"text":344,"config":345},"Press",{"href":346,"dataGaName":347,"dataGaLocation":44},"/press/","press",{"text":349,"config":350,"lists":351},"Contact us",{"dataNavLevelOne":291},[352],{"items":353},[354,357,362],{"text":51,"config":355},{"href":53,"dataGaName":356,"dataGaLocation":44},"talk to sales",{"text":358,"config":359},"Support portal",{"href":360,"dataGaName":361,"dataGaLocation":44},"https://support.gitlab.com","support portal",{"text":363,"config":364},"Customer portal",{"href":365,"dataGaName":366,"dataGaLocation":44},"https://customers.gitlab.com/customers/sign_in/","customer portal",{"close":368,"login":369,"suggestions":376},"Close",{"text":370,"link":371},"To search repositories and projects, login to",{"text":372,"config":373},"gitlab.com",{"href":58,"dataGaName":374,"dataGaLocation":375},"search login","search",{"text":377,"default":378},"Suggestions",[379,381,385,387,391,395],{"text":73,"config":380},{"href":78,"dataGaName":73,"dataGaLocation":375},{"text":382,"config":383},"Code Suggestions (AI)",{"href":384,"dataGaName":382,"dataGaLocation":375},"/solutions/code-suggestions/",{"text":24,"config":386},{"href":108,"dataGaName":24,"dataGaLocation":375},{"text":388,"config":389},"GitLab on AWS",{"href":390,"dataGaName":388,"dataGaLocation":375},"/partners/technology-partners/aws/",{"text":392,"config":393},"GitLab on Google Cloud",{"href":394,"dataGaName":392,"dataGaLocation":375},"/partners/technology-partners/google-cloud-platform/",{"text":396,"config":397},"Why GitLab?",{"href":86,"dataGaName":396,"dataGaLocation":375},{"freeTrial":399,"mobileIcon":404,"desktopIcon":409,"secondaryButton":412},{"text":400,"config":401},"Start free trial",{"href":402,"dataGaName":49,"dataGaLocation":403},"https://gitlab.com/-/trials/new/","nav",{"altText":405,"config":406},"Gitlab Icon",{"src":407,"dataGaName":408,"dataGaLocation":403},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1758203874/jypbw1jx72aexsoohd7x.svg","gitlab icon",{"altText":405,"config":410},{"src":411,"dataGaName":408,"dataGaLocation":403},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1758203875/gs4c8p8opsgvflgkswz9.svg",{"text":413,"config":414},"Get Started",{"href":415,"dataGaName":416,"dataGaLocation":403},"https://gitlab.com/-/trial_registrations/new?glm_source=about.gitlab.com/compare/gitlab-vs-github/","get started",{"freeTrial":418,"mobileIcon":423,"desktopIcon":425},{"text":419,"config":420},"Learn more about GitLab Duo",{"href":421,"dataGaName":422,"dataGaLocation":403},"/gitlab-duo/","gitlab duo",{"altText":405,"config":424},{"src":407,"dataGaName":408,"dataGaLocation":403},{"altText":405,"config":426},{"src":411,"dataGaName":408,"dataGaLocation":403},{"freeTrial":428,"mobileIcon":433,"desktopIcon":435},{"text":429,"config":430},"Back to pricing",{"href":185,"dataGaName":431,"dataGaLocation":403,"icon":432},"back to pricing","GoBack",{"altText":405,"config":434},{"src":407,"dataGaName":408,"dataGaLocation":403},{"altText":405,"config":436},{"src":411,"dataGaName":408,"dataGaLocation":403},{"title":438,"button":439,"config":444},"See how agentic AI transforms software delivery",{"text":440,"config":441},"Watch GitLab Transcend now",{"href":442,"dataGaName":443,"dataGaLocation":44},"/events/transcend/virtual/","transcend event",{"layout":445,"icon":446},"release","AiStar",{"data":448},{"text":449,"source":450,"edit":456,"contribute":461,"config":466,"items":471,"minimal":677},"Git is a trademark of Software Freedom Conservancy and our use of 'GitLab' is under license",{"text":451,"config":452},"View page source",{"href":453,"dataGaName":454,"dataGaLocation":455},"https://gitlab.com/gitlab-com/marketing/digital-experience/about-gitlab-com/","page source","footer",{"text":457,"config":458},"Edit this page",{"href":459,"dataGaName":460,"dataGaLocation":455},"https://gitlab.com/gitlab-com/marketing/digital-experience/about-gitlab-com/-/blob/main/content/","web ide",{"text":462,"config":463},"Please contribute",{"href":464,"dataGaName":465,"dataGaLocation":455},"https://gitlab.com/gitlab-com/marketing/digital-experience/about-gitlab-com/-/blob/main/CONTRIBUTING.md/","please contribute",{"twitter":467,"facebook":468,"youtube":469,"linkedin":470},"https://twitter.com/gitlab","https://www.facebook.com/gitlab","https://www.youtube.com/channel/UCnMGQ8QHMAnVIsI3xJrihhg","https://www.linkedin.com/company/gitlab-com",[472,519,572,616,643],{"title":183,"links":473,"subMenu":488},[474,478,483],{"text":475,"config":476},"View plans",{"href":185,"dataGaName":477,"dataGaLocation":455},"view plans",{"text":479,"config":480},"Why Premium?",{"href":481,"dataGaName":482,"dataGaLocation":455},"/pricing/premium/","why premium",{"text":484,"config":485},"Why Ultimate?",{"href":486,"dataGaName":487,"dataGaLocation":455},"/pricing/ultimate/","why ultimate",[489],{"title":490,"links":491},"Contact Us",[492,495,497,499,504,509,514],{"text":493,"config":494},"Contact sales",{"href":53,"dataGaName":54,"dataGaLocation":455},{"text":358,"config":496},{"href":360,"dataGaName":361,"dataGaLocation":455},{"text":363,"config":498},{"href":365,"dataGaName":366,"dataGaLocation":455},{"text":500,"config":501},"Status",{"href":502,"dataGaName":503,"dataGaLocation":455},"https://status.gitlab.com/","status",{"text":505,"config":506},"Terms