[{"data":1,"prerenderedAt":792},["ShallowReactive",2],{"/en-us/blog/how-we-removed-all-502-errors-by-caring-about-pid-1-in-kubernetes":3,"navigation-en-us":35,"banner-en-us":435,"footer-en-us":445,"blog-post-authors-en-us-Steve Azzopardi":687,"blog-related-posts-en-us-how-we-removed-all-502-errors-by-caring-about-pid-1-in-kubernetes":701,"assessment-promotions-en-us":743,"next-steps-en-us":782},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":24,"isFeatured":12,"meta":25,"navigation":26,"path":27,"publishedDate":20,"seo":28,"stem":32,"tagSlugs":33,"__hash__":34},"blogPosts/en-us/blog/how-we-removed-all-502-errors-by-caring-about-pid-1-in-kubernetes.yml","How We Removed All 502 Errors By Caring About Pid 1 In Kubernetes",[7],"steve-azzopardi",null,"engineering",{"slug":11,"featured":12,"template":13},"how-we-removed-all-502-errors-by-caring-about-pid-1-in-kubernetes",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"How we reduced 502 errors by caring about PID 1 in Kubernetes","For every deploy, scale down event, or pod termination, users of GitLab's Pages service were experiencing 502 errors. This explains how we found the root cause and rolled out a fix for it.",[18],"Steve Azzopardi","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749682305/Blog/Hero%20Images/KubeCon2022.jpg","2022-05-17","\n\n_This blog post and linked pages contain information related to upcoming products, features, and functionality. It is important to note that the information presented is for informational purposes only. Please do not rely on this information for purchasing or planning purposes. As with all projects, the items mentioned in this blog post and linked pages are subject to change or delay. The development, release, and timing of any products, features, or functionality remain at the sole discretion of GitLab Inc._\n\nOur [SRE on call](https://handbook.gitlab.com/handbook/engineering/infrastructure/incident-management/#engineer-on-call-eoc-responsibilities)\nwas getting paged daily that one of our\n[SLIs](https://www.youtube.com/watch?v=tEylFyxbDLE) was\nburning through our\n[SLOs](https://www.youtube.com/watch?v=tEylFyxbDLE) for the [GitLab\nPages](https://docs.gitlab.com/ee/user/project/pages/) service. It was\nintermittent and short-lived, but enough to cause user-facing impact which we\nweren't comfortable with. This turned into alert fatigue because there wasn't\nenough time for the SRE on call to investigate the issue and it wasn't\nactionable since it recovered on its own.\n\nWe decided to open up an [investigation issue](https://gitlab.com/gitlab-com/gl-infra/reliability/-/issues/15497)\nfor these alerts. We had to find out what the issue was since we were\nshowing `502` errors to our users and we needed a\n[DRI](https://handbook.gitlab.com/handbook/people-group/directly-responsible-individuals/)\nthat wasn't on call to investigate.\n\n## What is even going on?\n\nAs an [SRE](https://handbook.gitlab.com/job-families/engineering/infrastructure/site-reliability-engineer/)\nat GitLab, you get to touch a lot of services that you didn't build yourself and\ninteract with system dependencies that you might have not touched before.\nThere's always detective work to do!\n\nWhen we looked at the GitLab Pages logs we found that it's always returning\n[`ErrDomainDoesNotExist`](https://gitlab.com/gitlab-org/gitlab-pages/-/blob/e1f1effa23c520d3b8b717d831ccab7ba3dd494f/internal/routing/middleware.go#L22-26)\nerrors which result in a `502` error to our users. GitLab Pages [sends a request](https://gitlab.com/gitlab-org/gitlab-pages/-/blob/e1f1effa23c520d3b8b717d831ccab7ba3dd494f/internal/source/gitlab/client/client.go#L101-127)\nto [GitLab Workhorse](https://docs.gitlab.com/ee/development/workhorse/),\nspecifically the `/api/v4/internal/pages` route.\n\nGitLab Workhorse is a Go service in front of our Ruby on Rails monolith and\nit's deployed as a [sidecar](https://www.magalix.com/blog/the-sidecar-pattern)\ninside of the `webservice pod`, which runs Ruby on Rails using the `Puma` web\nserver.\n\nWe used the internal IP to correlate the GitLab Pages requests with GitLab Workhorse\ncontainers. We looked at multiple requests and found that all the 502 requests\nhad the following error attached to them: [`502 Bad Gateway with dial tcp 127.0.0.1:8080: connect: connection refused`](https://gitlab.com/gitlab-org/gitlab/-/blob/f64be48cc737f5d12c1c30f724af540a836dcc94/workhorse/internal/badgateway/roundtripper.go#L43).\nThis means that GitLab Workhorse couldn't connect to the Puma web server. So we\nneeded to go another layer deeper.\n\nThe Puma web server is what runs the Ruby on Rails monolith which has an\ninternal API endpoint but Puma was never getting these requests since it wasn't\nrunning. What this tells us is that Kubernetes kept our pod in the\n[service](https://kubernetes.io/docs/concepts/services-networking/service/)\neven when Puma wasn't responding, despite having [readiness probes](https://gitlab.com/gitlab-org/charts/gitlab/-/blob/4bb638bccc6a676f9fdd5bbf800f7d2b977efd55/charts/gitlab/charts/webservice/templates/deployment.yaml#L279-287)\nconfigured.\n\nBelow is the request flow between GitLab Pages, GitLab Workhorse, and Puma/Webservice to try and make it more clear:\n\n![overview of the request flow](https://about.gitlab.com/images/blogimages/how-we-removed-all-502-errors-by-caring-about-pid-1-in-kubernetes/overview.png){: .shadow.center}\n\n## Attempt 1: Red herring\n\nWe shifted our focus on GitLab Workhorse and Puma to try and understand how\nGitLab Workhorse was returning 502 errors in the first place. We found some\n`502 Bad Gateway with dial tcp 127.0.0.1:8080: connect: connection refused`\nerrors during container startup time. How could this be? With the readiness\nprobe, the pod shouldn't be added to the\n[Endpoint](https://kubernetes.io/docs/concepts/services-networking/service/#over-capacity-endpoints)\nuntil [all readiness probes pass](https://gitlab.com/gitlab-com/gl-infra/reliability/-/issues/15497#note_899321775).