[{"data":1,"prerenderedAt":794},["ShallowReactive",2],{"/en-us/blog/path-to-decomposing-gitlab-database-part1":3,"navigation-en-us":37,"banner-en-us":437,"footer-en-us":447,"blog-post-authors-en-us-Dylan Griffith":689,"blog-related-posts-en-us-path-to-decomposing-gitlab-database-part1":703,"assessment-promotions-en-us":745,"next-steps-en-us":784},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":25,"isFeatured":12,"meta":26,"navigation":27,"path":28,"publishedDate":20,"seo":29,"stem":33,"tagSlugs":34,"__hash__":36},"blogPosts/en-us/blog/path-to-decomposing-gitlab-database-part1.yml","Path To Decomposing Gitlab Database Part1",[7],"dylan-griffith",null,"engineering",{"slug":11,"featured":12,"template":13},"path-to-decomposing-gitlab-database-part1",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"Decomposing the GitLab backend database, Part 1: Designing and planning","A technical summary of the yearlong project to decompose GitLab's Postgres database. This first part focuses on the initial designing and planning of the project.",[18],"Dylan Griffith","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749663397/Blog/Hero%20Images/logoforblogpost.jpg","2022-08-04","\nRecently we finished [migrating the GitLab.com monolithic Postgres database to two independent databases: `Main` and `CI`](/blog/splitting-database-into-main-and-ci/). After we decided how to split things up, the project took about a year to complete.\n\nThis blog post on decomposing the GitLab backend database is part one in a three-part series. The posts give technical details about many of the challenges we had to\novercome, as well as links to issues, merge requests, epics, and developer-facing documentation.\nOur hope is that you can get as much detail as you want about how we work on complex projects at GitLab.\n\nWe highlight the most interesting details, but anyone undertaking a similar\nproject might learn a lot from seeing all\nthe different trade-offs we evaluated along the way.\n\n- \"Decomposing the GitLab backend database, Part 1\" focuses on the initial design and planning of the project.\n- [Part 2](/blog/path-to-decomposing-gitlab-database-part2/) focuses on the\nexecution of the final migration.\n- [Part 3](/blog/path-to-decomposing-gitlab-database-part3/) highlights some interesting technical challenges we had to solve along the way, as well as some surprises.\n\n## How it began\n\nBack in early 2021, GitLab formed a \"database sharding\" team in an effort to\ndeal with our ever-growing monolithic Postgres database. This database stored\nalmost all the data generated by GitLab.com users, excluding git data and some other\nsmaller things.\n\nAs this database grew over time, it became a common source of\nincidents for GitLab. We knew that eventually we had to move away from a single\nPostgres database. We were already approaching the limits of what we could do\non a single VM with 96 vCPU and continually trying to vertically scale this VM\nwould eventually not be possible. Even if we could vertically scale forever,\nmanaging such a large Postgres database just becomes more and more difficult.\n\nEven though our database architecture has been monolithic for a long time, we already made use of many scaling techniques, including:\n\n- Using Patroni to have a pool of replicas for read-only traffic\n- Using PGBouncer for pooling the vast number of connections across our application fleet\n\n![Database architecture before decomposition](https://about.gitlab.com/images/blogimages/2022-07-15-path-to-decomposing-gitlab-database/phase0.png)\n\nThese approaches only got us so far and ultimately would never fix the scaling\nbottleneck of the number of writes that need to happen, because all writes need to\ngo to the primary database.\n\nThe original objective of the database sharding team was to find a viable way\nto horizontally shard the data in the database. We started with exploring\n[sharding by top-level namespace][sharding_by_top_level_namespace_poc_epic]. This approach had some very complicated problems to solve, because the application\nwas never designed to have strict tenancy boundaries around top-level\nnamespaces. We believe that ultimately this will be a good way to split and\nscale the database, but we needed a shorter term solution to our scaling\nproblems.