[{"data":1,"prerenderedAt":814},["ShallowReactive",2],{"/en-us/blog/markdown-kramdown-tips-and-tricks":3,"navigation-en-us":33,"banner-en-us":443,"footer-en-us":453,"blog-post-authors-en-us-Marcia Ramos":695,"blog-related-posts-en-us-markdown-kramdown-tips-and-tricks":709,"blog-promotions-en-us":751,"next-steps-en-us":804},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":22,"isFeatured":12,"meta":23,"navigation":24,"path":25,"publishedDate":20,"seo":26,"stem":30,"tagSlugs":31,"__hash__":32},"blogPosts/en-us/blog/markdown-kramdown-tips-and-tricks.yml","Markdown Kramdown Tips And Tricks",[7],"marcia-ramos",null,"engineering",{"slug":11,"featured":12,"template":13},"markdown-kramdown-tips-and-tricks",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9},"Markdown Kramdown Tips and Tricks","Learn how to apply classes to markdown, create ToCs, embed iframes and much more!",[18],"Marcia Ramos","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749671850/Blog/Hero%20Images/markdown-kramdown-tips-and-tricks-cover.png","2016-07-19","If you use a markdown engine for writing your website content and you'd like to\nlearn a few tricks to have more freedom with it, this post is for you.\n\nThe markdown engine we use for [about.GitLab.com] is [Kramdown], and that is the one\nwe'll be referring to on this post.\n\n**Note:** We assume you already know what a markdown engine is and how it is applied to a website.\n\n\n\u003C!-- more -->\n\n----\n\n## On this post\n\n\n- TOC\n\n\n----\n\n## Our Markdown Guide\n\nLast week a lot of [people were happy][news] for our [Handbook] being open source, as we explained\nin details on the post \"[Our Handbook is open source: here's why][handbook-post]\".\nEvery GitLab Team member does touch our website, starting on his or her first weeks,\nas part of the onboarding tasks.\nDoesn't matter if he or she is an advanced programmer or never have seen an HTML code before,\ncollaborating is the key for making sure we are all on the same side. And we love it!\n\nOne of our Handbook pages is a full [Markdown Guide][guide] for the markup\nthat we use in our website, generated by [Middleman].\nIt brings a lot of details on how to use Kramdown for writing content.\nEvery markdown page of this website, which is an [open\nsource project][www-GitLab-com] available for peeking and contributing, can use any\nof the rules explained there. This April we changed the markdown engine from RDiscount to\nKramdown, and not everybody in our Team knew the new \"magical\" stuff we could use from this change. That's\nwhy we decided that writing a guide would be useful for those already used to markdown, and\nhelpful for those completely new to it.\n\n## Why Kramdown\n\nPerhaps your first question will be something like \"okay, why is Kramdown so special?\". My first\nexperience with markdown was when I first used a [Static Site Generator][SSGs], Jekyll. Coming from\nprevious experiences in web development on PHP and HTML, the first thing I wanted to do to a\nmarkdown post was adding a class to a particular heading. When I googled for that, I was pretty\ndisappointed because apparently we aren't supposed to apply classes inline into markdown files.\nSo, I had to experiment a lot until I got the desired result: add some color to my heading.\n\nAfter trying a lot of new tweaks, and digging through the web for answers that insisted on not coming, I finally\nfound out that with Kramdown, yes, I could do a lot of things. And finally I could apply some inline classes\nthrough my posts and have my blue headings when I wanted them blue. But at that time, I hadn't noticed\nthat we could do some really great magic with it, and that's what I'm sharing with you in this post.\n\n## The magic\n\nWe could say that the Kramdown magic concentrates to the following syntax: `{: something}`.\nThis little devil is the basis of a lot of awesome resources.\n\nLet's go over a few of them now, but you'll find a lot more in our [Markdown Guide][guide].\n\n## Classes, IDs and Attributes\n\n\nLet's start with something classic, as the ability of [applying CSS classes, custom IDs, and custom\nattributes][classes] to the elements.\n\n### Applying classes\n\nIf you think of any CSS class, what comes into your mind first? I suppose it's something like:\n\n```css\n.blue {\n color: blue;\n}\n```\n\nOkay, we have a `.blue` class. Let's say once in a while we want a blue paragraph or a blue heading. Just do:\n\n```md\nThis is a paragraph that for some reason we want blue.\n{: .blue}\n```\n\nAnd of course, the output will be:\n\n\u003Cdiv class=\"panel panel-info\">\n**Output**\n\n\u003Cdiv class=\"panel-body\">\nThis is a paragraph that for some reason we want blue.\n{: .blue}\n\u003C/div>\n\u003C/div>\n\nAnd if we want a blue heading, we do exact the same thing:\n\n```md\n#### A blue heading\n{: .blue}\n```\n\nAnd the output is going to behave as we expect it to:\n\n\u003Cdiv class=\"panel panel-info\">\n**Output**\n\n\u003Cdiv class=\"panel-body\">\n#### A blue heading\n{: .blue .no_toc}\n\u003C/div>\n\u003C/div>\n\nWhat if I want to apply two classes at the same time?