[{"data":1,"prerenderedAt":794},["ShallowReactive",2],{"/en-us/blog/how-gitlab-can-help-mitigate-deletion-open-source-images-docker-hub":3,"navigation-en-us":40,"banner-en-us":440,"footer-en-us":450,"blog-post-authors-en-us-Michael Friedrich":692,"blog-related-posts-en-us-how-gitlab-can-help-mitigate-deletion-open-source-images-docker-hub":706,"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":26,"isFeatured":12,"meta":27,"navigation":28,"path":29,"publishedDate":20,"seo":30,"stem":35,"tagSlugs":36,"__hash__":39},"blogPosts/en-us/blog/how-gitlab-can-help-mitigate-deletion-open-source-images-docker-hub.yml","How Gitlab Can Help Mitigate Deletion Open Source Images Docker Hub",[7],"michael-friedrich",null,"engineering",{"slug":11,"featured":12,"template":13},"how-gitlab-can-help-mitigate-deletion-open-source-images-docker-hub",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"How GitLab can help mitigate deletion of open source container images on Docker Hub","CI/CD and Kubernetes deployments can be affected by Docker Hub tier changes. This tutorial walks through analysis, mitigations, and long-term solutions.",[18],"Michael Friedrich","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749659883/Blog/Hero%20Images/post-cover-image.jpg","2023-03-16","Docker, Inc. shared an email update to Docker Hub users that it will [sunset Free Team organizations](https://www.infoworld.com/article/3690890/docker-sunsets-free-team-subscriptions-roiling-open-source-projects.html). If accounts do not upgrade to a paid plan before April 14, 2023, their organization's images may be deleted after 30 days. This change can affect open source organizations that publish their images on Docker Hub, as well as consumers of these container images, used in CI/CD pipelines, Kubernetes cluster deployments, or docker-compose demo environments. This blog post discusses tools and features on the GitLab DevSecOps platform to help users analyze and mitigate the potential impact on production environments.\n\n_Update (March 20, 2023): Docker, Inc. [published an apology blog post](https://www.docker.com/blog/we-apologize-we-did-a-terrible-job-announcing-the-end-of-docker-free-teams/), including a FAQ, and clarifies that the company will not delete container images by themselves. Maintainers can migrate to a personal account, join the Docker-sponsored open source program, or opt into a paid plan. If open source container image maintainers do nothing, this leads into another issue: Stale container images can become a security problem. The following blog post can help with security analysis and migration too._\n\n_Update (March 27, 2023): On March 24, 2023, Docker, Inc. [published another blog post](https://www.docker.com/blog/no-longer-sunsetting-the-free-team-plan/) announcing the reversal of the decision to sunset the Free team plan and updated its [FAQ for Free Team organization](https://www.docker.com/developers/free-team-faq/). While this is a welcome development for the entire community, it is still crucial to ensure the reliability of your software development lifecycle by ensuring redundancies are in place for your container registries, as detailed in this blog post._\n\n### Inventory of used container images\n\nCI/CD pipelines in GitLab can execute jobs in containers. This is specified by the [`image` keyword](https://docs.gitlab.com/ee/ci/yaml/#image) in jobs, job templates, or as a global [`default`](https://docs.gitlab.com/ee/ci/yaml/#default) attribute. For the first iteration, you can clone a GitLab project locally, and search for the `image` string in all CI/CD configuration files. The following example shows how to execute the `find` command on the command line interface (CLI), searching for files matching the name pattern `*ci.yml`, and looking for the `image` string in the file content. The command line prints a list of search pattern matches, and the corresponding file name to the standard output. The example inspects the [project](https://gitlab.com/gitlab-com/www-gitlab-com) for the [GitLab handbook](https://handbook.gitlab.com/handbook/) and [website](https://about.gitlab.com/) to analyze whether its CI/CD deployment pipelines could be affected by the Docker Hub changes.