[{"data":1,"prerenderedAt":792},["ShallowReactive",2],{"/en-us/blog/year-of-kubernetes":3,"navigation-en-us":37,"banner-en-us":437,"footer-en-us":447,"blog-post-authors-en-us-John Jarvis":689,"blog-related-posts-en-us-year-of-kubernetes":703,"assessment-promotions-en-us":743,"next-steps-en-us":782},{"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/year-of-kubernetes.yml","Year Of Kubernetes",[7],"john-jarvis",null,"engineering",{"slug":11,"featured":12,"template":13},"year-of-kubernetes",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"What we learned after a year of GitLab.com on Kubernetes","It's been one year since we moved GitLab.com to Kubernetes. We unpack the challenges and learnings from this major migration.",[18],"John Jarvis","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749681569/Blog/Hero%20Images/nico-e-AAbjUJsgjvE-unsplash.jpg","2020-09-16","\n\nFor about a year now, the infrastructure department has been working on migrating all services that run on GitLab.com to Kubernetes. The effort has not been without challenges, not only with moving services to Kubernetes but also managing a hybrid deployment during the transition. We have learned a number of lessons along the way that we will explore in this post.\n\nSince the very beginning of GitLab.com, servers for the website have run in the cloud on virtual machines. These VMs are managed by Chef and installed using our [official Linux package](/install/#ubuntu).\nWhen an application update is required, [our deployment strategy](https://gitlab.com/gitlab-org/release/docs/-/blob/master/general/deploy/gitlab-com-deployer.md) is to simply upgrade fleets of servers in a coordinated rolling fashion using a CI pipeline.\nThis method, while slow and a bit [boring](https://handbook.gitlab.com/handbook/values/#boring-solutions), ensures that GitLab.com is using the same installation methods and configuration as our self-managed customers who use Linux packages.\nWe use this method because it is especially important that any pain or joy felt by the community when installing or configuring self-managed GitLab is also felt by GitLab.com.\nThis approach worked well for us for a time but as GitLab.com has grown to hosting over 10 million projects we realized it would no longer serve our needs for scaling and deployments.\n\n## Enter Kubernetes and cloud native GitLab\n\nWe created the [GitLab Charts](https://gitlab.com/gitlab-org/charts) project in 2017 to prepare GitLab for deployments in the cloud and enable self-managed users to install GitLab into a Kubernetes cluster. We knew then that running GitLab.com on Kubernetes would benefit the SaaS platform for scaling, deployments, and efficient use of compute resources. At the time though there were still many application features that depended on NFS mounts that delayed our migration off of VMs.\n\nThe push for cloud native and Kubernetes gave engineering an opportunity to plan a gradual transition that removes some of the network storage dependencies on the application while continuing to develop new features. Since we started planning the migration in the summer of 2019, most of these limitations have been resolved and the journey to running all of GitLab.com on Kubernetes is now well underway!\n\n## Running GitLab.com on Kubernetes\n\nFor GitLab.com we use a single regional GKE cluster that services all application traffic. To minimize the complexity of the (already complex) migration we focus on services that don't depend on local storage or NFS. While GitLab.com is running from mostly monolithic Rails codebase, we route traffic depending on workload characteristics to different endpoints which are isolated into their own node pools.\n\nOn the frontend these types are divided into web, API, git SSH/HTTPs requests, and Registry.\nOn the backend we divide our queued jobs into different characteristics depending on [predefined resource boundaries](/blog/scaling-our-use-of-sidekiq/) that allow us to set Service-level Objective (SLO) targets for a range of different workloads.\n\nAll of these GitLab.com services are configured with the unmodified GitLab Helm chart, which configures them in sub-charts that can be selectively enabled as we gradually migrate services to the cluster.\nWhile we opted to not include some of our stateful services such as Redis, Postgres, GitLab Pages, and Gitaly, when the migration to Kubernetes is finished it will drastically reduce the number of VMs that we currently manage with Chef.\n\n## Transparency and managing the Kubernetes configuration\n\nAll configuration is managed in GitLab itself in three configuration projects using Terraform and Helm.\nWhile we use GitLab to run GitLab wherever possible, we maintain a separate GitLab installation for operations.\nThis is done to ensure we do not depend on the availability of GitLab.com for deployments and upgrades of GitLab.com.