[{"data":1,"prerenderedAt":791},["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":742,"next-steps-en-us":781},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":25,"isFeatured":12,"meta":26,"navigation":27,"path":28,"publishedDate":20,"seo":29,"stem":33,"tagSlugs":34,"__hash__":37},"blogPosts/en-us/blog/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 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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",[703,718,731],{"content":704,"config":716},{"title":705,"description":706,"authors":707,"heroImage":709,"date":710,"body":711,"category":9,"tags":712},"How to use GitLab Container Virtual Registry with Docker Hardened Images","Learn how to simplify container image management with this step-by-step guide.",[708],"Tim Rizzi","https://res.cloudinary.com/about-gitlab-com/image/upload/v1772111172/mwhgbjawn62kymfwrhle.png","2026-03-12","If you're a platform engineer, you've probably had this conversation:\n  \n*\"Security says we need to use hardened base images.\"*\n\n*\"Great, where do I configure credentials for yet another registry?\"*\n\n*\"Also, how do we make sure everyone actually uses them?\"*\n\nOr this one:\n\n*\"Why are our builds so slow?\"*\n\n*\"We're pulling the same 500MB image from Docker Hub in every single job.\"*\n\n*\"Can't we just cache these somewhere?\"*\n\nI've been working on [Container Virtual Registry](https://docs.gitlab.com/user/packages/virtual_registry/container/) at GitLab specifically to solve these problems. It's a pull-through cache that sits in front of your upstream registries — Docker Hub, dhi.io (Docker Hardened Images), MCR, and Quay — and gives your teams a single endpoint to pull from. Images get cached on the first pull. Subsequent pulls come from the cache. Your developers don't need to know or care which upstream a particular image came from.\n\nThis article shows you how to set up Container Virtual Registry, specifically with Docker Hardened Images in mind, since that's a combination that makes a lot of sense for teams concerned about security and not making their developers' lives harder.\n\n## What problem are we actually solving?\n\nThe Platform teams I usually talk to manage container images across three to five registries:\n\n* **Docker Hub** for most base images\n* **dhi.io** for Docker Hardened Images (security-conscious workloads)\n* **MCR** for .NET and Azure tooling\n* **Quay.io** for Red Hat ecosystem stuff\n* **Internal registries** for proprietary images\n\nEach one has its own:\n\n* Authentication mechanism\n* Network latency characteristics\n* Way of organizing image paths\n\nYour CI/CD configs end up littered with registry-specific logic. Credential management becomes a project unto itself. And every pipeline job pulls the same base images over the network, even though they haven't changed in weeks.\n\nContainer Virtual Registry consolidates this. One registry URL. One authentication flow (GitLab's). Cached images are served from GitLab's infrastructure rather than traversing the internet each time.\n\n## How it works\n\nThe model is straightforward:\n\n```text\nYour pipeline pulls:\n  gitlab.com/virtual_registries/container/1000016/python:3.13\n\nVirtual registry checks:\n  1. Do I have this cached? → Return it\n  2. No? → Fetch from upstream, cache it, return it\n\n```\n\nYou configure upstreams in priority order. When a pull request comes in, the virtual registry checks each upstream until it finds the image. The result gets cached for a configurable period (default 24 hours).\n\n```text\n┌─────────────────────────────────────────────────────────┐\n│                    CI/CD Pipeline                       │\n│                          │                              │\n│                          ▼                              │\n│   gitlab.com/virtual_registries/container/\u003Cid>/image   │\n└─────────────────────────────────────────────────────────┘\n                           │\n                           ▼\n┌─────────────────────────────────────────────────────────┐\n│            Container Virtual Registry                   │\n│                                                         │\n│  Upstream 1: Docker Hub ────────────────┐               │\n│  Upstream 2: dhi.io (Hardened) ────────┐│               │\n│  Upstream 3: MCR ─────────────────────┐││               │\n│  Upstream 4: Quay.io ────────────────┐│││               │\n│                                      ││││               │\n│                    ┌─────────────────┴┴┴┴──┐            │\n│                    │        Cache          │            │\n│                    │  (manifests + layers) │            │\n│                    └───────────────────────┘            │\n└─────────────────────────────────────────────────────────┘\n```\n\n## Why this matters for Docker Hardened Images\n\n[Docker Hardened Images](https://docs.docker.com/dhi/) are great because of the minimal attack surface, near-zero CVEs, proper software bills of materials (SBOMs), and SLSA provenance. If you're evaluating base images for security-sensitive workloads, they should be on your list.