[{"data":1,"prerenderedAt":795},["ShallowReactive",2],{"/en-us/blog/the-trouble-with-technical-interviews":3,"navigation-en-us":38,"banner-en-us":438,"footer-en-us":448,"blog-post-authors-en-us-Sara Kassabian":690,"blog-related-posts-en-us-the-trouble-with-technical-interviews":704,"assessment-promotions-en-us":746,"next-steps-en-us":785},{"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":34,"tagSlugs":35,"__hash__":37},"blogPosts/en-us/blog/the-trouble-with-technical-interviews.yml","The Trouble With Technical Interviews",[7],"sara-kassabian",null,"engineering",{"slug":11,"featured":12,"template":13},"the-trouble-with-technical-interviews",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"The trouble with technical interviews? They aren't like the job you're interviewing for","Forget the coding exercise. Here's how to create realistic scenarios for engineering candidates in technical interviews.",[18],"Sara Kassabian","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749681148/Blog/Hero%20Images/nycbrooklyn.jpg","2020-03-19","\n\nInterviewing for an engineering job in the tech world can mean [you’ll be asked all sorts of questions](https://stackify.com/devops-interview-questions/). Sometimes, the job interview questions can be pretty straightforward: “Tell me about a time that you have implemented an effective monitoring solution for a production system.” Other times, the questions are impossible to answer and designed to spark your creativity: “How many windows are in New York City?” After passing the initial interview, the applicant or candidate graduates to the next tier of interviewing: The often-dreaded technical interview.\n\n## What is a technical interview?\n\nA technical interview is one that is conducted to gauge a candidate’s skill level for positions in the information technology, engineering, and science fields. It may also determine how much a candidate knows in more niche areas of a company, such as marketing, sales, and HR.\n\n## How to prepare for a technical Interviews\n\nProspective engineers often face a challenge when it comes to preparing for the technical interview, largely because there is no playbook for how companies set them up technical. It’s unclear whether to prepare by memorizing many different topics, or focusing on specific projects. Is it better to practice with a computer or a peer engineer? There are an overwhelming number of resources available online, but with little clarity as to what the standard is for a technical interview and little guidance from the company on what to expect, most of the time engineers start technical interviews in the dark.\n\nInconsistencies in the technical interview process isn’t just a job candidate problem. In fact, many companies struggle to set up a technical interview process that is effective, equitable, and allows the hiring manager to compare candidates. The problem with technical interviewing compounds when a company is experiencing rapid growth.\n\n## What are the challenges of conducting technical interviews at a growing company\n\n\"Imagine you had a hiring target of doubling your team size and all your interviews are conducted remotely. Welcome to GitLab,\" says Clement Ho, [frontend engineering manager on the Monitor: Health team](/company/team/#ClemMakesApps) at GitLab.\n\n![Hiring chart shows GitLab more than doubled the number of hires from around 400 in 2019 to roughly 1300 by end of 2020](https://about.gitlab.com/images/blogimages/fei_hiringchart.jpg){: .shadow.medium.center}\n\nGitLab more than doubled the number of hires from around 400 in 2019 to roughly 1300 by end of 2020.\n\n\nWe identifed three core challenges with orchestrating technical interviews as GitLab grows.\n\n1. We didn't have enough interviewers for the pipeline of candidates.\n2. Our technical interviewing process was inconsistent and even a little biased.\n3. It was difficult to measure whether or not we were raising the bar.\n\n\"And by raising the bar, I mean making sure each candidate that joins the team makes the team better,\" says Clement.\n\nThese problems are by no means unique to GitLab. Any engineering company that is scaling rapidly will encounter some growing pains when it comes to hiring, and many will end up falling back on some of the typical models for conducting technical interviews.\n\n## The typical technical interview methods\n\nDuring his talk, [\"Using GitLab to Power our Frontend Technical Interviews\" at GitLab Commit San Francisco](https://www.youtube.com/watch?v=jSbCt8b_4ug), Clement explained the four different techniques that are often employed in technical interviews. Each method comes with advantages and disadvantages from the perspective of the hiring manager.