[{"data":1,"prerenderedAt":791},["ShallowReactive",2],{"/en-us/blog/gitlab-journey-to-cicd":3,"navigation-en-us":38,"banner-en-us":437,"footer-en-us":447,"blog-post-authors-en-us-Sara Kassabian":688,"blog-related-posts-en-us-gitlab-journey-to-cicd":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/gitlab-journey-to-cicd.yml","Gitlab Journey To Cicd",[7],"sara-kassabian",null,"engineering",{"slug":11,"featured":12,"template":13},"gitlab-journey-to-cicd",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"GitLab's unconventional journey to CI/CD and Kubernetes","How the Delivery team at GitLab used our existing resources to overhaul our system to make way for CI/CD.",[18],"Sara Kassabian","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749678397/Blog/Hero%20Images/raphael-biscaldi-cicd.jpg","2019-10-03","\nEngineering teams are under pressure to provide value in the form of new features, all while minimizing [cycle time](/blog/reduce-cycle-time/). Oftentimes the instinct is to adopt modern tooling to make that happen. Continuous integration and delivery (CI/CD) is baked into GitLab, our single application for the DevOps lifecycle, and we are undergoing a major migration to Kubernetes to speed up our cycle time even more. But our journey to CI/CD and eventually Kubernetes has been unconventional, as the [Delivery team](https://handbook.gitlab.com/handbook/engineering/infrastructure-platforms/gitlab-delivery/delivery/) elected to stress our current system as we step into [continuous delivery](/topics/continuous-delivery/) on GitLab.com before migrating entirely over to Kubernetes.\n\n## Releases before CI/CD\n\nThe wider GitLab community and GitLab team members [averaged 55 commits per day between Aug. 7 and Sept. 27, 2019](https://gitlab.com/gitlab-org/gitlab-ee/-/graphs/master/charts) as they continually iterate on our product to build new features for our customers. But before we adopted continuous delivery, we had to institute feature freeze periods beginning on the 7th of each month. During this period, engineers would shift their focus from building new features to fixing bugs in preparation for the upcoming release, which always happens on the 22nd.\n\n The use of a specific defined deadline encouraged behavior that ultimately caused developers to focus more on the due date and not around accomplishing the work.\n\n\"... developers would really play around the 7th because they would think ‘Oh, I have time, the 7th is in seven days,’ and then on the 6th at midnight they would panic merge things,\" said [Marin Jankovski](/company/team/#marin), engineering manager for the Delivery team. \"Because they know that if they missed this deadline they will have to wait for the next month, and if they get it in under this deadline they have a good two weeks to fix any problems that happen.\"\n\nSince the conception of GitLab.com, the feature freeze was used as a stabilization period, Marin explained.\n\nSoon though, the demand for new features from new users was pushing us to escalate our development velocity on GitLab.com. The stabilization period slowed our cycle time and created a significant drag in our turnover time for bug fixes, regression, and feature shipping for users both on GitLab.com and self-managed customers.\n\n“In some cases (the feature freezes) would even cause platform instability due to the fact that highest priority fixes couldn't find its way into customer hands quick enough,” said Marin. “By moving to CD, we can get both features and bug fixes alike into the hands of our users much quicker.”\n\nBefore the [Delivery team was created to manage GitLab.com's transition to continuous delivery](https://handbook.gitlab.com/handbook/engineering/infrastructure-platforms/gitlab-delivery/delivery/#top-level-responsibilities) – and eventually Kubernetes – we depended upon a [release manager](/blog/release-manager-the-invisible-hero/), a rotating position among developers, to prepare the release. The [release process was iterated on over a five-year period](/community/release-managers/) as the release managers created a knowledge base and some automation to make the release process work.\n\nBut this method was inefficient as the timing behind the deployment process and release preparations was unpredictable, taking between half a day to multiple days due to the [accumulation of manual tasks in the process](https://gitlab.com/gitlab-org/release/docs/blob/master/general/tooling.md).\n\n“The release manager would get a set task list to go through, a deadline by which the tasks should be completed and they would have to repeat these steps over again until the release is ready, but also stable on GitLab.com,” explained Marin. At the highest level overview, the release manager had to:\n\n*   Manually sync the various repositories that GitLab consists of\n*   Ensure that the correct versions are set in the manually created Git branches\n*   Once the release is tagged, manually deploy to GitLab.com environments for both non-production and production\n*   Verify that everything is operational and manually publish the packages for self-managed users\n\nDuring his [presentation on this topic at GitLab Commit Brooklyn](https://youtu.be/lD-cYylwOLg), Marin shared the results of a 2018 survey which revealed that in the 14-day period before a release, the Delivery team spent 60% of their time babysitting deploys, and another 26% of their time on manual or semi-manual tasks release tasks, such as writing the monthly release post.