\n\nThis is when we evaluated different ways to extract certain tables into a\nseparate database. This approach is often referred to as \"vertical\npartitioning\" or \"functional decomposition.\" We assumed this extraction would likely\nbe easier, as long as we found a set of tables with loose coupling to the rest\nof the database. We knew it would require us to remove all joins to the rest of the\ntables (more on that later).\n\n## Figuring out where most write activity occurs\n\nWe did [an analysis][analysis_of_decomposition_tables] of:\n\n- Where the bulk of our data was stored\n- The write traffic (since ultimately the number of writes was the thing we were trying to reduce)\n\nWe learned that CI tables (at the time) made up around 40% to 50% of our write traffic. This seemed like a\nperfect candidate, because splitting the database in half (by write traffic) would be\nthe optimal scaling step.\n\nWe analyzed the data by splitting the database the following ways:\n\n| Tables group   | DB size (GB) | DB size (%) | Reads/s   | Reads/s (%) | Writes/s | Writes/s (%) |\n|----------------|--------------|-------------|-----------|-------------|----------|--------------|\n| Webhook logs   | 2964.1       | 22.39%      | 52.5      | 0.00%       | 110.0    | 2.82%        |\n| Merge Requests | 2673.7       | 20.20%      | 126073.4  | 1.31%       | 795.4    | 20.40%       |\n| CI             | 4725.0       | 35.69%      | 1712843.8 | 17.87%      | 1909.2   | 48.98%       |\n| Rest           | 2876.3       | 21.73%      | 7748488.5 | 80.82%      | 1083.6   | 27.80%       |\n\nChoosing to split the CI tables from the database was partly based on instinct.\nWe knew the CI tables (particularly `ci_builds` and\nrelated metadata) were already some of the largest tables in our database. It\nwas also a convenient choice because the CI tables were already prefixed with\n`ci_`. In the end, we realized only three tables were CI tables that weren't\nprefixed with `ci_`. You can see the up-to-date list of tables and their respective\ndatabase in [`gitlab_schemas.yml`][gitlab_schemas_yml].\n\nThe next step was to see how viable it actually was.\n\n## Proving it can work\n\nThe [first proof-of-concept merge request][initial_poc_mr_for_ci_decomposition] was created\nin August 2021. The proof-of-concept process involved:\n\n- Separating the database and seeing what broke\n- Fixing blockers and marking todo's until we ended up with the application \"pretty much working\"\n\nWe never merged this proof of concept, but we progressively broke out changes into smaller merge requests\nor issues assigned to the appropriate teams to fix.\n\n![Screenshot of large proof-of-concept MR](https://about.gitlab.com/images/blogimages/2022-07-15-path-to-decomposing-gitlab-database/poc-mr-scale.png)\n\n## Chasing a moving target\n\nWhen tackling a large-scale architecture change, you might find\nyourself chasing a moving target.\n\nTo split the database, we had to change the application. Our code depended on all\nthe tables being in a single database. These changes took almost a year.\n\nIn the meantime, the application was constantly evolving\nand growing, and with contributions from many engineers who weren't necessarily\nfamiliar with the CI decomposition project. This meant that we couldn't just\nstart fixing problems. We knew we would likely find new problems being\nintroduced at a faster rate than we could remove them.\n\nTo solve this problem, we took an approach that was inspired by\n[how we handle new RuboCop rules](https://docs.gitlab.com/ee/development/contributing/style_guides.html#resolving-rubocop-exceptions).\nThe idea is to implement static or dynamic analysis to detect these\nproblems. Then we use this information to generate an allowlist of exceptions.\nAfter we have this allowlist of exceptions, we prevent any new violations from being created\n(as any new violations will fail the pipeline).\n\nThe result was a clear list to work on and visibility into our progress.\n\nAs part of making the application compatible with CI decomposition, we needed to\nbuild the following:\n\n- [Multiple databases documentation][docs_multiple_databases] taught\n  developers how to write code that is compatible with multiple databases.