\n\n## What are good technical interview questions\n\nA good technical interview needs to be about more than practical skills – it’s about the whole package.A candidate should possess the ideal coding skills but also be a team and culture fit and be able to discuss developer topics efficiently. A technical interview should include both situational interview questions and a skills assessment to discern a candidate’s potential.\n\nThe types of questions to ask can concern a candidate’s technical abilities and background, their career journey so far, and queries specific to the team or company.\n\n## Types of questions asked during a technical interview and their purpose\nEven though employers have already reviewed your resume and cover letter, they will want you to flesh that out during the interview to learn more about how you attained those skills. In order to assess your level of experience, they will likely also ask you to provide concrete examples from prior jobs.\nMake sure you are prepared—do your research on the company and the type of questions you may be potentially asked. This will help build your confidence level and reduce any nervousness you might feel. It’s also an opportunity for you to set yourself apart from other candidates by showcasing your knowledge and additional skills you can bring to the job.\nIt is important to be honest about your skill set because that is something employers value. You may find the company will be willing to hire someone who is transparent about the areas where they need to improve and where they’d like to gain more skills.\n\nExamples of common questions to expect in a technical interview:\n\n- What coding languages are you most familiar with?\n- What is your experience with Kubernetes with a specific example?\n- What’s the purpose of continuous integration in an automated build?\n- How have your previous technical roles prepared you for this job?\n- Tell me about a time when you received an unexpected assignment: how did you react, and what did the experience teach you?\n- Please provide more details about your educational background and how it prepared you for this position.\n- How did you go about teaching yourself a necessary technical skill while you were working on a project?\n- What are your strengths, and where do you think you need to improve your skills?\n- Do you have any technical certifications?\n- Please detail the work you did on the project you are most proud of.\n- What are your favorite and least favorite tech tools, and why?\n- What are the pros/cons of working in an agile environment?\n\n### Sample technical interview questions and answers\n- **How do you stay current with your technical knowledge and skills?** It’s a good idea to list online content you use to educate yourself, as well as tutorials and conferences you have attended to gain more knowledge. Perhaps you have also worked closely with vendors or attended sessions to learn about new product features.\n- **How do you troubleshoot technical problems?** Discuss the steps you take when you are answering a question. This will give employers a sense of how you problem-solve, and it provides a good overview of how well you understand the relevant concepts. Even if you don’t answer a question correctly, it will show the interviewer your process and reasoning, which are also important. You can mention resources you use, such as GitLab and Stack Exchange, as well as the developer community and any publications you read for advice.\n- **What is your level of experience with the software programs mentioned on your resume?** Describe how many years you have used the tools, your impressions of them, and bring up the companies you used them at, with specific examples.\n- **What programming language are you most proficient in?** You should discuss how you have become proficient in this language and why it is the one you are most comfortable using. You can also cite other languages you are familiar with.\n- **Describe a time you made an error and how you resolved it.** Don’t use an example of an egregious error since that may put you in a negative light. Be sure to emphasize that you took responsibility and acted with integrity, and did whatever it took to resolve the issue.\n\n## What are some soft skills and coding skills to highlight in a technical interview\n\nA technical interview assesses your technical expertise, coding skills, and ability to fit into a team. However, soft skills are just as important and often aid in the development of more technical skills – particularly in a team setting.\n\nAs the technical interview progresses, be prepared to tackle some questions about soft skills like:\n\n- **Communication skills:** How does the candidate contribute to group discussions, confront problems, or give and receive feedback?\n- **Organizational skills:** What are the ways in which the candidate provides visibility into their work processes and their methods of staying on task?