[{"data":1,"prerenderedAt":794},["ShallowReactive",2],{"/en-us/blog/cadence-is-everything-10x-engineering-organizations-for-10x-engineers":3,"navigation-en-us":37,"banner-en-us":437,"footer-en-us":447,"blog-post-authors-en-us-Sid Sijbrandij":687,"blog-related-posts-en-us-cadence-is-everything-10x-engineering-organizations-for-10x-engineers":705,"assessment-promotions-en-us":745,"next-steps-en-us":784},{"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__":36},"blogPosts/en-us/blog/cadence-is-everything-10x-engineering-organizations-for-10x-engineers.yml","Cadence Is Everything 10x Engineering Organizations For 10x Engineers",[7],"sid-sijbrandij",null,"engineering",{"slug":11,"featured":12,"template":13},"cadence-is-everything-10x-engineering-organizations-for-10x-engineers",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"Cadence is everything: 10x engineering organizations for 10x engineers","GitLab CEO and co-founder Sid Sijbrandij on the importance of cadence in engineering organizations.",[18],"Sid Sijbrandij","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749671909/Blog/Hero%20Images/Athlinks_running.jpg","2022-11-03","\nI confess: Although I don’t believe in Bigfoot or Nessie and do believe the moon landings happened, I am convinced that despite the current orthodoxies, [10x engineers](https://svdictionary.com/words/10x-engineer) very much exist and are a major positive force for the industry, and potentially your organization.  If you can find one, convince her to work for you and keep her happy and productive (but I repeat myself).\n\nAlas, finding one is not easy, and no, job adverts stating “We only hire the best” don’t help. However, what you can do is structure your development organization in a way to make such a person productive.  \n\nFortunately, making a 10x developer productive is pretty much the same, as you need to make your development organization productive for everyone, just dialed up to 11, particularly because an inefficient organization will affect a more efficient developer much more dramatically.\n\nUnfortunately, this state appears to be neither natural nor stable.\n\n[Effective organizations are unnatural](https://twitter.com/paulg/status/1556341452740775936?s=21&t=67hekF4Sus5tPryLdZmCHA). The natural state of organizations is bureaucracy and turf wars, and once deprived of effective leadership they revert to their natural state with shocking speed. Similar to organizations in general, development organizations naturally tend toward inefficiency.\n\nMore specifically, development organizations tend toward ever-lengthening cycle times just as much as organizations in general tend toward bureaucracy.  In both cases, this is always for good reasons.  This is really important:  If this tendency toward lengthening cycle times were just stupidity or laziness, it would be significantly easier to counter.  Anthropologist and historian [Joseph Tainter makes a similar point](https://www.youtube.com/watch?v=JsT9V3WQiNA) about civilizations, whose ever-increasing complexity leads to their collapse.  Here as well, the complexity is not introduced willy-nilly, but as a necessary response to problems the civilization faces.  \n\n## The sky’s the limit\n\nSoftware tends to be fairly abstract, but the principles of short cycle times are just applicable in more down-to-earth disciplines, or should I say down-to-air?  First, one of my favorites, the story of how Paul MacCready created the Gossamer Condor to win the first Kremer Prize for human-powered flight.  More recently, Elon Musk’s SpaceX has been out-iterating NASA and the legacy spaceflight companies with results that would have seemed miraculous a couple of decades ago.  Both examples show that while other factors are obviously more important, cadence actually dominates them in short order.\n\nMacGready had come into a bit of debt due to securing a friend’s business loan, and set his eyes on the first Kremer prize for human-powered flight. This had gone unclaimed for 17 years, but not for lack of trying: There had been over 50 official attempts and all failed.  It was a Very Hard Problem we couldn’t solve so it obviously required the most aerodynamically efficient and sophisticated designs possible.  So that’s what people did, and when their sophisticated plane inevitably crashed — after all they were working on the edge of the possible — it took them a year or more to rebuild it.\n\nMacGready approached this from the opposite angle:  He would concentrate on a plane that didn’t have to be so efficient and sophisticated, but instead would fly low and slow, be light and very repairable, aiming for 12 crashes a day. The Gossamer Condor was built out of some lightweight aluminum struts and mylar foil and could usually be repaired with Scotch tape. It was a weird contraption that didn’t look like it could fly.\n\n![The Condor](https://about.gitlab.com/images/blogimages/10x.png)\n\nWithin a few months, the team had accumulated more flights, and more crashes, than the rest of the competition combined. With all that experience, they then also understood the actual problems better than anyone else, for example, how to steer, and soon won the prize, which involved flying a mile in a circle eight.  \n\nThis wasn’t a [one-off fluke](https://www.youtube.com/watch?v=FvmTSpJU-Xc&t=3348s) either: The team went on to win the next Kremer prize as well, crossing the English Channel, then pioneered solar flight and broke the SR-71’s altitude record. The company that came out of the effort nowadays makes drones, including the successful Switchblade drones for the U.S. military that have recently been sent to help in the Ukraine conflict.\n\n## The sky’s not the limit\n\nMore recently, SpaceX has been demonstrating the efficacy of iterative development, first with the Falcon 9 rocket and now with the Starship program. While the latter hasn’t flown to space yet, and so may still fail completely, both the aim and the achievements so far have been breathtaking, particularly compared to NASA’s Space Launch System (SLS), which was started around the same time and is designed to have similar capabilities, lifting around 100 tons to low earth orbit.\n\nThe NASA SLS is a cost-reduced version of the Constellation program, which was canceled early after quickly outgrowing its projected $150 billion dollar budget.  The reduced development cost of the SLS (so far $23 billion in 10 years) has been achieved by reusing not just designs, but also actual parts from the Space Shuttle program.  Not just the solid rocket boosters, but some of the main engines are the actual parts that flew on shuttles and had been mothballed by NASA.  Despite this part reuse, launches of the fully expendable rocket are predicted to cost somewhat upward of $1 billion per pop.  As of Oct. 20, there have been no flights of any of the hardware (except on space shuttles), and the first test launch scheduled for Nov. 26th will fly the full stack as designed.\n\nIn comparison, the Starship program is estimated to have cost $3 billion so far, with estimates of total development costs varying between $5 billion and $10 billion. This is for a completely new rocket, pretty much unlike any that have come before, designed for full reusability and same-day turnaround after refueling, completely new methane-burning engines, assembly-line production using relatively inexpensive materials and a projected cost target of $10 million per launch. If they work as advertised, just a few Starships could turn the entire launch capacity of planet Earth thus far into a footnote, a rounding error, and they plan to build a thousand of them. That’s why they’re building a factory for making them.\n\nIt’s anyone’s guess whether all this launch capacity, at costs two or more magnitudes lower than currently possible, is really for making humanity multiplanetary by establishing a Mars colony or “just” for making space-based production and asteroid mining feasible.\n\nWhen asked, [Elon Musk put it quite simply](https://www.youtube.com/watch?v=E7MQb9Y4FAE&t=333s):\n\n_“Any given technology development is how many iterations do you have and what’s your time and progress between iterations.”_\n\nThe more quickly you can iterate, the more iterations you have available.  But doesn’t iterating more quickly make the progress between iterations correspondingly less, canceling the effect?  Surprisingly, that turns out not to be the case.  Elon Musk again:\n\n_“So if you have a high production rate, you can have a lot of iterations. You can try  lots of different things, and it’s OK if you blow up an engine because you’ve got a number of engines coming after that.  If you have a small number of engines then you have to be much more conservative, because you can’t risk blowing them up.”_\n\nThe higher iteration rate allows you to take more risks, which in turn allows you to push the boundaries more and thus gather more relevant feedback in each iteration, at the same time that the reduced time frame reduces what you can do. So there will be more failures. For example, engines blowing up or planes crashing.  But as long as the failures provide the information they were supposed to provide, and the individual failure modes aren’t fatal, they aren’t actually failures. You obviously don’t want to be cavalier about this, but accepting that risk allows you to push much farther per iteration.  Musk also mentioned that as one of the main problems of the Space Shuttle program:  They couldn’t afford to have one blow up because even the first flight was manned.\n\n“A high production rate solves many ills,” he says.\n\nIn software, the production rate is the iteration rate.  If you have lots of iterations, it’s OK if one of them was a potentially high-value experiment that didn’t pan out.  If you have one iteration per year, you are less likely to want to take that risk, and your reluctance will be justified. The willingness and ability to take risks is captured in the Extreme Programming (XP) [value of ‘courage.”](http://xp.c2.com/ExtremeValues.html)\n\n## Compound interest and experience\n\nThe reason this works out is mathematical.  If you iterate and actually use the feedback the iteration gives you to improve, you will improve a little bit each time because you will have learned something.  For simplicity’s sake, let’s assume an improvement of 5% per iteration.  This is like compound interest, and while it starts slow, once it ramps up, it gives outsize returns, like any exponential.