[{"data":1,"prerenderedAt":816},["ShallowReactive",2],{"/en-us/blog/gitlab-18-5-intelligence-that-moves-software-development-forward":3,"navigation-en-us":36,"banner-en-us":446,"footer-en-us":456,"blog-post-authors-en-us-Bill Staples":697,"blog-related-posts-en-us-gitlab-18-5-intelligence-that-moves-software-development-forward":711,"blog-promotions-en-us":754,"next-steps-en-us":806},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":26,"isFeatured":11,"meta":27,"navigation":11,"path":28,"publishedDate":20,"seo":29,"stem":32,"tagSlugs":33,"__hash__":35},"blogPosts/en-us/blog/gitlab-18-5-intelligence-that-moves-software-development-forward.yml","Gitlab 18 5 Intelligence That Moves Software Development Forward",[7],"bill-staples",null,"ai-ml",{"featured":11,"template":12,"slug":13},true,"BlogPost","gitlab-18-5-intelligence-that-moves-software-development-forward",{"heroImage":15,"title":16,"description":17,"authors":18,"date":20,"body":21,"category":9,"tags":22},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1760970883/asrc2c2hejqp5o1tan4c.png","GitLab 18.5: Intelligence that moves software development forward","GitLab 18.5 delivers new specialized agents, security insights that cut through the noise, and a reimagined interface that keeps your AI teammate always in view.",[19],"Bill Staples","2025-10-21","Software development teams are drowning in noise. Thousands of vulnerabilities flood security dashboards, but only a fraction pose real risk. Developers context-switch between planning backlogs, triaging security findings, reviewing code, and responding to CI/CD failures — losing hours to manual work. [GitLab 18.5](https://about.gitlab.com/releases/2025/10/16/gitlab-18-5-released/) calms this chaos.\n\nAt the heart of this release is a valuable improvement in overall usability of GitLab and how AI integrates into your user experience. A new panel-based UI makes it easier to see data in context, and allows GitLab Duo Chat to be persistently visible across the platform, wherever it is needed. Purpose-built agents tackle vulnerability triage and backlog management, and popular AI tools integrate with agentic workflows even more seamlessly than before. We’ve also extended our market-leading security capabilities to help you better identify exploitable vulnerabilities versus theoretical ones, distinguish active credentials from expired ones, and scan only changed code to keep developers in flow.\n\n## What’s new in 18.5\n\n18.5 represents our biggest release so far this year — watch our introduction to the release, and read more details below. \n\u003Cdiv>\u003Ciframe src=\"https://player.vimeo.com/video/1128975773?badge=0&autopause=0&player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"GitLab_18.5 Release_101925_MP_v2\">\u003C/iframe>\u003C/div>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\n\u003Cp>\u003C/p>\n\n### Modern user experience with quick access to GitLab Duo everywhere\n\nGitLab 18.5 delivers a modernized user experience with a more intuitive interface driven by a new panel-based layout.\n\nWith panels, key information appears side by side so that you can work contextually, without losing your place. For example, when you click on an issue in the issues list, its details automatically open in a side panel. You can also launch the GitLab Duo panel on the right, bringing Duo wherever you are in GitLab. This lets you ask contextual questions or give instructions, right alongside your work.\n\nSeveral usability improvements make navigation easier. The global search box now appears at the top center for improved accessibility. Global navigation elements, including Issues, Merge Requests, To-Dos, and your avatar have moved to the top right. Additionally, the left sidebar is now collapsible and expandable, giving you more control over your workspace.\n\nTeams using experimental and GitLab Duo beta features will be the first to receive the new interface, followed by all GitLab.com users who will be able to turn this experience on using the toggle located under your user icon. To learn more about this feature, reference our documentation [here](https://docs.gitlab.com/user/interface_redesign/#turn-new-navigation-on-or-off). Please share your feedback or report any issues [here](https://gitlab.com/gitlab-org/gitlab/-/issues/577554), you're helping us shape a better GitLab! \n\n### Updates to GitLab Duo Agent Platform\n\n**Security Analyst Agent: Transform manual vulnerability triage into intelligent automation**\n\nGitLab Duo [Security Analyst Agent](https://docs.gitlab.com/user/duo_agent_platform/agents/foundational_agents/security_analyst_agent/) automates vulnerability management workflows through AI-powered analysis, helping transform hours of manual triage into intelligent automation. Building on the Vulnerability Management Tools available through GitLab Duo Agentic Chat, Security Analyst Agent orchestrates multiple tools, applying security policies, and creating custom flows for recurring workflows automatically.