\n\n![Task breakdown before CI/CD](https://about.gitlab.com/images/blogimages/journey-to-cicd/release-task-spread.jpg){: .medium.center}\nResults of a 2018 survey showing how the Delivery team spent their time two weeks before a release, before continuous delivery.\n\n\n\"If you take a look at the whole thing, in 14 days, in two weeks, my team did nothing but sit on the computer and watch, well, paint dry, I guess,\" said Marin.\n\nBut by tackling 86% of the pie (60% deploys + 26% of the release manual tasks), the Delivery team could solve a few problems:\n\n1.  No release delays\n1.  Repeatable and faster deploys to enable no downtime\n1.  More time for our GitLab.com Kubernetes migration\n1.  More space to prepare the organization for continuous delivery\n\nAlthough CD is only on GitLab.com, our self-managed customers also benefit from our transition to CD. Now anything that isn't caught with CI testing is tested automatically and manually in environments before ever reaching GitLab.com. Anything that requires a fix that does reach GitLab.com can be fixed in a few hours, so the final release for self-managed customers won't include these particular issues.\n\n## Our unique approach to transitioning to CD and Kubernetes\n\nThe transition from using feature freezes to adopting CD on GitLab.com was inevitable as our features set grew, and a team of engineers, led by Marin, was formed to oversee this transition: “The Delivery team has been formed with the sole purpose of moving the company to a CD model for GitLab.com but at the same time for migrating GitLab.com to the Kubernetes platform to enable easier scaling and even faster turnaround times.”\n\nMany companies in GitLab’s position would have started this journey to CI/CD and Kubernetes by first integrating the new technologies into their workflow, and amending the development process as they go. We opted for a different approach.\n\nThe migration to Kubernetes requires a shift in both production systems and the engineering mindset, explained Marin. Kubernetes offers some features that teams can easily leverage without any extra investment. But in order to derive the greatest value from the free features Kubernetes offers, there ought to be some existing CI/CD process already in place.\n\nThe Delivery team recognized that in order to smooth the transition to Kubernetes for continuous delivery, our engineers must already be working with a CI/CD mindset – this includes a strong focus on quality assessments (QA) and stricter feature planning. So the Delivery team went with the [boring solution](https://handbook.gitlab.com/handbook/values/#boring-solutions) and used our existing tools to build a CD system and reorganize the application infrastructure of GitLab.com instead of first adopting new tooling and technologies for CD.\n\n“The idea was simple,” said Marin. “We [leverage the tools at our disposal](https://gitlab.com/gitlab-org/release/docs/blob/master/general/deploy/auto-deploy.md), automate most of the manual tasks and ‘stress test’ the whole static system. If the static system can withstand the test, we move toward a more dynamic test.”\n\nThere were two key benefits to taking this approach:\n\n**First**, any weaknesses in our application were exposed and stabilized by automating with CI, so our application is stronger and less brittle, making a complete migration to Kubernetes more likely to be a success.\n\n**Second**, by shifting the engineering team to the CD mindset, we created a cultural shift among the engineers at GitLab who were accustomed to weekly deploys and waiting up to a day to see the impact of their merge.\n\n> “The definition of ‘done’ for developers has changed since the adoption of CI/CD,” said Marin.\n\nBefore CI/CD, a change was “done” once the review was completed. This was excluding deployments to various environments which took a considerable amount of time. Today, deployments are shipped within hours so there is no reason to not confirm that a change is working in testing and production environments.\n\nThe adoption of review apps on Kubernetes allow developers to run QA checks in virtually real time, and the use of [feature flags](/blog/feature-flags-continuous-delivery/) for progressive delivery also helps to accelerate development.\n\n“Since the first step in CD, developers are required to react to any automated QA but also carry out another level of manual verification in both non-production and production environments. Additionally, developers can have their changes running in production within a day compared to multiple days (and weeks).”\n\nEveryone can run QA checks on their code more frequently with CD. Because code changes are shipped around the clock with our CI/CD system, developers now operate an on-call rotation to help with any outstanding issues that are happening live on GitLab.com since the \"incubation\" time is much shorter.\n\n## Our new method\n\nSince the adoption of a CI/CD system, 90% of the [release process is automated](https://gitlab.com/gitlab-org/release/tasks/issues/885) using the [CI features of GitLab](/direction/verify/continuous_integration/). The remaining 10% requires human intervention due to coordination between various stakeholders.