[{"data":1,"prerenderedAt":822},["ShallowReactive",2],{"/en-us/blog/top-reasons-for-software-release-delays":3,"navigation-en-us":43,"banner-en-us":454,"footer-en-us":464,"blog-post-authors-en-us-Valerie Silverthorne":703,"blog-related-posts-en-us-top-reasons-for-software-release-delays":717,"blog-promotions-en-us":760,"next-steps-en-us":812},{"id":4,"title":5,"authorSlugs":6,"authors":8,"body":10,"category":11,"categorySlug":11,"config":12,"content":16,"date":20,"description":17,"extension":26,"externalUrl":27,"featured":14,"heroImage":19,"isFeatured":14,"meta":28,"navigation":29,"path":30,"publishedDate":20,"rawbody":31,"seo":32,"slug":13,"stem":36,"tagSlugs":37,"tags":41,"template":15,"updatedDate":27,"__hash__":42},"blogPosts/en-us/blog/top-reasons-for-software-release-delays.yml","Top reasons for software release delays",[7],"valerie-silverthorne",[9],"Valerie Silverthorne","\n_What’s the most likely reason for a software release delay?_\n\nFrom 2019 through 2021, respondents to our Global DevSecOps Surveys _always_ blamed software testing. This year, however, was dramatically different.\n\nMore than 5,000 DevOps practitioners took our [2022 Global DevSecOps Survey](https://about.gitlab.com/developer-survey/), and, for the first time, they offered five equally valid reasons why releases might be tardy: code development, code review, security analysis, test data management, and, of course, testing.\n\nProcesses and priorities are clearly changing in DevOps teams today, and they’re affecting release delays. Here’s how to understand the forces at work.\n\n> Join us at [GitLab Commit 2022](/events/) and connect with the ideas, technologies, and people that are driving DevOps and digital transformation.\n\n## Code development and code review\n\nOver the past three years, code development and code review were the second- and third-ranked culprits for release delays. That’s to be expected: No one ever said code development was easy and code reviews have always been problematic.\n\nDevelopers report [a myriad of challenges with code review](/blog/the-code-review-struggle-is-real-heres-what-you-need-to-know/): It’s too labor intensive, no one is available to do it, and the culture often doesn’t support the process. But in this year’s survey, 76% of developers said they find code reviews “very” or “somewhat” valuable, and a majority said code review was one of the key steps in DevOps they wish they could do more of. All told, 27% of developers review code weekly while another 21% review it daily or with every commit.\n\nClearly, code review is important but [it takes work](/blog/tips-for-better-code-review/) to make them happen more efficiently. One up-and-coming solution that could help make code reviews easier is artificial intelligence. Our survey found 31% of DevOps teams use AI for code review today, more than double the percentage in 2021. GitLab is also excited about the possibilities found in AI’s close cousin machine learning – we’re using it to [improve the code review process](/blog/the-road-to-smarter-code-reviewer-recommendations/).\n\n## Keeping software secure\n\nCreating safe code requires security testing and the frustration around this step is both real and longstanding. Security has nearly always [been seen as a “blocker”](/blog/developer-security-divide/) when it comes to software development in general and software releases in particular. In our 2022 survey, though, priorities have changed. Security is now the top area DevOps teams plan to invest in this year, and a majority of developers report that the most difficult part of their job is keeping software secure. Here’s just a sample of what developers had to say about the challenges of their roles today:\n\n_We are trying to keep up with the latest tools and security for optimal performance and privacy._\n\n_We are trying to build applications that are secure and stable._\n\n_It is challenging to keep it secure and keep it updated._\n\n_Cyber security attacks are the biggest challenge facing us today._\n\n_Data security, data security, I repeat, data security._\n\nThe focus on security isn’t just talk, either. More than 50% of DevOps teams are running SAST, DAST, and container scans, all dramatic increases from 2021. But at the same time, this is the fourth year security pros have continued to blame developers for finding too few bugs too late in the process. Security is a developer performance metric for many teams, but sec team members say it is still very hard to get devs to actually fix bugs, a trend we’ve seen reflected over and over.\n\nIn other words, it’s complicated enough to make the potential of delays unsurprising.\n\n## Managing the test data\n\nToo much test data is one of those good and bad problems to have: 47% of DevOps teams we surveyed report full test automation, nearly double the percentage from last year, and more security scans are being run too. More than half of survey takers (53%) are testing their code as it’s being written, up 21% from last year.\n\nAll those tests result in a data management problem most teams aren’t actually set up to handle. Here’s one example: Less than one-third of teams are able to put DAST and SAST results into a developer’s workflow/IDE and those percentages remain stubbornly low year after year.\n\nTesting momentum and automation are growing by leaps and bounds, but teams now need better ways to evaluate, communicate, and act on the data.\n\n## The tricky nature of software testing\n\nSoftware testing has often worn the “DevOps scapegoat” mantle, and perhaps for good reason. Getting testing just right is critical, but it’s also elusive. There are so many kinds of tests teams can run, test automation requires a big process and culture investment, and test results are often seen as “flaky,” “noisy,” and “late” by busy developers not enthused about context switching or inaccurate results.