of use",{"href":507,"dataGaName":508,"dataGaLocation":455},"/terms/","terms of use",{"text":510,"config":511},"Privacy statement",{"href":512,"dataGaName":513,"dataGaLocation":455},"/privacy/","privacy statement",{"text":515,"config":516},"Cookie preferences",{"dataGaName":517,"dataGaLocation":455,"id":518,"isOneTrustButton":27},"cookie preferences","ot-sdk-btn",{"title":89,"links":520,"subMenu":529},[521,525],{"text":522,"config":523},"DevSecOps platform",{"href":71,"dataGaName":524,"dataGaLocation":455},"devsecops platform",{"text":526,"config":527},"AI-Assisted Development",{"href":421,"dataGaName":528,"dataGaLocation":455},"ai-assisted development",[530],{"title":531,"links":532},"Topics",[533,537,542,547,552,557,562,567],{"text":534,"config":535},"CICD",{"href":536,"dataGaName":36,"dataGaLocation":455},"/topics/ci-cd/",{"text":538,"config":539},"GitOps",{"href":540,"dataGaName":541,"dataGaLocation":455},"/topics/gitops/","gitops",{"text":543,"config":544},"DevOps",{"href":545,"dataGaName":546,"dataGaLocation":455},"/topics/devops/","devops",{"text":548,"config":549},"Version Control",{"href":550,"dataGaName":551,"dataGaLocation":455},"/topics/version-control/","version control",{"text":553,"config":554},"DevSecOps",{"href":555,"dataGaName":556,"dataGaLocation":455},"/topics/devsecops/","devsecops",{"text":558,"config":559},"Cloud Native",{"href":560,"dataGaName":561,"dataGaLocation":455},"/topics/cloud-native/","cloud native",{"text":563,"config":564},"AI for Coding",{"href":565,"dataGaName":566,"dataGaLocation":455},"/topics/devops/ai-for-coding/","ai for coding",{"text":568,"config":569},"Agentic AI",{"href":570,"dataGaName":571,"dataGaLocation":455},"/topics/agentic-ai/","agentic ai",{"title":573,"links":574},"Solutions",[575,577,579,584,588,591,595,598,600,603,606,611],{"text":130,"config":576},{"href":125,"dataGaName":130,"dataGaLocation":455},{"text":119,"config":578},{"href":103,"dataGaName":104,"dataGaLocation":455},{"text":580,"config":581},"Agile development",{"href":582,"dataGaName":583,"dataGaLocation":455},"/solutions/agile-delivery/","agile delivery",{"text":585,"config":586},"SCM",{"href":115,"dataGaName":587,"dataGaLocation":455},"source code management",{"text":534,"config":589},{"href":108,"dataGaName":590,"dataGaLocation":455},"continuous integration & delivery",{"text":592,"config":593},"Value stream management",{"href":158,"dataGaName":594,"dataGaLocation":455},"value stream management",{"text":538,"config":596},{"href":597,"dataGaName":541,"dataGaLocation":455},"/solutions/gitops/",{"text":168,"config":599},{"href":170,"dataGaName":171,"dataGaLocation":455},{"text":601,"config":602},"Small business",{"href":175,"dataGaName":176,"dataGaLocation":455},{"text":604,"config":605},"Public sector",{"href":180,"dataGaName":181,"dataGaLocation":455},{"text":607,"config":608},"Education",{"href":609,"dataGaName":610,"dataGaLocation":455},"/solutions/education/","education",{"text":612,"config":613},"Financial services",{"href":614,"dataGaName":615,"dataGaLocation":455},"/solutions/finance/","financial services",{"title":188,"links":617},[618,620,622,624,627,629,631,633,635,637,639,641],{"text":200,"config":619},{"href":202,"dataGaName":203,"dataGaLocation":455},{"text":205,"config":621},{"href":207,"dataGaName":208,"dataGaLocation":455},{"text":210,"config":623},{"href":212,"dataGaName":213,"dataGaLocation":455},{"text":215,"config":625},{"href":217,"dataGaName":626,"dataGaLocation":455},"docs",{"text":238,"config":628},{"href":240,"dataGaName":241,"dataGaLocation":455},{"text":233,"config":630},{"href":235,"dataGaName":236,"dataGaLocation":455},{"text":243,"config":632},{"href":245,"dataGaName":246,"dataGaLocation":455},{"text":251,"config":634},{"href":253,"dataGaName":254,"dataGaLocation":455},{"text":256,"config":636},{"href":258,"dataGaName":259,"dataGaLocation":455},{"text":261,"config":638},{"href":263,"dataGaName":264,"dataGaLocation":455},{"text":266,"config":640},{"href":268,"dataGaName":269,"dataGaLocation":455},{"text":271,"config":642},{"href":273,"dataGaName":274,"dataGaLocation":455},{"title":289,"links":644},[645,647,649,651,653,655,657,661,666,668,670,672],{"text":296,"config":646},{"href":298,"dataGaName":291,"dataGaLocation":455},{"text":301,"config":648},{"href":303,"dataGaName":304,"dataGaLocation":455},{"text":309,"config":650},{"href":311,"dataGaName":312,"dataGaLocation":455},{"text":314,"config":652},{"href":316,"dataGaName":317,"dataGaLocation":455},{"text":319,"config":654},{"href":321,"dataGaName":322,"dataGaLocation":455},{"text":324,"config":656},{"href":326,"dataGaName":327,"dataGaLocation":455},{"text":658,"config":659},"Sustainability",{"href":660,"dataGaName":658,"dataGaLocation":455},"/sustainability/",{"text":662,"config":663},"Diversity, inclusion and belonging (DIB)",{"href":664,"dataGaName":665,"dataGaLocation":455},"/diversity-inclusion-belonging/","Diversity, inclusion and belonging",{"text":329,"config":667},{"href":331,"dataGaName":332,"dataGaLocation":455},{"text":339,"config":669},{"href":341,"dataGaName":342,"dataGaLocation":455},{"text":344,"config":671},{"href":346,"dataGaName":347,"dataGaLocation":455},{"text":673,"config":674},"Modern