[{"data":1,"prerenderedAt":818},["ShallowReactive",2],{"/en-us/blog/gitlab-and-the-three-ways-of-devops":3,"navigation-en-us":40,"banner-en-us":450,"footer-en-us":460,"blog-post-authors-en-us-Vlad Budica":699,"blog-related-posts-en-us-gitlab-and-the-three-ways-of-devops":713,"blog-promotions-en-us":756,"next-steps-en-us":808},{"id":4,"title":5,"authorSlugs":6,"authors":8,"body":10,"category":11,"categorySlug":11,"config":12,"content":16,"date":20,"description":17,"extension":25,"externalUrl":26,"featured":14,"heroImage":19,"isFeatured":14,"meta":27,"navigation":28,"path":29,"publishedDate":20,"rawbody":30,"seo":31,"slug":13,"stem":35,"tagSlugs":36,"tags":38,"template":15,"updatedDate":26,"__hash__":39},"blogPosts/en-us/blog/gitlab-and-the-three-ways-of-devops.yml","GitLab and the three ways of DevOps",[7],"vlad-budica",[9],"Vlad Budica","\n\nMost of my daily conversations are focused on features and very deep technical concepts, which provide valuable and actionable insight. However, we miss the fact that tools and technology are leveraged to solve business challenges. When talking about features and technology, it's very easy to see the possible financial gain when replacing different tools with a unified platform. But it's missing all the improvement opportunities that will provide value at all the levels of a company from developers to executives.\n\nThe reality is that we're working in very complex systems, making it hard to see the forest from the trees. As an engineer, you're focused on solving the next immediate problem that arises without taking a step back to reevaluate the system itself. In some cases, the problem itself is created by the design of our software development lifecycle (SDLC). As an executive, it's difficult to balance the effort required to address the technical challenges with the pressure that comes from the business in this ever-increasing rhythm of change.\n\nMy goal with this article is to provide a high-level map that contains the most important DevOps principles and a shortcut. I know this is a bold statement as there is a lot of literature on this topic but my approach will be different.\n\\\nFirst, I'm going to use the [Three Ways](https://itrevolution.com/the-three-ways-principles-underpinning-devops/) as coined in [The DevOps Handbook](https://www.amazon.com/DevOps-Handbook-World-Class-Reliability-Organizations/dp/1942788002) because those are the three foundational principles of DevOps as they were refined from Lean, the Toyota Production System, Theory of Constraints, Six Sigma, and System Thinking principles. Second, I'll reference GitLab as the tool of choice because I think a good tool lets you focus on the work at hand, and GitLab does just that. \n> You’re invited! Join us on June 23rd for the [GitLab 15 launch event](https://page.gitlab.com/fifteen) with DevOps guru Gene Kim and several GitLab leaders. They’ll show you what they see for the future of DevOps and The One DevOps Platform.\n\nHere is a short description of what the Three Ways are, what they're about, and why you should care.\n\n## First Way: Maximize flow\n\nThe First Way is all about making work/value flow better through the whole value stream (left to right), and to do that, we need to have a systems thinking approach and always look at the end-to-end result. In the case of IT, this means we optimize for speed from the moment we had the idea, to generating value with software running in production.\n\nWe need to have a good understanding of the system to find potential bottlenecks and areas of improvement. Our improvements should always lead to better overall performance, be aware of the cases in which local enhancements lead to global degradation, and avoid that.\n\nIn this process, it is crucial to stop defects from passing downstream from one workflow stage to another. Why? Because defects generate waste (of time and resources).\n\n## Second Way: Feedback loops\n\nThe Second Way deals with feedback loops, amplifying and shortening feedback loops so that we get valuable insight into the work we're doing. The feedback can be related to the code that's written or the improvement initiatives. Feedback loops maximize flow from right to left of the value stream.\n\nQuick, strong feedback loops help build quality into the product and ensure that we're not passing defects downstream. The quicker we do this the quicker and cheaper we can solve them, continuously keeping our software in a deployable state. It's easier for a developer to fix a bug when they are working on that change, and the code and the thought process are fresh in their mind. Suppose days or even weeks pass between the moment of the commit and the moment we realize there is a problem with the change. It will be significantly harder to address the problem, not to mention that we probably realized the problem only when trying to deploy the software and we have a service that's not working on our hands. On the flip side, feedback loops enable learning and experimentation, a point on which I’ll return a bit later.\n\nUsually, more developers lead to more productivity but, as presented in [The State of DevOps Report](https://cloud.google.com/blog/products/devops-sre/announcing-dora-2021-accelerate-state-of-devops-report), this is true only for high performers. Why? If we have a team of 50 developers and problems aren't immediately detected, technical debt builds up. Things will only get worse when we have 100 developers because they will generate even more technical debt with every development cycle. A natural tendency would be to add more developers in the hope velocity will get better, but it will degrade, so we add even more developers, and things degrade even more, and deployment frequency starts to suffer as it takes a lot of time to fix all the problems that came from upstream in order to get to a deployable state.\n\n## Third Way: Continuous experimentation and learning\n\nThe Third Way is about creating a culture of trust where continuous experimentation and learning can thrive. This leverages the first two ways in order to be successful.\n\nMaking work flow easily through the value stream enables us to experiment and even take some risks, while failing fast and inexpensively. Feedback loops act as the guardrails that help us keep the risk in check but also facilitate learning because learning happens only when strong fast feedback is available. We can have a scientific approach, experiment with things, and extract the learning and improvement that results from these experiments and their feedback.