\n- **Collaboration skills:** Are they interested in helping their teammates? What do they think are the keys to successfully navigating a team project? How have they collaborated on past projects?\n- **Creative problem solving:** How do they work through a problem in a project? Do they use both analytical and creative thinking to come up with solutions?\n\n### How to prepare for verbal technical questions\n\nThere are countless articles online that try to prepare job candidates for a verbal technical interview, but whether this method truly effective for evaluating the technical competency of a software engineer is debatable.\n\nIn the typical scenario, the interviewer asks the candidate to describe a technical concept and tries to measure their fluency in said concept based on the quality of the conversation.\n\nThe advantage of this method is that the interviewer can understand how the candidate communicates, which is of particular importance when the engineering team is all-remote, as is the case at GitLab. The drawback? Being a good communicator does not necessarily mean the candidate knows how to code effectively.\n\n\"So I've interviewed candidates that could talk the talk, but they couldn't really write the code,” says Clement. \"And that's not a great situation for an engineer to join GitLab.\" Clement’s team has moved away from using verbal technical questions as a method for evaluating candidates.\n\n### Live coding exercises\n\nOne of the more popular methods for evaluating engineers is through live coding. While it allows the evaluator to see how engineering candidates answer data structure questions, it also has its disadvantages.\n\nA key advantage of live coding data structures is that it offers a fairly consistent measurement and evaluation.\n\n\"I can talk to another manager or another interviewer and be able to communicate, 'Hey, this person wasn't able to do a linked list, they got stuck here. They weren't able to understand a runtime efficiency here.' So it's pretty consistent,\" says Clement.\n\nBut the ability to create data structures is not always the best indicator of ability. Oftentimes engineers with a very traditional background or recent graduates will shine here, but someone who is more senior and able to do a lot of great things, but is perhaps not as brushed up on data structures, may struggle.\n\nLive coding interviews probably aren’t going anywhere fast, but the pitfalls of this method are well documented by engineers and hiring managers. Brennan Moore, a product engineer in New York City, explains why he does not conduct live coding interviews when evaluating a prospective candidate:\n\n> \"Much like the SAT when applying for college, live coding is a structured test. I didn’t go to a school that trained me to do live coding, and so will probably fail the test. As I’ve experienced it, live coding isn’t the meritocratic space that it pretends to be. Live coding interviews weed out the people who are good at live coding interviews,\" says Brennan in his [blog post](https://www.zamiang.com/post/why-i-don-t-do-live-coding-interviews).\n\nAt GitLab, we found that live coding exercises don't accurately represent engineering capability. Oftentimes, a recent computer science graduate will outperform a more senior candidate with a lot of valuable experience. In summary, live coding exercises will often disadvantage more senior candidates, people who are nervous in high-pressure situations (read: everyone), and advantages more junior engineers or people who have practiced live coding.\n\n### Digital prompt\n\nA third common method for evaluating candidates is to ask the engineer to code a UI using an online editor while on screen share with the evaluator.\n\nThe advantage of this method is that it allows the evaluator to observe how a candidate builds. The drawbacks here are similar to those with live coding. First, the engineer is under pressure to build while the evaluator watches on, making it a nerve-wracking situation. The other drawbacks come from an evaluation perspective: It is challenging to measure the effectiveness of this method and it is hard to compare between candidates.\n\n### Take-home project\n\nAny engineer (or writer, for that matter) can tell you, the supplemental take-home project is a very common ask when going through an interview process. The advantage here for us is that this assignment closely mimics the reality of building environments while working remotely at GitLab.\n\nBut this task comes with major drawbacks, mainly that it disadvantages candidates who may not have the time or capacity to complete the project.\n\n\"... imagine a scenario where you're a single parent and you have kids; you may not have as much opportunity to take dedicated time, a couple of hours after work to really focus on a take-home project compared to someone from a more privileged background,\" says Clement. \"They might be able to dedicate and output something better.