\n\n```md\nA blue and bold paragraph.\n{: .blue .bold}\n```\n\nAnd the output will be as expected:\n\n\u003Cdiv class=\"panel panel-info\">\n**Output**\n\n\u003Cdiv class=\"panel-body\">\nA blue and bold paragraph.\n{: .blue .bold}\n\u003C/div>\n\u003C/div>\n\nAs simple as that! The markup is simple and intuitive.\n\nNow, guess what, we can do exactly the same for IDs!\n\n### Custom IDs\n\nKramdown itself will append an ID for each heading, automatically. The ID will be all the words\nin the heading together, connected by dashes. For the example above, \"A blue heading\", the HTML output ID\nwill be `a-blue-heading`:\n\n```html\n\u003Ch4 class=\"blue\" id=\"a-blue-heading\">A blue heading\u003C/h4>\n```\n\nLet's say we want the ID called `blue-h`:\n\n```md\n#### A blue heading\n{: .blue #blue-h}\n```\n\nWill produce exactly what it's meant to (a blue heading with the custom ID):\n\n```html\n\u003Ch4 class=\"blue\" id=\"blue-h\">A blue heading\u003C/h4>\n```\n\nSo, the output would be:\n\n\u003Cdiv class=\"panel panel-info\">\n**Output**\n\n\u003Cdiv class=\"panel-body\">\n#### A blue heading\n{: .blue .no_toc #blue-h}\n\u003C/div>\n\u003C/div>\n\nNote that we can attribute both class and ID in one markup, as in `{: .class #custom-id}`. But we can use\njust one of them too: `{: .class}` or `{: #custom-id}`.\n\n\nInteresting, isn't it?\n\n### Custom Attributes\n\nYes, we can go even further and apply any _key/value_ pair we need:\n\n```md\nAn example of key/value pair\n{: .class #id key=\"value\"}\n```\n\nWe can use them, for example, for quickly applying general styles:\n\n```text\n#### A simple example\n{: #custom-id style=\"margin-top:0\"}\n```\n\nBut they are specially useful for links, as in:\n\n```md\n[text][identifier]{: #custom-id key=\"value\"}\n```\n\nThis way we can call a JavaScript function, for example:\n\n```md\n[CLICK ME][identifier]{: #custom-id onclick=\"myJsFunc();\"}\n\n\u003Cscript type=\"text/javascript\">\n function myJsFunc() {\n var answer = confirm (\"Please click on OK to continue.\")\n if (answer)\n window.location=\"#\";\n }\n\u003C/script>\n```\n\n\u003Cdiv class=\"panel panel-info\">\n**Output**\n\n\u003Cdiv class=\"panel-body\">\n[CLICK ME][identifier]{: #custom-id onclick=\"myJsFunc();\"}\n\n\u003Cscript type=\"text/javascript\">\nfunction myJsFunc() {\nvar answer = confirm (\"Please click on OK to continue.\")\nif (answer)\nwindow.location=\"#\";\n}\n\u003C/script>\n\u003C/div>\n\u003C/div>\n\n----\n\n## Table of Contents (ToC)\n\nA ToC is so awesome and easy to produce. Have you noticed [our ToC](#on-this-post)\non this post? It's generated automatically by Kramdown with this simple markup:\n\n```md\n- TOC\n{:toc}\n```\n\nAll the file headings will be all automatically included in the ToC, except for those we don't want there.\nFor these, we apply a class called `no_toc`, and Kramdown will respect our will:\n\n```md\n#### This heading will not be included in the ToC.\n{: .no_toc}\n```\n\nAnd of course, we can make the ToC an ordered list instead of unordered:\n\n```md\n1. TOC\n{:toc}\n```\n\nAwesome, isn't it?\n\n----\n\n## HTML Blocks\n\nWhenever we need HTML blocks, we can use them freely!\n\n```html\n\u003Cdiv>\n \u003Cp>Hello World\u003C/p>\n\u003C/div>\n```\n\nIn our [Marketing Handbook] you will find plenty of them.\n\n### Font Awesome\n\n[Font Awesome] is a good use-case for HTML blocks within markdown files.\n\nCheck this!\n\n```html\nWe \u003Ci class=\"fas fa-heart\" aria-hidden=\"true\" style=\"color:#c7254e\">\u003C/i> GitLab!\n```\n\n\u003Cdiv class=\"panel panel-info\">\n**Output**\n\n\u003Cdiv class=\"panel-body\">\nWe \u003Ci class=\"fas fa-heart\" aria-hidden=\"true\" style=\"color:#c7254e\">\u003C/i> GitLab!\n\u003C/div>\n\u003C/div>\n\n### Iframes\n\nWe can embed anything within `\u003Ciframe>` tags, such as [YouTube and Vimeo videos][videos],\nGoogle and OneDrive [documents][docs] and anything else available in iframes:\n\n```html\n\u003Cfigure class=\"video_container\">\n \u003Ciframe src=\"https://www.youtube.com/embed/NoFLJLJ7abE\" frameborder=\"0\" allowfullscreen=\"true\"> \u003C/iframe>\n\u003C/figure>\n```\n\nWe are using the class `video_container` to make it [responsive].\n\n\u003Cdiv class=\"panel panel-info\">\n**Output**\n\n\u003Cdiv class=\"panel-body\">\n\u003Cfigure class=\"video_container\">\n\u003Ciframe src=\"https://www.youtube.com/embed/NoFLJLJ7abE\" frameborder=\"0\" allowfullscreen=\"true\"> \u003C/iframe>\n\u003C/figure>\n\u003C/div>\n\u003C/div>\n\n### CodePen\n\n[CodePens] are really good for some cases, when you want to display codes and results, for example. Check this cute dog,\ncreated with HTML and Sass:\n\n```html\n\u003Cp data-height=\"431\" data-theme-id=\"dark\" data-slug-hash=\"OXzjLL\" data-default-tab=\"html,result\" data-user=\"virtuacreative\" data-embed-version=\"2\" class=\"codepen\">See the Pen \u003Ca href=\"http://codepen.io/virtuacreative/pen/OXzjLL/\">Dog\u003C/a> by Virtua Creative (\u003Ca href=\"http://codepen.io/virtuacreative\">@virtuacreative\u003C/a>) on \u003Ca href=\"http://codepen.io\">CodePen\u003C/a>.