\n\nThis is an iterative process that will lead to mastery (through increased repetition). This should be coupled with an environment where this local learning becomes global and is integrated into the daily work of all the teams. For this approach to work and start getting some results, 20% of our time should be reserved for these improvement activities. I'm aware how difficult it can be to carve 20% of your time for improvement initiatives when dealing with urgent problems is your full-time job. Protecting this improvement time helps us pay our technical debt and make sure things are not spiraling out of control.\n\n## GitLab and the Three Ways\n\t\nNow that we presented the Three Ways of DevOps, maximizing flow (left to right), feedback loops (maximizing flow right to left) and having a continuous learning process, implementing them requires some effort from a tooling and process perspective.\n\nIt’s time to introduce GitLab into the picture, the only DevOps platform that covers the whole SDLC. Why is this useful for you? Because there is a synergy that happens when all the capabilities you need are provided in the same platform, the result is more than the sum of the components. Additionally, a good tool lets you focus on your work, not on the tool itself, so you can spend more time and effort driving your DevOps transformation. The fact that you’ll spend less money and time integrating different tools is the first immediate return of your investment.\n\nWhen the goal is to maximize flow from left to right, GitLab can facilitate that, starting from idea to production. Having the benefit of being a platform built from the ground up, work can flow from Planning to the commit and source code management stage and forward to CI/CD seamlessly. Any person involved in the SDLC can perform their work from the same UI. All the information they need is available without a need to switch through different UIs while paying the mental context-switching cost associated when using disparate tooling.\nGitLab provides different control mechanisms to make sure that if defects are introduced they are isolated and they don’t move downstream. Working in short-lived feature branches, different controls around merging and MR Request Approval rules act as gates.\nBy having everything on the same platform it’s easier to understand the whole flow of work, coupling this with our Value Stream Metrics enables everyone involved to get a better understanding of the overall system and find potential bottlenecks and improvement opportunities.\n\n### Improved flow\n\nAs mentioned, flow in one direction - left to right - is not enough to deliver better software products faster. Feedback loops that are quick and provide strong feedback are crucial for great business outcomes. From a developer perspective, the results of the CI pipeline provides immediate feedback about your change. If this pipeline contains security scans it’s even better. Providing feedback from a security standpoint ensures that we’re not deploying vulnerable code and it gives the developer the opportunity to go back and fix it immediately. This is very actionable feedback that also provides a learning opportunity because the security reports come with information about the vulnerabilities, and also where possible, a potential solution to the vulnerability. All this is available for you without any additional work to integrate different tools.\n\nSwitching perspectives, someone that needs to review or approve a code change has everything they need at their fingertips in one place. It’s straightforward to pull in or “@mention” other necessary parties and they’ll get access to all necessary context. A decision can be made immediately and it’s based on accurate and clear feedback that you can trace back to the initial idea.\n### Metrics matter\n\nTaking another step back, we get different metrics (Value Stream, Contribution) at the project level. This is one of the advantages that comes with a platform approach, and these insights are very easy to obtain and feed back into the process. When doing software development at scale, more senior managers need this feedback at an even higher level, and, therefore, these are available across multiple teams, projects, or departments. All this information is very valuable from a current perspective, but also it helps guide and shape business decisions. If the velocity isn’t what is needed by the business we can look to remove bottlenecks, improve things or invest in some key areas.\n\nWith these two capabilities in place, we have a framework in which we can iterate quickly and safely. Experimentation becomes easy and very safe, we can test different business hypotheses, and see which ones work best with our customers. This should happen on an ongoing basis because this is the cornerstone of innovation.\n\n### Context is critical\nEvery experiment that we perform, every problem that we solve becomes valuable learning that should be accessible to everyone in the organization. Having everything (context, actions, results, learning) in one place enables us to open things up so that everyone can contribute. This requires an environment of trust where everyone feels comfortable to run small experiments that lead to improvements, and where these improvements can diffuse in your entire organization. By having a tool that just works and provides everything you need without any additional work, you gain back capacity that you can use to improve your product, overall system, or organization.\n\nIt’s been a long journey up to this point, with the purpose of taking a look beyond immediate feature comparisons and the immediate financial gain that is realized when replacing multiple tools with one. We looked at the core principles of DevOps as a map in your DevOps transformation and at GitLab as a tool to facilitate that. Improving very complex systems is hard, driving that change through your company is a challenge, knowing that you have a tool that just delivers on your needs you can focus on developing code and on your continuous improvement efforts.