\n\nBut adopting them creates the same operational friction as any new registry:\n\n* **Credential distribution**: You need to get Docker credentials to every system that pulls images from dhi.io.\n* **CI/CD changes**: Every pipeline needs to be updated to authenticate with dhi.io.\n* **Developer friction**: People need to remember to use the hardened variants.\n* **Visibility gap**: It's difficulat to tell if teams are actually using hardened images vs. regular ones.\n\nVirtual registry addresses each of these:\n\n**Single credential**: Teams authenticate to GitLab. The virtual registry handles upstream authentication. You configure Docker credentials once, at the registry level, and they apply to all pulls.\n\n**No CI/CD changes per-team**: Point pipelines at your virtual registry. Done. The upstream configuration is centralized.\n\n**Gradual adoption**: Since images get cached with their full path, you can see in the cache what's being pulled. If someone's pulling `library/python:3.11` instead of the hardened variant, you'll know.\n\n**Audit trail**: The cache shows you exactly which images are in active use. Useful for compliance, useful for understanding what your fleet actually depends on.\n\n## Setting it up\n\nHere's a real setup using the Python client from this demo project.\n\n### Create the virtual registry\n\n```python\nfrom virtual_registry_client import VirtualRegistryClient\n\nclient = VirtualRegistryClient()\n\nregistry = client.create_virtual_registry(\n    group_id=\"785414\",  # Your top-level group ID\n    name=\"platform-images\",\n    description=\"Cached container images for platform teams\"\n)\n\nprint(f\"Registry ID: {registry['id']}\")\n# You'll need this ID for the pull URL\n```\n\n### Add Docker Hub as an upstream\n\nFor official images like Alpine, Python, etc.:\n\n```python\ndocker_upstream = client.create_upstream(\n    registry_id=registry['id'],\n    url=\"https://registry-1.docker.io\",\n    name=\"Docker Hub\",\n    cache_validity_hours=24\n)\n```\n\n### Add Docker Hardened Images (dhi.io)\n\nDocker Hardened Images are hosted on `dhi.io`, a separate registry that requires authentication:\n\n```python\ndhi_upstream = client.create_upstream(\n    registry_id=registry['id'],\n    url=\"https://dhi.io\",\n    name=\"Docker Hardened Images\",\n    username=\"your-docker-username\",\n    password=\"your-docker-access-token\",\n    cache_validity_hours=24\n)\n```\n\n### Add other upstreams\n\n```python\n# MCR for .NET teams\nclient.create_upstream(\n    registry_id=registry['id'],\n    url=\"https://mcr.microsoft.com\",\n    name=\"Microsoft Container Registry\",\n    cache_validity_hours=48\n)\n\n# Quay for Red Hat stuff\nclient.create_upstream(\n    registry_id=registry['id'],\n    url=\"https://quay.io\",\n    name=\"Quay.io\",\n    cache_validity_hours=24\n)\n```\n\n### Update your CI/CD\n\nHere's a `.gitlab-ci.yml` that pulls through the virtual registry:\n\n```yaml\nvariables:\n  VIRTUAL_REGISTRY_ID: \u003Cyour_virtual_registry_ID>\n\n  \nbuild:\n  image: docker:24\n  services:\n    - docker:24-dind\n  before_script:\n    # Authenticate to GitLab (which handles upstream auth for you)\n    - echo \"${CI_JOB_TOKEN}\" | docker login -u gitlab-ci-token --password-stdin gitlab.com\n  script:\n    # All of these go through your single virtual registry\n    \n    # Official Docker Hub images (use library/ prefix)\n    - docker pull gitlab.com/virtual_registries/container/${VIRTUAL_REGISTRY_ID}/library/alpine:latest\n    \n    # Docker Hardened Images from dhi.io (no prefix needed)\n    - docker pull gitlab.com/virtual_registries/container/${VIRTUAL_REGISTRY_ID}/python:3.13\n    \n    # .NET from MCR\n    - docker pull gitlab.com/virtual_registries/container/${VIRTUAL_REGISTRY_ID}/dotnet/sdk:8.0\n```\n\n### Image path formats\n\nDifferent registries use different path conventions:\n\n| Registry | Pull URL Example |\n|----------|------------------|\n| Docker Hub (official) | `.../library/python:3.11-slim` |\n| Docker Hardened Images (dhi.io) | `.../python:3.13` |\n| MCR | `.../dotnet/sdk:8.0` |\n| Quay.io | `.../prometheus/prometheus:latest` |\n\n### Verify it's working\n\nAfter some pulls, check your cache:\n\n```python\nupstreams = client.list_registry_upstreams(registry['id'])\nfor upstream in upstreams:\n    entries = client.list_cache_entries(upstream['id'])\n    print(f\"{upstream['name']}: {len(entries)} cached entries\")\n\n```\n\n## What the numbers look like\n\nI ran tests pulling images through the virtual registry:\n\n| Metric | Without Cache | With Warm Cache |\n|--------|---------------|-----------------|\n| Pull time (Alpine) | 10.3s | 4.2s |\n| Pull time (Python 3.13 DHI) | 11.6s | ~4s |\n| Network roundtrips to upstream | Every pull | Cache misses only |\n\n\n\n\nThe first pull is the same speed (it has to fetch from upstream). Every pull after that, for the cache validity period, comes straight from GitLab's storage. No network hop to Docker Hub, dhi.io, MCR, or wherever the image lives.