[{"data":1,"prerenderedAt":808},["ShallowReactive",2],{"/en-us/blog/ci-deployment-and-environments":3,"navigation-en-us":42,"banner-en-us":442,"footer-en-us":452,"blog-post-authors-en-us-Ivan Nemytchenko|Cesar Saavedra":694,"blog-related-posts-en-us-ci-deployment-and-environments":720,"assessment-promotions-en-us":759,"next-steps-en-us":798},{"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__":41},"blogPosts/en-us/blog/ci-deployment-and-environments.yml","Ci Deployment And Environments",[7,8],"ivan-nemytchenko","cesar-saavedra",null,"engineering",{"slug":12,"featured":13,"template":14},"ci-deployment-and-environments",false,"BlogPost",{"title":16,"description":17,"authors":18,"heroImage":21,"date":22,"body":23,"category":10,"tags":24,"updatedDate":28},"How to use GitLab CI to deploy to multiple environments","We walk you through different scenarios to demonstrate the versatility and power of GitLab CI.",[19,20],"Ivan Nemytchenko","Cesar Saavedra","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749662033/Blog/Hero%20Images/intro.jpg","2021-02-05","This post is a success story of one imaginary news portal, and you're the happy\nowner, the editor, and the only developer. Luckily, you already host your project\ncode on GitLab.com and know that you can\n[run tests with GitLab CI/CD](https://docs.gitlab.com/ee/ci/testing/).\nNow you’re curious if it can be [used for deployment](/blog/how-to-keep-up-with-ci-cd-best-practices/), and how far can you go with it.\n\nTo keep our story technology stack-agnostic, let's assume that the app is just a\nset of HTML files. No server-side code, no fancy JS assets compilation.\n\nDestination platform is also simplistic – we will use [Amazon S3](https://aws.amazon.com/s3/).\n\nThe goal of the article is not to give you a bunch of copy-pasteable snippets.\nThe goal is to show the principles and features of [GitLab CI](/solutions/continuous-integration/) so that you can easily apply them to your technology stack.\n\n\nLet’s start from the beginning. There's no continuous integration (CI) in our story yet.\n\n## At the starting line\n\n**Deployment**: In your case, it means that a bunch of HTML files should appear on your\nS3 bucket (which is already configured for\n[static website hosting](http://docs.aws.amazon.com/AmazonS3/latest/dev/HowDoIWebsiteConfiguration.html?shortFooter=true)).\n\nThere are a million ways to do it. We’ll use the\n[awscli](http://docs.aws.amazon.com/cli/latest/reference/s3/cp.html#examples) library,\nprovided by Amazon.\n\nThe full command looks like this:\n\n```shell\naws s3 cp ./ s3://yourbucket/ --recursive --exclude \"*\" --include \"*.html\"\n```\n\n![Manual deployment](https://about.gitlab.com/images/blogimages/ci-deployment-and-environments/13.jpg){: .center}\nPushing code to repository and deploying are separate processes.\n\n\nImportant detail: The command\n[expects you](http://docs.aws.amazon.com/cli/latest/userguide/cli-chap-getting-started.html#config-settings-and-precedence)\nto provide `AWS_ACCESS_KEY_ID` and  `AWS_SECRET_ACCESS_KEY` environment\nvariables. Also you might need to specify `AWS_DEFAULT_REGION`.\n\n\nLet’s try to automate it using [GitLab CI](/solutions/continuous-integration/).\n\n## The first automated deployment\n\nWith GitLab, there's no difference on what commands to run.\nYou can set up GitLab CI in a way that tailors to your specific needs, as if it was your local terminal on your computer. As long as you execute commands there, you can tell CI to do the same for you in GitLab.\nPut your script to `.gitlab-ci.yml` and push your code – that’s it: CI triggers\na _job_ and your commands are executed.\n\nNow, let's add some context to our story: Our website is small, there is 20-30 daily\nvisitors and the code repository has only one default branch: `main`.\n\nLet's start by specifying a _job_ with the command from above in the `.gitlab-ci.yml` file:\n\n```yaml\ndeploy:\n  script: aws s3 cp ./ s3://yourbucket/ --recursive --exclude \"*\" --include \"*.html\"\n\n```\n\nNo luck:\n![Failed command](https://about.gitlab.com/images/blogimages/ci-deployment-and-environments/fail1.png){: .shadow}\n\nIt is our _job_ to ensure that there is an `aws` executable.\nTo install `awscli` we need `pip`, which is a tool for Python packages installation.