\nWe later found out that it's because of a [polling\nmechanisim](https://gitlab.com/gitlab-com/gl-infra/reliability/-/issues/15497#note_899629314)\nthat we have for [Geo](https://docs.gitlab.com/ee/administration/geo/) which\nruns in the background, using a Goroutine in GitLab Workhorse, and pings Puma for Geo information.\nWe don't have Geo enabled on GitLab.com so we [simply disabled it](https://gitlab.com/gitlab-com/gl-infra/k8s-workloads/gitlab-com/-/merge_requests/1670)\nto reduce the noise.\n\nWe removed the 502 errors, but not the ones we want, just a red herring.\n\n## Attempt 2: Close but not quite\n\nAt this time, we were still burning through our SLO from time to time, so this\nwas still an urgent thing that we needed to fix. Now that we had cleaner logs for\n`502` errors it started to become a bit clearer that this is happening on pod\ntermination:\n\n```text\n2022-04-05 06:03:49.000 UTC: Readiness probe failed\n2022-04-05 06:03:51.000 UTC: Puma (127.0.0.1:8080) started shutdown.\n2022-04-05 06:04:04.526 UTC: Puma shutdown finished.\n2022-04-05 06:04:04.000 UTC - 2022-04-05 06:04:46.000 UTC: workhorse started serving 502 constantly. 42 seconds of serving 502 requests for any request that comes in apart from /api/v4/jobs/request\n```\n\nIn the timeline shown above, we see that we've kept serving requests well after\nour `Puma`/`webservice` container exited, and the first readiness probe failed.\nIf we look at the readiness probes we had on that pod we see the following:\n\n```shell\n$ kubectl -n gitlab get po gitlab-webservice-api-785cb54bbd-xpln2 -o jsonpath='{range .spec.containers[*]} {@.name \":\\n\\tliveness:\"} {@.livenessProbe} {\"\\n\\treadiness:\"} {@.readinessProbe} {\"\\n\"} {end}'\n webservice:\n liveness: {\"failureThreshold\":3,\"httpGet\":{\"path\":\"/-/liveness\",\"port\":8080,\"scheme\":\"HTTP\"},\"initialDelaySeconds\":20,\"periodSeconds\":60,\"successThreshold\":1,\"timeoutSeconds\":30}\n readiness: {\"failureThreshold\":3,\"httpGet\":{\"path\":\"/-/readiness\",\"port\":8080,\"scheme\":\"HTTP\"},\"initialDelaySeconds\":60,\"periodSeconds\":10,\"successThreshold\":1,\"timeoutSeconds\":2}\n gitlab-workhorse:\n liveness: {\"exec\":{\"command\":[\"/scripts/healthcheck\"]},\"failureThreshold\":3,\"initialDelaySeconds\":20,\"periodSeconds\":60,\"successThreshold\":1,\"timeoutSeconds\":30}\n readiness: {\"exec\":{\"command\":[\"/scripts/healthcheck\"]},\"failureThreshold\":3,\"periodSeconds\":10,\"successThreshold\":1,\"timeoutSeconds\":2}\n\n```\n\nThis meant that for the `webservice` pod to be marked unhealthy and removed\nfrom the endpoints, Kubernetes had to get 3 consecutive failures with an\ninterval of 10 seconds, so in total that's 30 seconds. That seems a bit slow.\n\nOur next logical step was to reduce the `periodSeconds` for the readiness probe\nfor the `webservice` pod so we don't wait 30 seconds before removing the pod\nfrom the service when it becomes unhealthy.\n\nBefore doing so we had to understand if sending more requests to `/-/readiness`\nendpoint would have any knock-on effect with using more memory or anything\nelse. We had to [understand what the `/-/readiness` endpoint was doing](https://gitlab.com/gitlab-com/gl-infra/reliability/-/issues/15497#note_903812722)\nand if it was safe to increase the frequency at which we send requests. We\ndecided it was safe, and after enabling it on\n[staging](https://gitlab.com/gitlab-com/gl-infra/k8s-workloads/gitlab-com/-/merge_requests/1686#note_903877755),\nand\n[canary](https://gitlab.com/gitlab-com/gl-infra/k8s-workloads/gitlab-com/-/merge_requests/1688#note_904501848)\nwe didn't see any increase in CPU/Memory usage, as expected, and saw an\nimprovement in the removal of 502 errors, which made us more confident that\nthis was the issue. We rolled this out to\n[production](https://gitlab.com/gitlab-com/gl-infra/k8s-workloads/gitlab-com/-/merge_requests/1689)\nwith high hopes.\n\nAs usual, Production is a different story than Staging or Canary, and it showed\nthat it didn't remove all the 502 errors, just [enough to stop triggering the SLO every day](https://gitlab.com/gitlab-com/gl-infra/reliability/-/issues/15497#note_905993144),\nbut at least we removed the alert fatigue on the SRE on call. We were close, but not quite.\n\n## Attempt 3: All gone!\n\nAt this point, we were a bit lost and weren't sure what to look at next. We had\na bit of tunnel vision and kept focusing/blaming that we aren't removing the\nPod from the `Endpoint` quickly enough. We even looked at [Google Cloud Platform\nNEGs](https://cloud.google.com/kubernetes-engine/docs/how-to/standalone-neg) to\nsee if we could have faster readiness probes and remove the pod quicker. However,\nthis wasn't ideal [because we wouldn't have solved this for our self-hosting customers](https://gitlab.com/gitlab-com/gl-infra/reliability/-/issues/15497#note_908359286)\nwhich seem to be facing the same [problem](https://gitlab.com/gitlab-org/charts/gitlab/-/issues/2943).\n\nWhile researching we also came across a known problem with [running `Puma` in\nKubernetes](https://github.com/puma/puma/blob/bf2548ce300c2b4f671582bc756dcec5861e815f/docs/kubernetes.md),\nand thought that might be the solution. However, we already implemented a\n[blackout window](https://gitlab.com/gitlab-org/charts/gitlab/-/blob/c1b63f3a4867886bc1212d86985fc70e66b717c5/charts/gitlab/charts/webservice/templates/deployment.yaml#L223-224)\njust for this specific reason, so it couldn't be that either...in other words, it was another dead end.\n\nWe took a step back and looked at the [timelines one more time](https://gitlab.com/gitlab-com/gl-infra/reliability/-/issues/15497#note_910106152)\nand then it hit us. The Puma/webservice container is terminating within a\nfew seconds, but the GitLab Workhorse one is always taking 30 seconds. Is it because\nof the [long polling from GitLab Runner](https://gitlab.com/gitlab-org/gitlab-foss/-/issues/21698)? 