Slavery Transparency Statement",{"href":675,"dataGaName":676,"dataGaLocation":455},"https://handbook.gitlab.com/handbook/legal/modern-slavery-act-transparency-statement/","modern slavery transparency statement",{"items":678},[679,682,685],{"text":680,"config":681},"Terms",{"href":507,"dataGaName":508,"dataGaLocation":455},{"text":683,"config":684},"Cookies",{"dataGaName":517,"dataGaLocation":455,"id":518,"isOneTrustButton":27},{"text":686,"config":687},"Privacy",{"href":512,"dataGaName":513,"dataGaLocation":455},[689],{"id":690,"title":18,"body":8,"config":691,"content":693,"description":8,"extension":25,"meta":697,"navigation":27,"path":698,"seo":699,"stem":700,"__hash__":701},"blogAuthors/en-us/blog/authors/max-woolf.yml",{"template":692},"BlogAuthor",{"name":18,"config":694},{"headshot":695,"ctfId":696},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749659488/Blog/Author%20Headshots/gitlab-logo-extra-whitespace.png","Max-Woolf",{},"/en-us/blog/authors/max-woolf",{},"en-us/blog/authors/max-woolf","GI5Y2iOJMToVKF9b0_juI0fsK_IxgPXgb-eolS1kd2c",[703,716,728],{"content":704,"config":714},{"title":705,"description":706,"authors":707,"heroImage":709,"date":710,"category":9,"tags":711,"body":713},"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.",[708],"Nick Veenhof","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099013/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2814%29_6VTUA8mUhOZNDaRVNPeKwl_1750099012960.png","2026-01-08",[259,610,712],"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":715,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":717,"config":726},{"title":718,"description":719,"authors":720,"heroImage":721,"date":722,"category":9,"tags":723,"body":725},"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.",[708],"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",[610,259,724],"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":727,"featured":27,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":729,"config":742},{"category":9,"tags":730,"body":733,"date":734,"updatedDate":735,"heroImage":736,"authors":737,"title":740,"description":741},[731,732,24],"tutorial","git","\nEnterprise teams are increasingly migrating from Azure DevOps to GitLab to gain strategic advantages and accelerate secure software delivery. \n\n\n- GitLab comes with integrated controls, policies, and [compliance frameworks](https://docs.gitlab.com/user/compliance/compliance_frameworks/) that allow organizations to implement software delivery standards at scale. This is especially important for regulated industries.\n\n- [Security testing](https://docs.gitlab.com/user/application_security/) is embedded in the pipeline and results show in the developer workflow, including static application security testing (SAST), source code analysis (SCA), dynamic application security testing (DAST), infrastructure-as-code scanning (IaC), container scanning, and API scanning.\n\n- [AI capabilities](https://about.gitlab.com/gitlab-duo-agent-platform/) across the full software delivery lifecycle include advanced agent orchestration and customizable flows to support how your organizational teams work.\n\n\nGitLab's open-source, open-core approach, flexible deployment options such as single-tenant dedicated and self-managed, and truly unified platform eliminate integration complexity and security gaps. \n\n\nFor teams facing mounting pressure to accelerate delivery while strengthening security posture and maintaining regulatory compliance, GitLab represents not just a migration but a platform evolution.\n\n\nMigrating from Azure DevOps to GitLab can seem like a daunting task, but with the right approach and tools, it can be a smooth and efficient process. This guide will walk you through the steps needed to successfully migrate your projects, repositories, and pipelines from Azure DevOps to GitLab.\n\n\n## Overview\n\nGitLab provides both [Congregate](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/) (maintained by [GitLab Professional Services](https://about.gitlab.com/professional-services/) organization) and [a built-in Git repository import](https://docs.gitlab.com/user/project/import/repo_by_url/) for migrating projects from Azure DevOps (ADO). These options support repository-by-repository or bulk migration and preserve git commit history, branches, and tags. With Congregate and professional services tools, we support additional assets such as wikis, work items, CI/CD variables, container images, packages, pipelines, and more (see this [feature matrix](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/-/blob/master/customer/ado-migration-features-matrix.md)). Use this guide to plan and execute your migration and complete post-migration follow-up tasks.\n\n\nEnterprises migrating from ADO to GitLab commonly follow a multi-phase approach:\n\n\n- Migrate repositories from ADO to GitLab using Congregate or GitLab's built-in repository migration.\n\n- Migrate pipelines from Azure Pipelines to GitLab CI/CD.\n\n- Migrate remaining assets such as boards, work items, and artifacts to GitLab Issues, Epics, and the Package and Container Registries.