\n\nI hope this is useful to everyone involved in the SDLC, from the engineers who need to work with and within the system everyday, to senior leaders who need to deliver business results.\n","devsecops",{"slug":13,"featured":14,"template":15},"gitlab-and-the-three-ways-of-devops",false,"BlogPost",{"title":5,"description":17,"authors":18,"heroImage":19,"date":20,"body":10,"category":11,"tags":21},"DevOps isn't just an esoteric philosophy - it actually is a roadmap for faster and safer software releases, if you choose the right tool. Here's how to take the principles of DevOps and get the most out of the One DevOps Platform.",[9],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749667845/Blog/Hero%20Images/gl15.jpg","2022-06-15",[22,23,24],"DevOps","community","contributors","yml",null,{},true,"/en-us/blog/gitlab-and-the-three-ways-of-devops","seo:\n  title: GitLab and the three ways of DevOps\n  description: >-\n    DevOps isn't just an esoteric philosophy - it actually is a roadmap for\n    faster and safer software releases, if you choose the right tool. Here's how\n    to take the principles of DevOps and get the most out of the One DevOps\n    Platform.\n  ogTitle: GitLab and the three ways of DevOps\n  ogDescription: >-\n    DevOps isn't just an esoteric philosophy - it actually is a roadmap for\n    faster and safer software releases, if you choose the right tool. Here's how\n    to take the principles of DevOps and get the most out of the One DevOps\n    Platform.\n  noIndex: false\n  ogImage: >-\n    https://res.cloudinary.com/about-gitlab-com/image/upload/v1749667845/Blog/Hero%20Images/gl15.jpg\n  ogUrl: https://about.gitlab.com/blog/gitlab-and-the-three-ways-of-devops\n  ogSiteName: https://about.gitlab.com\n  ogType: article\n  canonicalUrls: https://about.gitlab.com/blog/gitlab-and-the-three-ways-of-devops\ncontent:\n  title: GitLab and the three ways of DevOps\n  description: >-\n    DevOps isn't just an esoteric philosophy - it actually is a roadmap for\n    faster and safer software releases, if you choose the right tool. Here's how\n    to take the principles of DevOps and get the most out of the One DevOps\n    Platform.\n  authors:\n    - Vlad Budica\n  heroImage: >-\n    https://res.cloudinary.com/about-gitlab-com/image/upload/v1749667845/Blog/Hero%20Images/gl15.jpg\n  date: '2022-06-15'\n  body: \"\n\n\n    Most of my daily conversations are focused on features and very deep\n    technical concepts, which provide valuable and actionable insight. However,\n    we miss the fact that tools and technology are leveraged to solve business\n    challenges. When talking about features and technology, it's very easy to\n    see the possible financial gain when replacing different tools with a\n    unified platform. But it's missing all the improvement opportunities that\n    will provide value at all the levels of a company from developers to\n    executives.\n\n\n    The reality is that we're working in very complex systems, making it hard to\n    see the forest from the trees. As an engineer, you're focused on solving the\n    next immediate problem that arises without taking a step back to reevaluate\n    the system itself. In some cases, the problem itself is created by the\n    design of our software development lifecycle (SDLC). As an executive, it's\n    difficult to balance the effort required to address the technical challenges\n    with the pressure that comes from the business in this ever-increasing\n    rhythm of change.\n\n\n    My goal with this article is to provide a high-level map that contains the\n    most important DevOps principles and a shortcut. I know this is a bold\n    statement as there is a lot of literature on this topic but my approach will\n    be different.\n\n    \\\\\n\n    First, I'm going to use the [Three\n    Ways](https://itrevolution.com/the-three-ways-principles-underpinning-devop\\\n    s/) as coined in [The DevOps\n    Handbook](https://www.amazon.com/DevOps-Handbook-World-Class-Reliability-Or\\\n    ganizations/dp/1942788002) because those are the three foundational\n    principles of DevOps as they were refined from Lean, the Toyota Production\n    System, Theory of Constraints, Six Sigma, and System Thinking principles.\n    Second, I'll reference GitLab as the tool of choice because I think a good\n    tool lets you focus on the work at hand, and GitLab does just that. \\\n\n\n    > You’re invited! Join us on June 23rd for the [GitLab 15 launch\n    event](https://page.gitlab.com/fifteen) with DevOps guru Gene Kim and\n    several GitLab leaders. They’ll show you what they see for the future of\n    DevOps and The One DevOps Platform.\n\n\n    Here is a short description of what the Three Ways are, what they're about,\n    and why you should care.\n\n\n    ## First Way: Maximize flow\n\n\n    The First Way is all about making work/value flow better through the whole\n    value stream (left to right), and to do that, we need to have a systems\n    thinking approach and always look at the end-to-end result. In the case of\n    IT, this means we optimize for speed from the moment we had the idea, to\n    generating value with software running in production.\n\n\n    We need to have a good understanding of the system to find potential\n    bottlenecks and areas of improvement. Our improvements should always lead to\n    better overall performance, be aware of the cases in which local\n    enhancements lead to global degradation, and avoid that.\n\n\n    In this process, it is crucial to stop defects from passing downstream from\n    one workflow stage to another. Why? Because defects generate waste (of time\n    and resources).\n\n\n    ## Second Way: Feedback loops\n\n\n    The Second Way deals with feedback loops, amplifying and shortening feedback\n    loops so that we get valuable insight into the work we're doing. The\n    feedback can be related to the code that's written or the improvement\n    initiatives. Feedback loops maximize flow from right to left of the value\n    stream.