[{"data":1,"prerenderedAt":806},["ShallowReactive",2],{"/en-us/blog/geo-is-available-on-staging-for-gitlab-com":3,"navigation-en-us":40,"banner-en-us":440,"footer-en-us":450,"blog-post-authors-en-us-Fabian Zimmer|Douglas Alexandre":692,"blog-related-posts-en-us-geo-is-available-on-staging-for-gitlab-com":718,"assessment-promotions-en-us":757,"next-steps-en-us":796},{"id":4,"title":5,"authorSlugs":6,"body":9,"categorySlug":10,"config":11,"content":15,"description":9,"extension":28,"isFeatured":13,"meta":29,"navigation":30,"path":31,"publishedDate":22,"seo":32,"stem":36,"tagSlugs":37,"__hash__":39},"blogPosts/en-us/blog/geo-is-available-on-staging-for-gitlab-com.yml","Geo Is Available On Staging For Gitlab Com",[7,8],"fabian-zimmer","douglas-alexandre",null,"engineering",{"slug":12,"featured":13,"template":14},"geo-is-available-on-staging-for-gitlab-com",false,"BlogPost",{"title":16,"description":17,"authors":18,"heroImage":21,"date":22,"body":23,"category":10,"tags":24},"Why we enabled Geo on the staging environment for GitLab.com","Geo is GitLab's solution for distributed teams and now we can validate and test it at scale.",[19,20],"Fabian Zimmer","Douglas Alexandre","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749669656/Blog/Hero%20Images/donald-giannatti-4qk3nQI3WHY-unsplash-small.jpg","2020-04-16","We're testing Geo at scale on GitLab.com – our largest installation of GitLab – because we believe the best way to guarantee that Geo works as expected is to [use it ourselves](https://handbook.gitlab.com/handbook/product/product-processes/#dogfood-everything).\n\nGeo is GitLab's [solution for distributed teams](https://docs.gitlab.com/ee/administration/geo/index.html). We want teams all over the world to have a great user experience - independent of how far away users are from their primary GitLab installation. To accomplish this goal, read-only Geo nodes can be created across the world in close geographical proximity to your teams. These Geo nodes replicate important data, such as projects or LFS files, from the primary GitLab instance and thereby make the data available to users. Geo can also be used as part of a disaster recovery strategy because it adds data redundancy. Geo nodes follow the primary installation closely and allow customers to failover to this node in case the primary node becomes unavailable.\n\nMany of GitLab's customers use Geo on self-managed installations that serve hundreds to thousands of users. Geo is a critical component of GitLab installations and our customers expect Geo to work at any scale. We are testing Geo at scale on our GitLab.com installation because if it works for us, chances are it will work for our worldwide group of users too.\n\nIn this blog post, we'll explain why and how we chose to enable GitLab Geo on our pre-production environment (from now on referred to as \"staging\"), the challenges we encountered, some of the immediate benefits to our customers, and what will be next.\n\n## Why do we need to use Geo at GitLab?\nIn order to build the best product possible, we believe it is imperative to [use GitLab ourselves](https://handbook.gitlab.com/handbook/product/product-processes/#dogfood-everything). Many of our Geo customers have thousands of users actively using GitLab and a major challenge for the team was to test and validate new Geo functionality at scale. Enabling Geo on the GitLab.com staging environment makes this task a lot easier.\n\nWe also used Geo to [migrate GitLab.com from Microsoft Azure to Google Cloud in 2018](/blog/moving-to-gcp/), which allowed us to improve the product by identifying bottlenecks. In the last two years, GitLab has grown dramatically and in order to push Geo forward, we need to enable it (again).\n\n### Test Geo at scale\nWhen the team decides to add new functionalities to Geo, for example [package repository replication](https://gitlab.com/groups/gitlab-org/-/epics/2346), we had to ensure that the feature's performance is as expected. Having Geo available on staging allows us to deploy these changes behind a feature flag first and evaluate the performance before shipping the feature to customers. This is especially relevant to some of Geo's PostgreSQL database queries. On a small test deployment, things may look fine, but at scale these queries can time out, resulting in replication issues.