\u003C/p>\n\u003Cscript async src=\"//assets.codepen.io/assets/embed/ei.js\">\u003C/script>\n```\n\n\u003Cp data-height=\"431\" data-theme-id=\"dark\" data-slug-hash=\"OXzjLL\" data-default-tab=\"html,result\" data-user=\"virtuacreative\" data-embed-version=\"2\" class=\"codepen\">See the Pen \u003Ca href=\"http://codepen.io/virtuacreative/pen/OXzjLL/\">Dog\u003C/a> by Virtua Creative (\u003Ca href=\"http://codepen.io/virtuacreative\">@virtuacreative\u003C/a>) on \u003Ca href=\"http://codepen.io\">CodePen\u003C/a>.\u003C/p>\n\u003Cscript async src=\"//assets.codepen.io/assets/embed/ei.js\">\u003C/script>\n\n----\n\n## Mix HTML with Markdown\n\nYes, we definitely can do this! We need to add the following markup to the markdown document before mixing up\nHTML and markdown:\n\n```md\n{::options parse_block_html=\"true\" /}\n```\n\nAnd we can close it any time, if necessary:\n\n```md\n{::options parse_block_html=\"false\" /}\n```\n\nThis is going to make this:\n\n```html\nSomething in **markdown**.\n\n\u003Cp>Then an HTML tag with crazy **markup**!\u003C/p>\n```\n\nTo be displayed like this:\n\n\u003Cdiv class=\"panel panel-info\">\n**Output**\n\n\u003Cdiv class=\"panel-body\">\nSomething in **markdown**.\n\u003Cp>Then an HTML tag with crazy **markup**!\u003C/p>\n\u003C/div>\n\u003C/div>\n\nBlue boxes, like this one above, used to [display the outputs][boxes] on this post, were generated with this resource.\n\n----\n\n## Styles\n\nOne of the most useful features is the ability to add `\u003Cstyle>` tags to our markdown file too!\nWe can do that for simply styling our web page without affecting the entire site. Just go on and add the\ntag to any part of your markdown:\n\n```html\n\u003Cstyle>\n.blue {\n color: blue;\n}\n.bold {\n font-weight: bold;\n}\n\u003C/style>\n```\n\nThis tag was applied to this very document to exemplify this case, also to help with the classes described\n[earlier in this post](#applying-classes).\n\n----\n\n## Conclusion\n\nThere is a lot more you can do, mix, and bring together using [Kramdown]. It's awesome! Check out\nour [Markdown Guide][guide] for more resources, examples and applications and use your creativity to create\nbeautiful posts, with great styles!\n\nAnything else you know of and is not in our [Guide]? Any new magic?\nAny trick? Please [contribute] by submitting an [MR] to the\n[source file]. Your collaboration is much appreciated.\n\nHappy markdowning!\n\nFollow [@GitLab] and stay tunned for the next post!\n\n\u003C!-- identifiers -->\n\n[about.GitLab.com]: /\n[@GitLab]: https://twitter.com/GitLab\n[boxes]: https://handbook.gitlab.com/docs/markdown-guide/\n[classes]: https://handbook.gitlab.com/docs/markdown-guide/\n[CodePens]: https://codepen.io\n[contribute]: https://gitlab.com/gitlab-com/www-gitlab-com/blob/master/CONTRIBUTING.md\n[docs]: https://handbook.gitlab.com/docs/markdown-guide/#embed-documents\n[font awesome]: http://fontawesome.io/\n[guide]: https://handbook.gitlab.com/docs/markdown-guide/\n[Handbook]: https://handbook.gitlab.com/\n[handbook-post]: /blog/our-handbook-is-open-source-heres-why/\n[identifier]: #\n[Kramdown]: http://kramdown.gettalong.org/\n[Marketing Handbook]: https://handbook.gitlab.com/handbook/marketing/\n[Middleman]: https://middlemanapp.com/\n[mr]: https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html \"Merge Request\"\n[news]: https://news.ycombinator.com/item?id=12091638\n[responsive]: https://css-tricks.com/NetMag/FluidWidthVideo/Article-FluidWidthVideo.php\n[SSGs]: /blog/ssg-overview-gitlab-pages-part-2/\n[videos]: https://handbook.gitlab.com/docs/markdown-guide/#videos\n[www-GitLab-com]: https://gitlab.com/gitlab-com/www-gitlab-com\n[source file]: https://gitlab.com/gitlab-com/www-gitlab-com/blob/master/source/handbook/markdown-guide/index.html.md\n\n\u003Cstyle>\n.blue {\n color: blue !important;\n}\n.bold {\n font-weight: 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CI/CD tools can run a build and ship a deployment. Where they diverge is what happens when your delivery needs get real: a monorepo with a dozen services, microservices spread across multiple repositories, deployments to dozens of environments, or a platform team trying to enforce standards without becoming a bottleneck.\n \nGitLab's pipeline execution model was designed for that complexity. Parent-child pipelines, DAG execution, dynamic pipeline generation, multi-project triggers, merge request pipelines with merged results, and CI/CD Components each solve a distinct class of problems. Because they compose, understanding the full model unlocks something more than a faster pipeline. In this article, you'll learn about the five patterns where that model stands out, each mapped to a real engineering scenario with the configuration to match.