[{"data":1,"prerenderedAt":796},["ShallowReactive",2],{"/en-us/blog/remote-development-beta":3,"navigation-en-us":43,"banner-en-us":443,"footer-en-us":453,"blog-post-authors-en-us-David O'Regan":692,"blog-related-posts-en-us-remote-development-beta":707,"assessment-promotions-en-us":747,"next-steps-en-us":786},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":29,"isFeatured":12,"meta":30,"navigation":31,"path":32,"publishedDate":20,"seo":33,"stem":37,"tagSlugs":38,"__hash__":42},"blogPosts/en-us/blog/remote-development-beta.yml","Remote Development Beta",[7],"david-oregan",null,"engineering",{"slug":11,"featured":12,"template":13},"remote-development-beta",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"Behind the scenes of the Remote Development Beta release","Discover the epic journey of GitLab's Remote Development team as they navigate last-minute pivots, adapt, and deliver new features for users worldwide.",[18],"David O'Regan","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749679888/Blog/Hero%20Images/remotedevelopment.jpg","2023-08-16","\nIn May 2023, the Create:IDE team faced an epic challenge – to merge the [Remote Development Rails monolith integration branch](https://gitlab.com/gitlab-org/gitlab/-/merge_requests/105783) into the `master` branch of the GitLab Project. This was no small ask, as the merge request was of considerable size and complexity. In this blog post, we'll delve into the background, justifications, and process behind this endeavor.\n\nThe merge request titled \"Remote Development feature behind a feature flag\" was initiated by the Create:IDE team, aiming to merge the branch \"remote_dev\" into the \"master\" branch in the Rails monolith GitLab project. The MR contained `4` commits, `258` pipelines, and `143` changes that amounted to a total of `+7243` lines of code added to the codebase.\n\nInitially, the MR was created to reflect the work related to \"Remote Development\" under the \"Category: Remote Development.\" It was primarily intended to have CI pipeline coverage for the integration branch and was not meant for individual review or direct merging. The plan was to merge this code into the master branch via the [\"Remote Development Beta - Review and merge\" Epic](https://gitlab.com/groups/gitlab-org/-/epics/10258).\n\n![SUM](https://about.gitlab.com/images/blogimages/remote-development/SUM.png){: .shadow.medium}\n\n### How the Remote Development project started\nAs a team, we embarked on an ambitious journey to create a greenfield feature: the [Remote Development](https://docs.gitlab.com/ee/user/project/remote_development/) offering at GitLab. This feature had a vast scope, many unknowns, and required solving numerous new problems. To efficiently tackle this task, we decided to work on an integration branch using a [low-ceremony process](https://stackoverflow.com/questions/68092498/what-does-low-ceremony-mean). This decision enabled us to develop and release the feature in an impressively short time frame of less than four months.\n\nWorking on an integration branch provided us the flexibility to make significant progress, but it was always intended to eventually break down the work into smaller, iterative MRs that would follow the standard [GitLab review process](https://docs.gitlab.com/ee/development/code_review.html). We had a [detailed plan](https://gitlab.com/gitlab-org/remote-development/gitlab-remote-development-docs/-/blob/main/doc/integration-branch-process.md#master-mr-process-summary) for this process, but we realized that following the original plan would not allow us to meet our goal of releasing of the feature in GitLab 16.0.\n\n### Merging the integration branch MR without breaking it up\nDuring the development of the Remote Development feature, our team faced several challenges that led us to adopt a new approach for merging the integration branch into the master. First, as part of our [velocity-based XP/Scrum style process](https://handbook.gitlab.com/handbook/engineering/devops/dev/create/remote-development/#-remote-development-iteration-planning), we realized that meeting the 16.0 release goal would require us to cut scope. A velocity report, \"[Velocity-based agile planning report](https://gitlab.com/gitlab-org/gitlab/-/merge_requests/118436),\" highlighted that breaking down and reviewing individual MRs would take too long, considering the impending due date and the likelihood of last-minute scope additions.\n\nSecond, we [made the decision](https://gitlab.com/gitlab-org/gitlab/-/issues/398227#note_1361192858) to release workspaces as a **beta feature for public projects** for customers in [GitLab 16.0](/releases/2023/05/22/gitlab-16-0-released/#remote-development-workspaces-available-in-beta-for-public-projects). This approach reduced the complexity of the rollout plan and allowed us to get valuable feedback earlier, but required us to enable the feature by default earlier than planned. To align with this decision, we determined that merging the integration branch after review was the best course of action. An announcement was made to explain the change in plan, and we set specific timelines for the review process to ensure smooth coordination.