\n\nEven though our pipelines that execute against the Kubernetes cluster run on this separate GitLab deployment, the code repositories are mirrored and publicly viewable at the following locations:\n\n* [k8s-workloads/gitlab-com](https://gitlab.com/gitlab-com/gl-infra/k8s-workloads/gitlab-com): GitLab.com configuration wrapper for the GitLab Helm chart.\n* [k8s-workloads/gitlab-helmfiles](https://gitlab.com/gitlab-com/gl-infra/k8s-workloads/gitlab-helmfiles/): Contains the configuration for services that are not directly related to the GitLab application. This includes configurations for cluster logging and monitoring and integrations like PlantUML.\n* [gitlab-com-infrastructure](https://gitlab.com/gitlab-com/gitlab-com-infrastructure): Terraform configuration for the Kubernetes and legacy VM infrastructure. All the resources necessary to run the cluster are configured here, including the cluster, node pools, service accounts, and IP address reservations.\n\n[![hpa](https://about.gitlab.com/images/blogimages/a_year_of_k8s/hpa.png)](https://gitlab.com/gitlab-com/gl-infra/k8s-workloads/gitlab-com/-/merge_requests/315#note_390180361)\nWhenever a change is proposed, a public [short summary](https://gitlab.com/gitlab-com/gl-infra/k8s-workloads/gitlab-com/-/merge_requests/315#note_390180361) is displayed, with a link to detailed diff that an SRE reviews before applying changes to the cluster.\n\n\nFor SREs, we link to a detailed diff on our operations GitLab instance that has limited access.\nThis allows employees and the community, who do not have access to the operational project which is limited to SREs, to have visibility into proposed config changes.\nBy having a public GitLab instance for code, and a private instance for [CI pipelines](/solutions/continuous-integration/), we are able to keep a single workflow while at the same time ensuring we don't have a dependency on GitLab.com for configuration updates.\n\n## The lessons we learned along the way\n\nWe have learned a few things along the way, lessons that we are applying to future migrations and new deployments into Kubernetes.\n\n### Increased billing from cross-AZ traffic\n\n![git egress](https://about.gitlab.com/images/blogimages/a_year_of_k8s/git_egress.png)\nDaily egress bytes/day from the Git storage fleet on GitLab.com.\n\n\nGoogle divides its network into regions and regions are divided into availability zones (AZs).\nBecause of the large amount of bandwidth required for Git hosting, it is important we are cognizant of network egress. For internal network traffic, egress is only free-of-charge if it remains in a single AZ.\nAt the time of writing this blog post, we deliver approximately 100TB on a typical work day for just Git repositories.\nOn legacy VM topology, services that were previously colocated on the same VMs are now running in Kubernetes pods.\nThis mean some network traffic that was previously local to a VM can now potentially traverse availability zones.\n\nRegional GKE clusters provide the convenience of spanning multiple availability zones for redundancy.\nWe are considering [splitting the regional GKE cluster into single zonal clusters](https://gitlab.com/gitlab-com/gl-infra/delivery/-/issues/1175) for services that use a lot of bandwidth to avoid network egress charges while maintaining redundancy at the cluster level.\n\n### Resource limits, requests, and scaling\n\n![replicas](https://about.gitlab.com/images/blogimages/a_year_of_k8s/replicas.png)\nNumber of replicas servicing production traffic on registry.gitlab.com, Registry traffic reaches it peak at ~15:00UTC.\n\n\nOur migration story began in August 2019 when we migrated the GitLab Container Registry to Kubernetes, the first service to move.\nThough this was a critical and high traffic service, it was a good choice for the first migration because it is a stateless application with only a few external dependencies.\nThe first challenge we experienced was the large number of evicted pods, due to memory constraints on our nodes.\nThis required multiple changes to requests and limits. We found that with an application that increases its memory utilization over time, low requests (which reserves memory for each pod) and a generous hard limit on utilization was a recipe for node saturation and a high rate of evictions.\nTo adjust for this [we eventually decided to use higher requests and lower limit](https://gitlab.com/gitlab-com/gl-infra/delivery/-/issues/998#note_388983696) which took pressure off of the nodes and allowed pods to be recycled without putting too much pressure on the node.\nAfter experiencing this once, we start our migrations with generous requests and limits that are close to the same value, and adjust down as needed.