\n \nThe configs below are illustrative. The scripts use echo commands to keep the signal-to-noise ratio low. Swap them out for your actual build, test, and deploy steps and they are ready to use.\n\n\n## 1. Monorepos: Parent-child pipelines + DAG execution\n\n\nThe problem: Your monorepo has a frontend, a backend, and a docs site. Every commit triggers a full rebuild of everything, even when only a README changed.\n\n\nGitLab solves this with two complementary features: [parent-child pipelines](https://docs.gitlab.com/ci/pipelines/downstream_pipelines/#parent-child-pipelines) (which let a top-level pipeline spawn isolated sub-pipelines) and [DAG execution via `needs`](https://docs.gitlab.com/ci/yaml/#needs) (which breaks rigid stage-by-stage ordering and lets jobs start the moment their dependencies finish).\n\n\nA parent pipeline detects what changed and triggers only the relevant child pipelines:\n\n```yaml\n# .gitlab-ci.yml\nstages:\n - trigger\n\ntrigger-services:\n stage: trigger\n trigger:\n include:\n - local: '.gitlab/ci/api-service.yml'\n - local: '.gitlab/ci/web-service.yml'\n - local: '.gitlab/ci/worker-service.yml'\n strategy: depend\n```\n\n\nEach child pipeline is a fully independent pipeline with its own stages, jobs, and artifacts. The parent waits for all of them via [strategy: depend](https://docs.gitlab.com/ci/pipelines/downstream_pipelines/#wait-for-downstream-pipeline-to-complete) so you get a single green/red signal at the top level, with full drill-down into each service's pipeline. This organizational separation is the bigger win for large teams: each service owns its pipeline config, changes in one cannot break another, and the complexity stays manageable as the repo grows.\n\n\nOne thing worth knowing: when you pass [multiple files to a single `trigger: include:`](https://docs.gitlab.com/ci/pipelines/downstream_pipelines/#combine-multiple-child-pipeline-configuration-files), GitLab merges them into a single child pipeline configuration. This means jobs defined across those files share the same pipeline context and can reference each other with `needs:`, which is what makes the DAG optimization possible. If you split them into separate trigger jobs instead, each would be its own isolated pipeline and cross-file `needs:` references would not work.\n\n\nCombine this with `needs:` inside each child pipeline and you get DAG execution. Your integration tests can start the moment the build finishes, without waiting for other jobs in the same stage.\n\n```yaml\n# .gitlab/ci/api-service.yml\nstages:\n - build\n - test\n\nbuild-api:\n stage: build\n script:\n - echo \"Building API service\"\n\ntest-api:\n stage: test\n needs: [build-api]\n script:\n - echo \"Running API tests\"\n```\n\n\nWhy it matters: Teams with large monorepos typically report significant reductions in pipeline runtime after switching to DAG execution, since jobs no longer wait on unrelated work in the same stage. Parent-child pipelines add the organizational layer that keeps the configuration maintainable as the repo and team grow.\n\n![Local downstream pipelines](https://res.cloudinary.com/about-gitlab-com/image/upload/v1775738759/Blog/Imported/hackathon-fake-blog-post-s/image3_vwj3rz.png \"Local downstream pipelines\")\n\n## 2. Microservices: Cross-repo, multi-project pipelines\n\n\nThe problem: Your frontend lives in one repo, your backend in another. When the frontend team ships a change, they have no visibility into whether it broke the backend integration and vice versa.\n\n\nGitLab's [multi-project pipelines](https://docs.gitlab.com/ci/pipelines/downstream_pipelines/#multi-project-pipelines) let one project trigger a pipeline in a completely separate project and wait for the result. The triggering project gets a linked downstream pipeline right in its own pipeline view.\n\n\nThe frontend pipeline builds an API contract artifact and publishes it, then triggers the backend pipeline. The backend fetches that artifact directly using the [Jobs API](https://docs.gitlab.com/ee/api/jobs.html#download-a-single-artifact-file-from-specific-tag-or-branch) and validates it before allowing anything to proceed. If a breaking change is detected, the backend pipeline fails and the frontend pipeline fails with it.\n\n```yaml\n# frontend repo: .gitlab-ci.yml\nstages:\n - build\n - test\n - trigger-backend\n\nbuild-frontend:\n stage: build\n script:\n - echo \"Building frontend and generating API contract...\"\n - mkdir -p dist\n - |\n echo '{\n \"api_version\": \"v2\",\n \"breaking_changes\": false\n }' > dist/api-contract.json\n - cat dist/api-contract.json\n artifacts:\n paths:\n - dist/api-contract.json\n expire_in: 1 hour\n\ntest-frontend:\n stage: test\n script:\n - echo \"All frontend tests passed!