\n\nImprove 2% per iteration, and after three iterations, you will have improved by 6%, which is essentially the same as a linear improvement.  After 200 iterations, however, and whereas the linear approach will have improved by a respectable factor of 4, the iterative approach will have improved by more than 50x.\n\nApart from the purely mathematical, there is also the human factor:  When we do things over and over again, we really start to figure out how it works. We develop an intuition.\n\n## What the science says\n\nThe simplistic mathematical function is obviously not an accurate model of the real world, but the science actually has concluded that higher iteration rates are the one most important factor for the output of software development teams, at least according to the researchers.  These findings have been published in the book “[Accelerate](https://itrevolution.com/product/accelerate/)\" by Nicole Forsgren, Jez Humble and Gene Kim.  The authors have since moved to Google as the DevOps Research and Assessment (DORA) team and make their [findings available here](https://cloud.google.com/blog/products/devops-sre/announcing-dora-2021-accelerate-state-of-devops-report).  \n\nIn short, they find that performance of software teams correlates strongly with cycle times, with the lowest- performing teams having cycle times measured in months, medium performers in weeks, good performers in days and excellent performers in hours. There is also good evidence for the causality going for cycle times to performance and not the other way around.\n\nBut there’s a deeper connection, because the method of iterating on real-world feedback is really just the scientific method, no more, no less.  It is somewhat surprising that in the field of software, we still often consider the scientific method as unruly and dangerous “cowboy coding,” and instead advocate for what is really little different from pre-science scholasticism as the proper approach to creating software.\n\nTo help us also be more scientific and data driven, the DORA team created metrics, called the [DORA metrics](https://cloud.google.com/blog/products/devops-sre/using-the-four-keys-to-measure-your-devops-performance). These are the following:\n\n- Deployment frequency — How often an organization successfully releases to production\n- Lead time for changes — The amount of time it takes a commit to get into production\n- Change failure rate — The percentage of deployments causing a failure in production\n- Time to restore service — How long it takes an organization to recover from a failure in production\n\n## The dangers of dead reckoning\n\nIn reality, it is much more dangerous to stay away from actual code and real feedback from users for any length of time.  For example, ships before GPS used essentially two methods for navigation: dead reckoning and external fixes.  With dead reckoning, you took a known position, added the course speed and known currents over time to come up with a new position.  However, despite the best equipment and methods, this method always introduces some error because the external factors cannot be known with certainty. And what’s worse, just like improvements accumulate and build on each other over time, so do these errors, making the position ever more uncertain over time.\n\nWhen you are in the middle of the ocean, that might not be a huge problem, but close to shore it can be deadly, which is why the amphibious ships of the Royal Navy were required to use position fixing in intervals of a few minutes. With position fixing, you use the actual external environment, landmarks that you can triangulate to determine your position (and of course GPS is just a version of this, except using satellites for the fix instead of landmarks).  This means you aren’t guessing where you are, you know where you are, and every new measurement clears the slate of any errors; there is no accumulation.\n\nSlides don’t crash, and Jira is patient. You can have 100 tasks that are marked as 99% completed in your tracker of choice and still never ship anything to customers.\n\nReality is that which, when you stop believing in it, doesn’t go away, said science fiction writer Phillip K. Dick, in [How to Build a Universe that Doesn’t Fall Apart Two Days Later](https://deoxy.org/pkd_how2build.htm).\n\nIn Part 2, The Process Equation, we will look at overcoming the forces that tend to push software engineering organizations toward higher cycle times and lower cadence.\n",[23,24],"careers","DevOps","yml",{},true,"/en-us/blog/cadence-is-everything-10x-engineering-organizations-for-10x-engineers",{"title":15,"description":16,"ogTitle":15,"ogDescription":16,"noIndex":12,"ogImage":19,"ogUrl":30,"ogSiteName":31,"ogType":32,"canonicalUrls":30},"https://about.gitlab.com/blog/cadence-is-everything-10x-engineering-organizations-for-10x-engineers","https://about.gitlab.com","article","en-us/blog/cadence-is-everything-10x-engineering-organizations-for-10x-engineers",[23,35],"devops","Gu0WR_YsT9H_39HstVcf5CWBE139EBAXNIQ86N5wJwU",{"data":38},{"logo":39,"freeTrial":44,"sales":49,"login":54,"items":59,"search":367,"minimal":398,"duo":417,"pricingDeployment":427},{"config":40},{"href":41,"dataGaName":42,"dataGaLocation":43},"/","gitlab logo","header",{"text":45,"config":46},"Get free