\n\n### Metrics and logging\n\n![registry-general](https://about.gitlab.com/images/blogimages/a_year_of_k8s/registry-general.png)\nThe Infrastructure department focuses on latency, error rates and saturation that have [Service-level objectives (SLOs)](https://en.wikipedia.org/wiki/Service-level_objective) that tie into our [overall system availability](https://dashboards.gitlab.net/d/general-slas/general-slas?orgId=1).\n\n\nOver the past year, one of the major changes in the infrastructure department was improvements to how we monitor and manage SLOs.\nSLOs allowed us to set targets on individual services which were monitored closely during the migration.\nYet even with this improved observability, we can't always see problems right away with our metric reporting and alerting.\nFor example, focusing on latency and error rates may not adequately cover all uses of the service that is being migrated.\nWe discovered this problem very early with some of the workloads that were moved into the cluster. This challenge was particularly acute when we had to validate features that do not receive many requests but have very specific configuration dependencies.\nOne of the key migration lessons was to also evaluate more than just monitoring metrics, but also logs, and the long-tail of errors in our monitoring.\nNow for every migration we include a detailed list of log queries and plan a clear rollback procedures that can be handed off from one shift to the next in case of issues.\n\nServing the same requests on legacy VM infrastructure and Kubernetes simultaneously presented a unique challenge.\nUnlike a lift-and-shift migration, running on legacy VMs and Kubernetes at the same time requires that our observability is compatible with both and combines metrics into one view.\nMost importantly, we are using the same dashboards and log queries to ensure the observability is consistent during the transition period.\n\n### Shifting traffic to the new cluster\n\nFor GitLab.com we maintain a segmentation of our fleet named the [canary stage](https://handbook.gitlab.com/handbook/engineering/#canary-testing).\nThis canary fleet services our internal projects, [or can be enabled by users](https://next.gitlab.com), and is deployed to first for infrastructure and application changes.\nThe first service we migrated started with taking limited traffic internally and we are continuing to use this method to ensure we are meeting our SLOs before committing all traffic to the cluster.\nWhat this means for the migration is requests to internal projects are first routed to Kubernetes and then we slowly move other traffic to the cluster using HAProxy backend weighting.\nWe learned in the process of moving from VMs to Kubernetes that it was extremely beneficial for us to have an easy way to move traffic between the old and new infrastructure, and to keep legacy infrastructure available for rollback in the first few days after the migration.\n\n### Reserved pod capacity and utilization\n\nOne problem we identified early was, while our pod start times for the Registry service were very short, our start times for Sidekiq took as long as [two minutes](https://gitlab.com/gitlab-org/charts/gitlab/-/issues/1775).\nThe long Sidekiq start times posed a challenge when we started moving workloads to Kubernetes for workers that need to process jobs quickly and scale fast.\nThe lesson here was while the Horizontal Pod Autoscaler (HPA) works well in Kubernetes for adapting to increased traffic, it is also important to evaluate workload characteristics and set reserved pod capacity, especially for uneven demand.\nIn our case, we saw a sudden spike in jobs which caused a large scaling event which saturated CPU before we could scale the node pool.\nWhile it is tempting to squeeze as much as possible out of the cluster, after experiencing some initial performance problems we now start with a generous pod budget and scale down later, while keeping a close eye on SLOs.\nThe pod start times for Sidekiq service have improved significantly and now average about 40 seconds. [Improving the pod start times](https://gitlab.com/gitlab-org/charts/gitlab/-/issues/1775) benefited GitLab.com as well as all the self-managed customers using the official GitLab Helm chart.\n\nAfter transitioning each service, we enjoyed many benefits of using Kubernetes in production, including much faster and safer deploys of the application, scaling, and more efficient resource allocation.\nThe migration benefits extend beyond GitLab.com. With each improvement of the official Helm chart, we provide additional benefits to our self-managed customers.