\"\n\n[Diversity and inclusion is a core value](https://handbook.gitlab.com/handbook/company/culture/inclusion/) for GitLab, and anything that disadvantages candidates from underrepresented groups is not inclusive, and therefore suboptimal for evaluating candidates based on their engineering abilities.\n\n## What are they looking for during a technical interview?\n\nCompanies want candidates who can discuss the industry in the context of the job they are applying for. Be prepared to discuss examples of your work. Many will want to hear about soft skills, too—your ability to communicate and collaborate and work with others to problem-solve issues.\n\nThey will also want to see how passionate and enthusiastic you are and whether you have the self-motivation to not only do the job but take the initiative to do more than what you’re tasked with.\n\nAlso, interviewers will want to see whether candidates have the desire to increase their technical knowledge.\n\n## What are some online preparation tools and resources for technical interviews\n\n- Indeed offers a career guide to [help prepare for](https://www.indeed.com/career-advice/interviewing/what-is-a-technical-interview) a technical interview.\n- Interview Kickstart has several [webinars](https://learn.interviewkickstart.com/) to help prepare engineers for interviews.\n- Udemy offers a course in [Technical Interview Skills](https://www.udemy.com/course/technical-interview-skills/?utm_source=bing&utm_medium=udemyads&utm_campaign=BG-DSA_Webindex_la.EN_cc.BE&utm_content=deal4584&utm_term=_._ag_1222657343651662_._ad__._kw_udemy_._de_c_._dm__._pl__._ti_dat-2328215871879260%3Aloc-190_._li_103429_._pd__._&matchtype=b&msclkid=9f5132d9c84c17b02f7951a4f46279d6).\n- [Codecademy](https://www.codecademy.com/learn/technical-interview-practice-python?utm_id=t_kwd-79027793284383:loc-190:ag_1264438993811076:cp_370314525:n_o:d_c&msclkid=550de1275d811b2cfc0f82592b6d9626&utm_source=bing&utm_medium=cpc&utm_campaign=US%20Language%3A%20Pro%20-%20Broad&utm_term=%2Btechnical%20%2Binterview%20%2Bprep&utm_content=technical%20interview%20practice) also offers a course called - Technical Interview Practice with Python.\n- Here are some more general [interview tips](https://www.roberthalf.com/blog/job-interview-tips/interview-tips-to-help-you-land-the-job-you-want) that are applicable to all candidates.\n\n## Meaningful questions to ask the interviewer\n\nCandidates will also be given a chance to ask questions they might have to learn more about the company. This is a great opportunity to gain more insight into how the company operates, what its philosophy is, and its vision for the long term.\n\nIt’s also a good way to glean how the company views its IT team. If you don’t ask questions, that could give the impression you are unprepared or not terribly interested in the job.\n\nQuestions to ask can include:\n\n- What does a typical day looks like in this role?\n- Are there opportunities for training and further advancement?\n- What software development methodology do you use?\n- What are your code review practices?\n- Do you have on-call rotations? If so, how long is one rotation?\n- What are the responsibilities of the person on call?\n- Please provide more details about the team I will be working with, such as how many people are there, what their roles are, what the hierarchy is, and what areas of improvement you would like to see on the team.\n\n## The new way\n\nWhile each method for conducting a technical interview comes with advantages, there are also numerous disadvantages when it comes to conducting an effective and measurable evaluation and creating an equitable interview process. Under the guidance of Clement, the [Monitor:Health team](https://handbook.gitlab.com/handbook/engineering/monitoring/) decided to interview frontend engineers in an entirely new way using GitLab.\n\nNow let's take a deep dive into the nuts and bolts of reinventing the technical interview for frontend engineers at GitLab. Just wondering about the key takeaways? [Skip ahead](#why-this-new-model-for-technical-interviews-is-better). As we continue to iterate on a more effective and measurable technical interview process, we hope this inspires other engineering organizations to rethink theirs and share learnings with us.\n\nOur first step: Standardize the interview process.\n\n### Fixing an MR on a test project\n\nThe team standardized the interview process by creating an open source test project, called `project-seeder`, which seeds projects to different candidates using a GitLab Bot. Candidates are assigned a merge request to troubleshoot in the project created for the technical interview. The `project-seeder` is powered by the GitLab Bot so the interviewer doesn't have to worry about API keys, and works in four steps:\n\n1. Exports the template project\n2. Imports template project\n3. Adds users with expiration\n4. Triggers pipeline for candidate to review MR\n\nThe candidate is sent an email with a link to the MR the candidate is assigned to fix as part of the technical interview.