\n\nBut there are a couple of promising signs: As we saw in 2021, developer respondents told us again this year that testing is high on their list of tasks they would like to do more of. And artificial intelligence is also making inroads: About 37% of teams are using AI/ML to test their code (a 23-point jump from 2021) and 20% more are planning to add it to their DevOps practice this year.\n\nWant to understand more about software release delays and DevOps best practices? Read our [2022 Global DevSecOps Survey](/resources/developer-survey/).\n","devsecops",{"slug":13,"featured":14,"template":15},"top-reasons-for-software-release-delays",false,"BlogPost",{"title":5,"description":17,"authors":18,"heroImage":19,"date":20,"body":10,"category":11,"tags":21},"In our 2022 Global DevSecOps survey, DevOps pros shared their frustrations with software releases, including security's shift left and complicated code reviews.",[9],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749664070/Blog/Hero%20Images/cloudwatch-gitlab-incident-management-bg.jpg","2022-08-30",[22,23,24,25],"developer survey","code review","releases","DevOps","yml",null,{},true,"/en-us/blog/top-reasons-for-software-release-delays","seo:\n  title: Top reasons for software release delays\n  description: >-\n    In our 2022 Global DevSecOps survey, DevOps pros shared their frustrations\n    with software releases, including security's shift left and complicated code\n    reviews.\n  ogTitle: Top reasons for software release delays\n  ogDescription: >-\n    In our 2022 Global DevSecOps survey, DevOps pros shared their frustrations\n    with software releases, including security's shift left and complicated code\n    reviews.\n  noIndex: false\n  ogImage: >-\n    https://res.cloudinary.com/about-gitlab-com/image/upload/v1749664070/Blog/Hero%20Images/cloudwatch-gitlab-incident-management-bg.jpg\n  ogUrl: https://about.gitlab.com/blog/top-reasons-for-software-release-delays\n  ogSiteName: https://about.gitlab.com\n  ogType: article\n  canonicalUrls: https://about.gitlab.com/blog/top-reasons-for-software-release-delays\ncontent:\n  title: Top reasons for software release delays\n  description: >-\n    In our 2022 Global DevSecOps survey, DevOps pros shared their frustrations\n    with software releases, including security's shift left and complicated code\n    reviews.\n  authors:\n    - Valerie Silverthorne\n  heroImage: >-\n    https://res.cloudinary.com/about-gitlab-com/image/upload/v1749664070/Blog/Hero%20Images/cloudwatch-gitlab-incident-management-bg.jpg\n  date: '2022-08-30'\n  body: >\n\n    _What’s the most likely reason for a software release delay?_\n\n\n    From 2019 through 2021, respondents to our Global DevSecOps Surveys _always_\n    blamed software testing. This year, however, was dramatically different.\n\n\n    More than 5,000 DevOps practitioners took our [2022 Global DevSecOps\n    Survey](https://about.gitlab.com/developer-survey/), and, for the first\n    time, they offered five equally valid reasons why releases might be tardy:\n    code development, code review, security analysis, test data management, and,\n    of course, testing.\n\n\n    Processes and priorities are clearly changing in DevOps teams today, and\n    they’re affecting release delays. Here’s how to understand the forces at\n    work.\n\n\n    > Join us at [GitLab Commit 2022](/events/) and connect with the ideas,\n    technologies, and people that are driving DevOps and digital transformation.\n\n\n    ## Code development and code review\n\n\n    Over the past three years, code development and code review were the second-\n    and third-ranked culprits for release delays. That’s to be expected: No one\n    ever said code development was easy and code reviews have always been\n    problematic.\n\n\n    Developers report [a myriad of challenges with code\n    review](/blog/the-code-review-struggle-is-real-heres-what-you-need-to-know/):\n    It’s too labor intensive, no one is available to do it, and the culture\n    often doesn’t support the process. But in this year’s survey, 76% of\n    developers said they find code reviews “very” or “somewhat” valuable, and a\n    majority said code review was one of the key steps in DevOps they wish they\n    could do more of. All told, 27% of developers review code weekly while\n    another 21% review it daily or with every commit.\n\n\n    Clearly, code review is important but [it takes\n    work](/blog/tips-for-better-code-review/) to make them happen more\n    efficiently. One up-and-coming solution that could help make code reviews\n    easier is artificial intelligence. Our survey found 31% of DevOps teams use\n    AI for code review today, more than double the percentage in 2021. GitLab is\n    also excited about the possibilities found in AI’s close cousin machine\n    learning – we’re using it to [improve the code review\n    process](/blog/the-road-to-smarter-code-reviewer-recommendations/).