[{"data":1,"prerenderedAt":804},["ShallowReactive",2],{"/en-us/blog/can-chatgpt-resolve-gitlab-issues":3,"navigation-en-us":41,"banner-en-us":440,"footer-en-us":450,"blog-post-authors-en-us-John Coghlan|Fatima Sarah Khalid":690,"blog-related-posts-en-us-can-chatgpt-resolve-gitlab-issues":716,"assessment-promotions-en-us":755,"next-steps-en-us":794},{"id":4,"title":5,"authorSlugs":6,"body":9,"categorySlug":10,"config":11,"content":15,"description":9,"extension":29,"isFeatured":13,"meta":30,"navigation":31,"path":32,"publishedDate":22,"seo":33,"stem":37,"tagSlugs":38,"__hash__":40},"blogPosts/en-us/blog/can-chatgpt-resolve-gitlab-issues.yml","Can Chatgpt Resolve Gitlab Issues",[7,8],"john-coghlan","fatima-sarah-khalid",null,"engineering",{"slug":12,"featured":13,"template":14},"can-chatgpt-resolve-gitlab-issues",false,"BlogPost",{"title":16,"description":17,"authors":18,"heroImage":21,"date":22,"body":23,"category":10,"tags":24},"Testing ChatGPT: Can it solve a GitLab issue?","We put ChatGPT to the test to see if it could contribute to GitLab. Here's what we learned.",[19,20],"John Coghlan","Fatima Sarah Khalid","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749670171/Blog/Hero%20Images/akshay-nanavati-Zq6HerrBPEs-unsplash.jpg","2022-12-15","\nChatGPT has taken the tech world by storm since its [launch on November 30](https://openai.com/blog/chatgpt/). Media coverage, front page posts on Hacker News, Twitter threads, and videos - everywhere you look, there is another story.\n\nThe [GitLab Slack](https://handbook.gitlab.com/handbook/communication/#slack) was no different. In threads across Slack channels, including those for developer evangelism, UX, the CEO, random news, and every space in between, our team was chatting about this exciting new tool.\n\nAs we got more familiar with the tool, we started to learn about numerous things it can do. Here are a few that we found:\n\n- It can write poetry about GitLab features.\n- It can write blog posts.\n- It can write unit tests.\n- It gives advice on how to use certain features of GitLab.\n- It conducts competitive analysis.\n\nThere’s quite a bit more out there, including [inventing a new language](https://maximumeffort.substack.com/p/i-taught-chatgpt-to-invent-a-language) and [building a virtual machine](https://www.engraved.blog/building-a-virtual-machine-inside/). We can’t recall any technology that has generated more excitement in such a short time.\n\nWe acknowledge there are ethical and licensing concerns around using AI-generated code. For the purpose of this blog post, we will focus strictly on the capabilities of ChatGPT.\n\n## Testing ChatGPT\n\nAs members of GitLab’s [Developer Relations team](https://handbook.gitlab.com/handbook/marketing/developer-relations/), where we’re focused on growing our community of contributors and evangelists, our first reaction was to think of how this tool can help our contributors. The responses to questions like “How can I get started contributing to GitLab?” were cool but didn’t move the needle. So then we asked ourselves: Can we use ChatGPT to make a contribution to GitLab?\n\nHaving already been testing the tool, we knew we’d need to look for a very specific type of issue. We started to fine-tune our search. Here are the steps we took to find a potential issue:\n\n- Visited [https://gitlab.com/gitlab-org](https://gitlab.com/gitlab-org) and pulled up all the open issues by clicking on `Issues` in the left side nav.\n- Searched for all issues with the [“good for new contributors” label](https://gitlab.com/gitlab-org/gitlab/-/issues/?sort=updated_desc&state=opened&label_name%5B%5D=good%20for%20new%20contributors&first_page_size=20). This returned 482 issues at the time of writing.\n- Set [`“Assignee = None”`](https://gitlab.com/gitlab-org/gitlab/-/issues/?sort=updated_desc&state=opened&label_name%5B%5D=good%20for%20new%20contributors&assignee_id=None&first_page_size=20) to filter out issues that have already been assigned to someone. This trimmed things down even more.