30 seconds\nis a \"special\" number for Kubernetes [pod termination](https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#pod-termination).\nWhen Kubernetes deletes a pod it firsts sends the `TERM` signal to the\ncontainer and waits 30 seconds, if the container hasn't exited yet, it will\nsend a `KILL` signal. This indicated that maybe GitLab Workhorse was never\nshutting down and Kubernetes had to kill it.\n\nOnce more we looked at GitLab Workhorse source code and [searched for the `SIGTERM` usage](https://gitlab.com/gitlab-org/gitlab/-/blob/d66f10e169a08cedcbfe70e3ea46cbfbb20d972d/workhorse/main.go#L238-258)\nand it did seem to support [graceful termination](https://gitlab.com/gitlab-org/gitlab/-/merge_requests/62701) and\nit also had explicit logic about long polling requests, so is this just another\ndead end? Luckily when the `TERM` signal is sent, Workhorse [logs a message that\nit's shutting down](https://gitlab.com/gitlab-org/gitlab/-/merge_requests/62701). We looked\nat our logs for this specific message and didn't see anything. Is this it? We\naren't gracefully shutting down? But how? Why does it result in 502 errors?\nWhy do the GitLab Pages keep using the same pod that is terminating?\n\nWe know that the `TERM` signal is being sent to PID 1 inside of the container,\nand that process should handle the `TERM` signal for graceful shutdown. We\nlooked at the GitLab Workhorse process tree and this is what we found:\n\n```sh\ngit@gitlab-webservice-default-5d85b6854c-sbx2z:/$ ps faux\nUSER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND\nroot 1015 0.0 0.0 805036 4588 ? Rsl 13:12 0:00 runc init\ngit 1005 0.3 0.0 5992 3784 pts/0 Ss 13:12 0:00 bash\ngit 1014 0.0 0.0 8592 3364 pts/0 R+ 13:12 0:00 \\_ ps faux\ngit 1 0.0 0.0 2420 532 ? Ss 12:52 0:00 /bin/sh -c /scripts/start-workhorse\ngit 16 0.0 0.0 5728 3408 ? S 12:52 0:00 /bin/bash /scripts/start-workhorse\ngit 19 0.0 0.3 1328480 33080 ? Sl 12:52 0:00 \\_ gitlab-workhorse -logFile stdout -logFormat json -listenAddr 0.0.0.0:8181 -documentRoot /srv/gitlab/public -secretPath /etc/gitlab/gitlab-workhorse/secret -config /srv/gitlab/config/workhorse-config.toml\n```\n\nBingo! `gitlab-workhorse` is PID 19 in this case, and a child process of a\n[script](https://gitlab.com/gitlab-org/build/CNG/-/blob/92d3e22e9ff6c5cbb685aeea99813751d5e19a9d/gitlab-workhorse/Dockerfile#L51)\nthat we invoke. Taking a close look at the\n[script](https://gitlab.com/gitlab-org/build/CNG/-/blob/92d3e22e9ff6c5cbb685aeea99813751d5e19a9d/gitlab-workhorse/scripts/start-workhors)\nwe check if it listens to `TERM` and it doesn't! So far everything indicated\nthat GitLab Workhorse was never getting the `TERM` signal which ended up in receiving\n`KILL` after 30 seconds. We updated our `scripts/start-workhorse` to use\n[`exec(1)`](https://linux.die.net/man/1/exec) so that `gitlab-workhorse`\nreplaced the PID of our bash script, that should have worked, right? When we tested\nthis locally we then saw the following process tree.\n\n```shell\ngit@gitlab-webservice-default-84c68fc9c9-xcsnm:/$ ps faux\nUSER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND\ngit 167 0.0 0.0 5992 3856 pts/0 Ss 14:27 0:00 bash\ngit 181 0.0 0.0 8592 3220 pts/0 R+ 14:27 0:00 \\_ ps faux\ngit 1 0.0 0.0 2420 520 ? Ss 14:24 0:00 /bin/sh -c /scripts/start-workhorse\ngit 17 0.0 0.3 1328228 32800 ? Sl 14:24 0:00 gitlab-workhorse -logFile stdout -logFormat json -listenAddr 0.0.0.0:8181 -documentRoot /srv/gitlab/public -secretPath /etc/gitlab/gitlab-workhorse/secret -config /srv/gitlab/config/workhorse-config.toml\n```\n\nThis changed a bit: this shows that `gitlab-workhorse` was no longer a child\nprocess of `/scripts/start-workhorse` however `/bin/sh` was still PID 1. What is even\ninvoking `/bin/sh` that we didn't see anywhere in our\n[Dockerfile](https://gitlab.com/gitlab-org/build/CNG/-/blob/92d3e22e9ff6c5cbb685aeea99813751d5e19a9d/gitlab-workhorse/Dockerfile)?\nAfter some thumb-twiddling, we had an idea that the container runtime is invoking\n`/bin/sh`. We went back to basics and looked at the\n[`CMD`](https://docs.docker.com/engine/reference/builder/#cmd) documentation to\nsee if we were missing something, and we were. We read the following:\n\n> If you use the shell form of the CMD, then the \u003Ccommand> will execute in `/bin/sh -c`:\n>\n> ```\n> FROM ubuntu\n> CMD echo \"This is a test.\" | wc -\n> ```\n>\n> If you want to run your \u003Ccommand> without a shell then you must express the command as a JSON array and give the full path to the executable. This array form is the preferred format of CMD. Any additional parameters must be individually expressed as strings in the array:\n>\n> ```\n> FROM ubuntu\n> CMD [\"/usr/bin/wc\",\"--help\"]\n> ```\n\nThis was exactly [what we were doing](https://gitlab.com/gitlab-org/build/CNG/-/blob/92d3e22e9ff6c5cbb685aeea99813751d5e19a9d/gitlab-workhorse/Dockerfile#L51)!