\n\n### Standardize the evaluation rubric\n\nThe team also created a standardized rubric for how the candidate's performance on a technical interview is evaluated.\n\n\"We don't want to be in a situation where unconscious bias or bias of one candidate over another plays a part because of our preconceived notions,\" says Clement.\n\nCreating a rubric that looks at multiple categories allows the evaluator to look at the performance of the candidate from a more holistic perspective, as opposed to looking at a candidate's performance on one technology.\n\nThe team created a [Periscope dashboard](https://handbook.gitlab.com/handbook/engineering/frontend/interview-metrics/) to create a feedback loop between the candidates and evaluators to identify opportunities for improvement in the technical interviewing process.\n\n![Frontend team used Periscrope to collect feedback from candidates who participate in technical interviews](https://about.gitlab.com/images/blogimages/fei_periscopedashboard.jpg){: .shadow.medium.center}\n\nThe frontend engineering team used Periscope to collect feedback from candidates who participate in technical interviews.\n\n\n## Demoing the technical interview\n\n### Inside the technical interview project\n\nClement created a sample project to demonstrate how we use GitLab to power our technical interviews.\n\nIn the [gl-commit-example](https://gitlab.com/gl-commit-example) group, there is a subgroup with all the interview projects we are seeding to the imaginary candidates, a template, and a project seeder.\n\n![A screenshot of the sample project shows the interview project's subgroup, template, and project seeder application](https://about.gitlab.com/images/blogimages/fei_interviewproject.jpg){: .shadow.medium.center}\n\nThe interview project's subgroup, template, and project seeder application lives inside the sample project for the technical interview.\n\n\n[Inside the template](https://gitlab.com/gl-commit-example/template), there are GitLab pages and the [interview test merge request](https://gitlab.com/gl-commit-example/template/-/merge_requests/1).\n\nThe assignment here is pretty simple. The candidate needs to update the website to say \"Hello GitLab Commit SF,\" but in order to accomplish this, the candidate will need to fix the failing pipeline.\n\n### Powering project-seeder\n\nWe use variables from GitLab CI to configure the [project-seeder application](https://gitlab.com/gl-commit-example/project-seeder).\n\n![Screenshot of the project for the project-seeder application](https://about.gitlab.com/images/blogimages/fei_projseederapp.jpg){: .shadow.medium.center}\n\nInside the project-seeder application which seeds the interview projects to job candidates.\n\n\n\"I'm creating `new-project-example-two`, and I'm adding this bot user that I created and the expiration, so I can just easily run this pipeline and it'll seed this project,\" says Clement.\n\n![We use variables from the GitLab CI to configure the project-seeder applications](https://about.gitlab.com/images/blogimages/fei_variables.jpg){: .shadow.medium.center}\n\nThe next step is to run the setup pipeline, which will create the project, import the project, export the project, and share it with the job candidate.\n\n![A look inside the pipeline that will create the test project](https://about.gitlab.com/images/blogimages/fei_insidethepipeline.jpg){: .shadow.medium.center}\nA look inside the pipeline that will create the test project.\n\n\nLooking inside example-one, we can see there is a project and [broken MR](https://gitlab.com/gl-commit-example/interview-projects/example-1/-/merge_requests/1).\n\n\"And an example for a candidate – they would probably look at the CI and see, 'Oh there's a failing test. Let's see what that's about. Oh, it looks like it's checking for \"hello world\". So since we changed the message earlier, we can just change this and get this test passing and then pass this interview,'\" says Clement.\n\n## Why this new model for technical interviews is better\n\nThe new model surpasses the old model because we created realistic scenarios that reflect what it's like to actually work for GitLab, and we established a more consistent method of measurement.\n\n\"So we're able to get better candidates overall. Candidates that pass through this technical interview, we're sure that they're going to be successful at GitLab,\" says Clement.