\n\nAfter poking through a few issues, this one caught our attention: an issue that is a request to [de-depulicate identical dropdown functionality from two Vue components into a shared component](https://gitlab.com/gitlab-org/gitlab/-/issues/221293).\n\n### Getting started\n\nWe opened up a ChatGPT thread via [https://chat.openai.com/chat](https://chat.openai.com/chat). If you don’t already have an account, you’ll need to register with OpenAI.\n\nThen we started a thread with Assistant (that’s what is returned when you ask ChatGPT what is its name). We asked Assistant to create a shared Vue component called `SharedDropdownFilter` from the duplicate code in `GroupsDropdownFilter` and `ProjectsDropdownFilter` and passed the scripts of both components.\n\nChatGPT replied with:\n\n>You can create a new `SharedDropdownFilter` component that contains the duplicate code and use it in both `GroupsDropdownFilter` and `ProjectsDropdownFilter`:\n\nand provided a template to describe the use. The template provided wasn’t quite what we were looking for.\n\n```xml\n\u003Ctemplate>\n  \u003CGlDropdown\n    :aria-label=\"label\"\n    :class=\"{ disabled: loading }\"\n    :disabled=\"loading\"\n    :selected=\"selectedProjectsLabel\"\n    :variant=\"multiSelect ? 'inline' : 'single-line'\"\n  >\n    \u003Ctemplate v-slot:menu>\n      \u003Cdiv class=\"py-4\">\n        \u003CGlSearchBoxByType\n          autofocus\n          class=\"search-box\"\n          :placeholder=\"searchPlaceholder\"\n          :type=\"searchType\"\n          v-model=\"searchTerm\"\n        />\n\n        \u003CGlDropdownHeader\n          v-if=\"selectedProjects.length && multiSelect\"\n          :class=\"{ 'd-none': !searchTerm }\"\n          class=\"js-dropdown-header\"\n        >\n          \u003Cspan>\n            {{ selectedProjectsLabel }}\n          \u003C/span>\n\n          \u003Cbutton\n\n```\n\nSo we tried again, this time being more specific and asking ChatGPT to “Create a shared Vue component that combines the two components `ProjectsDropdownFilter` and  `GroupsDropdownFilter`”. We passed in the full component files, including the templates.\n\nChatGPT responded with instructions, a sample Vue component, and an explanation of the functionality:\n\n> Here is a sample implementation of a shared Vue component that combines the two components `ProjectsDropdownFilter` and `GroupsDropdownFilter`:\n\n```vue\n\u003Ctemplate>\n  \u003Cdiv>\n    \u003CProjectsDropdownFilter\n      :groupId=\"groupId\"\n      :multiSelect=\"multiSelect\"\n      :label=\"label\"\n      :queryParams=\"queryParams\"\n      :defaultProjects=\"defaultProjects\"\n      @selected=\"onProjectsSelected\"\n    />\n    \u003CGroupsDropdownFilter\n      :multiSelect=\"multiSelect\"\n      :label=\"label\"\n      :queryParams=\"queryParams\"\n      :defaultGroups=\"defaultGroups\"\n      @selected=\"onGroupsSelected\"\n    />\n  \u003C/div>\n\u003C/template>\n\n\u003Cscript>\nimport { ProjectsDropdownFilter } from './ProjectsDropdownFilter.vue';\nimport { GroupsDropdownFilter } from './GroupsDropdownFilter.vue';\n\nexport default {\n  name: 'SharedDropdownFilter',\n  components: {\n    ProjectsDropdownFilter,\n    GroupsDropdownFilter,\n  },\n  props: {\n    groupId: {\n      type: Number,\n      required: true,\n    },\n    multiSelect: {\n      type: Boolean,\n      required: false,\n      default: false,\n    },\n    label: {\n      type: String,\n      required: false,\n      default: 'Dropdown filter',\n    },\n    queryParams: {\n      type: Object,\n      required: false,\n      default: () => ({}),\n    },\n    defaultProjects: {\n      type: Array,\n      required: false,\n      default: () => [],\n    },\n    defaultGroups: {\n      type: Array,\n      required: false,\n      default: () => [],\n    },\n  },\n  data() {\n    return {\n      selectedProjects: this.defaultProjects || [],\n      selectedGroups: this.defaultGroups || [],\n    };\n  },\n  methods: {\n    onProjectsSelected(selectedProjects) {\n      this.selectedProjects = selectedProjects;\n      this.$emit('selected', this.selectedProjects, this.selectedGroups);\n    },\n    onGroupsSelected(selectedGroups) {\n      this.selectedGroups = selectedGroups;\n      this.