\nwe weren't using `CMD` in `exec form`, but in `shell form`. Changing this confirmed\nthat `gitlab-workhorse` is now PID 1, and also receives the termination signal\nafter testing it locally:\n\n```shell\ngit@gitlab-webservice-default-84c68fc9c9-lzwmp:/$ ps faux\nUSER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND\ngit 65 1.0 0.0 5992 3704 pts/0 Ss 15:25 0:00 bash\ngit 73 0.0 0.0 8592 3256 pts/0 R+ 15:25 0:00 \\_ ps faux\ngit 1 0.2 0.3 1328228 32288 ? Ssl 15:24 0:00 gitlab-workhorse -logFile stdout -logFormat json -listenAddr 0.0.0.0:8181 -documentRoot /srv/gitlab/public -secretPath /etc/gitlab/gitlab-workhorse/secret -config /srv/gitlab/config/workhorse-config.toml\n```\n\n```text\n{\"level\":\"info\",\"msg\":\"shutdown initiated\",\"shutdown_timeout_s\":61,\"signal\":\"terminated\",\"time\":\"2022-04-13T15:27:57Z\"}\n{\"level\":\"info\",\"msg\":\"keywatcher: shutting down\",\"time\":\"2022-04-13T15:27:57Z\"}\n{\"error\":null,\"level\":\"fatal\",\"msg\":\"shutting down\",\"time\":\"2022-04-13T15:27:57Z\"}\n```\n\nOk, then we just needed to update `exec` and `CMD []` and we would have been\ndone, right? Almost. GitLab Workhorse proxies all of the requests for the API, Web, and Git requests so we couldn't just do a big change and expect that everything is going to be OK. We had to progressively roll this out to make\nsure we didn't break any existing working behavior since this affects all the\nrequests we get to GitLab.com. To do this, we hid it behind a [feature\nflag](https://gitlab.com/gitlab-org/build/CNG/-/merge_requests/972) so GitLab\nWorkhorse is only PID 1 when the `GITLAB_WORKHORSE_EXEC` environment variable\nis set. This allowed us to deploy the change and only enable it on a small part\nof our fleet to see if we see any problems. We were a bit more careful here and\nrolled it out zone by zone in Production since we run on 3 zones. When we\nrolled it out in the [first\nzone](https://gitlab.com/gitlab-com/gl-infra/reliability/-/issues/15497#note_919259030)\nwe saw all 502 errors disappear! After fully rolling this out we see that [the\nproblem is fixed and it had no negative side\neffects](https://gitlab.com/gitlab-com/gl-infra/reliability/-/issues/15497#note_920585707). Hurray!\n\nWe still had one question unanswered, why were GitLab Pages still trying to use\nthe same connection even after the Pod was removed from the Service because it was\nscheduled for deletion? When we looked at Go internals we see that [Go reuses\nTCP connections](https://gitlab.com/gitlab-com/gl-infra/reliability/-/issues/15497#note_920642770)\nif we close the body of the request. So even though it's not part of the Service\nwe can still keep the TCP connection open and send requests – this explains why\nwe kept seeing 502 on pod being terminated and always from the same GitLab\nPages pod.\n\nNow it's all gone!\n\n## More things that we can explore\n\n1. We've made graceful termination for GitLab Workhorse as [default](https://gitlab.com/gitlab-com/gl-infra/k8s-workloads/gitlab-com/-/merge_requests/1732).\n1. Audit all of our Dockerfiles that use `CMD command` and fix them. We've found 10, and [fixed all of them](https://gitlab.com/gitlab-org/charts/gitlab/-/issues/3249).\n1. [Better readiness Probe defaults for `webservice` pod](https://gitlab.com/gitlab-org/charts/gitlab/-/merge_requests/2518).\n1. Add [linting](https://gitlab.com/gitlab-org/charts/gitlab/-/issues/3253) for Dockerfiles.\n1. See if any of our child processes need [zombie process reaping](https://blog.phusion.nl/2015/01/20/docker-and-the-pid-1-zombie-reaping-problem/).\n\n## Takeaways\n\n1. We should always care about what is PID 1 in a container.\n1. Always try and use `CMD [\"executable\",\"param1\",\"param2\"]` in your Dockerfile.\n1. Pods are removed from the Service/Endpoint in async.\n1. If you are on GKE [NEGs](https://cloud.google.com/kubernetes-engine/docs/how-to/standalone-neg) might be better for readinessProbes.\n1. By default, there is a 30 second grace period between the `TERM` signal and the `KILL` signal when Pods terminate. You can update the time between the signals `terminationGracePeriodSeconds`.\n1. The Go `http.Client` will reuse the TCP connection if [the body is closed](https://cs.opensource.google/go/go/+/refs/tags/go1.18.2:src/net/http/response.go;l=59-64) which in this case made the issue worse.\n\nThank you to [@igorwwwwwwwwwwwwwwwwwwww](https://gitlab.com/igorwwwwwwwwwwwwwwwwwwww), [@gsgl](https://gitlab.com/gsgl), [@jarv](https://gitlab.com/jarv), and [@cmcfarland](https://gitlab.com/cmcfarland) for helping me debug this 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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.",[707],"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",[257,609,711],"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":714,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":716,"config":725},{"title":717,"description":718,"authors":719,"heroImage":720,"date":721,"category":9,"tags":722,"body":724},"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.",[707],"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",[609,257,723],"product","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":726,"featured":26,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":728,"config":741},{"category":9,"tags":729,"body":732,"date":733,"updatedDate":734,"heroImage":735,"authors":736,"title":739,"description":740},[730,731,104],"tutorial","git","\nEnterprise teams are increasingly migrating from Azure DevOps to GitLab to gain strategic advantages and accelerate secure software delivery. \n\n\n- GitLab comes with integrated controls, policies, and [compliance frameworks](https://docs.gitlab.com/user/compliance/compliance_frameworks/) that allow organizations to implement software delivery standards at scale. This is especially important for regulated industries.\n\n- [Security testing](https://docs.gitlab.com/user/application_security/) is embedded in the pipeline and results show in the developer workflow, including static application security testing (SAST), source code analysis (SCA), dynamic application security testing (DAST), infrastructure-as-code scanning (IaC), container scanning, and API scanning.\n\n- [AI capabilities](https://about.gitlab.com/gitlab-duo-agent-platform/) across the full software delivery lifecycle include advanced agent orchestration and customizable flows to support how your organizational teams work.\n\n\nGitLab's open-source, open-core approach, flexible deployment options such as single-tenant dedicated and self-managed, and truly unified platform eliminate integration complexity and security gaps. \n\n\nFor teams facing mounting pressure to accelerate delivery while strengthening security posture and maintaining regulatory compliance, GitLab represents not just a migration but a platform evolution.