\n\n\n    Quick, strong feedback loops help build quality into the product and ensure\n    that we're not passing defects downstream. The quicker we do this the\n    quicker and cheaper we can solve them, continuously keeping our software in\n    a deployable state. It's easier for a developer to fix a bug when they are\n    working on that change, and the code and the thought process are fresh in\n    their mind. Suppose days or even weeks pass between the moment of the commit\n    and the moment we realize there is a problem with the change. It will be\n    significantly harder to address the problem, not to mention that we probably\n    realized the problem only when trying to deploy the software and we have a\n    service that's not working on our hands. On the flip side, feedback loops\n    enable learning and experimentation, a point on which I’ll return a bit\n    later.\n\n\n    Usually, more developers lead to more productivity but, as presented in [The\n    State of DevOps\n    Report](https://cloud.google.com/blog/products/devops-sre/announcing-dora-2\\\n    021-accelerate-state-of-devops-report), this is true only for high\n    performers. Why? If we have a team of 50 developers and problems aren't\n    immediately detected, technical debt builds up. Things will only get worse\n    when we have 100 developers because they will generate even more technical\n    debt with every development cycle. A natural tendency would be to add more\n    developers in the hope velocity will get better, but it will degrade, so we\n    add even more developers, and things degrade even more, and deployment\n    frequency starts to suffer as it takes a lot of time to fix all the problems\n    that came from upstream in order to get to a deployable state.\n\n\n    ## Third Way: Continuous experimentation and learning\n\n\n    The Third Way is about creating a culture of trust where continuous\n    experimentation and learning can thrive. This leverages the first two ways\n    in order to be successful.\n\n\n    Making work flow easily through the value stream enables us to experiment\n    and even take some risks, while failing fast and inexpensively. Feedback\n    loops act as the guardrails that help us keep the risk in check but also\n    facilitate learning because learning happens only when strong fast feedback\n    is available. We can have a scientific approach, experiment with things, and\n    extract the learning and improvement that results from these experiments and\n    their feedback.\n\n\n    This is an iterative process that will lead to mastery (through increased\n    repetition). This should be coupled with an environment where this local\n    learning becomes global and is integrated into the daily work of all the\n    teams. For this approach to work and start getting some results, 20% of our\n    time should be reserved for these improvement activities. I'm aware how\n    difficult it can be to carve 20% of your time for improvement initiatives\n    when dealing with urgent problems is your full-time job. Protecting this\n    improvement time helps us pay our technical debt and make sure things are\n    not spiraling out of control.\n\n\n    ## GitLab and the Three Ways\n\n    \\t\n\n    Now that we presented the Three Ways of DevOps, maximizing flow (left to\n    right), feedback loops (maximizing flow right to left) and having a\n    continuous learning process, implementing them requires some effort from a\n    tooling and process perspective.\n\n\n    It’s time to introduce GitLab into the picture, the only DevOps platform\n    that covers the whole SDLC. Why is this useful for you? Because there is a\n    synergy that happens when all the capabilities you need are provided in the\n    same platform, the result is more than the sum of the components.\n    Additionally, a good tool lets you focus on your work, not on the tool\n    itself, so you can spend more time and effort driving your DevOps\n    transformation. The fact that you’ll spend less money and time integrating\n    different tools is the first immediate return of your investment.\n\n\n    When the goal is to maximize flow from left to right, GitLab can facilitate\n    that, starting from idea to production. Having the benefit of being a\n    platform built from the ground up, work can flow from Planning to the commit\n    and source code management stage and forward to CI/CD seamlessly. Any person\n    involved in the SDLC can perform their work from the same UI. All the\n    information they need is available without a need to switch through\n    different UIs while paying the mental context-switching cost associated when\n    using disparate tooling.\\\n\n\n    GitLab provides different control mechanisms to make sure that if defects\n    are introduced they are isolated and they don’t move downstream. Working in\n    short-lived feature branches, different controls around merging and MR\n    Request Approval rules act as gates.\\\n\n\n    By having everything on the same platform it’s easier to understand the\n    whole flow of work, coupling this with our Value Stream Metrics enables\n    everyone involved to get a better understanding of the overall system and\n    find potential bottlenecks and improvement opportunities.\n\n\n    ### Improved flow\n\n\n    As mentioned, flow in one direction - left to right - is not enough to\n    deliver better software products faster. Feedback loops that are quick and\n    provide strong feedback are crucial for great business outcomes. From a\n    developer perspective, the results of the CI pipeline provides immediate\n    feedback about your change. If this pipeline contains security scans it’s\n    even better. Providing feedback from a security standpoint ensures that\n    we’re not deploying vulnerable code and it gives the developer the\n    opportunity to go back and fix it immediately. This is very actionable\n    feedback that also provides a learning opportunity because the security\n    reports come with information about the vulnerabilities, and also where\n    possible, a potential solution to the vulnerability. All this is available\n    for you without any additional work to integrate different tools.\n\n\n    Switching perspectives, someone that needs to review or approve a code\n    change has everything they need at their fingertips in one place. It’s\n    straightforward to pull in or “@mention” other necessary parties and they’ll\n    get access to all necessary context. A decision can be made immediately and\n    it’s based on accurate and clear feedback that you can trace back to the\n    initial idea.