$emit('selected', this.selectedProjects, this.selectedGroups);\n    },\n  },\n};\n\u003C/script>\n```\n\n> In this implementation, the `SharedDropdownFilter` component is rendered as a container for the `ProjectsDropdownFilter` and` GroupsDropdownFilter` components. It passes down the `groupId`, `multiSelect`, `label`, `queryParams`, and `defaultProjects` props to the `ProjectsDropdownFilter` component, and the `multiSelect`, `label`, `queryParams`, and `defaultGroups` props to the `GroupsDropdownFilter` component. It also listens to the selected event emitted by the two components and updates its own `selectedProjects` and `selectedGroups` data accordingly. The `SharedDropdownFilter` component emits its own `selected` event with the updated `selectedProjects` and `selectedGroups` data when it receives the selected event from the `ProjectsDropdownFilter` and `GroupsDropdownFilter` components. This allows the parent component of the `SharedDropdownFilter` to be notified whenever the selected projects and groups are updated, so that it can take appropriate action, such as updating the data it displays.\n\nWith ChatGPT’s shared Vue component, we could start an MR for the issue, but would need to manually review the code and run tests in order to make sure the deduplication was done correctly.\n\n### Adjusting the filters\n\nIn hopes of finding an issue that ChatGPT could fully solve, this time we filtered using two labels (`good for new contributors` and `quick win`), Assignee = None, and added the keyword “refactor” to look for issues that required less net new code. At the time of writing, this [query](https://gitlab.com/gitlab-org/gitlab/-/issues/?search=refactor&sort=updated_asc&state=opened&label_name%5B%5D=quick%20win&label_name%5B%5D=good%20for%20new%20contributors&assignee_id=None&first_page_size=20) returned one issue: [a refactor for widget state tests](https://gitlab.com/gitlab-org/gitlab/-/issues/228611).\n\nAfter reviewing the issue, we opened the `/spec/frontend/vue_merge_request_widget/stores/get_state_key_spec.js` file mentioned in the issue description by navigating to that file on GitLab.com SaaS and opening the dropdown on the blue button at the top of the file frame, selecting “Open in Web IDE”, and then clicking the button to open the file in GitLab’s built-in Web IDE.\n\nWe copied the code from the file and asked ChatGPT to refactor these tests into a table of `it.each`. It was interesting to watch the output as ChatGPT provided an example of how we could refactor the tests using `it.each`:\n\n```javascript\nimport getStateKey from '~/vue_merge_request_widget/stores/get_state_key';\n\ndescribe('getStateKey', () => {\n  const context = {\n    mergeStatus: 'checked',\n    autoMergeEnabled: false,\n    canMerge: true,\n    onlyAllowMergeIfPipelineSucceeds: false,\n    isPipelineFailed: false,\n    hasMergeableDiscussionsState: false,\n    isPipelineBlocked: false,\n    canBeMerged: false,\n    projectArchived: false,\n    branchMissing: false,\n    commitsCount: 2,\n    hasConflicts: false,\n    draft: false,\n    detailedMergeStatus: null,\n  };\n\n  it.each([\n    [{}, null],\n    [{detailedMergeStatus: 'MERGEABLE'}, 'readyToMerge'],\n    [{detailedMergeStatus: 'DISCUSSIONS_NOT_RESOLVED'}, 'unresolvedDiscussions'],\n    [{detailedMergeStatus: 'DRAFT_STATUS'}, 'draft'],\n    [{detailedMergeStatus: 'CI_MUST_PASS'}, 'pipelineFailed'],\n    [{shouldBeRebased: true}, 'rebase'],\n    [{hasConflicts: true}, 'conflicts'],\n    [{detailedMergeStatus: 'CHECKING'}, 'checking'],\n    [{commitsCount: 0}, 'nothingToMerge'],\n    [{commitsCount: 1, branchMissing: true}, 'missingBranch'],\n    [{projectArchived: true}, 'archived'],\n  ])('should return \"%s\" when called with %p', (expected, input) => {\n    const bound = getStateKey.bind(Object.assign({}, context, input));\n    expect(bound()).toEqual(expected);\n  });\n\n  it('returns rebased state key', () => {\n    const context = {\n      mergeStatus: 'checked',\n      autoMergeEnabled: false,\n      canMerge: true,\n      onlyAllowMergeIfPipelineSucceeds: true,\n      isPipelineFailed: true,\n      hasMergeableDiscussionsState: false,\n      isPipelineBlocked: false,\n      canBeMerged: false,\n      shouldBeRebased: true,\n      projectArchived: false,\n      branchMissing: false,\n      commitsCount: 2,\n      hasConflicts: false,\n      draft: false,\n    };\n    const bound = getStateKey.bind(context);\n\n    expect(bound()).toEqual('rebase');\n  });\n});\n```\n\nAlong with an explanation of `it.each`:\n\n> Note that `it.each` is a utility provided by Jest that allows you to write the same test with different inputs and expected results. This can make your tests more concise and easier to read.