[{"data":1,"prerenderedAt":792},["ShallowReactive",2],{"/en-us/blog/how-to-migrate-gitlab-groups-and-projects-more-efficiently":3,"navigation-en-us":38,"banner-en-us":438,"footer-en-us":448,"blog-post-authors-en-us-Magdalena Frankiewicz":689,"blog-related-posts-en-us-how-to-migrate-gitlab-groups-and-projects-more-efficiently":703,"assessment-promotions-en-us":744,"next-steps-en-us":782},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":27,"isFeatured":12,"meta":28,"navigation":29,"path":30,"publishedDate":20,"seo":31,"stem":35,"tagSlugs":36,"__hash__":37},"blogPosts/en-us/blog/how-to-migrate-gitlab-groups-and-projects-more-efficiently.yml","How To Migrate Gitlab Groups And Projects More Efficiently",[7],"magdalena-frankiewicz",null,"devsecops",{"slug":11,"featured":12,"template":13},"how-to-migrate-gitlab-groups-and-projects-more-efficiently",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"How to migrate GitLab groups and projects more efficiently","Learn about performance improvements to GitLab migration by direct transfer and what's next.",[18],"Magdalena Frankiewicz","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749668760/Blog/Hero%20Images/migration2.jpg","2023-08-02","Migrating groups and projects using direct transfer enables you to easily move GitLab resources between GitLab instances using either the UI or API. In a [previous blog post](https://about.gitlab.com/blog/try-out-new-way-to-migrate-projects/), we announced the release of migrating projects as a beta\nfeature **available to everyone**. We described the benefits of the method and steps to try it out.\n\nSince then, we have made further improvements, especially focusing on [efficient](https://gitlab.com/groups/gitlab-org/-/epics/8983) and\n[reliable](https://gitlab.com/groups/gitlab-org/-/epics/8927) migrations for large projects. In this blog, we'll elaborate on these improvements, as well as their impact on the overall process and speed of migrations. We'll also discuss estimating the duration of migrations.\n\n## Imports of CI/CD pipelines\n### Problem: Timing out\nWe received [a bug report about imports of CI/CD pipelines timing out](https://gitlab.com/gitlab-org/gitlab/-/issues/365702) and realized we needed to refine the underlying migration process. We considered the root cause of the problem and possible solutions, and ran proofs of concept. We concluded that we should tackle the\nproblem of having one massive archive file for a project with a large number of a certain relation types (for example, pipelines).\n\n### What we improved\nTo fix the problem of timeouts, we decided to introduce batching to the process of exporting and importing relations (for example, merge requests or pipelines).\n\nBefore we could fully complete the [epic for introducing the batching](https://gitlab.com/groups/gitlab-org/-/epics/9036), we had to introduce a couple of other optimizations\nto the process of exporting CI/CD pipelines.\n\nIn GitLab 15.10, we started:\n- [preloading associations when exporting CI/CD pipelines](https://gitlab.com/gitlab-org/gitlab/-/issues/391593)\n- [exporting commit notes as a separate relation](https://gitlab.com/gitlab-org/gitlab/-/issues/391601)\n\nWith these optimizations, exporting CI/CD pipelines sped up considerably. That allowed for a large number of pipelines in a project to be successfully exported to an archive file and then imported on the destination instance. However, because we were finally importing the pipelines, the overall duration of the migration increased.\n\nIn GitLab 16.3, we are introducing [exporting and importing relations in batches](https://gitlab.com/groups/gitlab-org/-/epics/9036). This has two benefits:\n- improves migration performance by creating and transferring smaller archive files, instead of one file per relation. These files can be very big if a project has thousands of pipelines.\n- enables more parallelism. For example, the CI pipeline data is now split into multiple batches and concurrent Sidekiq jobs (assuming the Sidekiq workers are available on the destination instance, see below) import each batch.\n\nThis improvement is already available by default on GitLab.com.\n- **Users migrating from a self-managed GitLab instance to GitLab.com** have to have their self-managed instance on at least GitLab 16.2, where batched export is available, to benefit from this improvement.\n- **Users migrating from GitLab.com to a self-managed GitLab instance** have to have their self-managed instance on at least GitLab 16.2 and enable the `bulk_imports_batched_import_export` [feature flag](https://docs.gitlab.com/ee/administration/feature_flags.html) to benefit from this improvement.