\n\n\nMigrating from Azure DevOps to GitLab can seem like a daunting task, but with the right approach and tools, it can be a smooth and efficient process. This guide will walk you through the steps needed to successfully migrate your projects, repositories, and pipelines from Azure DevOps to GitLab.\n\n\n## Overview\n\nGitLab provides both [Congregate](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/) (maintained by [GitLab Professional Services](https://about.gitlab.com/professional-services/) organization) and [a built-in Git repository import](https://docs.gitlab.com/user/project/import/repo_by_url/) for migrating projects from Azure DevOps (ADO). These options support repository-by-repository or bulk migration and preserve git commit history, branches, and tags. With Congregate and professional services tools, we support additional assets such as wikis, work items, CI/CD variables, container images, packages, pipelines, and more (see this [feature matrix](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/-/blob/master/customer/ado-migration-features-matrix.md)). Use this guide to plan and execute your migration and complete post-migration follow-up tasks.\n\n\nEnterprises migrating from ADO to GitLab commonly follow a multi-phase approach:\n\n\n- Migrate repositories from ADO to GitLab using Congregate or GitLab's built-in repository migration.\n\n- Migrate pipelines from Azure Pipelines to GitLab CI/CD.\n\n- Migrate remaining assets such as boards, work items, and artifacts to GitLab Issues, Epics, and the Package and Container Registries.\n\n\nHigh-level migration phases:\n\n\n```mermaid\ngraph LR\n subgraph Prerequisites\n direction TB\n A[\"Set up identity provider (IdP) and\u003Cbr/>provision users\"]\n A --> B[\"Set up runners and\u003Cbr/>third-party integrations\"]\n B --> I[\"Users enablement and\u003Cbr/>change management\"]\n end\n \n subgraph MigrationPhase[\"Migration phase\"]\n direction TB\n C[\"Migrate source code\"]\n C --> D[\"Preserve contributions and\u003Cbr/> format history\"]\n D --> E[\"Migrate work items and\u003Cbr/>map to \u003Ca href=\"https://docs.gitlab.com/topics/plan_and_track/\">GitLab Plan \u003Cbr/>and track work\"]\n end\n \n subgraph PostMigration[\"Post-migration steps\"]\n direction TB\n F[\"Create or translate \u003Cbr/>ADO pipelines to GitLab CI\"]\n F --> G[\"Migrate other assets\u003Cbr/>packages and container images\"]\n G --> H[\"Introduce \u003Ca href=\"https://docs.gitlab.com/user/application_security/secure_your_application/\">security\u003C/a> and\u003Cbr/>SDLC improvements\"]\n end\n \n Prerequisites --> MigrationPhase\n MigrationPhase --> PostMigration\n\n style A fill:#FC6D26\n style B fill:#FC6D26\n style I fill:#FC6D26\n style C fill:#8C929D\n style D fill:#8C929D\n style E fill:#8C929D\n style F fill:#FFA500\n style G fill:#FFA500\n style H fill:#FFA500\n```\n\n\n## Planning your migration\n\n\n**To plan your migration, ask these questions:**\n\n\n- How soon do we need to complete the migration?\n\n- Do we understand what will be migrated?\n\n- Who will run the migration?\n\n- What organizational structure do we want in GitLab?\n\n- Are there any constraints, limitations, or pitfalls that need to be taken into account?\n\n\nDetermine your timeline, as it will largely dictate your migration approach. Identify champions or groups familiar with both ADO and GitLab platforms (such as early adopters) to help drive adoption and provide guidance.\n\n\n**Inventory what you need to migrate:**\n\n\n- The number of repositories, pull requests, and contributors\n\n- The number and complexity of work items and pipelines\n\n- Repository sizes and dependency relationships\n\n- Critical integrations and runner requirements (agent pools with specific capabilities)\n\n\nUse GitLab Professional Services's [Evaluate](https://gitlab.com/gitlab-org/professional-services-automation/tools/utilities/evaluate#beta-azure-devops) tool to produce a complete inventory of your entire Azure DevOps organization, including repositories, PR counts, contributor lists, number of pipelines, work items, CI/CD variables and more. If you're working with the GitLab Professional Services team, share this report with your engagement manager or technical architect to help plan the migration.\n\n\nMigration timing is primarily driven by pull request count, repository size, and amount of contributions (e.g. comments in PR, work items, etc). For example, 1,000 small repositories with few PRs and limited contributors can migrate much faster than a smaller set of repositories containing tens of thousands of PRs and thousands of contributors. Use your inventory data to estimate effort and plan test runs before proceeding with production migrations.\n\n\nCompare inventory against your desired timeline and decide whether to migrate all repositories at once or in batches. If teams cannot migrate simultaneously, batch and stagger migrations to align with team schedules. For example, in Professional Services engagements, we organize migrations into waves of 200-300 projects to manage complexity and respect API rate limits, both in [GitLab](https://docs.gitlab.com/security/rate_limits/) and [ADO](https://learn.microsoft.com/en-us/azure/devops/integrate/concepts/rate-limits?view=azure-devops).\n\n\nGitLab's built-in [repository importer](https://docs.gitlab.com/user/project/import/repo_by_url/) migrates Git repositories (commits, branches, and tags) one-by-one. Congregate is designed to preserve pull requests (known in GitLab as merge requests), comments, and related metadata where possible; the simple built-in repository import focuses only on the Git data (history, branches, and tags).