\"\n\ntrigger-backend-pipeline:\n stage: trigger-backend\n trigger:\n project: my-org/backend-service\n branch: main\n strategy: depend\n rules:\n - if: $CI_COMMIT_BRANCH == \"main\"\n```\n\n```yaml\n# backend repo: .gitlab-ci.yml\nstages:\n - build\n - test\n\nbuild-backend:\n stage: build\n script:\n - echo \"All backend tests passed!\"\n\nintegration-test:\n stage: test\n rules:\n - if: $CI_PIPELINE_SOURCE == \"pipeline\"\n script:\n - echo \"Fetching API contract from frontend...\"\n - |\n curl --silent --fail \\\n --header \"JOB-TOKEN: $CI_JOB_TOKEN\" \\\n --output api-contract.json \\\n \"${CI_API_V4_URL}/projects/${FRONTEND_PROJECT_ID}/jobs/artifacts/main/raw/dist/api-contract.json?job=build-frontend\"\n - cat api-contract.json\n - |\n if grep -q '\"breaking_changes\": true' api-contract.json; then\n echo \"FAIL: Breaking API changes detected - backend integration blocked!\"\n exit 1\n fi\n echo \"PASS: API contract is compatible!\"\n```\n\n\nA few things worth noting in this config. The `integration-test` job uses `$CI_PIPELINE_SOURCE == \"pipeline\"` to ensure it only runs when triggered by an upstream pipeline, not on a standalone push to the backend repo. The frontend project ID is referenced via `$FRONTEND_PROJECT_ID`, which should be set as a [CI/CD variable](https://docs.gitlab.com/ci/variables/) in the backend project settings to avoid hardcoding it.\n\n\nWhy it matters: Cross-service breakage that previously surfaced in production gets caught in the pipeline instead. The dependency between services stops being invisible and becomes something teams can see, track, and act on.\n\n\n![Cross-project pipelines](https://res.cloudinary.com/about-gitlab-com/image/upload/v1775738762/Blog/Imported/hackathon-fake-blog-post-s/image4_h6mfsb.png \"Cross-project pipelines\")\n\n\n## 3. Multi-tenant / matrix deployments: Dynamic child pipelines\n\n\nThe problem: You deploy the same application to 15 customer environments, or three cloud regions, or dev/staging/prod. Updating a deploy stage across all of them one by one is the kind of work that leads to configuration drift. Writing a separate pipeline for each environment is unmaintainable from day one.\n\n\nGitLab's [dynamic child pipelines](https://docs.gitlab.com/ci/pipelines/downstream_pipelines/#dynamic-child-pipelines) let you generate a pipeline at runtime. A job runs a script that produces a YAML file, and that YAML becomes the pipeline for the next stage. The pipeline structure itself becomes data.\n\n\n```yaml\n# .gitlab-ci.yml\nstages:\n - generate\n - trigger-environments\n\ngenerate-config:\n stage: generate\n script:\n - |\n # ENVIRONMENTS can be passed as a CI variable or read from a config file.\n # Default to dev, staging, prod if not set.\n ENVIRONMENTS=${ENVIRONMENTS:-\"dev staging prod\"}\n for ENV in $ENVIRONMENTS; do\n cat > ${ENV}-pipeline.yml \u003C\u003C EOF\n stages:\n - deploy\n - verify\n deploy-${ENV}:\n stage: deploy\n script:\n - echo \"Deploying to ${ENV} environment\"\n verify-${ENV}:\n stage: verify\n script:\n - echo \"Running smoke tests on ${ENV}\"\n EOF\n done\n artifacts:\n paths:\n - \"*.yml\"\n exclude:\n - \".gitlab-ci.yml\"\n\n.trigger-template:\n stage: trigger-environments\n trigger:\n strategy: depend\n\ntrigger-dev:\n extends: .trigger-template\n trigger:\n include:\n - artifact: dev-pipeline.yml\n job: generate-config\n\ntrigger-staging:\n extends: .trigger-template\n needs: [trigger-dev]\n trigger:\n include:\n - artifact: staging-pipeline.yml\n job: generate-config\n\ntrigger-prod:\n extends: .trigger-template\n needs: [trigger-staging]\n trigger:\n include:\n - artifact: prod-pipeline.yml\n job: generate-config\n when: manual\n```\n\n\nThe generation script loops over an `ENVIRONMENTS` variable rather than hardcoding each environment separately. Pass in a different list via a CI variable or read it from a config file and the pipeline adapts without touching the YAML. The trigger jobs use [extends:](https://docs.gitlab.com/ci/yaml/#extends) to inherit shared configuration from `.trigger-template`, so `strategy: depend` is defined once rather than repeated on every trigger job. Add a new environment by updating the variable, not by duplicating pipeline config. Add [when: manual](https://docs.gitlab.com/ci/yaml/#when) to the production trigger and you get a promotion gate baked right into the pipeline graph.\n\n\nWhy it matters: SaaS companies and platform teams use this pattern to manage dozens of environments without duplicating pipeline logic. The pipeline structure itself stays lean as the deployment matrix grows.\n\n\n![Dynamic pipeline](https://res.cloudinary.com/about-gitlab-com/image/upload/v1775738765/Blog/Imported/hackathon-fake-blog-post-s/image7_wr0kx2.png \"Dynamic pipeline\")\n\n\n## 4. MR-first delivery: Merge request pipelines, merged results, and workflow routing\n\n\nThe problem: Your pipeline runs on every push to every branch. Expensive tests run on feature branches that will never merge. Meanwhile, you have no guarantee that what you tested is actually what will land on `main` after a merge.