\n\nSecurity teams can access enriched vulnerability data, including CVE details, static reachability analysis, and code flow information, while executing operations like dismissing false positives, confirming threats, adjusting severity levels, and creating linked issues for remediation — all through conversational AI. The agent reduces repetitive clicking through vulnerability dashboards and replaces custom scripts with simple natural language commands.\n\nFor example, when a security scan reveals dozens of vulnerabilities, simply prompt: \"Dismiss vulnerabilities with reachable=FALSE and create issues for critical findings.\" Security Analyst Agent analyzes reachability data, applies security policies, and completes bulk operations in moments — helping decrease work that would otherwise take hours. \n\nWhile individual Vulnerability Management Tools can be accessed directly through Agentic Chat for specific tasks, Security Analyst Agent orchestrates these tools intelligently and automates complex multi-step workflows. Note that Vulnerability Management Tools are available through Agentic Chat on GitLab Self-managed and GitLab.com instances, and Security Analyst Agent is available on GitLab.com only for 18.5, while availability in Self-managed and Dedicated environments will come with our next release.\nWatch this demo:\n\n\u003Cdiv>\u003Ciframe src=\"https://player.vimeo.com/video/1128975984?badge=0&autopause=0&player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"18.5 Security Demo\">\u003C/iframe>\u003C/div>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\n\u003Cp>\u003C/p>\n\n**GitLab Duo Planner: Turn backlog chaos into strategic clarity**\n\nManaging complex software delivery requires constant context-switching between planning tasks. [GitLab Duo Planner](https://docs.gitlab.com/user/duo_agent_platform/agents/foundational_agents/planner/) addresses the real-world planning challenges we see teams face every day. Duo Planner acts as your teammate with awareness of your project context, including how you manage issues, epics, and merge requests. Unlike generic AI assistants, it's purpose-built with deep knowledge of GitLab's planning workflows coupled with Agile and prioritization frameworks to help you balance effort, risk, and strategic alignment.\n\nGitLab Duo Planner can turn vague ideas into structured planning hierarchies, identify stale backlog items, and draft executive updates. For example, when refining your backlog with hundreds of issues accumulated over months, simply prompt: \"Identify stale backlog items and suggest priorities.\" Within seconds, you'll receive a structured summary showing issues without recent activity, items missing key details, duplicate work, and recommended priorities based on labels and milestones, complete with actionable recommendations. \n\nFor teams managing complex roadmaps, the Planner aims to eliminate hours of manual analysis and context-switching, helping Product Managers and engineering leads make faster, more informed decisions. As of 18.5, GitLab Duo Planner is currently “read-only,” meaning that it can analyze, plan, and suggest, but cannot yet take direct action to modify anything. Please see our [documentation](https://docs.gitlab.com/user/duo_agent_platform/agents/foundational_agents/planner/) for more information. \n\n**Extensible Agent Catalog: Popular AI tools as native GitLab agents**\n\nGitLab 18.5 introduces popular AI agents directly into the [AI Catalog](https://docs.gitlab.com/user/duo_agent_platform/ai_catalog/), making external tools like Claude, OpenAI Codex, Google Gemini CLI, Amazon Q Developer, and OpenCode available as native GitLab agents. Users can now discover, configure, and deploy these agents through the same unified catalog interface used for GitLab's built-in agents, with automatic syncing of foundational agents across organization catalogs. \n\nThis eliminates the complexity of manual agent setup by providing a point-and-click catalog experience while maintaining enterprise-grade security through GitLab's authentication and audit systems. GitLab Duo Enterprise subscriptions now include built-in usage of Claude and Codex within GitLab, allowing you to use your existing GitLab subscription for these tools without requiring separate API keys or additional billing setup. Other agents may still require separate subscriptions and configuration while we finalize our integration plans.\n\n**Self-hosted GitLab Duo Agent Platform (Beta): Address data sovereignty requirements without sacrificing AI power**\n\nGitLab 18.5 moves GitLab Duo Agent Platform's self-hosted capabilities from experimental to beta, enabling organizations to execute AI agents and flows entirely within their own infrastructure — critical for regulated industries and data sovereignty requirements. The beta release includes improved timeout configurations and AI Gateway settings, allowing teams to use AI agents for code reviews, bug fixes, and feature implementations, while providing enterprise-grade security for sensitive code.