\n\n\n**Items that typically require separate migration or manual recreation:**\n\n\n- Azure Pipelines - create equivalent GitLab CI/CD pipelines (consult with [CI/CD YAML](https://docs.gitlab.com/ci/yaml/) and/or with [CI/CD components](https://docs.gitlab.com/ci/components/)). Alternatively, consider using AI-based pipeline conversion available in Congregate.\n\n- Work items and boards - map to GitLab Issues, Epics, and Issue Boards.\n\n- Artifacts, container images (ACR) - migrate to GitLab Package Registry or Container Registry.\n\n- Service hooks and external integrations - recreate in GitLab.\n\n- [Permissions models](https://docs.gitlab.com/user/permissions/) differ between ADO and GitLab; review and plan permissions mapping rather than assuming exact preservation.\n\n\nReview what each tool (Congregate vs. built-in import) will migrate and choose the one that fits your needs. Make a list of any data or integrations that must be migrated or recreated manually.\n\n\n**Who will run the migration?**\n\n\nMigrations are typically run by a GitLab group owner or instance administrator, or by a designated migrator who has been granted the necessary permissions on the destination group/project. Congregate and the GitLab import APIs require valid authentication tokens for both Azure DevOps and GitLab.\n\n\n- Decide whether a group owner/admin will perform the migrations or whether you will grant a specific team/person delegated access.\n\n- Ensure the migrator has correctly configured personal access tokens (Azure DevOps and GitLab) with the scopes required by your chosen migration tool (for example, api/read_repository scopes and any tool-specific requirements). \n\n- Test tokens and permissions with a small pilot migration.\n\n**Note:** Congregate leverages file-based import functionality for ADO migrations and requires instance administrator permissions to run ([see our documentation](https://docs.gitlab.com/user/project/settings/import_export/#migrate-projects-by-uploading-an-export-file)). If you are migrating to GitLab.com, consider engaging Professional Services. For more information, see the [Professional Services Full Catalog](https://about.gitlab.com/professional-services/catalog/). Non-admin account cannot preserve contribution attribution!\n\n\n**What organizational structure do we want in GitLab?**\n\nWhile it's possible to map ADO structure directly to GitLab structure, it's recommended to rationalize and simplify the structure during migration. Consider how teams will work in GitLab and design the structure to facilitate collaboration and access management. Here is a way to think about mapping ADO structure to GitLab structure:\n\n\n```mermaid\ngraph TD\n subgraph GitLab\n direction TB\n A[\"Top-level Group\"]\n B[\"Subgroup (optional)\"]\n C[\"Projects\"]\n A --> B\n A --> C\n B --> C\n end\n\n subgraph AzureDevOps[\"Azure DevOps\"]\n direction TB\n F[\"Organizations\"]\n G[\"Projects\"]\n H[\"Repositories\"]\n F --> G\n G --> H\n end\n\n style A fill:#FC6D26\n style B fill:#FC6D26\n style C fill:#FC6D26\n style F fill:#8C929D\n style G fill:#8C929D\n style H fill:#8C929D\n```\n\nRecommended approach:\n\n\n- Map each ADO organization to a GitLab group (or a small set of groups), not to many small groups. Avoid creating a GitLab group for every ADO team project. Use migration as an opportunity to rationalize your GitLab structure.\n\n- Use subgroups and project-level permissions to group related repositories.\n\n- Manage access to sets of projects by using GitLab groups and group membership (groups and subgroups) rather than one group per team project.\n\n- Review GitLab [permissions](https://docs.gitlab.com/ee/user/permissions.html) and consider [SAML Group Links](https://docs.gitlab.com/user/group/saml_sso/group_sync/) to implement an enterprise RBAC model for your GitLab instance (or a GitLab.com namespace).\n\n\n**ADO Boards and work items: State of migration**\n\n\nIt's important to understand how work items migrate from ADO into GitLab Plan (issues, epics, and boards).\n\n\n- ADO Boards and work items map to GitLab Issues, Epics, and Issue Boards. Plan how your workflows and board configurations will translate.\n\n- ADO Epics and Features become GitLab Epics.\n\n- Other work item types (e.g., user stories, tasks, bugs) become project-scoped issues.\n\n- Most standard fields are preserved; selected custom fields can be migrated when supported.\n\n- Parent-child relationships are retained so Epics reference all related issues.\n\n- Links to pull requests are converted to merge request links to maintain development traceability.\n\n\nExample: Migration of an individual work item to a GitLab Issue, including field accuracy and relationships:\n\n\n![Example: Migration of an individual work item to a GitLab Issue](https://res.cloudinary.com/about-gitlab-com/image/upload/v1764769188/ztesjnxxfbwmfmtckyga.png)\n\n\nBatching guidance:\n\n\n- If you need to run migrations in batches, use your new group/subgroup structure to define batches (for example, by ADO organization or by product area).\n\n- Use inventory reports to drive batch selection and test each batch with a pilot migration before scaling.\n\n\n**Pipelines migration**\n\n\nCongregate [recently introduced](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/-/merge_requests/1298) AI-powered conversion for multi-stage YAML pipelines from Azure DevOps to GitLab CI/CD. This automated conversion works best for simple, single-file pipelines and is designed to provide a working starting point rather than a production-ready `.gitlab-ci.yml` file. The tool generates a functionally equivalent GitLab pipeline that you can then refine and optimize for your specific needs.\n\n\n- Converts Azure Pipelines YAML to `.gitlab-ci.yml` format automatically.\n\n- Best suited for straightforward, single-file pipeline configurations.\n\n- Provides a boilerplate to accelerate migration, not a final production artifact.