\n\n> Hello Reviewers/Maintainers 👋 We have opened up a Zoom room through all of next week as an easy sync place for us all to collaborate and triage questions. As the MR is quite large, it might be overwhelming to determine where to begin. To help, we will aim to furnish a summary of what we have included, such as two new database tables and a couple of GraphQL/REST APIs. We will also be available through the week in the Zoom room and without it being too prescriptive of a approach, I would suggest we do a sync walkthrough of the MR first and then kick off the reviews.\n\nAddressing the concerns about risk, team members discussed the challenges and potential solutions. While there were apprehensions, we were confident in the overall quality of the feature. A disciplined plan for merging MRs was initially considered, but based on our velocity metrics, it was evident that meeting the public beta release goal required a new strategy.\n\nDespite the deviations from our usual practices, we acknowledged the urgency to deliver the initial release on time. The decision was not taken lightly, and we ensured that the merge had extensive [test coverage](https://docs.gitlab.com/ee/ci/testing/test_coverage_visualization.html) and [feature flags](https://docs.gitlab.com/ee/operations/feature_flags.html) in place to address any potential issues. We accepted that some aspects would be overlooked in the initial MR review cycle, but we committed to addressing them in subsequent iterations.\n\n### Keeping the pipeline green and stable for the merge\nTo ensure the successful merge of the integration branch containing the Remote Development feature, our team made significant efforts to keep the pipeline green and stable. As the MR was quite large and contained critical functionality, it was crucial to maintain a high level of quality and reduce the risk of introducing regressions.\n\nTo address these challenges, the team adopted a disciplined approach to [CI/CD](https://about.gitlab.com/topics/ci-cd/). Throughout the development process, CI pipelines were carefully monitored, and any failing tests or issues were promptly addressed. The team conducted rigorous testing and code reviews to identify and fix potential bugs and ensure that the changes did not negatively impact the existing functionality of the codebase.\n\nAdditionally, extensive test coverage was put in place to ensure that the new feature worked as expected and did not cause unintended side effects. The team utilized GitLab's [test coverage visualization](https://docs.gitlab.com/ee/ci/testing/test_coverage_visualization.html) capabilities to track the extent of test coverage and identify areas that required additional testing.\n\n![PIPE](https://about.gitlab.com/images/blogimages/remote-development/PIPE.png){: .shadow.medium}\n\n## The merging process\nAs part of the Remote Development team, we took a strategic approach to the merging process. We identified three categories of follow-up tasks that needed to be addressed after the release:\n\n1. **To-dos:** This category encompassed follow-up issues that required further attention.\n2. **Disabled linting rules:** Any issues related to disabled linting rules were included in this category.\n3. **Follow-up from review:** Non-blocking concerns raised during the review process were categorized here.\n\nTo manage this process effectively, we organized these categories into [child epics](https://docs.gitlab.com/ee/user/group/epics/manage_epics.html#multi-level-child-epics) under the main epic representing the merging effort.\n\n1. Child epic for [to-do follow-up issues](https://gitlab.com/groups/gitlab-org/-/epics/10472)\n2. Child epic for [disabled linting rules follow-up issues](https://gitlab.com/groups/gitlab-org/-/epics/10473)\n3. Child epic for [follow-up issues from review](https://gitlab.com/groups/gitlab-org/-/epics/10474)\n\n\n## Reviewer resources\nDuring the integration branch merge process for the Remote Development feature, we ensured a smooth and collaborative review experience for all involved. To facilitate this, we set up the following resources and documented the information in GitLab's issue, epic, and MR reviews for better persistence and traceability:\n\n1. **Dedicated Slack channel:** We had a Slack channel that served as our primary hub for coordinating reviews and resolving any blockers that arose during the process. The discussions, decisions, and important points discussed in this channel were documented in the related GitLab issues and epics. This approach enabled us to maintain a historical record of the conversations for to refer back to in the future.\n2. **General Slack channel:** For non-urgent or non-blocking questions and discussions, reviewers could use the a general Slack channel. Similar to the dedicated channel, we documented the relevant information from this channel in the corresponding issues and MR reviews in GitLab.