\\\n\n\n    ### Metrics matter\n\n\n    Taking another step back, we get different metrics (Value Stream,\n    Contribution) at the project level. This is one of the advantages that comes\n    with a platform approach, and these insights are very easy to obtain and\n    feed back into the process. When doing software development at scale, more\n    senior managers need this feedback at an even higher level, and, therefore,\n    these are available across multiple teams, projects, or departments. All\n    this information is very valuable from a current perspective, but also it\n    helps guide and shape business decisions. If the velocity isn’t what is\n    needed by the business we can look to remove bottlenecks, improve things or\n    invest in some key areas.\n\n\n    With these two capabilities in place, we have a framework in which we can\n    iterate quickly and safely. Experimentation becomes easy and very safe, we\n    can test different business hypotheses, and see which ones work best with\n    our customers. This should happen on an ongoing basis because this is the\n    cornerstone of innovation.\n\n\n    ### Context is critical\\\n\n\n    Every experiment that we perform, every problem that we solve becomes\n    valuable learning that should be accessible to everyone in the organization.\n    Having everything (context, actions, results, learning) in one place enables\n    us to open things up so that everyone can contribute. This requires an\n    environment of trust where everyone feels comfortable to run small\n    experiments that lead to improvements, and where these improvements can\n    diffuse in your entire organization. By having a tool that just works and\n    provides everything you need without any additional work, you gain back\n    capacity that you can use to improve your product, overall system, or\n    organization.\n\n\n    It’s been a long journey up to this point, with the purpose of taking a look\n    beyond immediate feature comparisons and the immediate financial gain that\n    is realized when replacing multiple tools with one. We looked at the core\n    principles of DevOps as a map in your DevOps transformation and at GitLab as\n    a tool to facilitate that. Improving very complex systems is hard, driving\n    that change through your company is a challenge, knowing that you have a\n    tool that just delivers on your needs you can focus on developing code and\n    on your continuous improvement efforts.\n\n\n    I hope this is useful to everyone involved in the SDLC, from the engineers\n    who need to work with and within the system everyday, to senior leaders who\n    need to deliver business results.\\n\"\n  category: devsecops\n  tags:\n    - DevOps\n    - community\n    - contributors\nconfig:\n  slug: gitlab-and-the-three-ways-of-devops\n  featured: false\n  template: 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software development the easy way using GitLab","Learn how University of Washington lecturer Stephen G. Dame uses GitLab for Education to manage student assignments, distribute course materials, and provide inline code feedback at scale.\n",[719],"Rod Burns","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749659537/Blog/Hero%20Images/display-article-image-0679-1800x945-fy26.png","2026-04-29","For instructors teaching software development, one of the biggest logistical challenges is assignment distribution and feedback at scale. How do you give large groups of students access to course materials, keep solution code private, and still deliver meaningful, contextual feedback without lots of administrative overhead?\n\nThe **[GitLab for Education program](https://about.gitlab.com/solutions/education/)** provides qualifying institutions with free access to **GitLab Ultimate**, enabling instructors to build professional-grade workflows that mirror real-world software development environments. In this article, you'll learn how Stephen G. Dame, a lecturer in the Computing and Software Systems department at the University of Washington, Bothell, uses simple workflows in GitLab to manage everything from course materials to student feedback across multiple classes.\n\n## From aerospace to academia: Bringing GitLab to the classroom\n\nDame came to academia with years of experience as a chief software engineer at Boeing Commercial Airplanes, where GitLab was used for aerospace projects. As an adjunct professor, he became an early advocate for GitLab within the university, joining the GitLab for Education program to access the full feature set needed to run structured, scalable course workflows.\n\n> **\"GitLab provides the greatest way to organize multiple classes, student assignments, lectures, and code samples through the use of Groups and Subgroups, which I found to be unique to GitLab compared to other repository platforms.\"**\n>\n> - Stephen G. Dame, University of Washington, Bothell\n\n## Set up groups: Build the right structure before writing a line of code\n\nThe foundation of an effective GitLab-based course is a well-planned group hierarchy. GitLab's **[Groups and Subgroups](https://docs.gitlab.com/tutorials/manage_user/#create-the-organization-parent-group-and-subgroups)** allow instructors to model the natural structure of a university department institution, course, and role with precise, inheritable permissions at every level.\n\nDame's structure places the university at the root (`UWTeaching`), with each course occupying its own subgroup (e.g. `css430`). Within each course sit repositories for `lecture-materials` and `code`, alongside dedicated Subgroups for `students` and `graders`. Instructor materials remain private, while student and grader subgroups are configured with controlled permissions so that assignment briefs and solutions are visible only to the right people.\n\n![Screenshot of GitLab group hierarchy — institution, course subgroup, and per-student subgroups](https://res.cloudinary.com/about-gitlab-com/image/upload/v1777463673/dpxfnitv76pdmvcqtgag.png)\n\nPermissions cascade downward through the hierarchy via **Manage > Members**, allowing Dame to add students to a course's `students` subgroup with `Reporter` access and an expiration date tied to the end of the academic quarter. Students can clone and pull from assignment repositories but cannot push — keeping solution code firmly under instructor control.