\n\n## Smarter, faster security: Prioritize real risks and keep developers in the flow\n\nGitLab 18.5 introduces new application security capabilities that help teams focus on exploitable risk, reduce noise, and strengthen software supply chain security. These updates continue our commitment to building security directly into the development process — delivering precision, speed, and insight without disrupting developer flow.\n\n**Static Reachability Analysis**\n\nWith over [37,000 new CVEs](https://www.cvedetails.com/) issued this year, security teams face an overwhelming volume of vulnerabilities and struggle to understand which ones are truly exploitable. Static Reachability Analysis, now in limited availability, brings library-level precision by helping to identify whether vulnerable code is actually invoked in your application, not just present in dependencies. \n\nPaired with our [recently released](https://docs.gitlab.com/user/application_security/vulnerabilities/risk_assessment_data/) Exploit Prediction Scoring System (EPSS) and Known Exploited Vulnerability (KEV) data, security teams can more effectively accelerate vulnerability triage and prioritize real risks to help strengthen overall supply chain security. In 18.5, we’re adding support for Java, alongside existing support for Python, JavaScript, and TypeScript. \n\n**Secret Validity Checks**\n\nJust as Static Reachability Analysis helps teams prioritize exploitable vulnerabilities from open source dependencies, Secret Validity Checks bring the same insight to exposed secrets — currently available in beta on GitLab.com and GitLab Self-Managed. For GitLab-issued security tokens, instead of manually verifying whether a leaked credential or API key is active, GitLab automatically distinguishes active secrets from expired ones directly in the [Vulnerability Report](https://docs.gitlab.com/user/application_security/vulnerability_report/). This helps enable security and development teams to focus remediation efforts on genuine risks. Support for AWS- and GCP-issued secrets is planned for future releases. \n\n**Custom rules for Advanced SAST**\n\nAdvanced SAST runs on rules informed by our in-house security research team, designed to maximize accuracy out of the box. However, some teams required additional flexibility to tune the SAST engine for their specific organization. With Custom Rules for Advanced SAST, AppSec teams can define atomic, pattern-based detection logic to help capture security issues specific to their organization — like flagging banned function calls — while still using GitLab’s curated ruleset as the baseline. Customizations are managed through simple TOML files, just like other SAST ruleset configurations. While these rules will not support taint analysis, they do give organizations greater flexibility in achieving accurate SAST results. \n\n**Advanced SAST C and C++ language support** \n\nWe’re expanding our language coverage for Advanced SAST to include C and C++, which are widely used languages in embedded systems software development. To enable scanning, projects must generate a compilation database that captures compiler commands and includes paths used during builds. This works to ensure the scanner can accurately parse and analyze source files, delivering precise, context-aware results that help security teams identify real vulnerabilities in the development process. The implementation requirements for C and C++ require specific configurations, which can be found in our [documentation](https://docs.gitlab.com/user/application_security/sast/cpp_advanced_sast/). Advanced SAST C and C++ support are currently available in beta. \n\n**Diff-based SAST scanning** \n\nTraditional SAST scans re-analyze entire codebases with every commit, slowing pipelines and disrupting developer flow. The developer experience is a critical consideration that can make or break the adoption of application security testing. Diff-based SAST scanning aims to speed up scan times by focusing only on the code changed in a merge request, reducing redundant analysis and surfacing relevant results tied to the developer’s work. By aligning scans with actual code changes, GitLab delivers faster, more focused feedback that helps keep developers in flow while maintaining strong security coverage.\n\n## Simplify API configurations\n\nAPI-driven workflows offer power and flexibility, but they can also create unnecessary complexity for tasks that teams need to perform regularly. The new Maven Virtual Registry interface brings a UI layer to these operations.\n\n### Maven Virtual Registry interface\n\nThe new web-based interface for managing Maven Virtual Registries turns complex API configurations into visual simplicity, providing a more intuitive experience for package administrators and platform engineers.