\n3. **Addressing urgent issues:** When urgent issues required immediate attention, reviewers could directly address our technical leads [Vishal Tak](https://gitlab.com/vtak) and/or [Chad Woolley](https://gitlab.com/cwoolley-gitlab) in their Slack messages. However, we kindly requested that [direct messages were avoided](https://handbook.gitlab.com/handbook/communication/#avoid-direct-messages) to promote open collaboration. The resolutions to these urgent issues were documented in the corresponding GitLab issues or MR discussions.\n4. **Zoom collaboration room:** The collaborative sessions held in the open Zoom room were not only beneficial for real-time discussions but also for fostering a collaborative environment. After each session, we summarized the key points and decisions made during the meeting in the associated GitLab issue or MR, making sure all important outcomes were captured and accessible to the team.\n\nThroughout the review process, we were committed to maintaining a seamless and well-documented workflow. By capturing all relevant information in GitLab issues, epics, and MR reviews, we ensured that the knowledge was persistently available, and future team members could easily understand the context and decisions made during the integration process.\n\n## Application security review\nDuring the application security review process, we focused on providing a secure and reliable Remote Development feature for our users. Here are the key resources and updates related to the application security review:\n\n1. **Main application security review issue:** The main application security review issue served as the central hub for tracking security-related considerations. You can find the defined process we followed [here](https://handbook.gitlab.com/handbook/security/product-security/application-security/appsec-reviews/).\n2. **Application security review comment:** The application security review issue contained a comment indicating that the merge was not blocked unless there were severe issues that could impact production. \"In order to maintain a smooth merge process, we do not block MRs from being merged unless we identify severe issues that could prevent the feature from going into production, such as S1 or S2 level problems. If you are aware of any design flaws or concerns that might qualify as such issues, please bring them to our attention. We can review them together and address any questions or concerns that arise. Let's work collaboratively to find an approach that works for both parties. 👍\"\n3. **Engineering perspective:** For managing the application security review process from an engineering team perspective, we had a dedicated issue, which is kept confidential for security reasons.\n4. **Security and authentication matters:** All security and authentication concerns pertaining to the Beta release were documented within the [`Remote Development Beta -Auth` epic](https://gitlab.com/groups/gitlab-org/-/epics/10377). As of April 30, 2023, we are delighted to announce that **no known issues or obstacles were found that would impede the merge**. This represents a significant accomplishment, considering the intricate nature of this new feature.\n5. **Initial question raised:** During the application security review, one initial question was raised, and we promptly addressed it. You can track the issue and our response [here](https://gitlab.com/gitlab-org/gitlab/-/issues/409317).\n\n## Database review\nTo ensure the reliability and efficiency of the Remote Development feature, we sought guidance from the database reviewer. Although the team had not conducted a thorough self-review, we were fully prepared to address any blocking issues raised during the review process. Our references for the review were:\n\n- [Database review documentation](https://docs.gitlab.com/ee/development/database_review.html)\n- [Database reviewer guidelines](https://docs.gitlab.com/ee/development/database/database_reviewer_guidelines.html)\n\nAs an example, during the database migration review, a discussion arose between [Alper Akgun](https://gitlab.com/a_akgun) and Chad, regarding the efficient ordering of columns in the workspaces table. Alper initially suggested placing integer values at the beginning of the table based on relevant documentation.\n\nChad questioned the benefit of this suggestion, pointing out that the specific integer field, `max_hours_before_termination`, would still be padded with empty bytes even if moved to the front, due to its current position between two text fields.\n\nAlper proposed an alternative approach, emphasizing that organizing variable-sized fields (such as `text`, `varchar`, `arrays`, `json`, `jsonb`) at the end of the table could be sufficient for the workspaces table.\n\nUltimately, Chad took the initiative to implement the changes, moving all variable length fields to the end of the table, and documented the discussion as a comment to address review suggestions.\n\nWith this collaborative effort, the workspaces table was efficiently optimized, and the team gained valuable insights into database column ordering strategies.\n\n![DB](https://about.gitlab.com/images/blogimages/remote-development/DB.png){: .shadow.medium}\n\n## Ruby code review\nDuring the Ruby code review phase, we followed a meticulous approach by conducting a comprehensive self-review of every line of code. Our goal was to ensure the highest code quality and address any potential issues identified by the reviewers effectively.