\n\nFor a team running hundreds of pipeline jobs per day, that's hours of cumulative build time saved.\n\n## Practical considerations\nHere are some considerations to keep in mind:\n\n### Cache validity\n\n24 hours is the default. For security-sensitive images where you want patches quickly, consider 12 hours or less:\n\n```python\nclient.create_upstream(\n    registry_id=registry['id'],\n    url=\"https://dhi.io\",\n    name=\"Docker Hardened Images\",\n    username=\"your-username\",\n    password=\"your-token\",\n    cache_validity_hours=12\n)\n```\n\nFor stable, infrequently-updated images (like specific version tags), longer validity is fine.\n\n### Upstream priority\n\nUpstreams are checked in order. If you have images with the same name on different registries, the first matching upstream wins.\n\n### Limits\n\n* Maximum of 20 virtual registries per group\n* Maximum of 20 upstreams per virtual registry\n\n## Configuration via UI\n\nYou can also configure virtual registries and upstreams directly from the GitLab UI—no API calls required. Navigate to your group's **Settings > Packages and registries > Virtual Registry** to:\n\n* Create and manage virtual registries\n* Add, edit, and reorder upstream registries\n* View and manage the cache\n* Monitor which images are being pulled\n\n## What's next\n\nWe're actively developing:\n\n* **Allow/deny lists**: Use regex to control which images can be pulled from specific upstreams.\n\nThis is beta software. It works, people are using it in production, but we're still iterating based on feedback.\n\n## Share your feedback\n\nIf you're a platform engineer dealing with container registry sprawl, I'd like to understand your setup:\n\n* How many upstream registries are you managing?\n* What's your biggest pain point with the current state?\n* Would something like this help, and if not, what's missing?\n\nPlease share your experiences in the [Container Virtual Registry feedback issue](https://gitlab.com/gitlab-org/gitlab/-/work_items/589630).\n## Related resources\n- [New GitLab metrics and registry features help reduce CI/CD bottlenecks](https://about.gitlab.com/blog/new-gitlab-metrics-and-registry-features-help-reduce-ci-cd-bottlenecks/#container-virtual-registry)\n- [Container Virtual Registry documentation](https://docs.gitlab.com/user/packages/virtual_registry/container/)\n- [Container Virtual Registry API](https://docs.gitlab.com/api/container_virtual_registries/)",[713,714,715],"tutorial","product","features",{"featured":12,"template":13,"slug":717},"using-gitlab-container-virtual-registry-with-docker-hardened-images",{"content":719,"config":729},{"title":720,"description":721,"authors":722,"heroImage":724,"date":725,"category":9,"tags":726,"body":728},"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.",[723],"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",[259,610,727],"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":730,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":732,"config":740},{"title":733,"description":734,"authors":735,"heroImage":736,"date":737,"category":9,"tags":738,"body":739},"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.",[723],"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",[610,259,714],"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":741,"featured":27,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"promotions":743},[744,758,769],{"id":745,"categories":746,"header":748,"text":749,"button":750,"image":755},"ai-modernization",[747],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":751,"config":752},"Get your AI maturity score",{"href":753,"dataGaName":754,"dataGaLocation":241},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":756},{"src":757},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":759,"categories":760,"header":761,"text":749,"button":762,"image":766},"devops-modernization",[714,556],"Are you just managing tools or shipping innovation?",{"text":763,"config":764},"Get your DevOps maturity score",{"href":765,"dataGaName":754,"dataGaLocation":241},"/assessments/devops-modernization-assessment/",{"config":767},{"src":768},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":770,"categories":771,"header":773,"text":749,"button":774,"image":778},"security-modernization",[772],"security","Are you trading speed for security?",{"text":775,"config":776},"Get your security maturity score",{"href":777,"dataGaName":754,"dataGaLocation":241},"/assessments/security-modernization-assessment/",{"config":779},{"src":780},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":782,"blurb":783,"button":784,"secondaryButton":789},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":785,"config":786},"Get your free trial",{"href":787,"dataGaName":49,"dataGaLocation":788},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":493,"config":790},{"href":53,"dataGaName":54,"dataGaLocation":788},1773350806612]