\n\n```bash\n$ git clone https://gitlab.com/gitlab-com/www-gitlab-com && cd www-gitlab-com\n\n$ find . -type f -iname '*ci.yml' -exec sh -c \"grep 'image:' '{}' && echo {}\" \\;\n\n  image: registry.gitlab.com/gitlab-org/gitlab-build-images:www-gitlab-com-debian-${DEBIAN_VERSION}-ruby-3.0-node-16\n  image: alpine:edge\n  image: alpine:edge\n  image: debian:stable-slim\n  image: debian:stable-slim\n  image: registry.gitlab.com/gitlab-org/gitlab-build-images:danger\n./.gitlab-ci.yml\n```\n\nA [discussion on Hacker News](https://news.ycombinator.com/item?id=35168802) mentions that \"official Docker images\" are not affected, but this is not officially confirmed by Docker yet. [Official Docker images](https://hub.docker.com/u/library) do not use a namespace prefix, i.e. `namespace/imagename` but instead `debian:\u003Ctagname>` for example. `registry.gitlab.com/gitlab-org/gitlab-build-images:danger` uses a full URL image string, which includes the image registry server domain, `registry.gitlab.com` in the shown example.\n\nIf there is no full URL prefix in the image string, this is an indicator that this image could be pulled from Docker Hub by default. There might be other infrastructure safety nets put in place, for example a cloud provider registry which caches the Docker Hub images (Google Cloud, AWS, Azure, etc.).\n\n#### Advanced search for images\n\nYou can use the [project lint API endpoint](https://docs.gitlab.com/ee/api/lint.html#validate-a-projects-ci-configuration) to fetch the CI configuration. The following script uses the [python-gitlab API library](https://python-gitlab.readthedocs.io/en/stable/gl_objects/ci_lint.html) to implement the API endpoint:\n\n1. Collect all projects from either a single project ID, a group ID with projects, or from the instance.\n2. Run the `project.ci_lint.get()` method to get a merged yaml configuration for CI/CD from the current GitLab project.\n3. Parse the yaml content and print only the job names, and the image keys.\n\nThe [full script is located here](https://gitlab.com/gitlab-da/use-cases/gitlab-api/gitlab-api-python/-/blob/main/get_all_cicd_job_images.py), and is open source, licensed under MIT.\n\n```python\n#!/usr/bin/env python\n\nimport gitlab\nimport os\nimport sys\nimport yaml\n\nGITLAB_SERVER = os.environ.get('GL_SERVER', 'https://gitlab.com')\nGITLAB_TOKEN = os.environ.get('GL_TOKEN') # token requires developer permissions\nPROJECT_ID = os.environ.get('GL_PROJECT_ID') #optional\n# https://gitlab.com/gitlab-da/use-cases/docker\nGROUP_ID = os.environ.get('GL_GROUP_ID', 65096153) #optional\n\n#################\n# Main\n\nif __name__ == \"__main__\":\n    if not GITLAB_TOKEN:\n        print(\"🤔 Please set the GL_TOKEN env variable.\")\n        sys.exit(1)\n\n    gl = gitlab.Gitlab(GITLAB_SERVER, private_token=GITLAB_TOKEN)\n\n    # Collect all projects, or prefer projects from a group id, or a project id\n    projects = []\n\n    # Direct project ID\n    if PROJECT_ID:\n        projects.append(gl.projects.get(PROJECT_ID))\n\n    # Groups and projects inside\n    elif GROUP_ID:\n        group = gl.groups.get(GROUP_ID)\n\n        for project in group.projects.list(include_subgroups=True, all=True):\n            # https://python-gitlab.readthedocs.io/en/stable/gl_objects/groups.html#examples\n            manageable_project = gl.projects.get(project.id)\n            projects.append(manageable_project)\n\n    # All projects on the instance (may take a while to process)\n    else:\n        projects = gl.projects.list(get_all=True)\n\n    print(\"# Summary of projects and their CI/CD image usage\")\n\n    # Loop over projects, fetch .gitlab-ci.yml, run the linter to get the full translated config, and extract the `image:` setting\n    for project in projects:\n\n        print(\"# Project: {name}, ID: {id}\\n\\n\".format(name=project.name_with_namespace, id=project.id))\n\n        # https://python-gitlab.readthedocs.io/en/stable/gl_objects/ci_lint.html\n        lint_result = project.ci_lint.get()\n\n        data = yaml.safe_load(lint_result.merged_yaml)\n\n        for d in data:\n            print(\"Job name: {n}\".format(n=d))\n            for attr in data[d]:\n                if 'image' in attr:\n                    print(\"Image: {i}\".format(i=data[d][attr]))\n\n        print(\"\\n\\n\")\n\nsys.exit(0)\n```\n\nThe [script](https://gitlab.com/gitlab-da/use-cases/gitlab-api/gitlab-api-python/-/blob/main/get_all_cicd_job_images.py) requires Python (tested with 3.11) and the python-gitlab and pyyaml modules. Example on macOS with Homebrew:\n\n```shell\n$ brew install python\n$ pip3 install python-gitlab pyyaml\n```\n\nYou can execute the script and set the different environment variables to control its behavior:\n\n```shell\n$ export GL_TOKEN=$GITLAB_TOKEN\n\n$ export GL_GROUP_ID=12345\n$ export GL_PROJECT_ID=98765\n\n$ python3 get_all_cicd_job_images.py\n\n# Summary of projects and their CI/CD image usage\n# Project: Developer Evangelism at GitLab  / use-cases / Docker Use cases  / Custom Container Image Python, ID: 44352983\n\nJob name: docker-build\nImage: docker:latest\n\n# Project: Developer Evangelism at GitLab  / use-cases / Docker Use cases  / Gitlab Dependency Proxy, ID: 44351128\n\nJob name: .test-python-version\nJob name: image-docker-hub\nImage: python:3.11\nJob name: image-docker-hub-dep-proxy\nImage: ${CI_DEPENDENCY_PROXY_GROUP_IMAGE_PREFIX}/python:3.11\n```\n\nPlease verify the script and fork it for your own analysis and mitigation. The missing parts are checking the image URLs, and doing a more sophisticated search. The code has been prepared to either check against a single project, a group with projects, or an instance (this may take very long, use with care).\n\nYou can perform a more history-focused analysis by fetching the CI/CD job logs from GitLab and search for the pulled container image to get an overview of past Docker executor runs – for example: `Using Docker executor with image python:3.11 ...`. The screenshot shows the CI/CD job logs UI search – you can automate the search using the GitLab API, and the [python-gitlab library](https://python-gitlab.readthedocs.io/en/stable/gl_objects/pipelines_and_jobs.html#jobs), for example.\n\n![GitLab CI/CD job logs, searching for the `image` keyword](https://about.gitlab.com/images/blogimages/docker-hub-oss-image-deletion-mitigation/cicd_gitlab_job_logs_search_image.png)\n\nThis snippet can be used in combination with the code shared for the CI lint API endpoint. It fetches the job trace logs, and searches for the `image` keyword in the log. The missing parts are splitting the log line by line, and extracting the image key information. This is left as an exercise for the reader.\n\n```python\n\n        for job in project.jobs.list():\n            log_trace = str(job.trace())\n\n            print(log_trace)\n\n            if 'image' in log_trace:\n                print(\"Job ID: {i}, URL {u}\".format(i=job.id, u=job.web_url))\n                print(log_trace)\n\n```\n\n### More inventory considerations\n\nSimilar to the API script for CI/CD navigating through all projects, you will need to analyze all Kubernetes manifest configuration files – using either a pull- or push-based approach. This can be achieved by using the [python-gitlab methods to load files from the repository](https://python-gitlab.readthedocs.io/en/stable/gl_objects/projects.html#project-files) and searching the content in similar ways. Helm charts use container images, too, and will require additional analysis.\n\nAn additional search possibility: Custom-built container images that use Docker Hub images as a source. A project will consist of:\n\n1. `Dockerfile` file that uses `FROM \u003Cimagename>`\n2. `.gitlab-ci.yml` configuration file that builds container images (using Docker-in-Docker, Kaniko, etc.)