\n\nTo ensure clarity, it's important to clarify that the Ruby code review primarily focused on backend changes and server-side improvements. This included optimizing performance, enhancing functionalities, and refining the overall codebase to deliver a seamless user experience.\n\nFor the code review process, we referred to the [Code review documentation](https://docs.gitlab.com/ee/development/code_review.html), a valuable resource that guided us in maintaining industry best practices and adhering to the GitLab community's coding standards.\n\n### Example: Enhance error messages for unavailable features\nAs an example during the code review, we addressed an essential aspect of the workspace method, focusing on how we handle scenarios related to the `remote_development_feature_flag` and the `remote_development` licensed feature. The primary objective was to enhance the error messages presented to users when these features are not available.\n\nInitially, the code employed identical error messages for both cases, making it less clear to users whether the issue was due to a missing license or a disabled feature flag. This ambiguity could lead to confusion and hinder the user experience.\n\n#### The suggested improvement\nDuring the review, one of our maintainers, [Peter Leitzen](https://gitlab.com/splattael), raised an important question: \"Are we OK with having only a single error message for both cases (missing license and missing feature flag)?\"\n\nRecognizing the importance of clear communication, Chad proposed enhancing the error messages to provide distinct descriptions for each case. This improvement aimed to empower users by precisely conveying the reason behind the unavailability of certain features.\n\n#### The revised implementation\nFollowing Chad's suggestion, the code underwent the following changes:\n\n```ruby\nunless ::Feature.enabled?(:remote_development_feature_flag)\n  # TODO: Could have `included Gitlab::Graphql::Authorize::AuthorizeResource` and then use\n  #       raise_resource_not_available_error!, but didn't want to take the risk to mix that into\n  #       the root query type\n  raise ::Gitlab::Graphql::Errors::ResourceNotAvailable,\n    \"'remote_development_feature_flag' feature flag is disabled\"\nend\n\nunless License.feature_available?(:remote_development)\n  # TODO: Could have `included Gitlab::Graphql::Authorize::AuthorizeResource` and then use\n  #       raise_resource_not_available_error!, but didn't want to take the risk to mix that into\n  #       the root query type\n  raise ::Gitlab::Graphql::Errors::ResourceNotAvailable,\n    \"'remote_development' licensed feature is not available\"\nend\n\nraise_resource_not_available_error!('Feature is not available') unless current_user&.can?(:read_workspace)\n```\n\n#### The value of distinct error messages\nBy implementing distinct and descriptive error messages, we reinforce our commitment to user-centric development. Users interacting with our system will receive accurate feedback, helping them navigate potential roadblocks effectively. This enhancement not only improves the user experience but also streamlines troubleshooting and support processes.\n\nThis code review example highlights the significance of concise and informative error messages in delivering a top-notch user experience within the GitLab ecosystem. Our team's collaborative efforts ensure that users can confidently interact with our platform, knowing they'll receive clear and helpful error messages when needed.\n\n![BE1](https://about.gitlab.com/images/blogimages/remote-development/BE1.png){: .shadow.medium}\n\n### Example: Improving performance and addressing N+1 issues in WorkspaceType\nIn a recent code review, our team focused on optimizing the WorkspaceType and addressing potential N+1 query problems. The discussion involved two key contributors, [Laura Montemayor](https://gitlab.com/lauraX) and Chad, who worked together to enhance the performance of the codebase.\n\n#### Identifying the performance concerns\nDuring the review, Laura raised a performance concern regarding the possibility of N+1 queries in the WorkspaceType resolver. She suggested that preloading certain associations could be beneficial to avoid this common performance issue.\n\n#### A separate issue for N+1 control\nChad took prompt action and created a separate issue specifically aimed at resolving the N+1 query problems. The new issue, titled \"Address review feedback: Resolve N+1 issues,\" would address the concerns raised by Laura and implement the necessary preloading.\n\n#### Evaluating the potential N+1 impact\nChad provided insightful information about the low risk of real N+1 impact from two particular fields in the current implementation. He elaborated on how the queries for user and agent associations would largely be cache hits due to scoping and usage patterns. Chad diligently examined the cache hits happening in development, confirming the potential optimization.