\n\nWe also deploy code to our staging environment twice a week, which means that any regressions surface before a new packaged release.\n\n### Prove that Geo can be deployed as part of our production infrastructure\nA large amount of automation is required to run GitLab.com with millions of users, and our SRE team is constantly improving how we run GitLab.com. The first step bringing Geo into our production environment is to deploy Geo as a part of our staging environment. Without the right monitoring, runbooks, and processes in place, it would not be possible to move Geo into production where it could be used to enable geo-replication and/or as part of our disaster recovery strategy.\n\n## Setting up Geo on staging\n\nSetting up Geo on staging had some unique challenges, you can get a detailed overview in our [Geo on staging documentation](https://handbook.gitlab.com/handbook/engineering/infrastructure/environments/staging-ref/).\n\nIn order to deploy Geo, we opted for a minimally viable approach that is sufficient for a first iteration. Geo is currently deployed as a single all-in-one box, not yet as a [Geo high-availability configuration](https://docs.gitlab.com/ee/administration/geo/replication/multiple_servers.html). Geo deploys happen automatically via Chef, similar to any other part of the infrastructure.\n\n![Geo staging Diagram](https://about.gitlab.com/images/blogimages/geo-on-staging/geo_staging_diagram.png){: .shadow.medium.center}\n\nWe currently replicate only a subset of data using [Geo's selective synchronization feature](https://docs.gitlab.com/ee/administration/geo/replication/configuration.html#selective-synchronization), which also allows us to dogfood this feature. Selective synchronization uses a number of complex database queries and this helps us validate those at scale. We chose to replicate the `gitlab-org` group, which contains mostly of GitLab's projects (including [GitLab](https://gitlab.com/gitlab-org/gitlab) itself).\n\nWe also needed to configure Geo to use the same logical [Gitaly shards](https://docs.gitlab.com/ee/administration/repository_storage_paths.html) on the secondary compared to the primary node. We'll [improve our Geo documentation](https://gitlab.com/gitlab-org/gitlab/-/issues/213840) to ensure it is clear when this is required.\n\nA logical Gitaly shard is an entry in the GitLab configuration file that points to a path on the file system and a Gitaly address:\n\n```text\n\"git_data_dirs\": {\n  \"default\": {\n    \"path\": \"/var/opt/gitlab/git-data-file01\",\n    \"gitaly_address\": \"unix:/var/opt/gitlab/gitaly/gitaly.socket\"\n  }\n}\n```\n\nIn the example above, we have only one logical shard identified by the key `default`, but we could have as many as needed.\nEvery project on GitLab is associated with a logical Gitaly shard, which means that we know where all relevant data (repositories, uploads, etc.) is stored. A project `example` that is associated with the logical Gitaly shard `default`, would therefore be stored at `/var/opt/gitlab/git-data-file01` and the Gitaly server would be available at `/var/opt/gitlab/git-data-file01`.\n\nThis information is stored in the PostgreSQL database and in order for Geo to replicate projects successfully we needed to create the same Gitaly shard layout. On the Geo secondary node, we are using only one physical shard to store the data for all projects. To allow it to replicate any project from the primary node, we had to point all the logical Gitaly shards to the same physical shard on the secondary node.\n\nGeo on staging is configured to use [cascading streaming replication](https://www.postgresql.org/docs/current/warm-standby.html#CASCADING-REPLICATION), which allows one standby node in the staging [Patroni cluster](https://github.com/zalando/patroni) to act as relay and stream write-ahead logs (WAL) to the Geo secondary. This setup also has the advantage that Geo can't put an additional load onto the primary database node and we are also not using physical replication slots to further reduce the load. [Patroni will likely be supported in Omnibus packages](https://gitlab.com/groups/gitlab-org/-/epics/2588) and we will review these settings to allow our customers to benefit from this setup.