\n- [Cross-join detection][mr_cross_join_detection] analyzed all SQL queries\n  and raised an error if the query spanned multiple databases.\n- [Cross-database transaction detection][mr_cross_db_transaction_detection]\n  analyzed all transactions and raised an error if queries were sent to two\n  different databases within the context of a single transaction.\n- [Query analyzer metrics][mr_query_analyzer_metrics] analyzed all SQL queries\n  and tracked the different databases that would be queried (based on table\n  names). These metrics, which were sampled at a rate of 1/10,000 queries, because they are\n  expensive to parse, were sent to Prometheus. We used this data to get a sense\n  of whether we were whittling down the list of cross-joins in production.\n  It also helped us catch code paths that weren't covered by tests but were\n  executed in production.\n- [A Rubocop rule for preventing the use of\n  `ActiveRecord::Base`][mr_rubocop_rule_ar_base] ensured that we always\n  used an explicit database connection for Main or CI.\n\n## Using Rails multiple database support\n\nWhen we began this project, there were many improvements being added to Rails to\nsupport multiple databases. We wanted to make use of as much of this Rails\nbuilt-in support as possible to minimize the amount of custom database\nconnection logic we had to maintain.\n\nOne considerable challenge with this was our existing\n[custom database load balancing logic](https://docs.gitlab.com/ee/administration/postgresql/database_load_balancing.html).\nThe development of this complex implementation spans a long period of time, and\nit was designed differently to how Rails connections were managed in the new\nmulti-database support.\n\nIn the end, were able to use parts of Rails multiple database support, but\n[we still hope to one day remove our custom logic and only use what is supported by Rails][epic_to_move_to_native_rails_multiple_dataabase_support].\n\n## Implementing loose foreign keys\n\nThere were still some foreign keys that existed between CI and non-CI tables.\nWe needed a way to remove these keys but still keep the functionality of cascading\ndeletes.\n\nIn the end, [we implemented a solution][lfk_mr]\nwe call [\"loose foreign keys\"][lfk_docs]. This solution provides similar functionality and\nsupport for cascading `NULLIFY` or `DELETE` when a parent record is deleted in\nPostgres. It's implemented using Postgres on delete triggers, so it guarantees all\ndeletes (including bulk deletes) will be handled. The trigger writes to another\n\"queue\" table in Postgres, which then is picked up by a periodic Sidekiq worker\nto clean up all the impacted child records.\n\nWhen implementing this solution, we also considered the option of using\n[`ActiveRecord` `before_destroy` callbacks](https://apidock.com/rails/ActiveRecord/Callbacks/before_destroy).\nHowever they couldn't give us the same guarantees as Postgres foreign keys,\nbecause they can be intentionally or accidentally skipped.\n\nIn the end, the \"loose foreign keys\" solution also helped to solve another problem\nwe have, where very large cascading deletes cause timeouts and user experience issues.\nBecause it's asynchronous, we could easily control timing and batch sizes to never\nhave database timeouts and never overload the database with a single large\ndelete.\n\n## Mirroring namespaces and projects\n\nOne of the most difficult dependencies between CI and Main features in GitLab\nis how CI Runners are configured. Runners are assigned to projects and groups\nwhich then dictates which jobs they will run. This meant there were many join\nqueries from the `ci_runners` table to the `projects` and `namespaces` tables.\nWe solved most of these issues by refactoring our Rails code and queries, but\nsome proved very difficult to do efficiently.\n\nTo work around this issue, [we implemented][mr_namespace_project_mirroring] a mechanism to\n[mirror the relevant columns on `projects` and `namespaces` to the CI database][docs_ci_mirrored_tables].\n\nIt's not ideal to have to duplicate data that must be kept up-to-date like\nthis, but while we expected this may be necessary in a few places, it turns out\nthat we only ended up doing this for those two tables. All other joins could be\nhandled without mirroring.