\nLet's specify Docker image with preinstalled Python, which should contain `pip` as well:\n\n```yaml\ndeploy:\n  image: python:latest\n  script:\n  - pip install awscli\n  - aws s3 cp ./ s3://yourbucket/ --recursive --exclude \"*\" --include \"*.html\"\n\n```\n\n![Automated deployment](https://about.gitlab.com/images/blogimages/ci-deployment-and-environments/14.jpg){: .center}\nYou push your code to GitLab, and it is automatically deployed by CI.\nThe installation of `awscli` extends the job execution time, but that is not a big\ndeal for now. If you need to speed up the process, you can always [look for\na Docker image](https://hub.docker.com/explore/) with preinstalled `awscli`,\nor create an image by yourself.\n\n\nAlso, let’s not forget about these environment variables, which you've just grabbed\nfrom [AWS Console](https://console.aws.amazon.com/):\n\n```yaml\nvariables:\n  AWS_ACCESS_KEY_ID: \"AKIAIOSFODNN7EXAMPLE\"\n  AWS_SECRET_ACCESS_KEY: \"wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY\"\ndeploy:\n  image: python:latest\n  script:\n  - pip install awscli\n  - aws s3 cp ./ s3://yourbucket/ --recursive --exclude \"*\" --include \"*.html\"\n\n```\nIt should work, but keeping secret keys open, even in a private repository,\nis not a good idea. Let's see how to deal with this situation.\n\n### Keeping secret things secret\n\nGitLab has a special place for secret variables: **Settings > CI/CD > Variables**\n\n![Picture of Variables page](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674076/Blog/Content%20Images/add-variable-updated.png)\n\nWhatever you put there will be turned into **environment variables**.\nChecking the \"Mask variable\" checkbox will obfuscate the variable in job logs. Also, checking the \"Protect variable\" checkbox will export the variable to only pipelines running on protected branches and tags. Users with Owner or Maintainer permissions to a project will have access to this section.\n\nWe could remove `variables` section from our CI configuration. However, let’s use it for another purpose.\n\n### How to specify and use variables that are not secret\n\nWhen your configuration gets bigger, it is convenient to keep some of the\nparameters as variables at the beginning of your configuration. Especially if you\nuse them in more than one place. Although it is not the case in our situation yet,\nlet's set the S3 bucket name as a [**variable**](https://docs.gitlab.com/ee/ci/variables/) for the purpose of this demonstration:\n\n```yaml\nvariables:\n  S3_BUCKET_NAME: \"yourbucket\"\ndeploy:\n  image: python:latest\n  script:\n  - pip install awscli\n  - aws s3 cp ./ s3://$S3_BUCKET_NAME/ --recursive --exclude \"*\" --include \"*.html\"\n\n```\n\nSo far so good:\n\n![Successful build](https://about.gitlab.com/images/blogimages/ci-deployment-and-environments/build.png){: .shadow.medium.center}\n\nIn our hypothetical scenario, the audience of your website has grown, so you've hired a developer to help you.\nNow you have a team. Let's see how teamwork changes the GitLab CI workflow.\n\n## How to use GitLab CI with a team\n\nNow, that there are two users working in the same repository, it is no longer convenient\nto use the `main` branch for development. You decide to use separate branches\nfor both new features and new articles and merge them into `main` when they are ready.\n\nThe problem is that your current CI config doesn’t care about branches at all.\nWhenever you push anything to GitLab, it will be deployed to S3.\n\nPreventing this problem is straightforward. Just add `only: main` to your `deploy` job.\n\n![Automated deployment of main branch](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674076/Blog/Content%20Images/15-updated.png){: .center}\nYou don't want to deploy every branch to the production website but it would also be nice to preview your changes from feature-branches somehow.\n\n\n### How to set up a separate place for testing code\n\nThe person you recently hired, let's call him Patrick, reminds you that there is a featured called\n[GitLab Pages](https://docs.gitlab.com/ee/user/project/pages/). It looks like a perfect candidate for\na place to preview your work in progress.