\n\n\n    ## Keeping software secure\n\n\n    Creating safe code requires security testing and the frustration around this\n    step is both real and longstanding. Security has nearly always [been seen as\n    a “blocker”](/blog/developer-security-divide/) when it comes to software\n    development in general and software releases in particular. In our 2022\n    survey, though, priorities have changed. Security is now the top area DevOps\n    teams plan to invest in this year, and a majority of developers report that\n    the most difficult part of their job is keeping software secure. Here’s just\n    a sample of what developers had to say about the challenges of their roles\n    today:\n\n\n    _We are trying to keep up with the latest tools and security for optimal\n    performance and privacy._\n\n\n    _We are trying to build applications that are secure and stable._\n\n\n    _It is challenging to keep it secure and keep it updated._\n\n\n    _Cyber security attacks are the biggest challenge facing us today._\n\n\n    _Data security, data security, I repeat, data security._\n\n\n    The focus on security isn’t just talk, either. More than 50% of DevOps teams\n    are running SAST, DAST, and container scans, all dramatic increases from\n    2021. But at the same time, this is the fourth year security pros have\n    continued to blame developers for finding too few bugs too late in the\n    process. Security is a developer performance metric for many teams, but sec\n    team members say it is still very hard to get devs to actually fix bugs, a\n    trend we’ve seen reflected over and over.\n\n\n    In other words, it’s complicated enough to make the potential of delays\n    unsurprising.\n\n\n    ## Managing the test data\n\n\n    Too much test data is one of those good and bad problems to have: 47% of\n    DevOps teams we surveyed report full test automation, nearly double the\n    percentage from last year, and more security scans are being run too. More\n    than half of survey takers (53%) are testing their code as it’s being\n    written, up 21% from last year.\n\n\n    All those tests result in a data management problem most teams aren’t\n    actually set up to handle. Here’s one example: Less than one-third of teams\n    are able to put DAST and SAST results into a developer’s workflow/IDE and\n    those percentages remain stubbornly low year after year.\n\n\n    Testing momentum and automation are growing by leaps and bounds, but teams\n    now need better ways to evaluate, communicate, and act on the data.\n\n\n    ## The tricky nature of software testing\n\n\n    Software testing has often worn the “DevOps scapegoat” mantle, and perhaps\n    for good reason. Getting testing just right is critical, but it’s also\n    elusive. There are so many kinds of tests teams can run, test automation\n    requires a big process and culture investment, and test results are often\n    seen as “flaky,” “noisy,” and “late” by busy developers not enthused about\n    context switching or inaccurate results.\n\n\n    But there are a couple of promising signs: As we saw in 2021, developer\n    respondents told us again this year that testing is high on their list of\n    tasks they would like to do more of. And artificial intelligence is also\n    making inroads: About 37% of teams are using AI/ML to test their code (a\n    23-point jump from 2021) and 20% more are planning to add it to their DevOps\n    practice this year.\n\n\n    Want to understand more about software release delays and DevOps best\n    practices? 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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",[723],"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/).",[625,728],"open source",{"featured":14,"template":15,"slug":730},"teaching-software-development-the-easy-way-using-gitlab",{"content":732,"config":744},{"description":733,"authors":734,"heroImage":736,"date":737,"title":738,"body":739,"category":11,"tags":740},"AI-generated code is 34% of development work. Discover how to balance productivity gains with quality, reliability, and security.",[735],"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.",[741,742,743],"AI/ML","DevOps platform","security",{"featured":29,"template":15,"slug":745},"ai-is-reshaping-devsecops-attend-gitlab-transcend-to-see-whats-next",{"content":747,"config":758},{"title":748,"description":749,"authors":750,"heroImage":752,"date":753,"body":754,"category":11,"tags":755},"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.",[751],"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.",[576,569,756,757],"product","features",{"featured":29,"template":15,"slug":759},"atlassian-ending-data-center-as-gitlab-maintains-deployment-choice",{"promotions":761},[762,776,787,798],{"id":763,"categories":764,"header":766,"text":767,"button":768,"image":773},"ai-modernization",[765],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":769,"config":770},"Get your AI maturity score",{"href":771,"dataGaName":772,"dataGaLocation":247},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":774},{"src":775},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":777,"categories":778,"header":779,"text":767,"button":780,"image":784},"devops-modernization",[756,11],"Are you just managing tools or shipping innovation?",{"text":781,"config":782},"Get your DevOps maturity score",{"href":783,"dataGaName":772,"dataGaLocation":247},"/assessments/devops-modernization-assessment/",{"config":785},{"src":786},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":788,"categories":789,"header":790,"text":767,"button":791,"image":795},"security-modernization",[743],"Are you trading speed for security?",{"text":792,"config":793},"Get your security maturity score",{"href":794,"dataGaName":772,"dataGaLocation":247},"/assessments/security-modernization-assessment/",{"config":796},{"src":797},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":799,"paths":800,"header":803,"text":804,"button":805,"image":810},"github-azure-migration",[801,802],"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":806,"config":807},"See how GitLab compares to GitHub",{"href":808,"dataGaName":809,"dataGaLocation":247},"/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":811},{"src":786},{"header":813,"blurb":814,"button":815,"secondaryButton":820},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":816,"config":817},"Get your free trial",{"href":818,"dataGaName":54,"dataGaLocation":819},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":510,"config":821},{"href":58,"dataGaName":59,"dataGaLocation":819},1777493626690]