\n\nAn important part of our mirroring architecture is periodic\n[consistency checking][mr_namespace_project_mirroring_consistency_check].\nEvery time this process runs, it takes a batch of the mirrored rows and compares them\nwith the expected values. If there is a discrepancy, it schedules them to be fixed.\nAfter it's done with this batch, it updates a cursor in Redis to be used for the\nnext batch.\n\n## Creating a phased rollout strategy\n\nA key part of ensuring our live migration went as smooth as possible was by\nmaking it as small as possible. This was quite difficult as the migration from\n1 database to 2 databases is a discrete change that seems hard to break up into\nsmaller steps that can be rolled out individually.\n\nOne [early insight][initial_migration_plan_mr] was that we could actually reconfigure GitLab.com ahead of\ntime so that the Rails application behaved as though it was talking to two\nseparate databases long before we actually split the databases. Basically the\nidea was that the Rails processes already had two separate database connections,\nbut ultimately they were going to the same database. We could even break things\nout further since our read-only connections are designed to read from slightly\ndelayed replicas. So we could already have read-only connections going to the\nnewly created CI read-only replicas before the migration.\n\n![Database architecture before final migration step](https://about.gitlab.com/images/blogimages/2022-07-15-path-to-decomposing-gitlab-database/phase4.png)\n\nThese insights led to our [seven-phase migration process][phased_migration_epic].\nThis process meant that by the time we got to the final migration on production\n(Phase 7), we were already incredibly confident that the application would work\nwith separate databases and the actual change being shipped was just trivial\nreconfiguration of a single database host. This also meant that all phases\n(except for Phase 7) had a very trivial rollback process, introduced very\nlittle risk of incident and could be shipped before we were finished with every\ncode change necessary to make the application support two databases.\n\nThe seven phases were:\n\n1. Deploy a Patroni cluster\n2. Configure Patroni standby cluster\n3. Serve CI reads from CI standby cluster\n4. Separate write connections for CI and Main (still going to the same primary host)\n5. Do a staging dry run and finishing the migration plan\n6. Validate metrics and additional logging\n7. Promote the CI database and send writes to it\n\n## Using labels to distribute work and prioritize\n\nNow that we had a clear set of phases we could prioritize our work. All issues\nwere assigned [scoped labels](https://docs.gitlab.com/ee/user/project/labels.html#scoped-labels)\nbased on the specific phase they corresponded to. Since the work spanned many\nteams in development and infrastructure, those teams could use the\nlabel to easily tell which issues needed to be worked on first. Additionally,\nsince we kept an up-to-date timeline of when we expected to ship each phase,\neach team could use the phase label to determine a rough deadline of when that\nwork should get done to not delay the project. Overall there were at least 193\nissues over all phases. Phase 1 and 2 were mostly infrastructure tasks tracked\nin a different group and with different labels, but the other phases contained\nthe bulk of the development team requirements:\n\n1. [8 Phase 3 issues](https://gitlab.com/gitlab-org/gitlab/-/issues/?sort=created_date&state=opened&label_name%5B%5D=ci-decomposition%3A%3Aphase3)\n1. [78 Phase 4 issues](https://gitlab.com/gitlab-org/gitlab/-/issues/?sort=created_date&state=opened&label_name%5B%5D=ci-decomposition%3A%3Aphase4)\n1. [7 Phase 5 issues](https://gitlab.com/gitlab-org/gitlab/-/issues/?sort=created_date&state=opened&label_name%5B%5D=ci-decomposition%3A%3Aphase5)\n1. [64 Phase 6 issues](https://gitlab.com/gitlab-org/gitlab/-/issues/?sort=created_date&state=opened&label_name%5B%5D=ci-decomposition%3A%3Aphase6)\n1. [34 Phase 7 issues](https://gitlab.com/gitlab-org/gitlab/-/issues/?sort=created_date&state=opened&label_name%5B%5D=ci-decomposition%3A%3Aphase7)\n\n## Continue reading\n\nYou can read more about the final migration process and results of the migration in [Part 2](/blog/path-to-decomposing-gitlab-database-part2/).