\n\nAn alternative search method for customers is available by using the [Advanced Search](https://docs.gitlab.com/ee/user/search/advanced_search.html) through the GitLab UI and API. The following example uses the [scope: blobs](https://docs.gitlab.com/ee/api/search.html#scope-blobs-premium-2) to search for the `FROM` string:\n\n```shell\n$ export GITLAB_TOKEN=xxxxxxxxx\n\n# Search in https://gitlab.com/gitlab-da\n/use-cases/docker/custom-container-image-python\n\n$ curl --header \"PRIVATE-TOKEN: $GITLAB_TOKEN\" \"https://gitlab.com/api/v4/projects/44352983/search?scope=blobs&search=FROM%20filename:Dockerfile*\"\n```\n\n![Command line output from Advanced Search API, scope blobs, search `FROM` in `Dockerfile*` file names.](https://about.gitlab.com/images/blogimages/docker-hub-oss-image-deletion-mitigation/cli_gitlab_advanced_search_api_dockerfile_from.png)\n\n## Mitigations and solutions\n\nThe following sections discuss potential mitigation strategies, and long-term solutions.\n\n### Mitigation: GitLab dependency proxy\n\nThe dependency proxy provides a caching mechanism for Docker Hub images. It helps reduce the bandwidth and time required to download and pull the images. It also helped to [mitigate the Docker Hub pull rate limits introduced in 2020](/blog/minor-breaking-change-dependency-proxy/). The dependency proxy can be configured for public and private projects.\n\nThe [dependency proxy](https://docs.gitlab.com/ee/user/packages/dependency_proxy/) needs to be enabled for a group. It also needs to be enabled by an instance administrator for self-managed environments, if turned off.\n\nThe following example creates two jobs: `image-docker-hub` and `image-docker-hub-dep-proxy`. The dependency proxy job uses the `CI_DEPENDENCY_PROXY_GROUP_IMAGE_PREFIX` CI/CD variable to instruct GitLab to store the image in the cache, and only pull it once when not available.\n\n```yaml\n.test-python-version:\n  script:\n    - echo \"Testing Python version:\"\n    - python --version\n\nimage-docker-hub:\n  extends: .test-python-version\n  image: python:3.11\n\nimage-docker-hub-dep-proxy:\n  extends: .test-python-version\n  image: ${CI_DEPENDENCY_PROXY_GROUP_IMAGE_PREFIX}/python:3.11\n\n```\n\nThe configuration is available in [this project](https://gitlab.com/gitlab-da/use-cases/docker/gitlab-dependency-proxy).\n\nThe stored container image is visible at the group level in the `Package and container registries > Dependency Proxy` menu.\n\n### Mitigation: Container registry mirror\n\n[This blog post](/blog/mitigating-the-impact-of-docker-hub-pull-requests-limits/) describes how to run a local container registry mirror. Skopeo from Red Hat is another alternative for syncing container image registries, a practical example is described [in this article](https://marcbrandner.com/blog/transporting-container-images-with-skopeo/).\n\nThe GitLab Cloud Native installation ([Helm charts](https://docs.gitlab.com/charts/) and [Operator](https://docs.gitlab.com/operator/)) use a [mirror of tagged images](https://gitlab.com/gitlab-org/cloud-native/mirror/images) consumed by the related projects. Other product stages follow a similar approach, the [security scanners are shipped in container images](https://docs.gitlab.com/ee/user/application_security/offline_deployments/#container-registries-and-package-repositories) maintained by GitLab. This also enables self-managed airgapped installations.\n\n### Mitigation: Custom images in GitLab container registry\n\nReproducible builds and compliance requirements may have required you to create custom container images for CI/CD and Kubernetes already. This is also key to verify that no untested and untrusted images are being used in production. GitLab provides a fully integrated [container registry](https://docs.gitlab.com/ee/user/packages/container_registry/), which can be used natively within CI/CD pipelines and [GitOps workflows with the agent for Kubernetes](https://docs.gitlab.com/ee/user/clusters/agent/gitops.html).\n\nThe following `Dockerfile` example extends an existing image layer, and installs additional tools using the Debian Apt package manager.