\n\n- Requires review and adjustment for complex scenarios, custom tasks, or enterprise requirements.\n\n- Does not support Azure DevOps classic release pipelines — [convert these to multi-stage YAML](https://learn.microsoft.com/en-us/azure/devops/pipelines/release/from-classic-pipelines?view=azure-devops) first.\n\n\nRepository owners should review the [GitLab CI/CD documentation](https://docs.gitlab.com/ci/) to further optimize and enhance their pipelines after the initial conversion.\n\n\nExample of converted pipelines:\n\n\n```yml \n\n# azure-pipelines.yml\n\ntrigger:\n - main\n\nvariables:\n imageName: myapp\n\nstages:\n - stage: Build\n jobs:\n - job: Build\n pool:\n vmImage: 'ubuntu-latest'\n steps:\n - checkout: self\n\n - task: Docker@2\n displayName: Build Docker image\n inputs:\n command: build\n repository: $(imageName)\n Dockerfile: '**/Dockerfile'\n tags: |\n $(Build.BuildId)\n\n - stage: Test\n jobs:\n - job: Test\n pool:\n vmImage: 'ubuntu-latest'\n steps:\n - checkout: self\n\n # Example: run tests inside the container\n - script: |\n docker run --rm $(imageName):$(Build.BuildId) npm test\n displayName: Run tests\n\n - stage: Push\n jobs:\n - job: Push\n pool:\n vmImage: 'ubuntu-latest'\n steps:\n - checkout: self\n\n - task: Docker@2\n displayName: Login to ACR\n inputs:\n command: login\n containerRegistry: '\u003Cyour-acr-service-connection>'\n\n - task: Docker@2\n displayName: Push image to ACR\n inputs:\n command: push\n repository: $(imageName)\n tags: |\n $(Build.BuildId)\n\n```\n\n```yaml\n\n# .gitlab-ci.yml\n\nvariables:\n imageName: myapp\n\nstages:\n - build\n - test\n - push\n\nbuild:\n stage: build\n image: docker:latest\n services:\n - docker:dind\n script:\n - docker build -t $imageName:$CI_PIPELINE_ID -f $(find . -name Dockerfile) .\n only:\n - main\n\ntest:\n stage: test\n image: docker:latest\n services:\n - docker:dind\n script:\n - docker run --rm $imageName:$CI_PIPELINE_ID npm test\n only:\n - main\n\npush:\n stage: push\n image: docker:latest\n services:\n - docker:dind\n before_script:\n - docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY\n script:\n - docker tag $imageName:$CI_PIPELINE_ID $CI_REGISTRY/$CI_PROJECT_PATH/$imageName:$CI_PIPELINE_ID\n - docker push $CI_REGISTRY/$CI_PROJECT_PATH/$imageName:$CI_PIPELINE_ID\n only:\n - main\n\n```\n\n**Final checklist:**\n\n\n- Decide timeline and batch strategy.\n\n- Produce a full inventory of repositories, PRs, and contributors.\n\n- Choose Congregate or the built-in import based on scope (PRs and metadata vs. Git data only).\n\n- Decide who will run migrations and ensure tokens/permissions are configured.\n\n- Identify assets that must be migrated separately (pipelines, work items, artifacts, and hooks) and plan those efforts.\n\n- Run pilot migrations, validate results, then scale according to your plan.\n\n\n## Running your migrations\n\n\nAfter planning, execute migrations in stages, starting with trial runs. Trial migrations help surface org-specific issues early and let you measure duration, validate outcomes, and fine-tune your approach before production.\n\n\nWhat trial migrations validate:\n\n\n- Whether a given repository and related assets migrate successfully (history, branches, tags; plus MRs/comments if using Congregate)\n\n- Whether the destination is usable immediately (permissions, runners, CI/CD variables, integrations)\n\n- How long each batch takes, to set schedules and stakeholder expectations\n\n\nDowntime guidance:\n\n\n- GitLab's built-in Git import and Congregate do not inherently require downtime.\n\n- For production waves, freeze changes in ADO (branch protections or read-only) to avoid missed commits, PR updates, or work items created mid-migration.\n\n- Trial runs do not require freezes and can be run anytime.\n\n\nBatching guidance:\n\n\n- Run trial batches back-to-back to shorten elapsed time; let teams validate results asynchronously.\n\n- Use your planned group/subgroup structure to define batches and respect API rate limits.\n\n\nRecommended steps:\n\n\n1. Create a test destination in GitLab for trials:\n\n\n - GitLab.com: create a dedicated group/namespace (for example, my-org-sandbox)\n\n - Self-managed: create a top-level group or a separate test instance if needed\n\n\n2. Prepare authentication:\n\n\n - Azure DevOps PAT with required scopes.\n\n - GitLab Personal Access Token with api and read_repository (plus admin access for file-based imports used by Congregate).\n\n\n3. Run trial migrations:\n\n\n - Repos only: use GitLab's built-in import (Repo by URL)\n\n - Repos + PRs/MRs and additional assets: use Congregate\n\n\n4. Post-trial follow-up:\n\n\n - Verify repo history, branches, tags; merge requests (if migrated), issues/epics (if migrated), labels, and relationships.\n\n - Check permissions/roles, protected branches, required approvals, runners/tags, variables/secrets, integrations/webhooks.\n\n - Validate pipelines (`.gitlab-ci.yml`) or converted pipelines where applicable.\n\n\n5. Ask users to validate functionality and data fidelity.\n\n6. Resolve issues uncovered during trials and update your runbooks.\n\n7. Network and security:\n\n\n - If your destination uses IP allow lists, add the IPs of your migration host and any required runners/integrations so imports can succeed.\n\n\n8. Run production migrations in waves:\n\n\n - Enforce change freezes in ADO during each wave.\n\n - Monitor progress and logs; retry or adjust batch sizes if you hit rate limits.\n\n\n9. Optional: remove the sandbox group or archive it after you finish.