\n\nPostgreSQL will automatically fall back on its `restore_command` to pull archived WAL segments using [wal-e](https://github.com/wal-e/wal-e), if it cannot retrieve the segment by streaming replication. This can happen after a failover, or if the replication target has deleted the relevant segment if Geo is lagging behind it.\n\nIn the future, we will use this to experiment with [high-availability configurations of PostgreSQL on a secondary Geo node](https://gitlab.com/groups/gitlab-org/-/epics/2536).\n\n## What we learned and how we can improve\n\nWe opened [23 issues before successfully rolling out Geo on our staging environment](https://gitlab.com/groups/gitlab-org/-/epics/1908) - this is too many. We know that installing and configuring Geo in complex environments is time-consuming and error-prone, and is an area where we can improve. The current process for a self-managed installation requires [more than 70 individual steps](https://gitlab.com/gitlab-org/gitlab-design/issues/731) - this is too much. [Geo should be simple to install](https://gitlab.com/groups/gitlab-org/-/epics/1465) and we aim to reduce the number of steps to below 10. Using Geo ourselves really underscored the importance of improvements in this area.\n\n### Some Geo PostgreSQL queries don't perform well\n\nGeo uses PostgreSQL Foreign Data Wrappers (FDW) to perform some cross-database queries between the secondary replica and the tracking database. FDW queries are quite elegant but have lead to some issues in the past. Specifically, staging is still running PostgreSQL 9.6, and Geo benefits from some FDW improvements available only in PostgreSQL 10 and later, such as join push-down and aggregate push-down.\n\nWhile enabling Geo on staging, some FDW queries timed out during the backfill phase. Until staging is being upgraded to a newer version of PostgreSQL, increasing the statement timeout to 20 minutes on the Geo secondary node was sufficient to allow us to proceed with the backfill.\n\nAs a direct consequence of enabling GitLab on staging, we are working to [improve Geo scalability by simplifying backfill operations](https://gitlab.com/groups/gitlab-org/-/epics/2851), eliminating these cross-database queries, and removing the FDW requirement. We also plan to [upgrade to PostgreSQL 11 in GitLab 13.0](https://gitlab.com/groups/gitlab-org/-/epics/2414).\n\n### Bug fixes\nWe've also discovered and fixed a number of bugs in the process, such as [failing to synchronize uploads with missing mount points](https://gitlab.com/gitlab-org/gitlab/-/issues/209752), [invalid ActiveRecord operations](https://gitlab.com/gitlab-org/gitlab/-/issues/210589), and [excessively re-synchronizing files in some situations](https://gitlab.com/gitlab-org/gitlab/-/issues/207808).\n\n## What's next?\nWe are already providing value to our customers by enabling Geo on staging because the Geo team can test and validate Geo at scale at lot easier. Next up is enabling [automatic runs of our end-to-end test on staging](https://gitlab.com/gitlab-org/quality/team-tasks/issues/385), which would reduce the manual testing burden even further. There are also some other improvements, such as [enabling high-availability configurations of PostgreSQL using Patroni on Geo nodes](https://gitlab.com/groups/gitlab-org/-/epics/2536) that we would like to test on staging.\n\nEven though enabling Geo on staging is already very useful, it is just a step forward to rolling out Geo on GitLab.com in production. We are currently evaluating the business case for enabling Geo on GitLab.com as part of our disaster recovery strategy and for geo replication.\n\nCover image by [Donald Giannatti](https://unsplash.com/photos/4qk3nQI3WHY) on [Unsplash](https://www.unsplash.com)\n",[25,26,27],"features","inside GitLab","google","yml",{},true,"/en-us/blog/geo-is-available-on-staging-for-gitlab-com",{"title":16,"description":17,"ogTitle":16,"ogDescription":17,"noIndex":13,"ogImage":21,"ogUrl":33,"ogSiteName":34,"ogType":35,"canonicalUrls":33},"https://about.gitlab.com/blog/geo-is-available-on-staging-for-gitlab-com","https://about.gitlab.com","article","en-us/blog/geo-is-available-on-staging-for-gitlab-com",[25,38,27],"inside-gitlab","OGkzg0zXD18gliT7Kk4H32v7w9Q4Sd-B1AtG7xJLm5c",{"data":41},{"logo":42,"freeTrial":47,"sales":52,"login":57,"items":62,"search":370,"minimal":401,"duo":420,"pricingDeployment":430},{"config":43},{"href":44,"dataGaName":45,"dataGaLocation":46},"/","gitlab 