\n\n\nHigh-level migration phases:\n\n\n```mermaid\ngraph LR\n    subgraph Prerequisites\n        direction TB\n        A[\"Set up identity provider (IdP) and\u003Cbr/>provision users\"]\n        A --> B[\"Set up runners and\u003Cbr/>third-party integrations\"]\n        B --> I[\"Users enablement and\u003Cbr/>change management\"]\n    end\n    \n    subgraph MigrationPhase[\"Migration phase\"]\n        direction TB\n        C[\"Migrate source code\"]\n        C --> D[\"Preserve contributions and\u003Cbr/> format history\"]\n        D --> E[\"Migrate work items and\u003Cbr/>map to \u003Ca href=\"https://docs.gitlab.com/topics/plan_and_track/\">GitLab Plan \u003Cbr/>and track work\"]\n    end\n    \n    subgraph PostMigration[\"Post-migration steps\"]\n        direction TB\n        F[\"Create or translate \u003Cbr/>ADO pipelines to GitLab CI\"]\n        F --> G[\"Migrate other assets\u003Cbr/>packages and container images\"]\n        G --> H[\"Introduce \u003Ca href=\"https://docs.gitlab.com/user/application_security/secure_your_application/\">security\u003C/a> and\u003Cbr/>SDLC improvements\"]\n    end\n    \n    Prerequisites --> MigrationPhase\n    MigrationPhase --> PostMigration\n\n    style A fill:#FC6D26\n    style B fill:#FC6D26\n    style I fill:#FC6D26\n    style C fill:#8C929D\n    style D fill:#8C929D\n    style E fill:#8C929D\n    style F fill:#FFA500\n    style G fill:#FFA500\n    style H fill:#FFA500\n```\n\n\n## Planning your migration\n\n\n**To plan your migration, ask these questions:**\n\n\n- How soon do we need to complete the migration?\n\n- Do we understand what will be migrated?\n\n- Who will run the migration?\n\n- What organizational structure do we want in GitLab?\n\n- Are there any constraints, limitations, or pitfalls that need to be taken into account?\n\n\nDetermine your timeline, as it will largely dictate your migration approach. Identify champions or groups familiar with both ADO and GitLab platforms (such as early adopters) to help drive adoption and provide guidance.\n\n\n**Inventory what you need to migrate:**\n\n\n- The number of repositories, pull requests, and contributors\n\n- The number and complexity of work items and pipelines\n\n- Repository sizes and dependency relationships\n\n- Critical integrations and runner requirements (agent pools with specific capabilities)\n\n\nUse GitLab Professional Services's [Evaluate](https://gitlab.com/gitlab-org/professional-services-automation/tools/utilities/evaluate#beta-azure-devops) tool to produce a complete inventory of your entire Azure DevOps organization, including repositories, PR counts, contributor lists, number of pipelines, work items, CI/CD variables and more. If you're working with the GitLab Professional Services team, share this report with your engagement manager or technical architect to help plan the migration.\n\n\nMigration timing is primarily driven by pull request count, repository size, and amount of contributions (e.g. comments in PR, work items, etc). For example, 1,000 small repositories with few PRs and limited contributors can migrate much faster than a smaller set of repositories containing tens of thousands of PRs and thousands of contributors. Use your inventory data to estimate effort and plan test runs before proceeding with production migrations.\n\n\nCompare inventory against your desired timeline and decide whether to migrate all repositories at once or in batches. If teams cannot migrate simultaneously, batch and stagger migrations to align with team schedules. For example, in Professional Services engagements, we organize migrations into waves of 200-300 projects to manage complexity and respect API rate limits, both in [GitLab](https://docs.gitlab.com/security/rate_limits/) and [ADO](https://learn.microsoft.com/en-us/azure/devops/integrate/concepts/rate-limits?view=azure-devops).\n\n\nGitLab's built-in [repository importer](https://docs.gitlab.com/user/project/import/repo_by_url/) migrates Git repositories (commits, branches, and tags) one-by-one. Congregate is designed to preserve pull requests (known in GitLab as merge requests), comments, and related metadata where possible; the simple built-in repository import focuses only on the Git data (history, branches, and tags).\n\n\n**Items that typically require separate migration or manual recreation:**\n\n\n- Azure Pipelines - create equivalent GitLab CI/CD pipelines (consult with [CI/CD YAML](https://docs.gitlab.com/ci/yaml/) and/or with [CI/CD components](https://docs.gitlab.com/ci/components/)). Alternatively, consider using AI-based pipeline conversion available in Congregate.\n\n- Work items and boards - map to GitLab Issues, Epics, and Issue Boards.\n\n- Artifacts, container images (ACR) - migrate to GitLab Package Registry or Container Registry.\n\n- Service hooks and external integrations - recreate in GitLab.\n\n- [Permissions models](https://docs.gitlab.com/user/permissions/) differ between ADO and GitLab; review and plan permissions mapping rather than assuming exact preservation.\n\n\nReview what each tool (Congregate vs. built-in import) will migrate and choose the one that fits your needs. Make a list of any data or integrations that must be migrated or recreated manually.\n\n\n**Who will run the migration?