\n\nStudents are guided to set up SSH keys across all their working environments (local machines, cloud shells, virtual machines) so they can clone repositories and receive weekly updates via `git pull`. They copy relevant code into their own private repositories to manage their own version history.\n\n**Tip for large classes:** For larger cohorts, adding students by hand is impractical. GitLab's REST API lets you automate subgroup creation and membership from a list of usernames. Below is a sample Python script that handles this:\n\n```python\n    import gitlab\n    from datetime import datetime\n\n    # Connect to your GitLab instance\n    gl = gitlab.Gitlab('https://gitlab.com', private_token='YOUR_PRIVATE_TOKEN')\n\n    # Target parent group ID (e.g., the ID for \"css430 > students\")\n    parent_group_id = 12345678\n\n    # Set expiration: typically the beginning of the next month after quarter end\n    expiry_date = '2025-01-01'\n\n    # List of collected student usernames\n    student_list = ['alice_css430', 'bob_css430', 'carol_css430', 'dave_css430', 'eve_css430']\n\n    for username in student_list:\n        try:\n            # 1. Create a personal subgroup for the student\n            subgroup = gl.groups.create({\n                'name': username,\n                'path': username,\n                'parent_id': parent_group_id,\n                'visibility': 'private'\n            })\n\n            # 2. Add student to the new subgroup with Expiration\n            user = gl.users.list(username=username)[0]\n            subgroup.members.create({\n                'user_id': user.id,\n                'access_level': gitlab.const.REPORTER_ACCESS,\n                'expires_at': expiry_date\n            })\n            print(f\"Success: Subgroup created and student added for {username}\")\n        except Exception as e:\n            print(f\"Error processing {username}: {e}\")\n```\nThere is also an [open source project that automates class management](https://gitlab.com/edu-docs/class-management-automation) published by GitLab that provides additional tooling for this workflow.\n## Give feedback where the work actually lives\n\nOnce the structure is in place, the feedback workflow is where GitLab's value becomes most apparent to students. Dame asks students to submit assignments by opening a **[merge request](https://docs.gitlab.com/user/project/merge_requests/)** in their repository. This gives instructors an immediate, clean diff of everything the student has written.\n![A GitLab merge request showing inline code comment function for an instructor](https://res.cloudinary.com/about-gitlab-com/image/upload/v1777467468/icclzyglbkwlvfysggbi.png)\nInstructors can click any line of code and leave an **inline comment** — not just flagging what is wrong, but explaining why, and pointing to what to look at next. Students receive this feedback in direct context with their code, which is far more actionable than a comment at the bottom of a submitted document.\n\n## Join GitLab for Education\n\nSetting up your first GitLab assignment takes some initial effort, but once the structure is in place it largely runs itself. The real payoff goes beyond organization: Students graduate having worked daily in an environment that mirrors professional software development, building habits around [version control](https://about.gitlab.com/topics/version-control/) and [code review](https://docs.gitlab.com/development/code_review/) rather than learning them as abstract concepts.\n\nIf you are just getting started, keep it simple. Begin with a single course group, one assignment template, and a basic pipeline. The structure will grow naturally alongside your confidence with the platform.\n\nMake sure to **[sign up for GitLab for Education](https://about.gitlab.com/solutions/education/join/)** so that you and your students can access all top-tier features, including unlimited reviewers on merge requests, additional compute minutes, and expanded storage.\n\n> [Apply to the GitLab for Education program today](https://about.gitlab.com/solutions/education/join/).",[621,724],"open source",{"featured":14,"template":15,"slug":726},"teaching-software-development-the-easy-way-using-gitlab",{"content":728,"config":740},{"description":729,"authors":730,"heroImage":732,"date":733,"title":734,"body":735,"category":11,"tags":736},"AI-generated code is 34% of development work. Discover how to balance productivity gains with quality, reliability, and security.",[731],"Manav Khurana","https://res.cloudinary.com/about-gitlab-com/image/upload/v1767982271/e9ogyosmuummq7j65zqg.png","2026-01-08","AI is reshaping DevSecOps: Attend GitLab Transcend to see what’s next","AI promises a step change in innovation velocity, but most software teams are hitting a wall. According to our latest [Global DevSecOps Report](https://about.gitlab.com/developer-survey/), AI-generated code now accounts for 34% of all development work. Yet 70% of DevSecOps professionals report that AI is making compliance management more difficult, and 76% say agentic AI will create unprecedented security challenges.\n\nThis is the AI paradox: AI accelerates coding, but software delivery slows down as teams struggle to test, secure, and deploy all that code.\n\n## Productivity gains meet workflow bottlenecks\nThe problem isn't AI itself. It's how software gets built today. The traditional DevSecOps lifecycle contains hundreds of small tasks that developers must navigate manually: updating tickets, running tests, requesting reviews, waiting for approvals, fixing merge conflicts, addressing security findings. These tasks drain an average of seven hours per week from every team member, according to our research.\n\nDevelopment teams are producing code faster than ever, but that code still crawls through fragmented toolchains, manual handoffs, and disconnected processes. In fact, 60% of DevSecOps teams use more than five tools for software development overall, and 49% use more than five AI tools. This fragmentation creates collaboration barriers, with 94% of DevSecOps professionals experiencing factors that limit collaboration in the software development lifecycle.\n\nThe answer isn't more tools. It's intelligent orchestration that brings software teams and their AI agents together across projects and release cycles, with enterprise-grade security, governance, and compliance built in.