\n\nHere's a code snippet from the initial implementation:\n\n```ruby\n# Initial Implementation\nclass WorkspaceType \u003C BaseType\n  field :user, ::Types::UserType,\n    description: \"User associated with this workspace\",\n    null: true\n\n  field :agent, ::Types::AgentType,\n    description: \"Agent associated with this workspace\",\n    null: true\n\n  # Resolver for the user association\n  def user\n    object.user\n  end\n\n  # Resolver for the agent association\n  def agent\n    object.agent\n  end\nend\n```\n\n#### Treating performance as a priority\nBoth contributors acknowledged the significance of addressing the performance concern, with Laura emphasizing its importance. They agreed to prioritize the separate issue dedicated to resolving the N+1 queries and ensuring proper test coverage.\n\nHere's a code snippet from the revised implementation:\n\n```ruby\n# Revised Implementation with Preloading\nclass WorkspaceType \u003C BaseType\n  field :user, ::Types::UserType,\n    description: \"User associated with this workspace\",\n    null: true\n\n  field :agent, ::Types::AgentType,\n    description: \"Agent associated with this workspace\",\n    null: true\n\n  # Resolver for the user association with preloading\n  def user\n    ::Dataloader.for(::User).load(object.user_id)\n  end\n\n  # Resolver for the agent association with preloading\n  def agent\n    ::Dataloader.for(::Agent).load(object.agent_id)\n  end\nend\n```\n\n#### Considering future usage\nChad expressed excitement about the possibility of the new feature gaining significant usage. He humorously stated that encountering enough legitimate traffic on workspaces to trigger any performance impact would be a delightful problem to have, as it would indicate a growing user base.\n\n#### Collaboration and performance improvement\nThe code review exemplifies the collaborative and proactive approach of our team in optimizing the WorkspaceType. The team's dedication to addressing performance concerns ensures that our codebase remains performant and efficient, even as our user base grows.\n\n![BE2](https://about.gitlab.com/images/blogimages/remote-development/BE2.png){: .shadow.medium}\n\n## Frontend code review\nThe frontend code review process was managed by our resident `Create: IDE` frontend maintainers, [Paul Slaughter](https://gitlab.com/pslaughter) and [Enrique Alcátara](https://gitlab.com/ealcantara). Additionally, a significant portion of the new frontend UI code had already undergone separate reviews and was merged to master, contributing to the overall quality of the Remote Development feature.\n\n### Example: Collaborative code improvement for ApolloCache Mutators\nPaul started a thread on an old version of the diff related to `ee/spec/frontend/remote_development/pages/create_spec.js``. The code snippet in question involved creating a mock Apollo instance and writing queries to the cache.\n\n#### The initial implementation\nInitially, the code involved writing to the cache twice, which raised concerns among the maintainers, Paul and Enrique. Paul pointed out that the duplicate write was unintentional and wondered if the writeQuery was even necessary, given the removal of @client directives. However, he also acknowledged the need to test that the created workspace was added to the ApolloCache.\n\n```javascript\n// Initial Implementation\nconst buildMockApollo = () => {\n  // ... Other mock setup ...\n\n  // Initial writeQuery for userWorkspacesQuery\n  mockApollo.clients.defaultClient.cache.writeQuery({\n    query: userWorkspacesQuery,\n    data: USER_WORKSPACES_QUERY_EMPTY_RESULT.data,\n  });\n\n  // ... Other mock setup ...\n};\n```\n\n#### Identifying a potential issue\nEnrique agreed that the duplicate write was unintentional and probably introduced during a rebase. He explained that pre-populating the cache with a user workspaces query empty result was essential for the mutator to have a place to add the workspace. However, he encountered difficulties in making the workaround work effectively in unit tests.\n\n#### Resolving the issue\nPaul highlighted the significance of pre-populating the cache with the user workspaces query empty result. He suggested leaving a comment to explain the necessity of the initial writeQuery, as it would be implicitly coupled to future writeQuery operations.\n\n```javascript\n// Resolving the Issue - Leaving a Comment\n// Pre-populate the cache with user workspaces query empty result to provide a place\n// for the mutator to add the Workspace later. This is needed for both test and production environments.\nmockApollo.clients.defaultClient.cache.writeQuery({\n  query: userWorkspacesQuery,\n  data: USER_WORKSPACES_QUERY_EMPTY_RESULT.data,\n});\n```\n\nHowever, upon further investigation, Paul discovered that the writeQuery might not be needed, and the issue might be a symptom of an underlying problem. He decided to open a separate thread to address this concern and indicated that he would work on a separate MR to handle it.\n\n```javascript\n// Resolving the Issue - Opening a Separate Thread and MR\n// Open a separate thread to discuss potential underlying issues.\n// Plan to work on a separate MR to handle it.\n// Stay tuned for updates!