\n\nBy designing our technical interviews this way, we can ensure that the interview project matches our actual product architecture at GitLab, which in this case is Ruby on Rails for Vue JS.\n\nWe also struggled in the past with finding a good way to check that the candidate knows how to use Git, and can navigate pipelines and testing. By using GitLab for interviews, we're able to confirm a candidate's competency with Git implicitly by evaluating their performance on the technical interviews.\n\nWe wanted to mirror the actual experience of troubleshooting a broken MR while working at GitLab, so we allow our candidates to use the internet during their technical interview. This allows the evaluator to see how the candidate solves problems and see their resourcefulness.\n\n\"If you're already using GitLab for your tooling, you're just exposing them to what it's like to work at GitLab; it's a more accurate representation,\" says Clement. \"And you can also make sure you're measuring testing proficiency and you make sure they understand how that works before they join your company.\"\n\n## Four key takeaways from our technical interview update\n\nWhether or not a company uses GitLab, there are a few key lessons that we learned by iterating on how we conduct technical interviews for engineers.\n\n1. **Make technical interviews as much like real work as possible**: Nine times out of ten, an engineering manager isn't going to sit back and watch an engineer break a sweat in a live coding exercise, any more than they will watch on as an engineer builds in UI. Create realistic scenarios based on the actual work and evaluate based on the candidate's performance.\n\n2. **Make any technical interview process \"open-book\"**: Engineering doesn't involve much rote memorization. Instead, allow the engineering candidate to use the internet (and in our case, the [GitLab Handbook](https://handbook.gitlab.com/handbook/)) to look up their questions. It's better to see how a candidate applies their knowledge and troubleshoots the inevitable problems that may arise. This change will likely improve your candidate experience too.\n\n3. **Standardize your rubric**: However the technical interview is done, make sure that the rubric is as objective as possible and that the candidate is evaluated based on various criteria, not on their familiarity with a particular technology. 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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.",[710],"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",[260,612,714],"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":717,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":719,"config":728},{"title":720,"description":721,"authors":722,"heroImage":723,"date":724,"category":9,"tags":725,"body":727},"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.",[710],"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",[612,260,726],"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":729,"featured":27,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":731,"config":744},{"category":9,"tags":732,"body":735,"date":736,"updatedDate":737,"heroImage":738,"authors":739,"title":742,"description":743},[733,734,107],"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",[740,741],"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":745},"migration-from-azure-devops-to-gitlab",{"promotions":747},[748,762,773],{"id":749,"categories":750,"header":752,"text":753,"button":754,"image":759},"ai-modernization",[751],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":755,"config":756},"Get your AI maturity score",{"href":757,"dataGaName":758,"dataGaLocation":242},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":760},{"src":761},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":763,"categories":764,"header":765,"text":753,"button":766,"image":770},"devops-modernization",[726,558],"Are you just managing tools or shipping innovation?",{"text":767,"config":768},"Get your DevOps maturity score",{"href":769,"dataGaName":758,"dataGaLocation":242},"/assessments/devops-modernization-assessment/",{"config":771},{"src":772},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":774,"categories":775,"header":777,"text":753,"button":778,"image":782},"security-modernization",[776],"security","Are you trading speed for security?",{"text":779,"config":780},"Get your security maturity score",{"href":781,"dataGaName":758,"dataGaLocation":242},"/assessments/security-modernization-assessment/",{"config":783},{"src":784},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":786,"blurb":787,"button":788,"secondaryButton":793},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":789,"config":790},"Get your free trial",{"href":791,"dataGaName":49,"dataGaLocation":792},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":494,"config":794},{"href":53,"dataGaName":54,"dataGaLocation":792},1772652103599]