\n\n\n\u003Cfigure class=\"video_container\">\n \u003Ciframe src=\"https://www.youtube.com/embed/ibIXGfrVbi4?si=ZxOVnXjCF-h4Ne0N\" frameborder=\"0\" allowfullscreen=\"true\">\u003C/iframe>\n\u003C/figure>\n\n\n## Terminology reference for GitLab and Azure DevOps\n\n| GitLab | Azure DevOps | Similarities & Key Differences |\n| ---------------------------------------------------------------- | -------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Group | Organization | Top-level namespace, membership, policies. ADO org contains Projects; GitLab Group contains Subgroups and Projects. |\n| Group or Subgroup | Project | Logical container, permissions boundary. ADO Project holds many repos; GitLab Groups/Subgroups organize many Projects. |\n| Project (includes a Git repo) | Repository (inside a Project) | Git history, branches, tags. In GitLab, a \"Project\" is the repo plus issues, CI/CD, wiki, etc. One repo per Project. |\n| Merge Request (MR) | Pull Request (PR) | Code review, discussions, approvals. MR rules include approvals, required pipelines, code owners. |\n| Protected Branches, MR Approval Rules, Status Checks | Branch Policies | Enforce reviews and checks. GitLab combines protections + approval rules + required status checks. |\n| GitLab CI/CD | Azure Pipelines | YAML pipelines, stages/jobs, logs. ADO also has classic UI pipelines; GitLab centers on .gitlab-ci.yml. |\n| .gitlab-ci.yml | azure-pipelines.yml | Defines stages/jobs/triggers. Syntax/features differ; map jobs, variables, artifacts, and triggers. |\n| Runners (shared/specific) | Agents / Agent Pools | Execute jobs on machines/containers. Target via demands (ADO) vs tags (GitLab). Registration/scoping differs. |\n| CI/CD Variables (project/group/instance), Protected/Masked | Pipeline Variables, Variable Groups, Library | Pass config/secrets to jobs. GitLab supports group inheritance and masking/protection flags. |\n| Integrations, CI/CD Variables, Deploy Keys | Service Connections | External auth to services/clouds. Map to integrations or variables; cloud-specific helpers available. |\n| Environments & Deployments (protected envs) | Environments (with approvals) | Track deploy targets/history. Approvals via protected envs and manual jobs in GitLab. |\n| Releases (tag + notes) | Releases (classic or pipelines) | Versioned notes/artifacts. GitLab Release ties to tags; deployments tracked separately. |\n| Job Artifacts | Pipeline Artifacts | Persist job outputs. Retention/expiry configured per job or project. |\n| Package Registry (NuGet/npm/Maven/PyPI/Composer, etc.) | Azure Artifacts (NuGet/npm/Maven, etc.) | Package hosting. Auth/namespace differ; migrate per package type. |\n| GitLab Container Registry | Azure Container Registry (ACR) or others | OCI images. GitLab provides per-project/group registries. |\n| Issue Boards | Boards | Visualize work by columns. GitLab boards are label-driven; multiple boards per project/group. |\n| Issues (types/labels), Epics | Work Items (User Story/Bug/Task) | Track units of work. Map ADO types/fields to labels/custom fields; epics at group level. |\n| Epics, Parent/Child Issues | Epics/Features | Hierarchy of work. Schema differs; use epics + issue relationships. |\n| Milestones and Iterations | Iteration Paths | Time-boxing. GitLab Iterations (group feature) or Milestones per project/group. |\n| Labels (scoped labels) | Area Paths | Categorization/ownership. Replace hierarchical areas with scoped labels. |\n| Project/Group Wiki | Project Wiki | Markdown wiki. Backed by repos in both; layout/auth differ slightly. |\n| Test reports via CI, Requirements/Test Management, integrations | Test Plans/Cases/Runs | QA evidence/traceability. No 1:1 with ADO Test Plans; often use CI reports + issues/requirements. |\n| Roles (Owner/Maintainer/Developer/Reporter/Guest) + custom roles | Access levels + granular permissions | Control read/write/admin. Models differ; leverage group inheritance and protected resources. |\n| Webhooks | Service Hooks | Event-driven integrations. Event names/payloads differ; reconfigure endpoints. |\n| Advanced Search | Code Search | Full-text repo search. Self-managed GitLab may need Elasticsearch/OpenSearch for advanced features. |\n","2025-12-03","2026-01-16","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749658924/Blog/Hero%20Images/securitylifecycle-light.png",[737,738],"Evgeny Rudinsky","Michael Leopard","Guide: Migrate from Azure DevOps to GitLab","Learn how to carry out the full migration from Azure DevOps to GitLab using GitLab Professional Services migration tools — from planning and execution to post-migration follow-up tasks.",{"featured":26,"template":13,"slug":742},"migration-from-azure-devops-to-gitlab",{"promotions":744},[745,759,770],{"id":746,"categories":747,"header":749,"text":750,"button":751,"image":756},"ai-modernization",[748],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":752,"config":753},"Get your AI maturity score",{"href":754,"dataGaName":755,"dataGaLocation":239},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":757},{"src":758},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":760,"categories":761,"header":762,"text":750,"button":763,"image":767},"devops-modernization",[723,555],"Are you just managing tools or shipping innovation?",{"text":764,"config":765},"Get your DevOps maturity score",{"href":766,"dataGaName":755,"dataGaLocation":239},"/assessments/devops-modernization-assessment/",{"config":768},{"src":769},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":771,"categories":772,"header":774,"text":750,"button":775,"image":779},"security-modernization",[773],"security","Are you trading speed for security?",{"text":776,"config":777},"Get your security maturity score",{"href":778,"dataGaName":755,"dataGaLocation":239},"/assessments/security-modernization-assessment/",{"config":780},{"src":781},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":783,"blurb":784,"button":785,"secondaryButton":790},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":786,"config":787},"Get your free trial",{"href":788,"dataGaName":46,"dataGaLocation":789},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":491,"config":791},{"href":50,"dataGaName":51,"dataGaLocation":789},1772652074237]