\n\nTo [host websites on GitLab Pages](/blog/gitlab-pages-setup/) your CI configuration file should satisfy three simple rules:\n\n- The _job_ should be named `pages`\n- There should be an `artifacts` section with folder `public` in it\n- Everything you want to host should be in this `public` folder\n\nThe contents of the public folder will be hosted at `http://\u003Cusername>.gitlab.io/\u003Cprojectname>/`\n\n\nAfter applying the [example config for plain-html websites](https://gitlab.com/pages/plain-html/blob/master/.gitlab-ci.yml),\nthe full CI configuration looks like this:\n\n```yaml\nvariables:\n  S3_BUCKET_NAME: \"yourbucket\"\n\ndeploy:\n  image: python:latest\n  script:\n  - pip install awscli\n  - aws s3 cp ./ s3://$S3_BUCKET_NAME/ --recursive --exclude \"*\" --include \"*.html\"\n  only:\n  - main\n\npages:\n  image: alpine:latest\n  script:\n  - mkdir -p ./public\n  - cp ./*.html ./public/\n  artifacts:\n    paths:\n    - public\n  except:\n  - main\n\n```\n\nWe specified two jobs. One job deploys the website for your customers to S3 (`deploy`).\nThe other one (`pages`) deploys the website to GitLab Pages.\nWe can name them \"Production environment\" and \"Staging environment\", respectively.\n\n![Deployment to two places](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674076/Blog/Content%20Images/16-updated.png){: .center}\nAll branches, except main, will be deployed to GitLab Pages.\n\n\n## Introducing environments\n\nGitLab offers\n [support for environments](https://docs.gitlab.com/ee/ci/environments/) (including dynamic environments and static environments),\n and all you need to do it to specify the corresponding environment for each deployment *job*:\n\n```yaml\nvariables:\n  S3_BUCKET_NAME: \"yourbucket\"\n\ndeploy to production:\n  environment: production\n  image: python:latest\n  script:\n  - pip install awscli\n  - aws s3 cp ./ s3://$S3_BUCKET_NAME/ --recursive --exclude \"*\" --include \"*.html\"\n  only:\n  - main\n\npages:\n  image: alpine:latest\n  environment: staging\n  script:\n  - mkdir -p ./public\n  - cp ./*.html ./public/\n  artifacts:\n    paths:\n    - public\n  except:\n  - main\n\n```\n\nGitLab keeps track of your deployments, so you always know what is currently being deployed on your servers:\n\n![List of environments](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674076/Blog/Content%20Images/envs-updated.png){: .shadow.center}\n\nGitLab provides full history of your deployments for each of your current environments:\n\n![List of deployments to staging environment](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674077/Blog/Content%20Images/staging-env-detail-updated.png){: .shadow.center}\n\n![Environments](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674077/Blog/Content%20Images/17-updated.png){: .center}\n\nNow, with everything automated and set up, we’re ready for the new challenges that are just around the corner.\n\n## How to troubleshoot deployments\n\nIt has just happened again.\nYou've pushed your feature-branch to preview it on staging and a minute later Patrick pushed\nhis branch, so the staging environment was rewritten with his work. Aargh!! It was the third time today!\n\nIdea! \u003Ci class=\"far fa-lightbulb\" style=\"color:#FFD900; font-size:.85em\" aria-hidden=\"true\">\u003C/i> Let's use Slack to notify us of deployments, so that people will not push their stuff if another one has been just deployed!\n\n> Learn how to [integrate GitLab with Slack](https://docs.gitlab.com/ee/user/project/integrations/gitlab_slack_application.html).\n\n## Teamwork at scale\n\nAs the time passed, your website became really popular, and your team has grown from two people to eight people.\nPeople develop in parallel, so the situation when people wait for each other to\npreview something on Staging has become pretty common. \"Deploy every branch to staging\" stopped working.\n\n![Queue of branches for review on Staging](https://about.gitlab.com/images/blogimages/ci-deployment-and-environments/queue.jpg){: .center}\n\nIt's time to modify the process one more time. You and your team agreed that if\nsomeone wants to see their changes on the staging\nserver, they should first merge the changes to the \"staging\" branch.