**\n\n\nMigrations are typically run by a GitLab group owner or instance administrator, or by a designated migrator who has been granted the necessary permissions on the destination group/project. Congregate and the GitLab import APIs require valid authentication tokens for both Azure DevOps and GitLab.\n\n\n- Decide whether a group owner/admin will perform the migrations or whether you will grant a specific team/person delegated access.\n\n- Ensure the migrator has correctly configured personal access tokens (Azure DevOps and GitLab) with the scopes required by your chosen migration tool (for example, api/read_repository scopes and any tool-specific requirements). \n\n- Test tokens and permissions with a small pilot migration.\n\n**Note:** Congregate leverages file-based import functionality for ADO migrations and requires instance administrator permissions to run ([see our documentation](https://docs.gitlab.com/user/project/settings/import_export/#migrate-projects-by-uploading-an-export-file)). If you are migrating to GitLab.com, consider engaging Professional Services. For more information, see the [Professional Services Full Catalog](https://about.gitlab.com/professional-services/catalog/). Non-admin account cannot preserve contribution attribution!\n\n\n**What organizational structure do we want in GitLab?**\n\nWhile it's possible to map ADO structure directly to GitLab structure, it's recommended to rationalize and simplify the structure during migration. Consider how teams will work in GitLab and design the structure to facilitate collaboration and access management. Here is a way to think about mapping ADO structure to GitLab structure:\n\n\n```mermaid\ngraph TD\n    subgraph GitLab\n        direction TB\n        A[\"Top-level Group\"]\n        B[\"Subgroup (optional)\"]\n        C[\"Projects\"]\n        A --> B\n        A --> C\n        B --> C\n    end\n\n    subgraph AzureDevOps[\"Azure DevOps\"]\n        direction TB\n        F[\"Organizations\"]\n        G[\"Projects\"]\n        H[\"Repositories\"]\n        F --> G\n        G --> H\n    end\n\n    style A fill:#FC6D26\n    style B fill:#FC6D26\n    style C fill:#FC6D26\n    style F fill:#8C929D\n    style G fill:#8C929D\n    style H fill:#8C929D\n```\n\nRecommended approach:\n\n\n- Map each ADO organization to a GitLab group (or a small set of groups), not to many small groups. Avoid creating a GitLab group for every ADO team project. Use migration as an opportunity to rationalize your GitLab structure.\n\n- Use subgroups and project-level permissions to group related repositories.\n\n- Manage access to sets of projects by using GitLab groups and group membership (groups and subgroups) rather than one group per team project.\n\n- Review GitLab [permissions](https://docs.gitlab.com/ee/user/permissions.html) and consider [SAML Group Links](https://docs.gitlab.com/user/group/saml_sso/group_sync/) to implement an enterprise RBAC model for your GitLab instance (or a GitLab.com namespace).\n\n\n**ADO Boards and work items: State of migration**\n\n\nIt's important to understand how work items migrate from ADO into GitLab Plan (issues, epics, and boards).\n\n\n- ADO Boards and work items map to GitLab Issues, Epics, and Issue Boards. Plan how your workflows and board configurations will translate.\n\n- ADO Epics and Features become GitLab Epics.\n\n- Other work item types (e.g., user stories, tasks, bugs) become project-scoped issues.\n\n- Most standard fields are preserved; selected custom fields can be migrated when supported.\n\n- Parent-child relationships are retained so Epics reference all related issues.\n\n- Links to pull requests are converted to merge request links to maintain development traceability.\n\n\nExample: Migration of an individual work item to a GitLab Issue, including field accuracy and relationships:\n\n\n![Example: Migration of an individual work item to a GitLab Issue](https://res.cloudinary.com/about-gitlab-com/image/upload/v1764769188/ztesjnxxfbwmfmtckyga.png)\n\n\nBatching guidance:\n\n\n- If you need to run migrations in batches, use your new group/subgroup structure to define batches (for example, by ADO organization or by product area).\n\n- Use inventory reports to drive batch selection and test each batch with a pilot migration before scaling.\n\n\n**Pipelines migration**\n\n\nCongregate [recently introduced](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/-/merge_requests/1298) AI-powered conversion for multi-stage YAML pipelines from Azure DevOps to GitLab CI/CD. This automated conversion works best for simple, single-file pipelines and is designed to provide a working starting point rather than a production-ready `.gitlab-ci.yml` file. The tool generates a functionally equivalent GitLab pipeline that you can then refine and optimize for your specific needs.\n\n\n- Converts Azure Pipelines YAML to `.gitlab-ci.yml` format automatically.\n\n- Best suited for straightforward, single-file pipeline configurations.\n\n- Provides a boilerplate to accelerate migration, not a final production artifact.\n\n- Requires review and adjustment for complex scenarios, custom tasks, or enterprise requirements.