\n\n## Seeking deeper human-AI partnerships\nDevSecOps professionals don't want AI to take over — they want reliable partnerships. The vast majority (82%) say using agentic AI would increase their job satisfaction, and 43% envision an ideal future with a 50/50 split between human and AI contributions. They're ready to trust AI with 37% of their daily tasks without human review, particularly for documentation, test writing, and code reviews.\n\nWhat we heard resoundingly from DevSecOps professionals is that AI won't replace them; rather, it will fundamentally reshape their roles. 83% of DevSecOps professionals believe AI will significantly change their work within five years, and notably, 76% think this will create more engineering jobs, not fewer. As coding becomes easier with AI, engineers who can architect systems, ensure quality, and apply business context will be in high demand.\n\nCritically, 88% agree there are essential human qualities that AI will never fully replace, including creativity, innovation, collaboration, and strategic vision.\n\nSo how can organizations bridge the gap between AI’s promise and the reality of fragmented workflows?\n\n## Join us at GitLab Transcend: Explore how to drive real value with agentic AI\nOn February 10, 2026, GitLab will be hosting Transcend, where we'll reveal how intelligent orchestration transforms AI-powered software development. You'll get a first look at GitLab's upcoming product roadmap and learn how teams are solving real-world challenges by modernizing development workflows with AI.\n\nOrganizations winning in this new era balance AI adoption with security, compliance, and platform consolidation. AI offers genuine productivity gains when implemented thoughtfully — not by replacing human developers, but by freeing DevSecOps professionals to focus on strategic thinking and creative innovation.\n\n[Register for Transcend today](https://about.gitlab.com/events/transcend/virtual/) to secure your spot and discover how intelligent orchestration can help your software teams stay in flow.",[737,738,739],"AI/ML","DevOps platform","security",{"featured":28,"template":15,"slug":741},"ai-is-reshaping-devsecops-attend-gitlab-transcend-to-see-whats-next",{"content":743,"config":754},{"title":744,"description":745,"authors":746,"heroImage":748,"date":749,"body":750,"category":11,"tags":751},"Atlassian ending Data Center as GitLab maintains deployment choice","As Atlassian transitions Data Center customers to cloud-only, GitLab presents a menu of deployment choices that map to business needs.",[747],"Emilio Salvador","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750098354/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%281%29_5XrohmuWBNuqL89BxVUzWm_1750098354056.png","2025-10-07","Change is never easy, especially when it's not your choice. Atlassian's announcement that [all Data Center products will reach end-of-life by March 28, 2029](https://www.atlassian.com/blog/announcements/atlassian-ascend), means thousands of organizations must now reconsider their DevSecOps deployment and infrastructure. But you don't have to settle for deployment options that don't fit your needs. GitLab maintains your freedom to choose — whether you need self-managed for compliance, cloud for convenience, or hybrid for flexibility — all within a single AI-powered DevSecOps platform that respects your requirements.\n\nWhile other vendors force migrations to cloud-only architectures, GitLab remains committed to supporting the deployment choices that match your business needs. Whether you're managing sensitive government data, operating in air-gapped environments, or simply prefer the control of self-managed deployments, we understand that one size doesn't fit all.\n\n## The cloud isn't the answer for everyone\n\nFor the many companies that invested millions of dollars in Data Center deployments, including those that migrated to Data Center [after its Server products were discontinued](https://about.gitlab.com/blog/atlassian-server-ending-move-to-a-single-devsecops-platform/), this announcement represents more than a product sunset. It signals a fundamental shift away from customer-centric architecture choices, forcing enterprises into difficult positions: accept a deployment model that doesn't fit their needs, or find a vendor that respects their requirements.\n\nMany of the organizations requiring self-managed deployments represent some of the world's most important organizations: healthcare systems protecting patient data, financial institutions managing trillions in assets, government agencies safeguarding national security, and defense contractors operating in air-gapped environments.\n\nThese organizations don't choose self-managed deployments for convenience; they choose them for compliance, security, and sovereignty requirements that cloud-only architectures simply cannot meet. Organizations operating in closed environments with restricted or no internet access aren't exceptions — they represent a significant portion of enterprise customers across various industries.\n\n![GitLab vs. Atlassian comparison table](https://res.cloudinary.com/about-gitlab-com/image/upload/v1759928476/ynl7wwmkh5xyqhszv46m.jpg)\n\n## The real cost of forced cloud migration goes beyond dollars\n\nWhile cloud-only vendors frame mandatory migrations as \"upgrades,\" organizations face substantial challenges beyond simple financial costs:\n\n* **Lost integration capabilities:** Years of custom integrations with legacy systems, carefully crafted workflows, and enterprise-specific automations become obsolete. Organizations with deep integrations to legacy systems often find cloud migration technically infeasible.\n\n* **Regulatory constraints:** For organizations in regulated industries, cloud migration isn't just complex — it's often not permitted. Data residency requirements, air-gapped environments, and strict regulatory frameworks don't bend to vendor preferences. The absence of single-tenant solutions in many cloud-only approaches creates insurmountable compliance barriers.