\n\nOur next steps were to:\n- Paste the output from ChatGPT into the Web IDE.\n- Click the blue “Commit” button to commit the code.\n- Name the branch.\n- Open a merge request.\n\nAll of this can be done inside [GitLab’s Web IDE](https://docs.gitlab.com/ee/user/project/web_ide/) without leaving the browser.\n\n### Examining the results\n\nOnce we opened the merge request, a CI/CD pipeline was created to test the change. Unfortunately, the pipeline jobs for the Jest tests failed because the tests were returning `null` for each case instead of the expected results. We went back to ChatGPT to see if it could help us understand why the test was returning null for all cases. ChatGPT suggested a few different implementations to check to make sure things are defined currently:\n\n> There are a few reasons why the tests in the `it.each` function might be returning null for every case. Here are a few possibilities:\n>\n> If the `getStateKey` function is not implemented correctly, it might always return null, regardless of the input.\n> If the `getStateKey` function relies on certain variables that are not defined in the test cases, it might return null because those variables are undefined.\n> If the context object passed to the `getStateKey` function is not being merged correctly with the input object in the test cases, the function might not have access to all of the necessary information, and it might return null.\n\nWhile ChatGPT couldn’t solve the issue with the returned value directly, it provided a lot of possibilities to look into and offered suggestions of what variables or functions to debug. The suggestions prompted us to add code changes that logged the variable values onto the [JavaScript debug console](https://www.w3schools.com/js/js_debugging.asp), find the implementation of the `getStateKey` function, and figure out why the return value was null. Whenever we came across something unfamiliar in the code, like syntax in the `it.each` that wasn’t familiar, we asked ChatGPT for clarification or a helpful example. Many times throughout this experiment, working with ChatGPT felt like “rubber duck debugging,” but with an AI with which you have to be very specific about your ask.\n\n## What we learned from ChatGPT\n\nIn the end, we weren’t able to figure out why our tests were returning null, so we asked the front-end team if someone could review the code. Senior Frontend Engineer [Angelo Gulina](https://gitlab.com/agulina) reviewed the MR. He found that the solution was actually quite trivial: The order of parameters was inverted, resulting in a comparison that led to null! In his assessment, ChatGPT wasn’t able to provide a working solution, but would be able to provide solutions and ideas to an engineer with some experience with the codebase. It delivered a clean, organized solution and answered the task of combining the tests into an it.each table. It could not, however, catch the actual error (the inversion of parameters) or correctly guess why the tests were returning null.\n\nLet's circle back to the question that started this experiment: Can we use ChatGPT to contribute to GitLab? At this time, we’d say, \"yes,\" and you will need some understanding of the code to complete your solution. Since ChatGPT is a language model trained by OpenAI, it can only answer questions and provide information addressed in the model, which means answers requiring contextual specificity may fall short of what is needed to resolve an issue. However, it’s a tool that can help you if you’re stuck, need more clarification on a code snippet, or are trying to refactor some code. It was fascinating for us to experiment with ChatGPT and we were excited to see what it was capable of. The code provided, however, lacked some of the valuable insight and industry experience that a community of contributors can provide.