\n\nThe change of `.gitlab-ci.yml` is minimal:\n\n```yaml\nexcept:\n- main\n```\n\nis now changed to\n\n```yaml\nonly:\n- staging\n```\n\n![Staging branch](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674077/Blog/Content%20Images/18-updated.png){: .center}\nPeople have to merge their feature branches before preview on the staging server.\n\n\nOf course, it requires additional time and effort for merging, but everybody agreed that it is better than waiting.\n\n### How to handle emergencies\n\nYou can't control everything, so sometimes things go wrong. Someone merged branches incorrectly and\npushed the result straight to production exactly when your site was on top of HackerNews.\nThousands of people saw your completely broken layout instead of your shiny main page.\n\nLuckily, someone found the **Rollback** button, so the\nwebsite was fixed a minute after the problem was discovered.\n\n![List of environments](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674077/Blog/Content%20Images/prod-env-rollback-arrow-updated.png){: .shadow.center}\nRollback relaunches the previous job with the previous commit\n\n\nAnyway, you felt that you needed to react to the problem and decided to turn off\nauto-deployment to Production and switch to manual deployment.\nTo do that, you needed to add `when: manual` to your _job_.\n\nAs you expected, there will be no automatic deployment to Production after that.\nTo deploy manually go to **CI/CD > Pipelines**, and click the button:\n\n![Skipped job is available for manual launch](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674076/Blog/Content%20Images/manual-pipeline-arrow-updated.png){: .shadow.center}\n\nFast forward in time. Finally, your company has turned into a corporation. Now, you have hundreds of people working on the website,\nso all the previous compromises no longer work.\n\n### Time to start using Review Apps\n\nThe next logical step is to boot up a temporary instance of the application per feature branch for review.\n\nIn our case, we set up another bucket on S3 for that. The only difference is that\nwe copy the contents of our website to a \"folder\" with the name of the\nthe development branch, so that the URL looks like this:\n\n`http://\u003CREVIEW_S3_BUCKET_NAME>.s3-website-us-east-1.amazonaws.com/\u003Cbranchname>/`\n\nHere's the replacement for the `pages` _job_ we used before:\n\n```yaml\nreview apps:\n  variables:\n    S3_BUCKET_NAME: \"reviewbucket\"\n  image: python:latest\n  environment: review\n  script:\n  - pip install awscli\n  - mkdir -p ./$CI_BUILD_REF_NAME\n  - cp ./*.html ./$CI_BUILD_REF_NAME/\n  - aws s3 cp ./ s3://$S3_BUCKET_NAME/ --recursive --exclude \"*\" --include \"*.html\"\n\n```\n\nThe interesting thing is where we got this `$CI_BUILD_REF_NAME` variable from.\nGitLab predefines [many environment variables](https://docs.gitlab.com/ee/ci/variables/predefined_variables.html) so that you can use them in your jobs.\n\nNote that we defined the `S3_BUCKET_NAME` variable inside the *job*. You can do this to rewrite top-level definitions.\n\n\nVisual representation of this configuration:\n![Review apps]![How to use GitLab CI - update - 19 - updated](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674077/Blog/Content%20Images/19-updated.png){: .illustration}\n\nThe details of the Review Apps implementation varies widely, depending upon your real technology\nstack and on your deployment process, which is outside the scope of this blog post.\n\nIt will not be that straightforward, as it is with our static HTML website.\nFor example, you had to make these instances temporary, and booting up these instances\nwith all required software and services automatically on the fly is not a trivial task.\nHowever, it is doable, especially if you use Docker containers, or at least Chef or Ansible.\n\nWe'll cover deployment with Docker in a future blog post.\nI feel a bit guilty for simplifying the deployment process to a simple HTML files copying, and not\nadding some hardcore scenarios. If you need some right now, I recommend you read the article [\"Building an Elixir Release into a Docker image using GitLab CI.\"](/blog/building-an-elixir-release-into-docker-image-using-gitlab-ci-part-1/)\n\nFor now, let's talk about one final thing.\n\n### Deploying to different platforms\n\nIn real life, we are not limited to S3 and GitLab Pages. We host, and therefore,\ndeploy our apps and packages to various services.