\n\n\nGitLab has three interlocking features that solve this together:\n\n\n* [Merge request pipelines](https://docs.gitlab.com/ci/pipelines/merge_request_pipelines/) run only when a merge request exists, not on every branch push. This alone eliminates a significant amount of wasted compute.\n\n* [Merged results pipelines](https://docs.gitlab.com/ci/pipelines/merged_results_pipelines/) go further. GitLab creates a temporary merge commit (your branch plus the current target branch) and runs the pipeline against that. You are testing what will actually exist after the merge, not just your branch in isolation.\n\n* [Workflow rules](https://docs.gitlab.com/ci/yaml/workflow/) let you define exactly which pipeline type runs under which conditions and suppress everything else. The `$CI_OPEN_MERGE_REQUESTS` guard below prevents duplicate pipelines firing for both a branch and its open MR simultaneously.\n\n\nWith those three working together, here is what a tiered pipeline looks like:\n\n```yaml\n# .gitlab-ci.yml\nworkflow:\n rules:\n - if: $CI_PIPELINE_SOURCE == \"merge_request_event\"\n - if: $CI_COMMIT_BRANCH && $CI_OPEN_MERGE_REQUESTS\n when: never\n - if: $CI_COMMIT_BRANCH\n - if: $CI_PIPELINE_SOURCE == \"schedule\"\n\nstages:\n - fast-checks\n - expensive-tests\n - deploy\n\nlint-code:\n stage: fast-checks\n script:\n - echo \"Running linter\"\n rules:\n - if: $CI_PIPELINE_SOURCE == \"push\"\n - if: $CI_PIPELINE_SOURCE == \"merge_request_event\"\n - if: $CI_COMMIT_BRANCH == \"main\"\n\nunit-tests:\n stage: fast-checks\n script:\n - echo \"Running unit tests\"\n rules:\n - if: $CI_PIPELINE_SOURCE == \"push\"\n - if: $CI_PIPELINE_SOURCE == \"merge_request_event\"\n - if: $CI_COMMIT_BRANCH == \"main\"\n\nintegration-tests:\n stage: expensive-tests\n script:\n - echo \"Running integration tests (15 min)\"\n rules:\n - if: $CI_PIPELINE_SOURCE == \"merge_request_event\"\n - if: $CI_COMMIT_BRANCH == \"main\"\n\ne2e-tests:\n stage: expensive-tests\n script:\n - echo \"Running E2E tests (30 min)\"\n rules:\n - if: $CI_PIPELINE_SOURCE == \"merge_request_event\"\n - if: $CI_COMMIT_BRANCH == \"main\"\n\nnightly-comprehensive-scan:\n stage: expensive-tests\n script:\n - echo \"Running full nightly suite (2 hours)\"\n rules:\n - if: $CI_PIPELINE_SOURCE == \"schedule\"\n\ndeploy-production:\n stage: deploy\n script:\n - echo \"Deploying to production\"\n rules:\n - if: $CI_COMMIT_BRANCH == \"main\"\n when: manual\n```\n\nWith this setup, the pipeline behaves differently depending on context. A push to a feature branch with no open MR runs lint and unit tests only. Once an MR is opened, the workflow rules switch from a branch pipeline to an MR pipeline, and the full integration and E2E suite runs against the merged result. Merging to `main` queues a manual production deployment. A nightly schedule runs the comprehensive scan once, not on every commit.\n\n\nWhy it matters: Teams routinely cut CI costs significantly with this pattern, not by running fewer tests, but by running the right tests at the right time. Merged results pipelines catch the class of bugs that only appear after a merge, before they ever reach `main`.\n\n\n![Conditional pipelines (within a branch with no MR)](https://res.cloudinary.com/about-gitlab-com/image/upload/v1775738768/Blog/Imported/hackathon-fake-blog-post-s/image6_dnfcny.png \"Conditional pipelines (within a branch with no MR)\")\n\n\n\n![Conditional pipelines (within an MR)](https://res.cloudinary.com/about-gitlab-com/image/upload/v1775738772/Blog/Imported/hackathon-fake-blog-post-s/image1_wyiafu.png \"Conditional pipelines (within an MR)\")\n\n\n\n![Conditional pipelines (on the main branch)](https://res.cloudinary.com/about-gitlab-com/image/upload/v1775738774/Blog/Imported/hackathon-fake-blog-post-s/image5_r6lkfd.png \"Conditional pipelines (on the main branch)\")\n\n## 5. Governed pipelines: CI/CD Components\n\n\nThe problem: Your platform team has defined the right way to build, test, and deploy. But every team has their own `.gitlab-ci.yml` with subtle variations. Security scanning gets skipped. Deployment standards drift. Audits are painful.\n\n\nGitLab [CI/CD Components](https://docs.gitlab.com/ci/components/) let platform teams publish versioned, reusable pipeline building blocks. Application teams consume them with a single `include:` line and optional inputs — no copy-paste, no drift. Components are discoverable through the [CI/CD Catalog](https://docs.gitlab.com/ci/components/#cicd-catalog), which means teams can find and adopt approved building blocks without needing to go through the platform team directly.