\n\n“We are slowly reducing those 10% as well with the goal of having only approvals needed to publish a release,” said Marin. [In the current iteration, the CI/CD process operates as follows](/direction/ops/):\n\n*   CI automatically looks for specific labels in merged MRs, applied by code reviewers and developers.\n*   CI automatically syncs all required repositories but also creates required Git branches, tags, as well as setting the correct versions of the release we want to ship.\n*   When the builds complete, packages are automatically deployed to non-production environments.\n*   Automated QA tasks are executed and, if passing, the deployment is rolled out to a small subset of users in production.\n*   In parallel, developers do another level of manual QA to ensure that new features are functioning as expected.\n*   If a high severity issue is discovered with manual verification, the deployments are stopped.\n*   When the above is completed, a member of the Delivery team will trigger a rollout to all users on GitLab.com.\n*   Self-managed release is then created from the last known working deployment running on GitLab.com.\n\nAs is true for any engineering team, scaling remains a challenge for us. But one of the biggest technical challenges is making sure there is enough QA coverage, which can be labor intensive for a product as big at GitLab.com. Also, making sure the monitoring and alerting is sufficient so the product isn’t operating solely based upon pre-set rules.\n\nThe second major challenge is the complexity of our GitLab.com system, and communicating the change in process across our engineering teams. “Dismantling more than five years of built-up process and habit is never easy,” said Marin.\n\n## The results\n\nGitLab is already benefitting from the shift to CI/CD in a number of ways.\n\nThe results of a new 2019 survey assessing how the Delivery team spends their time in the same 14-day period before the release shows that today, 82% of the team's time is freed up to work on other important tasks.\n\n![Task breakdown since CI/CD](https://about.gitlab.com/images/blogimages/journey-to-cicd/chart.jpg){: .medium.center}\nThe results of a 2019 survey measuring the same two weeks before the release shows the switch to CD has freed up valuable developer time.\n\n\nBy automating manual tasks, the Delivery team was able to shift their focus toward changing the GitLab.com infrastructure to better support our development velocity and user traffic, as well as beginning the migration to Kubernetes.\n\n> \"And, did I mention, none of this is on Kubernetes. All of this is using our 'old' legacy system,\" said Marin to the GitLab Commit Brooklyn audience. \"But what happened with this is we bought ourselves time, so my team actually has time to work on the migration. But one of the biggest changes that happened was in the habits of the engineering organization.\"\n\nThe results since the shift have been significant. The Delivery team went from around seven deploys under the old system in May 2019 to 35 deploys on GitLab.com in August 2019, and is on track to surpass these numbers considerably now that they're shipping multiple deploys a day.\n\n“We have just completed the migration of our Registry service to Kubernetes and if you use [Container Registry on GitLab.com](https://gitlab.com/groups/gitlab-com/gl-infra/-/epics/70), all your requests are served from the Kubernetes platform,\" said Marin. \"Since GitLab is a multi-component system, we are continuing to isolate and migrate other services.”\n\nNew CI/CD features are included in each release. For example, in our 12.3 release, we [expanded the GitLab Container Registry to allow users to leverage CI/CD to build and push images/tags to their project](/releases/2019/09/22/gitlab-12-3-released/#remove-container-images-from-cicd) among other exciting new features.\n\n## Transitioning your system to continuous delivery?\n\nFor companies considering the transition to CD, Marin advised to start with what you’ve got.\n\n“From my perspective, waiting for migrating to a new platform is the real ‘enemy,’” said Marin. “Most systems can be altered in some ways to enable faster turnaround time without migrating to a fully new system. Speeding up the development/release cycle has multiplier return per engineer in that system and that frees up more time for migrations to new platforms, such as Kubernetes.”\n\nIf you’re curious about what’s up next, [check out this detailed summary of the exciting new CI/CD features](/blog/a-look-ahead-for-gitlab-cicd/) on track to be released in 12.4 and beyond.\n\n## Missed GitLab Commit Brooklyn?\n\nIf you missed Marin's presentation on the prequel to Kubernetes, watch the entire video below and catch us in Europe at [GitLab Commit London on October 9](/events/)!\n\n\u003Cfigure class=\"video_container\">\n  \u003Ciframe src=\"https://www.youtube.com/embed/lD-cYylwOLg\" frameborder=\"0\" allowfullscreen=\"true\"> \u003C/iframe>\n\u003C/figure>\n\n[Cover Photo](https://unsplash.com/photos/rE3kbKmLmhE) by [Raphaël Biscaldi](https://unsplash.com/@les_photos_de_raph?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText) on 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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/sara-kassabian.yml",{"template":692},"BlogAuthor",{"name":18,"config":694},{"headshot":695,"ctfId":696},"","skassabian",{},"/en-us/blog/authors/sara-kassabian",{},"en-us/blog/authors/sara-kassabian","6cCCPpjzkCDfb77tMVCyG8_FImRVQXA2VCMyiAjhFX0",[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},1773350814679]