\n\n- Does not support Azure DevOps classic release pipelines — [convert these to multi-stage YAML](https://learn.microsoft.com/en-us/azure/devops/pipelines/release/from-classic-pipelines?view=azure-devops) first.\n\n\nRepository owners should review the [GitLab CI/CD documentation](https://docs.gitlab.com/ci/) to further optimize and enhance their pipelines after the initial conversion.\n\n\nExample of converted pipelines:\n\n\n```yml \n\n# azure-pipelines.yml\n\ntrigger:\n  - main\n\nvariables:\n  imageName: myapp\n\nstages:\n  - stage: Build\n    jobs:\n      - job: Build\n        pool:\n          vmImage: 'ubuntu-latest'\n        steps:\n          - checkout: self\n\n          - task: Docker@2\n            displayName: Build Docker image\n            inputs:\n              command: build\n              repository: $(imageName)\n              Dockerfile: '**/Dockerfile'\n              tags: |\n                $(Build.BuildId)\n\n  - stage: Test\n    jobs:\n      - job: Test\n        pool:\n          vmImage: 'ubuntu-latest'\n        steps:\n          - checkout: self\n\n          # Example: run tests inside the container\n          - script: |\n              docker run --rm $(imageName):$(Build.BuildId) npm test\n            displayName: Run tests\n\n  - stage: Push\n    jobs:\n      - job: Push\n        pool:\n          vmImage: 'ubuntu-latest'\n        steps:\n          - checkout: self\n\n          - task: Docker@2\n            displayName: Login to ACR\n            inputs:\n              command: login\n              containerRegistry: '\u003Cyour-acr-service-connection>'\n\n          - task: Docker@2\n            displayName: Push image to ACR\n            inputs:\n              command: push\n              repository: $(imageName)\n              tags: |\n                $(Build.BuildId)\n\n```\n\n```yaml\n\n# .gitlab-ci.yml\n\nvariables:\n  imageName: myapp\n\nstages:\n  - build\n  - test\n  - push\n\nbuild:\n  stage: build\n  image: docker:latest\n  services:\n    - docker:dind\n  script:\n    - docker build -t $imageName:$CI_PIPELINE_ID -f $(find . -name Dockerfile) .\n  only:\n    - main\n\ntest:\n  stage: test\n  image: docker:latest\n  services:\n    - docker:dind\n  script:\n    - docker run --rm $imageName:$CI_PIPELINE_ID npm test\n  only:\n    - main\n\npush:\n  stage: push\n  image: docker:latest\n  services:\n    - docker:dind\n  before_script:\n    - docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY\n  script:\n    - docker tag $imageName:$CI_PIPELINE_ID $CI_REGISTRY/$CI_PROJECT_PATH/$imageName:$CI_PIPELINE_ID\n    - docker push $CI_REGISTRY/$CI_PROJECT_PATH/$imageName:$CI_PIPELINE_ID\n  only:\n    - main\n\n```\n\n**Final checklist:**\n\n\n- Decide timeline and batch strategy.\n\n- Produce a full inventory of repositories, PRs, and contributors.\n\n- Choose Congregate or the built-in import based on scope (PRs and metadata vs. Git data only).\n\n- Decide who will run migrations and ensure tokens/permissions are configured.\n\n- Identify assets that must be migrated separately (pipelines, work items, artifacts, and hooks) and plan those efforts.\n\n- Run pilot migrations, validate results, then scale according to your plan.\n\n\n## Running your migrations\n\n\nAfter planning, execute migrations in stages, starting with trial runs. Trial migrations help surface org-specific issues early and let you measure duration, validate outcomes, and fine-tune your approach before production.\n\n\nWhat trial migrations validate:\n\n\n- Whether a given repository and related assets migrate successfully (history, branches, tags; plus MRs/comments if using Congregate)\n\n- Whether the destination is usable immediately (permissions, runners, CI/CD variables, integrations)\n\n- How long each batch takes, to set schedules and stakeholder expectations\n\n\nDowntime guidance:\n\n\n- GitLab's built-in Git import and Congregate do not inherently require downtime.\n\n- For production waves, freeze changes in ADO (branch protections or read-only) to avoid missed commits, PR updates, or work items created mid-migration.\n\n- Trial runs do not require freezes and can be run anytime.\n\n\nBatching guidance:\n\n\n- Run trial batches back-to-back to shorten elapsed time; let teams validate results asynchronously.\n\n- Use your planned group/subgroup structure to define batches and respect API rate limits.\n\n\nRecommended steps:\n\n\n1. Create a test destination in GitLab for trials:\n\n\n  - GitLab.com: create a dedicated group/namespace (for example, my-org-sandbox)\n\n  - Self-managed: create a top-level group or a separate test instance if needed\n\n\n2. Prepare authentication:\n\n\n  - Azure DevOps PAT with required scopes.\n\n  - GitLab Personal Access Token with api and read_repository (plus admin access for file-based imports used by Congregate).\n\n\n3. Run trial migrations:\n\n\n  - Repos only: use GitLab's built-in import (Repo by URL)\n\n  - Repos + PRs/MRs and additional assets: use Congregate\n\n\n4. Post-trial follow-up:\n\n\n  - Verify repo history, branches, tags; merge requests (if migrated), issues/epics (if migrated), labels, and relationships.\n\n  - Check permissions/roles, protected branches, required approvals, runners/tags, variables/secrets, integrations/webhooks.