\n\n## Can we estimate the duration of a migration?\nThis question has been asked time and again. The answer is that duration of migration with direct transfer depends on many different factors. Some of them are:\n- Hardware and database resources available on the source and destination GitLab instances. More resources on the source and destination instances can result in shorter migration duration because:\n  - the source instance receives API requests, and extracts and serializes the entities to export\n  - the destination instance runs the jobs and creates the entities in its database\n- Complexity and size of data to be exported. For example, imagine you want to migrate two different projects with 1,000 merge requests each. The two projects can take very different amounts of time to migrate if one of the projects has a lot more attachments, comments, and other items on the merge requests. Therefore, the number of merge requests on a project is a poor predictor of how long a project will take to migrate.\n\nThere’s no exact formula to reliably estimate a migration. However, we checked the duration of each job importing a project relation to share with you the average numbers, so you can get an idea of how long importing your projects might take. Here is what we found:\n\n- importing an empty project takes about 2.4 seconds\n- importing one MR takes about 1 second\n- importing one issue takes about 0.1 seconds\n\nYou can find more project relations and the average duration to import them in the table below.\n\n| Project resource type | Average time (in seconds) to import a single record |\n| ---- | ---- |\n| Empty project\t| 2.4 |\n| Repository | 20 |\n| Project attributes\t| 1.5 |\n| Members\t| 0.2 |\n| Labels\t| 0.1 |\n| Milestones\t| 0.07 |\n| Badges\t| 0.1 |\n| Issues\t| 0.1 |\n| Snippets\t| 0.05 |\n| Snippet repositories | 0.5 |\n| Boards\t| 0.1 |\n| Merge requests\t| 1 |\n| External pull requests\t| 0.5 |\n| Protected branches\t| 0.1 |\n| Project feature\t| 0.3 |\n| Container expiration policy\t| 0.3 |\n| Service desk setting\t| 0.3 |\n| Releases | 0.1 |\n| CI/CD pipelines\t| 0.2 |\n| Commit notes\t| 0.05 |\n| Wiki\t| 10 |\n| Uploads |\t0.5 |\n| LFS objects\t| 0.5 |\n| Design\t| 0.1 |\n| Auto DevOps\t| 0.1 |\n| Pipeline schedules\t| 0.5 |\n| References\t| 5 |\n| Push rule\t| 0.1 |\n\n## How can we migrate efficiently?\nWe also know what is needed to achieve the most efficient migration possible.\nA single direct transfer migration runs up to five entities (groups or projects) per import at a time, independent of the number of Sidekiq workers available on the destination instance. Importing five concurrent entities is the maximum allowed per migration by direct transfer. This limit has been set to not overload the source GitLab instance, because\nwe saw network timeouts from source instances when we removed this limitation.\n\nThat doesn't mean that if more than five Sidekiq workers are available on the destination instance that they won't be utilized during a migration. On the contrary, more Sidekiq\nworkers help speed up the migration by decreasing the time it takes to import each entity. Import of relations is distributed across multiple jobs and a single project entity\nhas over 30 relations to be migrated. [Exporting and importing relations in batches](https://gitlab.com/groups/gitlab-org/-/epics/9036) mentioned above results in even more\njobs to be processed by the Sidekiq workers.\nIncreasing the number of Sidekiq workers on the destination instance helps speed up the migration until the source instance hardware resources are saturated. For more information on\nincreasing the number of Sidekiq workers (increasing concurrency), see [Set up Sidekiq instance](https://docs.gitlab.com/ee/administration/sidekiq/#set-up-sidekiq-instance).\n\nThe number of Sidekiq workers on the source instance should at least be enough to export the five concurrent entities in parallel (for each running import). Otherwise, there will\nbe delays and potential timeouts as the destination is waiting for exported data to become available.\n\nDistributing projects in different groups helps to avoid timeouts. If several large projects are in the same group, you can:\n1. Move large projects to different groups or subgroups.\n1. Start separate migrations each group and subgroup.\n\nThe GitLab UI can only migrate top-level groups. Using the API, you can also migrate subgroups.