\n\n[initial_poc_mr_for_ci_decomposition]: https://gitlab.com/gitlab-org/gitlab/-/merge_requests/67486\n[initial_migration_plan_mr]: https://gitlab.com/gitlab-com/www-gitlab-com/-/merge_requests/84588\n[lfk_mr]: https://gitlab.com/gitlab-org/gitlab/-/merge_requests/69165\n[lfk_docs]: https://docs.gitlab.com/ee/development/database/loose_foreign_keys.html\n[epic_to_move_to_native_rails_multiple_dataabase_support]: https://gitlab.com/gitlab-org/gitlab/-/issues/296870\n[phased_migration_epic]: https://gitlab.com/groups/gitlab-org/-/epics/6160\n[sharding_by_top_level_namespace_poc_epic]: https://gitlab.com/groups/gitlab-org/-/epics/5838\n[analysis_of_decomposition_tables]: https://gitlab.com/groups/gitlab-org/-/epics/5883#summary-of-impact\n[gitlab_schemas_yml]: https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/database/gitlab_schemas.yml\n[docs_ci_mirrored_tables]: https://docs.gitlab.com/ee/development/database/ci_mirrored_tables.html\n[mr_cross_join_detection]: https://gitlab.com/gitlab-org/gitlab/-/merge_requests/68620\n[mr_cross_db_transaction_detection]: https://gitlab.com/gitlab-org/gitlab/-/merge_requests/67213\n[mr_query_analyzer_metrics]: https://gitlab.com/gitlab-org/gitlab/-/merge_requests/73839\n[mr_rubocop_rule_ar_base]: https://gitlab.com/gitlab-org/gitlab/-/merge_requests/64937\n[mr_namespace_project_mirroring]: https://gitlab.com/gitlab-org/gitlab/-/merge_requests/75517\n[mr_namespace_project_mirroring_consistency_check]: https://gitlab.com/gitlab-org/gitlab/-/merge_requests/81836\n[docs_multiple_databases]: https://docs.gitlab.com/ee/development/database/multiple_databases.html\n",[23,24],"inside 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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.",[709],"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",[259,611,713],"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":716,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":718,"config":727},{"title":719,"description":720,"authors":721,"heroImage":722,"date":723,"category":9,"tags":724,"body":726},"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.",[709],"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",[611,259,725],"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":728,"featured":27,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":730,"config":743},{"category":9,"tags":731,"body":734,"date":735,"updatedDate":736,"heroImage":737,"authors":738,"title":741,"description":742},[732,733,106],"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",[739,740],"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":27,"template":13,"slug":744},"migration-from-azure-devops-to-gitlab",{"promotions":746},[747,761,772],{"id":748,"categories":749,"header":751,"text":752,"button":753,"image":758},"ai-modernization",[750],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":754,"config":755},"Get your AI maturity score",{"href":756,"dataGaName":757,"dataGaLocation":241},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":759},{"src":760},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":762,"categories":763,"header":764,"text":752,"button":765,"image":769},"devops-modernization",[725,557],"Are you just managing tools or shipping innovation?",{"text":766,"config":767},"Get your DevOps maturity score",{"href":768,"dataGaName":757,"dataGaLocation":241},"/assessments/devops-modernization-assessment/",{"config":770},{"src":771},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":773,"categories":774,"header":776,"text":752,"button":777,"image":781},"security-modernization",[775],"security","Are you trading speed for security?",{"text":778,"config":779},"Get your security maturity score",{"href":780,"dataGaName":757,"dataGaLocation":241},"/assessments/security-modernization-assessment/",{"config":782},{"src":783},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":785,"blurb":786,"button":787,"secondaryButton":792},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":788,"config":789},"Get your free trial",{"href":790,"dataGaName":48,"dataGaLocation":791},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":493,"config":793},{"href":52,"dataGaName":53,"dataGaLocation":791},1772652086167]