trial",{"href":47,"dataGaName":48,"dataGaLocation":43},"https://gitlab.com/-/trial_registrations/new?glm_source=about.gitlab.com&glm_content=default-saas-trial/","free 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statement",{"items":677},[678,681,684],{"text":679,"config":680},"Terms",{"href":507,"dataGaName":508,"dataGaLocation":455},{"text":682,"config":683},"Cookies",{"dataGaName":517,"dataGaLocation":455,"id":518,"isOneTrustButton":27},{"text":685,"config":686},"Privacy",{"href":512,"dataGaName":513,"dataGaLocation":455},[688],{"id":689,"title":18,"body":8,"config":690,"content":692,"description":8,"extension":25,"meta":700,"navigation":27,"path":701,"seo":702,"stem":703,"__hash__":704},"blogAuthors/en-us/blog/authors/sid-sijbrandij.yml",{"template":691},"BlogAuthor",{"role":693,"name":18,"bio":694,"config":695},"Co-founder, Chief Executive Officer and Board Chair of GitLab Inc.","Sid Sijbrandij (pronounced see-brandy) is the Co-founder, Chief Executive Officer and Board Chair of GitLab Inc., the most comprehensive AI-powered DevSecOps platform. GitLab's single application helps organizations deliver software faster and more efficiently while strengthening their security and compliance.\n\nSid's career path has been anything but traditional. He spent four years building recreational submarines for U-Boat Worx and while at Ministerie van Justitie en Veiligheid he worked on the Legis project, which developed several innovative web applications to aid lawmaking. He first saw Ruby code in 2007 and loved it so much that he taught himself how to program. In 2012, as a Ruby programmer, he encountered GitLab and discovered his passion for open source. Soon after, Sid commercialized GitLab, and by 2015 he led the company through Y Combinator's Winter 2015 batch. Under his leadership, the company has grown with an estimated 30 million+ registered users from startups to global enterprises.\n\nSid studied at the University of Twente in the Netherlands where he received an M.S. in Management Science. Sid was named one of the greatest minds of the pandemic by Forbes for spreading the gospel of remote work.",{"headshot":696,"twitter":697,"linkedin":698,"ctfId":699},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749665383/Blog/Author%20Headshots/sytses-headshot.png","https://twitter.com/sytses","https://www.linkedin.com/in/sijbrandij","sytses",{},"/en-us/blog/authors/sid-sijbrandij",{},"en-us/blog/authors/sid-sijbrandij","ZdVvFbtL6NKLtKZEjFCVOecdpvuPzX3wmEZBrC6pRWg",[706,721,734],{"content":707,"config":719},{"title":708,"description":709,"authors":710,"heroImage":712,"date":713,"body":714,"category":9,"tags":715},"How to use GitLab Container Virtual Registry with Docker Hardened Images","Learn how to simplify container image management with this step-by-step guide.",[711],"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/)",[716,717,718],"tutorial","product","features",{"featured":12,"template":13,"slug":720},"using-gitlab-container-virtual-registry-with-docker-hardened-images",{"content":722,"config":732},{"title":723,"description":724,"authors":725,"heroImage":727,"date":728,"category":9,"tags":729,"body":731},"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.",[726],"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",[259,609,730],"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":733,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":735,"config":743},{"title":736,"description":737,"authors":738,"heroImage":739,"date":740,"category":9,"tags":741,"body":742},"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.",[726],"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",[609,259,717],"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":744,"featured":27,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"promotions":746},[747,761,772],{"id":748,"categories":749,"header":751,"text":752,"button":753,"image":758},"ai-modernization",[750],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":754,"config":755},"Get your AI maturity score",{"href":756,"dataGaName":757,"dataGaLocation":241},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":759},{"src":760},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":762,"categories":763,"header":764,"text":752,"button":765,"image":769},"devops-modernization",[717,555],"Are you just managing tools or shipping innovation?",{"text":766,"config":767},"Get your DevOps maturity score",{"href":768,"dataGaName":757,"dataGaLocation":241},"/assessments/devops-modernization-assessment/",{"config":770},{"src":771},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":773,"categories":774,"header":776,"text":752,"button":777,"image":781},"security-modernization",[775],"security","Are you trading speed for security?",{"text":778,"config":779},"Get your security maturity score",{"href":780,"dataGaName":757,"dataGaLocation":241},"/assessments/security-modernization-assessment/",{"config":782},{"src":783},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":785,"blurb":786,"button":787,"secondaryButton":792},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":788,"config":789},"Get your free trial",{"href":790,"dataGaName":48,"dataGaLocation":791},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":493,"config":793},{"href":52,"dataGaName":53,"dataGaLocation":791},1773350815783]