\n\n## What's next for migrating by direct transfer?\nOf course, we're not done yet! We will continue to improve the direct transfer method, aiming towards coming out of beta and into general availability. Next, we are working on:\n\n- [Moving hardcoded limits of direct transfer to settings](https://gitlab.com/gitlab-org/gitlab/-/issues/384976) - Migration by direct transfer has some hardcoded limits that can be made configurable to allow self-managed GitLab administrators to tune them according to their needs. For GitLab.com, we could set these limits higher than their hardcoded setting.\n- [Removing a 90-minute export timeout](https://gitlab.com/gitlab-org/gitlab/-/issues/392725) - Removing this limit will allow exporting of even larger projects, because only projects that can be migrated in under 90 minutes are supported at the moment.\n\nMore details can be found on our [migrating by direct transfer roadmap direction page](https://about.gitlab.com/direction/foundations/). We are excited about this roadmap and hope you are too!\n\nWe want to hear from you. What's the most important missing piece for you? What else can we improve? Let us know\nin the [feedback issue](https://gitlab.com/gitlab-org/gitlab/-/issues/284495) or [schedule time](https://calendly.com/gitlab-magdalenafrankiewicz/45mins) with the Import and Integrations group product manager, and we'll keep iterating!\n\n_Disclaimer: This blog contains information related to upcoming products, features, and functionality. It is important to note that the information in this blog post is for informational purposes only. Please do not rely on this information for purchasing or planning purposes. As with all projects, the items mentioned in this blog and linked pages are subject to change or delay. 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code is 34% of development work. Discover how to balance productivity gains with quality, reliability, and security.",[708],"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.",[714,715,716],"AI/ML","DevOps platform","security",{"featured":29,"template":13,"slug":718},"ai-is-reshaping-devsecops-attend-gitlab-transcend-to-see-whats-next",{"content":720,"config":729},{"title":721,"description":722,"authors":723,"heroImage":725,"date":726,"body":727,"category":9,"tags":728},"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.",[724],"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/), 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/project/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/project/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.",[562,555,26,23],{"featured":29,"template":13,"slug":730},"atlassian-ending-data-center-as-gitlab-maintains-deployment-choice",{"content":732,"config":742},{"title":733,"description":734,"authors":735,"heroImage":738,"date":739,"category":9,"tags":740,"body":741},"Why financial services choose single-tenant SaaS","Discover how GitLab Dedicated can help financial services organizations achieve compliant DevSecOps without compromising performance.",[736,737],"George Kichukov","Allie Holland","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749662023/Blog/Hero%20Images/display-dedicated-for-government-article-image-0679-1800x945-fy26.png","2025-08-14",[616,715],"Walk into any major financial institution and you'll see the contradiction immediately. Past the armed guards, through the biometric scanners, beyond the reinforced walls and multiple security checkpoints, you'll find developers building the algorithms that power global finance — on shared infrastructure alongside millions of strangers.\n\nThe software powering today's financial institutions is anything but ordinary. It includes credit risk models that protect billions in assets, payment processing algorithms handling millions of transactions, customer intelligence platforms that drive business strategy, and regulatory systems ensuring operational compliance  — all powered by source code that serves as both operational core and strategic asset.\n\n## When shared infrastructure becomes systemic risk\n\nThe rise of software-as-a-service platforms has created an uncomfortable reality for financial institutions. Every shared tenant becomes an unmanaged third-party risk, turning platform-wide incidents into industry-wide disruptions. This is the exact kind of concentration risk drawing increasing attention from regulators.