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statement",{"items":682},[683,686,689],{"text":684,"config":685},"Terms",{"href":510,"dataGaName":511,"dataGaLocation":458},{"text":687,"config":688},"Cookies",{"dataGaName":520,"dataGaLocation":458,"id":521,"isOneTrustButton":30},{"text":690,"config":691},"Privacy",{"href":515,"dataGaName":516,"dataGaLocation":458},[693,706],{"id":694,"title":19,"body":9,"config":695,"content":697,"description":9,"extension":28,"meta":701,"navigation":30,"path":702,"seo":703,"stem":704,"__hash__":705},"blogAuthors/en-us/blog/authors/fabian-zimmer.yml",{"template":696},"BlogAuthor",{"name":19,"config":698},{"headshot":699,"ctfId":700},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1750713473/q6awwqbxtg0a4x9gtmhs.png","3TK88UogcX5lx83kWMVuvI",{},"/en-us/blog/authors/fabian-zimmer",{},"en-us/blog/authors/fabian-zimmer","qPVb4mKZuBff6-yly4-T5Bar6IdyXcx_tJHGlSL8QIA",{"id":707,"title":20,"body":9,"config":708,"content":709,"description":9,"extension":28,"meta":713,"navigation":30,"path":714,"seo":715,"stem":716,"__hash__":717},"blogAuthors/en-us/blog/authors/douglas-alexandre.yml",{"template":696},{"name":20,"config":710},{"headshot":711,"ctfId":712},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749659488/Blog/Author%20Headshots/gitlab-logo-extra-whitespace.png","Douglas-Alexandre",{},"/en-us/blog/authors/douglas-alexandre",{},"en-us/blog/authors/douglas-alexandre","9oIVDz8T3S38e4STEdDnYFoN7NNjji5DBqDlbWomMxo",[719,733,746],{"content":720,"config":731},{"title":721,"description":722,"authors":723,"heroImage":725,"date":726,"body":727,"category":10,"tags":728},"How to use GitLab Container Virtual Registry with Docker Hardened Images","Learn how to simplify container image management with this step-by-step guide.",[724],"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/)",[729,730,25],"tutorial","product",{"featured":13,"template":14,"slug":732},"using-gitlab-container-virtual-registry-with-docker-hardened-images",{"content":734,"config":744},{"title":735,"description":736,"authors":737,"heroImage":739,"date":740,"category":10,"tags":741,"body":743},"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.",[738],"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",[262,614,742],"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":745,"featured":13,"template":14},"how-iit-bombay-students-code-future-with-gitlab",{"content":747,"config":755},{"title":748,"description":749,"authors":750,"heroImage":751,"date":752,"category":10,"tags":753,"body":754},"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.",[738],"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",[614,262,730],"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":756,"featured":30,"template":14},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"promotions":758},[759,773,784],{"id":760,"categories":761,"header":763,"text":764,"button":765,"image":770},"ai-modernization",[762],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":766,"config":767},"Get your AI maturity score",{"href":768,"dataGaName":769,"dataGaLocation":244},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":771},{"src":772},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":774,"categories":775,"header":776,"text":764,"button":777,"image":781},"devops-modernization",[730,560],"Are you just managing tools or shipping innovation?",{"text":778,"config":779},"Get your DevOps maturity score",{"href":780,"dataGaName":769,"dataGaLocation":244},"/assessments/devops-modernization-assessment/",{"config":782},{"src":783},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":785,"categories":786,"header":788,"text":764,"button":789,"image":793},"security-modernization",[787],"security","Are you trading speed for security?",{"text":790,"config":791},"Get your security maturity score",{"href":792,"dataGaName":769,"dataGaLocation":244},"/assessments/security-modernization-assessment/",{"config":794},{"src":795},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":797,"blurb":798,"button":799,"secondaryButton":804},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":800,"config":801},"Get your free trial",{"href":802,"dataGaName":51,"dataGaLocation":803},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":496,"config":805},{"href":55,"dataGaName":56,"dataGaLocation":803},1773350807969]