\n\n```text\nFROM python:3.11-bullseye\n\nENV DEBIAN_FRONTEND noninteractive\n\nRUN apt update && apt -y install git curl jq && rm -rf /var/lib/apt/lists/*\n```\n\nYou can [use Docker to build container images](https://docs.gitlab.com/ee/ci/docker/using_docker_build.html), and alternative options are Kaniko or Podman. On GitLab.com SaaS, you can use the Docker CI/CD template to build and push images. The following example modifies the `docker-build` job to only build the latest tag from the default branch:\n\n```yaml\ninclude:\n  - template: Docker.gitlab-ci.yml\n\ndocker-build:\n  stage: build\n  rules:\n    - if: '$CI_COMMIT_REF_NAME == $CI_DEFAULT_BRANCH || $CI_COMMIT_TAG'\n      #when: manual\n      #allow_failure: true\n\n```\n\nFor this example, we specifically want to provide a Git tag that gets used for the container image tag as well.\n\n```shell\n$ git tag 3-11-bullseye\n$ git push --tags\n```\n\nThe image will be available at the GitLab container registry URL and the project namespace path.This path needs to be replaced in all projects that use a Python-based image. You can [create scripts for the GitLab API](/blog/efficient-devsecops-workflows-hands-on-python-gitlab-api-automation/) to update files and create MRs automatically,\n\n```text\nimage: registry.gitlab.com/gitlab-da/use-cases/docker/custom-container-image-python:3-11-bullseye\n```\n\n_Note: This is a demo project and not actively maintained. Please fork/copy it for your own needs._\n\n## Observability and security\n\nThe [number of failed CI/CD pipelines](https://docs.gitlab.com/ee/user/analytics/ci_cd_analytics.html) can be a good service level indicator (SLI) to verify whether the environment is affected by the Docker Hub changes. The same SLI applies for CI/CD jobs that build container images, using a `Dockerfile` file, which is based on Docker Hub images (FROM \u003Cimagename>).\n\nA similar SLI applies to Kubernetes cluster deployments – if they continue to generate failures in GitOps pull or CI/CD push scenarios, additional analysis and actions are required. The pod status `ErrImagePull` and [`ImagePullBackOff`](https://kubernetes.io/docs/concepts/containers/images/#imagepullbackoff) will immediately show the problems. The [image pull policy](https://kubernetes.io/docs/concepts/containers/images/#image-pull-policy) should also be revised – `Always` will immediately cause a problem, while `IfNotPresent` will use the local image cache.\n\n[This alert rule example](https://awesome-prometheus-alerts.grep.to/rules.html#rule-kubernetes-1-18) for Prometheus observing a Kubernetes cluster can help detect the pod state as not healthy.\n\n```yaml\n\n  - alert: KubernetesPodNotHealthy\n    expr: sum by (namespace, pod) (kube_pod_status_phase{phase=~\"Pending|Unknown|Failed\"}) > 0\n    for: 15m\n    labels:\n      severity: critical\n    annotations:\n      summary: Kubernetes Pod not healthy (instance {{ $labels.instance }})\n      description: \"Pod has been in a non-ready state for longer than 15 minutes.\\n  VALUE = {{ $value }}\\n  LABELS = {{ $labels }}\"\n\n```\n\nCI/CD pipeline linters and Git hooks can also be helpful to enforce using a GitLab registry URL prefix in all `image` tags, when new updates to CI/CD configurations are being pushed into merge requests.\n\nKubernetes deployment images can be controlled through additional integrations with the [Open Policy Agent Gatekeeper](https://www.openpolicyagent.org/docs/latest/kubernetes-introduction/) or [Kyverno](https://kyverno.io/policies/best-practices/restrict_image_registries/restrict_image_registries/). Kyverno also allows you to [mutate the image registry location](https://kyverno.io/policies/other/replace_image_registry/replace_image_registry/), and redirect the pod image to trusted sources.\n\n[Operational container scanning](https://docs.gitlab.com/ee/user/clusters/agent/vulnerabilities.html) in Kubernetes clusters and [container scanning in CI/CD pipelines](https://docs.gitlab.com/ee/user/application_security/container_scanning/) are recommended. This ensures that all images do not expose security vulnerabilities.