\n\nJPMorgan Chase's Chief Information Security Officer Patrick Opet recently issued a stark warning to the industry in an [open letter](https://www.jpmorgan.com/technology/technology-blog/open-letter-to-our-suppliers) to third-party suppliers. He highlighted how SaaS adoption \"is creating a substantial vulnerability that is weakening the global economic system\" by embedding \"concentration risk into global critical infrastructure.\" The letter emphasizes that \"an attack on one major SaaS or PaaS provider can immediately ripple through its customers,” creating exactly the systemic risk that multi-tenant cloud platforms for source code management, CI builds, CD deployments, and security scanning introduce.\n\nConsider the regulatory complexity this creates. In shared environments, your compliance posture becomes hostage to potential incidents impacting other tenants as well as the concentration risks of large attack surface providers. A misconfiguration affecting any organization on the platform can trigger wider impact across the entire ecosystem. \n\nData sovereignty challenges compound this risk. Shared platforms distribute workloads across multiple regions and jurisdictions, often without granular control over where your source code executes. For institutions operating under strict regulatory requirements, this geographic distribution can create compliance gaps that are difficult to remediate.\n\nThen there's the amplification effect. Every shared tenant effectively becomes an indirect third-party risk to your operations. Their vulnerabilities increase your attack surface. Their incidents can impact your availability. Their compromises can affect your environment.\n\n## Purpose-built for what matters most\n\nGitLab recognizes that your source code deserves the same security posture as your most sensitive customer data. Rather than forcing you to choose between cloud-scale efficiency and enterprise-grade security, GitLab delivers both through [GitLab Dedicated](https://about.gitlab.com/dedicated/), purpose-built infrastructure that maintains complete isolation.\n\nYour development workflows, source code [repositories](https://docs.gitlab.com/user/project/repository/), and [CI/CD pipelines](https://docs.gitlab.com/ci/pipelines/) run in an environment exclusively dedicated to your organization. The [hosted runners](https://docs.gitlab.com/administration/dedicated/hosted_runners/) for GitLab Dedicated exemplify this approach. These runners connect securely to your data center through outbound private links, allowing access to your private services without exposing any traffic to the public internet. The [auto-scaling architecture](https://docs.gitlab.com/runner/runner_autoscale/) provides the performance you need, without compromising security or control. \n \n## Rethinking control\n\nFor financial institutions, minimizing shared risk is only part of the equation — true resilience requires precise control over how systems operate, scale, and comply with regulatory frameworks. GitLab Dedicated enables comprehensive data sovereignty through multiple layers of customer control. You maintain complete authority over [encryption keys](https://docs.gitlab.com/administration/dedicated/encryption/#encrypted-data-at-rest) through [bring-your-own-key (BYOK)](https://docs.gitlab.com/administration/dedicated/encryption/#bring-your-own-key-byok) capabilities, ensuring that sensitive source code and configuration data remains accessible only to your organization. Even GitLab cannot access your encrypted data without your keys.\n\n[Data residency](https://docs.gitlab.com/subscriptions/gitlab_dedicated/data_residency_and_high_availability/) becomes a choice rather than a constraint. You select your preferred AWS region to meet regulatory requirements and organizational data governance policies, maintaining full control over where your sensitive source code and intellectual property are stored.\n\nThis control extends to [compliance frameworks](https://docs.gitlab.com/user/compliance/compliance_frameworks/) that financial institutions require. The platform provides [comprehensive audit trails](https://docs.gitlab.com/user/compliance/audit_events/) and logging capabilities that support compliance efforts for financial services regulations like [Sarbanes-Oxley](https://about.gitlab.com/compliance/sox-compliance/) and [GLBA Safeguards Rule](https://www.ftc.gov/business-guidance/privacy-security/gramm-leach-bliley-act).\n\nWhen compliance questions arise, you work directly with GitLab's dedicated support team — experienced professionals who understand the regulatory challenges that organizations in highly regulated industries face.