\n```\n\n![FE](https://about.gitlab.com/images/blogimages/remote-development/FE.png){: .shadow.medium}\n\n## What we learned\nAs part of the Remote Development team, we faced the challenge of merging the Remote Development Rails monolith integration branch to meet our ambitious release goal. We adapted to last-minute pivots and focused on minimizing risks during the review process. The successful merge brought us one step closer to benefiting GitLab users worldwide. We acknowledged areas for improvement and remained committed to refining the feature's quality. Our journey reflects our dedication to delivering results, embracing change, and pushing boundaries in the DevOps community. The release of the Remote Development feature in GitLab 16.0 is a significant milestone for GitLab, and we continue to iterate and grow, providing innovative solutions for developers worldwide.\n\nAn outcome of this process was an ongoing conversation to propose a [simplified review process for greenfield features](https://gitlab.com/gitlab-org/gitlab/-/merge_requests/125117). Through this proposal, we aim to distill the lessons we learned during this experience and provide guidance to future teams facing similar challenges.\n\n## What is next for Remote Development?\nAfter the merge of the MR, several changes were implemented:\n- The first production tests were conducted to ensure the stability and functionality of the merged code.\n- Collaboration took place between the Dev Evangelism and Technical Marketing teams, focusing on [creating content](https://gitlab.com/groups/gitlab-com/marketing/developer-relations/-/epics/190). This collaboration aimed to troubleshoot any issues that arose during the merge.\n- Feedback from the community was taken into account, and changes were made to address the concerns raised. This feedback was incorporated into an [issue](https://gitlab.com/gitlab-org/gitlab/-/issues/410031) and influenced the overall roadmap and direction of the project.\n\nDo you want to [contribute to GitLab](/community/contribute/)? 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Oregan",{"template":697},"BlogAuthor",{"name":18,"config":699},{"headshot":700,"ctfId":701},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749659853/Blog/Author%20Headshots/oregand-headshot.png","oregand",{},"/en-us/blog/authors/david-oregan",{},"en-us/blog/authors/david-oregan","CX5gLc3Gs5FrmvpMNVkBtC5zRi3vj8l3wJGnW0iSa6Y",[708,720,732],{"content":709,"config":718},{"title":710,"description":711,"authors":712,"heroImage":714,"date":715,"category":9,"tags":716,"body":717},"How IIT Bombay students are coding the future with GitLab","At GitLab, we often talk about how software accelerates innovation. But sometimes, you have to step away from the Zoom calls and stand in a crowded university hall to remember why we do this.",[713],"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",[265,614,28],"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":719,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":721,"config":730},{"title":722,"description":723,"authors":724,"heroImage":725,"date":726,"category":9,"tags":727,"body":729},"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.",[713],"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",[614,265,728],"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":731,"featured":31,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":733,"config":745},{"category":9,"tags":734,"body":736,"date":737,"updatedDate":738,"heroImage":739,"authors":740,"title":743,"description":744},[23,735,112],"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",[741,742],"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":31,"template":13,"slug":746},"migration-from-azure-devops-to-gitlab",{"promotions":748},[749,763,774],{"id":750,"categories":751,"header":753,"text":754,"button":755,"image":760},"ai-modernization",[752],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":756,"config":757},"Get your AI maturity score",{"href":758,"dataGaName":759,"dataGaLocation":247},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":761},{"src":762},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":764,"categories":765,"header":766,"text":754,"button":767,"image":771},"devops-modernization",[728,39],"Are you just managing tools or shipping innovation?",{"text":768,"config":769},"Get your DevOps maturity score",{"href":770,"dataGaName":759,"dataGaLocation":247},"/assessments/devops-modernization-assessment/",{"config":772},{"src":773},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":775,"categories":776,"header":778,"text":754,"button":779,"image":783},"security-modernization",[777],"security","Are you trading speed for security?",{"text":780,"config":781},"Get your security maturity score",{"href":782,"dataGaName":759,"dataGaLocation":247},"/assessments/security-modernization-assessment/",{"config":784},{"src":785},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":787,"blurb":788,"button":789,"secondaryButton":794},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":790,"config":791},"Get your free trial",{"href":792,"dataGaName":54,"dataGaLocation":793},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":499,"config":795},{"href":58,"dataGaName":59,"dataGaLocation":793},1772652083124]