\n\n  - Validate pipelines (`.gitlab-ci.yml`) or converted pipelines where applicable.\n\n\n5. Ask users to validate functionality and data fidelity.\n\n6. Resolve issues uncovered during trials and update your runbooks.\n\n7. Network and security:\n\n\n  - If your destination uses IP allow lists, add the IPs of your migration host and any required runners/integrations so imports can succeed.\n\n\n8. Run production migrations in waves:\n\n\n  - Enforce change freezes in ADO during each wave.\n\n  - Monitor progress and logs; retry or adjust batch sizes if you hit rate limits.\n\n\n9. Optional: remove the sandbox group or archive it after you finish.\n\n\n\u003Cfigure class=\"video_container\">\n  \u003Ciframe src=\"https://www.youtube.com/embed/ibIXGfrVbi4?si=ZxOVnXjCF-h4Ne0N\" frameborder=\"0\" allowfullscreen=\"true\">\u003C/iframe>\n\u003C/figure>\n\n\n## Terminology reference for GitLab and Azure DevOps\n\n| GitLab                                                           | Azure DevOps                                 | Similarities & Key Differences                                                                                                                                          |\n| ---------------------------------------------------------------- | -------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Group                                                            | Organization                                 | Top-level namespace, membership, policies. ADO org contains Projects; GitLab Group contains Subgroups and Projects.                                                   |\n| Group or Subgroup                                                | Project                                      | Logical container, permissions boundary. ADO Project holds many repos; GitLab Groups/Subgroups organize many Projects.                                                |\n| Project (includes a Git repo)                                    | Repository (inside a Project)                | Git history, branches, tags. In GitLab, a \"Project\" is the repo plus issues, CI/CD, wiki, etc. One repo per Project.                                                  |\n| Merge Request (MR)                                               | Pull Request (PR)                            | Code review, discussions, approvals. MR rules include approvals, required pipelines, code owners.                                                                     |\n| Protected Branches, MR Approval Rules, Status Checks             | Branch Policies                              | Enforce reviews and checks. GitLab combines protections + approval rules + required status checks.                                                                    |\n| GitLab CI/CD                                                     | Azure Pipelines                              | YAML pipelines, stages/jobs, logs. ADO also has classic UI pipelines; GitLab centers on .gitlab-ci.yml.                                                               |\n| .gitlab-ci.yml                                                   | azure-pipelines.yml                          | Defines stages/jobs/triggers. Syntax/features differ; map jobs, variables, artifacts, and triggers.                                                                   |\n| Runners (shared/specific)                                        | Agents / Agent Pools                         | Execute jobs on machines/containers. Target via demands (ADO) vs tags (GitLab). Registration/scoping differs.                                                         |\n| CI/CD Variables (project/group/instance), Protected/Masked       | Pipeline Variables, Variable Groups, Library | Pass config/secrets to jobs. GitLab supports group inheritance and masking/protection flags.                                                                          |\n| Integrations, CI/CD Variables, Deploy Keys                       | Service Connections                          | External auth to services/clouds. Map to integrations or variables; cloud-specific helpers available.                                                                 |\n| Environments & Deployments (protected envs)                      | Environments (with approvals)                | Track deploy targets/history. Approvals via protected envs and manual jobs in GitLab.                                                                                 |\n| Releases (tag + notes)                                           | Releases (classic or pipelines)              | Versioned notes/artifacts. GitLab Release ties to tags; deployments tracked separately.                                                                               |\n| Job Artifacts                                                    | Pipeline Artifacts                           | Persist job outputs. Retention/expiry configured per job or project.                                                                                                  |\n| Package Registry (NuGet/npm/Maven/PyPI/Composer, etc.)           | Azure Artifacts (NuGet/npm/Maven, etc.)      | Package hosting. Auth/namespace differ; migrate per package type.                                                                                                     |\n| GitLab Container Registry                                        | Azure Container Registry (ACR) or others     | OCI images. GitLab provides per-project/group registries.                                                                                                             |\n| Issue Boards                                                     | Boards                                       | Visualize work by columns. GitLab boards are label-driven; multiple boards per project/group.                                                                         |\n| Issues (types/labels), Epics                                     | Work Items (User Story/Bug/Task)             | Track units of work. Map ADO types/fields to labels/custom fields; epics at group level.                                                                              |\n| Epics, Parent/Child Issues                                       | Epics/Features                               | Hierarchy of work. Schema differs; use epics + issue relationships.                                                                                                   |\n| Milestones and Iterations                                        | Iteration Paths                              | Time-boxing. GitLab Iterations (group feature) or Milestones per project/group.                                                                                       |\n| Labels (scoped labels)                                           | Area Paths                                   | Categorization/ownership. Replace hierarchical areas with scoped labels.                                                                                              |\n| Project/Group Wiki                                               | Project Wiki                                 | Markdown wiki. Backed by repos in both; layout/auth differ slightly.                                                                                                  |\n| Test reports via CI, Requirements/Test Management, integrations  | Test Plans/Cases/Runs                        | QA evidence/traceability. No 1:1 with ADO Test Plans; often use CI reports + issues/requirements.                                                                     |\n| Roles (Owner/Maintainer/Developer/Reporter/Guest) + custom roles | Access levels + granular permissions         | Control read/write/admin. Models differ; leverage group inheritance and protected resources.                                                                          |\n| Webhooks                                                         | Service Hooks                                | Event-driven integrations. Event names/payloads differ; reconfigure endpoints.                                                                                        |\n| Advanced Search                                                  | Code Search                                  | Full-text repo search. Self-managed GitLab may need Elasticsearch/OpenSearch for advanced features.                                                                   |\n","2025-12-03","2026-01-16","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749658924/Blog/Hero%20Images/securitylifecycle-light.png",[738,739],"Evgeny Rudinsky","Michael Leopard","Guide: Migrate from Azure DevOps to GitLab","Learn how to carry out the full migration from Azure DevOps to GitLab using GitLab Professional Services migration tools — from planning and execution to post-migration follow-up tasks.",{"featured":27,"template":13,"slug":743},"migration-from-azure-devops-to-gitlab",{"promotions":745},[746,760,771],{"id":747,"categories":748,"header":750,"text":751,"button":752,"image":757},"ai-modernization",[749],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":753,"config":754},"Get your AI maturity score",{"href":755,"dataGaName":756,"dataGaLocation":241},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":758},{"src":759},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":761,"categories":762,"header":763,"text":751,"button":764,"image":768},"devops-modernization",[724,556],"Are you just managing tools or shipping innovation?",{"text":765,"config":766},"Get your DevOps maturity score",{"href":767,"dataGaName":756,"dataGaLocation":241},"/assessments/devops-modernization-assessment/",{"config":769},{"src":770},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":772,"categories":773,"header":775,"text":751,"button":776,"image":780},"security-modernization",[774],"security","Are you trading speed for security?",{"text":777,"config":778},"Get your security maturity score",{"href":779,"dataGaName":756,"dataGaLocation":241},"/assessments/security-modernization-assessment/",{"config":781},{"src":782},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":784,"blurb":785,"button":786,"secondaryButton":791},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":787,"config":788},"Get your free trial",{"href":789,"dataGaName":49,"dataGaLocation":790},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":493,"config":792},{"href":53,"dataGaName":54,"dataGaLocation":790},1772652063601]