\n\n## Operational excellence without operational overhead\n\nGitLab Dedicated maintains [high availability](https://docs.gitlab.com/subscriptions/gitlab_dedicated/data_residency_and_high_availability/) with [built-in disaster recovery](https://docs.gitlab.com/subscriptions/gitlab_dedicated/), ensuring your development operations remain resilient even during infrastructure failures. The dedicated resources scale with your organization's needs without the performance variability that shared environments introduce.\n\nThe [zero-maintenance approach](https://docs.gitlab.com/subscriptions/gitlab_dedicated/maintenance/) to CI/CD infrastructure eliminates a significant operational burden. Your teams focus on development while GitLab manages the underlying infrastructure, auto-scaling, and maintenance — including rapid security patching to protect your critical intellectual property from emerging threats. This operational efficiency doesn't come at the cost of security: the dedicated infrastructure provides enterprise-grade controls while delivering cloud-scale performance.\n\n## The competitive reality\n\nWhile some institutions debate infrastructure strategies, industry leaders are taking decisive action. [NatWest Group](https://about.gitlab.com/press/releases/2022-11-30-gitlab-dedicated-launches-to-meet-complex-compliance-requirements/), one of the UK's largest financial institutions, chose GitLab Dedicated to transform their engineering capabilities:\n\n> *\"NatWest Group is adopting GitLab Dedicated to enable our engineers to use a common cloud engineering platform; delivering new customer outcomes rapidly, frequently and securely with high quality, automated testing, on demand infrastructure and straight-through deployment. This will significantly enhance collaboration, improve developer productivity and unleash creativity via a 'single-pane-of-glass' for software development.\"*\n>\n> **Adam Leggett**, Platform Lead - Engineering Platforms, NatWest\n\n## The strategic choice\n\nThe most successful financial institutions face a unique challenge: They have the most to lose from shared infrastructure risks, but also the resources to architect better solutions. \n\n**The question that separates industry leaders from followers:** Will you accept shared infrastructure risks as the price of digital transformation, or will you invest in infrastructure that treats your source code with the strategic importance it deserves?\n\nYour trading algorithms aren't shared. Your risk models aren't shared. Your customer data isn't shared.\n\n**Why is your development platform shared?**\n\n*Ready to treat your source code like the strategic asset it is? [Let’s chat](https://about.gitlab.com/solutions/finance/) about how GitLab Dedicated provides the security, compliance, and performance that financial institutions demand — without the compromises of shared infrastructure.*",{"featured":12,"template":13,"slug":743},"why-financial-services-choose-single-tenant-saas",{"promotions":745},[746,760,771],{"id":747,"categories":748,"header":750,"text":751,"button":752,"image":757},"ai-modernization",[749],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":753,"config":754},"Get your AI maturity score",{"href":755,"dataGaName":756,"dataGaLocation":242},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":758},{"src":759},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":761,"categories":762,"header":763,"text":751,"button":764,"image":768},"devops-modernization",[26,9],"Are you just managing tools or shipping innovation?",{"text":765,"config":766},"Get your DevOps maturity score",{"href":767,"dataGaName":756,"dataGaLocation":242},"/assessments/devops-modernization-assessment/",{"config":769},{"src":770},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":772,"categories":773,"header":774,"text":751,"button":775,"image":779},"security-modernization",[716],"Are you trading speed for security?",{"text":776,"config":777},"Get your security maturity score",{"href":778,"dataGaName":756,"dataGaLocation":242},"/assessments/security-modernization-assessment/",{"config":780},{"src":781},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":783,"blurb":784,"button":785,"secondaryButton":790},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":786,"config":787},"Get your free trial",{"href":788,"dataGaName":49,"dataGaLocation":789},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":494,"config":791},{"href":53,"dataGaName":54,"dataGaLocation":789},1772652077499]