\n\nWe hope you enjoyed reading about our Kubernetes migration journey. As we continue to migrate more services to the cluster you can read more at following links:\n\n* [Why are we migrating to Kubernetes?](https://handbook.gitlab.com/handbook/engineering/architecture/design-documents/gitlab_to_kubernetes_communication/)\n* [GitLab.com on Kubernetes](https://handbook.gitlab.com/handbook/engineering/infrastructure/production/architecture/#gitlab-com-on-kubernetes)\n* [Tracking epic for the GitLab.com Kubernetes Migration](https://gitlab.com/groups/gitlab-com/gl-infra/-/epics/112)\n\nCover image by [Nico E.](https://unsplash.com/@xnico) on [Unsplash](https://www.unsplash.com/)\n\n\n## Read more on Kubernetes:\n\n- [How to install and use the GitLab Kubernetes Operator](/blog/gko-on-ocp/)\n\n- [Threat modeling the Kubernetes Agent: from MVC to continuous improvement](/blog/threat-modeling-kubernetes-agent/)\n\n- [How to deploy the GitLab Agent for Kubernetes with limited permissions](/blog/setting-up-the-k-agent/)\n\n- [A new era of Kubernetes integrations on GitLab.com](/blog/gitlab-kubernetes-agent-on-gitlab-com/)\n\n- [Understand Kubernetes terminology from namespaces to pods](/blog/kubernetes-terminology/)\n",[23,24],"inside GitLab","production","yml",{},true,"/en-us/blog/year-of-kubernetes",{"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/year-of-kubernetes","https://about.gitlab.com","article","en-us/blog/year-of-kubernetes",[35,24],"inside-gitlab","VXHqoxCh_1RISmrUzZXBzX9EVPXDfBV0nOwdgIK8qDA",{"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 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statement",{"items":679},[680,683,686],{"text":681,"config":682},"Terms",{"href":507,"dataGaName":508,"dataGaLocation":455},{"text":684,"config":685},"Cookies",{"dataGaName":517,"dataGaLocation":455,"id":518,"isOneTrustButton":27},{"text":687,"config":688},"Privacy",{"href":512,"dataGaName":513,"dataGaLocation":455},[690],{"id":691,"title":18,"body":8,"config":692,"content":694,"description":8,"extension":25,"meta":698,"navigation":27,"path":699,"seo":700,"stem":701,"__hash__":702},"blogAuthors/en-us/blog/authors/john-jarvis.yml",{"template":693},"BlogAuthor",{"name":18,"config":695},{"headshot":696,"ctfId":697},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749678622/Blog/Author%20Headshots/jarv-headshot.jpg","jarv",{},"/en-us/blog/authors/john-jarvis",{},"en-us/blog/authors/john-jarvis","VWpIs3Q1XFVS2133bt3YMUb_e7ezj1Rf6P2P1JogPvI",[704,719,732],{"content":705,"config":717},{"title":706,"description":707,"authors":708,"heroImage":710,"date":711,"body":712,"category":9,"tags":713},"How to use GitLab Container Virtual Registry with Docker Hardened Images","Learn how to simplify container image management with this step-by-step guide.",[709],"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/)",[714,715,716],"tutorial","product","features",{"featured":12,"template":13,"slug":718},"using-gitlab-container-virtual-registry-with-docker-hardened-images",{"content":720,"config":730},{"title":721,"description":722,"authors":723,"heroImage":725,"date":726,"category":9,"tags":727,"body":729},"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.",[724],"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",[259,611,728],"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":731,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":733,"config":741},{"title":734,"description":735,"authors":736,"heroImage":737,"date":738,"category":9,"tags":739,"body":740},"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.",[724],"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",[611,259,715],"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":742,"featured":27,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"promotions":744},[745,759,770],{"id":746,"categories":747,"header":749,"text":750,"button":751,"image":756},"ai-modernization",[748],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":752,"config":753},"Get your AI maturity score",{"href":754,"dataGaName":755,"dataGaLocation":241},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":757},{"src":758},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":760,"categories":761,"header":762,"text":750,"button":763,"image":767},"devops-modernization",[715,557],"Are you just managing tools or shipping innovation?",{"text":764,"config":765},"Get your DevOps maturity score",{"href":766,"dataGaName":755,"dataGaLocation":241},"/assessments/devops-modernization-assessment/",{"config":768},{"src":769},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":771,"categories":772,"header":774,"text":750,"button":775,"image":779},"security-modernization",[773],"security","Are you trading speed for security?",{"text":776,"config":777},"Get your security maturity score",{"href":778,"dataGaName":755,"dataGaLocation":241},"/assessments/security-modernization-assessment/",{"config":780},{"src":781},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":783,"blurb":784,"button":785,"secondaryButton":790},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":786,"config":787},"Get your free trial",{"href":788,"dataGaName":48,"dataGaLocation":789},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":493,"config":791},{"href":52,"dataGaName":53,"dataGaLocation":789},1773350829884]