\n\n## Long-term solutions\n\nAs a long-term solution, analyze the affected Docker Hub organizations images and match them against your image usage inventory. Some organizations have raised their concerns in [this Docker Hub feedback issue](https://github.com/docker/hub-feedback/issues/2314). Be sure to identify critical production CI/CD workflows and replace all external dependencies with local maintained images.\n\nFork/copy project Dockerfile files from the upstream Git repositories, and use them as the single source of truth for custom container builds. This will also require training and documentation for DevSecOps teams, for example optimizing container images for [efficient CI/CD pipelines](https://docs.gitlab.com/ee/ci/pipelines/pipeline_efficiency.html). More DevSecOps efficiency tips can be found in my Chemnitz Linux Days talk about \"Efficient DevSecOps Pipelines in a Cloud Native World\" ([slides](https://go.gitlab.com/RPog2h)).\n\n\u003Ciframe src=\"https://docs.google.com/presentation/d/e/2PACX-1vT3jcfpddKL2jq7leX01QX6S4Y8vfLLBZMz4L1ZHMLY3xzB4IGOOIExODLEzH8YQM1atCNPm07Bw9m_/embed?start=false&loop=true&delayms=3000\" frameborder=\"0\" width=\"960\" height=\"569\" allowfullscreen=\"true\" mozallowfullscreen=\"true\" webkitallowfullscreen=\"true\">\u003C/iframe>\n\nPlease share your ideas and thoughts about Docker Hub change mitigations and tools on the [GitLab community forum](https://forum.gitlab.com/). Thank you!\n\nCover image by [Roger Hoyles](https://unsplash.com/photos/sTOQyRD8m74) on [Unsplash](https://www.unsplash.com)\n",[23,24,25],"CI","kubernetes","open source","yml",{},true,"/en-us/blog/how-gitlab-can-help-mitigate-deletion-open-source-images-docker-hub",{"title":31,"description":16,"ogTitle":31,"ogDescription":16,"noIndex":12,"ogImage":19,"ogUrl":32,"ogSiteName":33,"ogType":34,"canonicalUrls":32},"GitLab helps mitigate Docker Hub's open source image removal","https://about.gitlab.com/blog/how-gitlab-can-help-mitigate-deletion-open-source-images-docker-hub","https://about.gitlab.com","article","en-us/blog/how-gitlab-can-help-mitigate-deletion-open-source-images-docker-hub",[37,24,38],"ci","open-source","lfh4i_beMJcuY2nh4LKMoXH2wuK915JOx2vzhWK3ypM",{"data":41},{"logo":42,"freeTrial":47,"sales":52,"login":57,"items":62,"search":370,"minimal":401,"duo":420,"pricingDeployment":430},{"config":43},{"href":44,"dataGaName":45,"dataGaLocation":46},"/","gitlab 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to use GitLab Container Virtual Registry with Docker Hardened Images","Learn how to simplify container image management with this step-by-step guide.",[712],"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/)",[717,718,719],"tutorial","product","features",{"featured":12,"template":13,"slug":721},"using-gitlab-container-virtual-registry-with-docker-hardened-images",{"content":723,"config":732},{"title":724,"description":725,"authors":726,"heroImage":728,"date":729,"category":9,"tags":730,"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.",[727],"Nick Veenhof","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099013/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2814%29_6VTUA8mUhOZNDaRVNPeKwl_1750099012960.png","2026-01-08",[262,614,25],"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.",[727],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099203/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2820%29_2bJGC5ZP3WheoqzlLT05C5_1750099203484.png","2025-12-10",[614,262,718],"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":28,"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":244},"/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",[718,560],"Are you just managing tools or shipping innovation?",{"text":766,"config":767},"Get your DevOps maturity score",{"href":768,"dataGaName":757,"dataGaLocation":244},"/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":244},"/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":51,"dataGaLocation":791},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":496,"config":793},{"href":55,"dataGaName":56,"dataGaLocation":791},1773350812039]