\n\nMoreover, at some point, you could decide to move to a new platform and will need to rewrite all your deployment scripts.\nYou can use a gem called `dpl` to minimize the damage.\n\nIn the examples above we used `awscli` as a tool to deliver code to an example\nservice (Amazon S3).\nHowever, no matter what tool and what destination system you use, the principle is the same:\nYou run a command with some parameters and somehow pass a secret key for authentication purposes.\n\nThe `dpl` deployment tool utilizes this principle and provides a\nunified interface for [this list of providers](https://github.com/travis-ci/dpl#supported-providers).\n\nHere's how a production deployment _job_ would look if we use `dpl`:\n\n```yaml\nvariables:\n  S3_BUCKET_NAME: \"yourbucket\"\n\ndeploy to production:\n  environment: production\n  image: ruby:latest\n  script:\n  - gem install dpl\n  - dpl --provider=s3 --bucket=$S3_BUCKET_NAME\n  only:\n  - main\n\n```\n\nIf you deploy to different systems or change destination platform frequently, consider\nusing `dpl` to make your deployment scripts look uniform.\n\n## Five key takeaways\n\n1. Deployment is just a command (or a set of commands) that is regularly executed. Therefore it can run inside GitLab CI.\n2. Most times you'll need to provide some secret key(s) to the command you execute. Store these secret keys in **Settings > CI/CD > Variables**.\n3. With GitLab CI, you can flexibly specify which branches to deploy to.\n4. If you deploy to multiple environments, GitLab will conserve the history of deployments,\nwhich allows you to rollback to any previous version.\n5. 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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.",[726],"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/)",[27,731,732],"product","features",{"featured":13,"template":14,"slug":734},"using-gitlab-container-virtual-registry-with-docker-hardened-images",{"content":736,"config":746},{"title":737,"description":738,"authors":739,"heroImage":741,"date":742,"category":10,"tags":743,"body":745},"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.",[740],"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",[264,616,744],"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":747,"featured":13,"template":14},"how-iit-bombay-students-code-future-with-gitlab",{"content":749,"config":757},{"title":750,"description":751,"authors":752,"heroImage":753,"date":754,"category":10,"tags":755,"body":756},"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.",[740],"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",[616,264,731],"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":758,"featured":31,"template":14},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"promotions":760},[761,775,786],{"id":762,"categories":763,"header":765,"text":766,"button":767,"image":772},"ai-modernization",[764],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":768,"config":769},"Get your AI maturity score",{"href":770,"dataGaName":771,"dataGaLocation":246},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":773},{"src":774},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":776,"categories":777,"header":778,"text":766,"button":779,"image":783},"devops-modernization",[731,562],"Are you just managing tools or shipping innovation?",{"text":780,"config":781},"Get your DevOps maturity score",{"href":782,"dataGaName":771,"dataGaLocation":246},"/assessments/devops-modernization-assessment/",{"config":784},{"src":785},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":787,"categories":788,"header":790,"text":766,"button":791,"image":795},"security-modernization",[789],"security","Are you trading speed for security?",{"text":792,"config":793},"Get your security maturity score",{"href":794,"dataGaName":771,"dataGaLocation":246},"/assessments/security-modernization-assessment/",{"config":796},{"src":797},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":799,"blurb":800,"button":801,"secondaryButton":806},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":802,"config":803},"Get your free trial",{"href":804,"dataGaName":53,"dataGaLocation":805},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":498,"config":807},{"href":57,"dataGaName":58,"dataGaLocation":805},1773350830691]