\n\n* **Productivity impacts:** Cloud-only architectures often require juggling multiple products: separate tools for planning, code management, CI/CD, and documentation. Each tool means another context switch, another integration to maintain, another potential point of failure. GitLab research shows [30% of developers spend at least 50% of their job maintaining and/or integrating their DevSecOps toolchain](https://about.gitlab.com/developer-survey/). Fragmented architectures exacerbate this challenge rather than solving it.\n\n## GitLab offers choice, commitment, and consolidation\n\nEnterprise customers deserve a trustworthy technology partner. That's why we've committed to supporting a range of deployment options — whether you need on-premises for compliance, hybrid for flexibility, or cloud for convenience, the choice remains yours. That commitment continues with [GitLab Duo](https://about.gitlab.com/gitlab-duo-agent-platform/), our AI solution that supports developers at every stage of their workflow.\n\nBut we offer more than just deployment flexibility. While other vendors might force you to cobble together their products into a fragmented toolchain, GitLab provides everything in a **comprehensive AI-native DevSecOps platform**. Source code management, CI/CD, security scanning, Agile planning, and documentation are all managed within a single application and a single vendor relationship.\n\nThis isn't theoretical. When Airbus and [Iron Mountain](https://about.gitlab.com/customers/iron-mountain/) evaluated their existing fragmented toolchains, they consistently identified challenges: poor user experience, missing functionalities like built-in security scanning and review apps, and management complexity from plugin troubleshooting. **These aren't minor challenges; they're major blockers for modern software delivery.**\n\n## Your migration path: Simpler than you think\n\nWe've helped thousands of organizations migrate from other vendors, and we've built the tools and expertise to make your transition smooth:\n\n* **Automated migration tools:** Our [Bitbucket Server importer](https://docs.gitlab.com/user/import/bitbucket_server/) brings over repositories, pull requests, comments, and even Large File Storage (LFS) objects. For Jira, our [built-in importer](https://docs.gitlab.com/user/project/import/jira/) handles issues, descriptions, and labels, with professional services available for complex migrations.\n\n* **Proven at scale:** A 500 GiB repository with 13,000 pull requests, 10,000 branches, and 7,000 tags is likely to [take just 8 hours to migrate](https://docs.gitlab.com/user/import/bitbucket_server/) from Bitbucket to GitLab using parallel processing.\n\n* **Immediate ROI:** A [Forrester Consulting Total Economic Impact™ study commissioned by GitLab](https://about.gitlab.com/resources/study-forrester-tei-gitlab-ultimate/) found that investing in GitLab Ultimate confirms these benefits translate to real bottom-line impact, with a three-year 483% ROI, 5x time saved in security related activities, and 25% savings in software toolchain costs.\n\n## Start your journey to a unified DevSecOps platform\n\nForward-thinking organizations aren't waiting for vendor-mandated deadlines. They're evaluating alternatives now, while they have time to migrate thoughtfully to platforms that protect their investments and deliver on promises.\n\nOrganizations invest in self-managed deployments because they need control, compliance, and customization. When vendors deprecate these capabilities, they remove not just features but the fundamental ability to choose environments matching business requirements.\n\nModern DevSecOps platforms should offer complete functionality that respects deployment needs, consolidates toolchains, and accelerates software delivery, without forcing compromises on security or data sovereignty.\n\n[Talk to our sales team](https://about.gitlab.com/sales/) today about your migration options, or explore our [comprehensive migration resources](https://about.gitlab.com/move-to-gitlab-from-atlassian/) to see how thousands of organizations have already made the switch.\n\nYou also can [try GitLab Ultimate with GitLab Duo Enterprise](https://about.gitlab.com/free-trial/devsecops/) for free for 30 days to see what a unified DevSecOps platform can do for your organization.",[572,565,752,753],"product","features",{"featured":28,"template":15,"slug":755},"atlassian-ending-data-center-as-gitlab-maintains-deployment-choice",{"promotions":757},[758,772,783,794],{"id":759,"categories":760,"header":762,"text":763,"button":764,"image":769},"ai-modernization",[761],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":765,"config":766},"Get your AI maturity score",{"href":767,"dataGaName":768,"dataGaLocation":244},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":770},{"src":771},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":773,"categories":774,"header":775,"text":763,"button":776,"image":780},"devops-modernization",[752,11],"Are you just managing tools or shipping innovation?",{"text":777,"config":778},"Get your DevOps maturity score",{"href":779,"dataGaName":768,"dataGaLocation":244},"/assessments/devops-modernization-assessment/",{"config":781},{"src":782},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":784,"categories":785,"header":786,"text":763,"button":787,"image":791},"security-modernization",[739],"Are you trading speed for security?",{"text":788,"config":789},"Get your security maturity score",{"href":790,"dataGaName":768,"dataGaLocation":244},"/assessments/security-modernization-assessment/",{"config":792},{"src":793},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":795,"paths":796,"header":799,"text":800,"button":801,"image":806},"github-azure-migration",[797,798],"migration-from-azure-devops-to-gitlab","integrating-azure-devops-scm-and-gitlab","Is your team ready for GitHub's Azure move?","GitHub is already rebuilding around Azure. Find out what it means for you.",{"text":802,"config":803},"See how GitLab compares to GitHub",{"href":804,"dataGaName":805,"dataGaLocation":244},"/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":807},{"src":782},{"header":809,"blurb":810,"button":811,"secondaryButton":816},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":812,"config":813},"Get your free trial",{"href":814,"dataGaName":51,"dataGaLocation":815},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":506,"config":817},{"href":55,"dataGaName":56,"dataGaLocation":815},1777493572296]