\n\n\nHere is a component definition from a shared library:\n\n```yaml\n# templates/deploy.yml\nspec:\n inputs:\n stage:\n default: deploy\n environment:\n default: production\n---\ndeploy-job:\n stage: $[[ inputs.stage ]]\n script:\n - echo \"Deploying $APP_NAME to $[[ inputs.environment ]]\"\n - echo \"Deploy URL: $DEPLOY_URL\"\n environment:\n name: $[[ inputs.environment ]]\n```\nAnd here is how an application team consumes it:\n\n```yaml\n# Application repo: .gitlab-ci.yml\nvariables:\n APP_NAME: \"my-awesome-app\"\n DEPLOY_URL: \"https://api.example.com\"\n\ninclude:\n - component: gitlab.com/my-org/component-library/build@v1.0.6\n - component: gitlab.com/my-org/component-library/test@v1.0.6\n - component: gitlab.com/my-org/component-library/deploy@v1.0.6\n inputs:\n environment: staging\n\nstages:\n - build\n - test\n - deploy\n```\n\nThree lines of `include:` replace hundreds of lines of duplicated YAML. The platform team can push a security fix to `v1.0.7` and teams opt in on their own schedule — or the platform team can pin everyone to a minimum version. Either way, one change propagates everywhere instead of needing to be applied repo by repo.\n\n\nPair this with [resource groups](https://docs.gitlab.com/ci/resource_groups/) to prevent concurrent deployments to the same environment, and [protected environments](https://docs.gitlab.com/ci/environments/protected_environments/) to enforce approval gates - and you have a governed delivery platform where compliance is the default, not the exception.\n\n\nWhy it matters: This is the pattern that makes GitLab CI/CD scale across hundreds of teams. Platform engineering teams enforce compliance without becoming a bottleneck. Application teams get a fast path to a working pipeline without reinventing the wheel.\n\n\n![Component pipeline (imported jobs)](https://res.cloudinary.com/about-gitlab-com/image/upload/v1775738776/Blog/Imported/hackathon-fake-blog-post-s/image2_pizuxd.png \"Component pipeline (imported jobs)\")\n\n## Putting it all together\n\nNone of these features exist in isolation. The reason GitLab's pipeline model is worth understanding deeply is that these primitives compose:\n\n* A monorepo uses parent-child pipelines, and each child uses DAG execution\n\n* A microservices platform uses multi-project pipelines, and each project uses MR pipelines with merged results\n\n* A governed platform uses CI/CD components to standardize the patterns above across every team\n\n\nMost teams discover one of these features when they hit a specific pain point. The ones who invest in understanding the full model end up with a delivery system that actually reflects how their engineering organization works, not a pipeline that fights it.\n\n## Other patterns worth exploring\n\n\nThe five patterns above cover the most common structural pain points, but GitLab's pipeline model goes further. A few others worth looking into as your needs grow:\n\n\n* [Review apps with dynamic environments](https://docs.gitlab.com/ci/environments/) let you spin up a live preview for every feature branch and tear it down automatically when the MR closes. Useful for teams doing frontend work or API changes that need stakeholder sign-off before merging.\n\n* [Caching and artifact strategies](https://docs.gitlab.com/ci/caching/) are often the fastest way to cut pipeline runtime after the structural work is done. Structuring `cache:` keys around dependency lockfiles and being deliberate about what gets passed between jobs with [artifacts:](https://docs.gitlab.com/ci/yaml/#artifacts) can make a significant difference without changing your pipeline shape at all.\n\n* [Scheduled and API-triggered pipelines](https://docs.gitlab.com/ci/pipelines/schedules/) are worth knowing about because not everything should run on a code push. Nightly security scans, compliance reports, and release automation are better modeled as scheduled or [API-triggered](https://docs.gitlab.com/ci/triggers/) pipelines with `$CI_PIPELINE_SOURCE` routing the right jobs for each context.\n\n## How to get started\n\nModern software delivery is complex. Teams are managing monorepos with dozens of services, coordinating across multiple repositories, deploying to many environments at once, and trying to keep standards consistent as organizations grow. GitLab's pipeline model was built with all of that in mind.\n\nWhat makes it worth investing time in is how well the pieces fit together. Parent-child pipelines bring structure to large codebases. Multi-project pipelines make cross-team dependencies visible and testable. Dynamic pipelines turn environment management into something that scales gracefully. MR-first delivery with merged results ensures confidence at every step of the review process. And CI/CD Components give platform teams a way to share best practices across an entire organization without becoming a bottleneck.\n\nEach of these features is powerful on its own, and even more so when combined. GitLab gives you the building blocks to design a delivery system that fits how your team actually works, and grows with you as your needs evolve.