\n\nAt GitLab, our [community and our open source stewardship](https://handbook.gitlab.com/handbook/company/strategy/#dual-flywheels) are part of our company strategy. Thousands of open source contributors worldwide have helped make GitLab what it is today. We see potential for ChatGPT and similar AI tools, not as a replacement for our community, but a way to make our community more efficient and enable more people to contribute GitLab.\n\n\n\n\n",[25,26,27,28],"tutorial","community","contributors","DevOps","yml",{},true,"/en-us/blog/can-chatgpt-resolve-gitlab-issues",{"title":16,"description":17,"ogTitle":16,"ogDescription":17,"noIndex":13,"ogImage":21,"ogUrl":34,"ogSiteName":35,"ogType":36,"canonicalUrls":34},"https://about.gitlab.com/blog/can-chatgpt-resolve-gitlab-issues","https://about.gitlab.com","article","en-us/blog/can-chatgpt-resolve-gitlab-issues",[25,26,27,39],"devops","vw5IorIWvERshGTFnXUlGbFRMgBjdvB4D1Fiz6PXE3M",{"data":42},{"logo":43,"freeTrial":48,"sales":53,"login":58,"items":63,"search":370,"minimal":401,"duo":420,"pricingDeployment":430},{"config":44},{"href":45,"dataGaName":46,"dataGaLocation":47},"/","gitlab logo","header",{"text":49,"config":50},"Get free 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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.",[722],"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/)",[25,727,728],"product","features",{"featured":13,"template":14,"slug":730},"using-gitlab-container-virtual-registry-with-docker-hardened-images",{"content":732,"config":742},{"title":733,"description":734,"authors":735,"heroImage":737,"date":738,"category":10,"tags":739,"body":741},"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.",[736],"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",[26,612,740],"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":743,"featured":13,"template":14},"how-iit-bombay-students-code-future-with-gitlab",{"content":745,"config":753},{"title":746,"description":747,"authors":748,"heroImage":749,"date":750,"category":10,"tags":751,"body":752},"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.",[736],"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",[612,26,727],"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":754,"featured":31,"template":14},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"promotions":756},[757,771,782],{"id":758,"categories":759,"header":761,"text":762,"button":763,"image":768},"ai-modernization",[760],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":764,"config":765},"Get your AI maturity score",{"href":766,"dataGaName":767,"dataGaLocation":245},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":769},{"src":770},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":772,"categories":773,"header":774,"text":762,"button":775,"image":779},"devops-modernization",[727,558],"Are you just managing tools or shipping innovation?",{"text":776,"config":777},"Get your DevOps maturity score",{"href":778,"dataGaName":767,"dataGaLocation":245},"/assessments/devops-modernization-assessment/",{"config":780},{"src":781},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":783,"categories":784,"header":786,"text":762,"button":787,"image":791},"security-modernization",[785],"security","Are you trading speed for security?",{"text":788,"config":789},"Get your security maturity score",{"href":790,"dataGaName":767,"dataGaLocation":245},"/assessments/security-modernization-assessment/",{"config":792},{"src":793},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":795,"blurb":796,"button":797,"secondaryButton":802},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":798,"config":799},"Get your free trial",{"href":800,"dataGaName":52,"dataGaLocation":801},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":496,"config":803},{"href":56,"dataGaName":57,"dataGaLocation":801},1773350801765]