\n\n> [Start a free trial of GitLab Ultimate](https://about.gitlab.com/free-trial/) to use pipeline logic today.\n\n## Read more\n\n* [Variable and artifact sharing in GitLab parent-child pipelines](https://about.gitlab.com/blog/variable-and-artifact-sharing-in-gitlab-parent-child-pipelines/)\n* [CI/CD inputs: Secure and preferred method to pass parameters to a pipeline](https://about.gitlab.com/blog/ci-cd-inputs-secure-and-preferred-method-to-pass-parameters-to-a-pipeline/)\n* [Tutorial: How to set up your first GitLab CI/CD component](https://about.gitlab.com/blog/tutorial-how-to-set-up-your-first-gitlab-ci-cd-component/)\n* [How to include file references in your CI/CD components](https://about.gitlab.com/blog/how-to-include-file-references-in-your-ci-cd-components/)\n* [FAQ: GitLab CI/CD Catalog](https://about.gitlab.com/blog/faq-gitlab-ci-cd-catalog/)\n* [Building a GitLab CI/CD pipeline for a monorepo the easy way](https://about.gitlab.com/blog/building-a-gitlab-ci-cd-pipeline-for-a-monorepo-the-easy-way/)\n* [A CI/CD component builder's journey](https://about.gitlab.com/blog/a-ci-component-builders-journey/)\n* [CI/CD Catalog goes GA: No more building pipelines from scratch](https://about.gitlab.com/blog/ci-cd-catalog-goes-ga-no-more-building-pipelines-from-scratch/)","5 ways GitLab pipeline logic solves real engineering problems","Learn how to scale CI/CD with composable patterns for monorepos, microservices, environments, and governance.",[716],"Omid Khan","https://res.cloudinary.com/about-gitlab-com/image/upload/v1772721753/frfsm1qfscwrmsyzj1qn.png","2026-04-09",[102,720,721,722],"DevOps platform","tutorial","features",{"featured":24,"template":13,"slug":724},"5-ways-gitlab-pipeline-logic-solves-real-engineering-problems",{"content":726,"config":736},{"title":727,"description":728,"authors":729,"heroImage":731,"date":732,"body":733,"category":9,"tags":734},"How to use GitLab Container Virtual Registry with Docker Hardened Images","Learn how to simplify container image management with this step-by-step guide.",[730],"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 difficult 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/)",[721,735,722],"product",{"featured":12,"template":13,"slug":737},"using-gitlab-container-virtual-registry-with-docker-hardened-images",{"content":739,"config":749},{"title":740,"description":741,"authors":742,"heroImage":744,"date":745,"category":9,"tags":746,"body":748},"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.",[743],"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",[255,617,747],"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-agent-platform/) 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":750,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"promotions":752},[753,767,778,790],{"id":754,"categories":755,"header":757,"text":758,"button":759,"image":764},"ai-modernization",[756],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":760,"config":761},"Get your AI maturity score",{"href":762,"dataGaName":763,"dataGaLocation":237},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":765},{"src":766},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":768,"categories":769,"header":770,"text":758,"button":771,"image":775},"devops-modernization",[735,563],"Are you just managing tools or shipping innovation?",{"text":772,"config":773},"Get your DevOps maturity score",{"href":774,"dataGaName":763,"dataGaLocation":237},"/assessments/devops-modernization-assessment/",{"config":776},{"src":777},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":779,"categories":780,"header":782,"text":758,"button":783,"image":787},"security-modernization",[781],"security","Are you trading speed for security?",{"text":784,"config":785},"Get your security maturity score",{"href":786,"dataGaName":763,"dataGaLocation":237},"/assessments/security-modernization-assessment/",{"config":788},{"src":789},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":791,"paths":792,"header":795,"text":796,"button":797,"image":802},"github-azure-migration",[793,794],"migration-from-azure-devops-to-gitlab","integrating-azure-devops-scm-and-gitlab","Is your team ready for GitHub's Azure move?","GitHub is already rebuilding around Azure. Find out what it means for you.",{"text":798,"config":799},"See how GitLab compares to GitHub",{"href":800,"dataGaName":801,"dataGaLocation":237},"/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":803},{"src":777},{"header":805,"blurb":806,"button":807,"secondaryButton":812},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":808,"config":809},"Get your free trial",{"href":810,"dataGaName":44,"dataGaLocation":811},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":499,"config":813},{"href":48,"dataGaName":49,"dataGaLocation":811},1776675423150]