\n\nPreviously, teams configured and maintained virtual registries only through API calls, which made routine maintenance time-consuming and required specialized platform knowledge. The new interface removes that barrier, helping to make everyday tasks faster and easier.\n\nWith this update, you can now:\n\n* Create virtual registries to simplify dependency configuration  \n* Create and order upstreams to help improve performance and compliance  \n* Browse and clear stale cache entries directly in the UI\n\nThis visual experience helps reduce operational overhead and provides development teams with clearer insight into how dependencies are resolved, enabling them to make better decisions about build performance and security policies.\n\nWatch a demo:\n\n\u003C!-- blank line -->\n\u003Cfigure class=\"video_container\">\n\u003Ciframe src=\"https://www.youtube.com/embed/CiOZJPhAvaI?si=cYaoR_OIgqFKbyM2\" frameborder=\"0\" allowfullscreen=\"true\"> \u003C/iframe>\n\u003C/figure>\n\u003C!-- blank line -->\n\n\u003Cp>\u003C/p>\n\nWe invite enterprise customers to join the [Maven Virtual Registry Beta program](https://gitlab.com/gitlab-org/gitlab/-/issues/543045) and share feedback to help shape the final release. \n\n## AI that adapts to your workflow\n\nThis release represents more than new capabilities — it's about choice and control. Watch the walkthrough video here:\n\n\u003Cp>\u003C/p>\n\n\u003Cdiv>\u003Ciframe src=\"https://player.vimeo.com/video/1128992281?badge=0&autopause=0&player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"18.5-tech-demo\">\u003C/iframe>\u003C/div>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\n\u003Cp>\u003C/p>\n\nGitLab Premium and Ultimate users can start using these capabilities today on [GitLab.com](https://GitLab.com) and self-managed environments, with availability for GitLab Dedicated customers planned for next month. \n\nGitLab Duo Agent Platform is currently in **beta** — enable beta and experimental features to experience how full-context AI can transform the way your teams build software. New to GitLab? [Start your free trial](https://about.gitlab.com/free-trial/devsecops/) and see why the future of development is AI-powered, secure, and orchestrated through the world’s most comprehensive DevSecOps platform.\n\n***Note:** Platform capabilities that are in beta are available as part of the GitLab Beta program. They are free to use during the beta period, and when generally available, they will be made available with a paid add-on option for GitLab Duo Agent Platform.*\n\n### Stay up to date with GitLab\n\nTo make sure you’re getting the latest features, security updates, and performance improvements, we recommend keeping your GitLab instance up to date. The following resources can help you plan and complete your upgrade:\n\n* [Upgrade Path Tool](https://gitlab-com.gitlab.io/support/toolbox/upgrade-path/) – enter your current version and see the exact upgrade steps for your instance  \n* [Upgrade Documentation](https://docs.gitlab.com/update/upgrade_paths/) – detailed guides for each supported version, including requirements, step-by-step instructions, and best practices\n\nBy upgrading regularly, you’ll ensure your team benefits from the newest GitLab capabilities and remains secure and supported.\n\nFor organizations that want a hands-off approach, consider [GitLab’s Managed Maintenance service](https://content.gitlab.com/viewer/d1fe944dddb06394e6187f0028f010ad#1). With Managed Maintenance, your team stays focused on innovation while GitLab experts keep your Self-Managed instance reliably upgraded, secure, and ready to lead in DevSecOps. Ask your account manager for more information. \n\n*This blog post contains \"forward‑looking statements\" within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934. Although we believe that the expectations reflected in these statements are reasonable, they are subject to known and unknown risks, uncertainties, assumptions and other factors that may cause actual results or outcomes to differ materially. Further information on these risks and other factors is included under the caption \"Risk Factors\" in our filings with the SEC. We do not undertake any obligation to update or revise these statements after the date of this blog post, except as required by law.*",[23,24,25],"features","product","DevSecOps platform","yml",{},"/en-us/blog/gitlab-18-5-intelligence-that-moves-software-development-forward",{"config":30,"title":16,"description":17},{"noIndex":31},false,"en-us/blog/gitlab-18-5-intelligence-that-moves-software-development-forward",[23,24,34],"devsecops-platform","XzZv1NX8GCUneo6xZmDcC-J_zFWx-9KWxhPTSS7nUdc",{"data":37},{"logo":38,"freeTrial":43,"sales":48,"login":53,"items":58,"search":366,"minimal":397,"duo":416,"switchNav":425,"pricingDeployment":436},{"config":39},{"href":40,"dataGaName":41,"dataGaLocation":42},"/","gitlab logo","header",{"text":44,"config":45},"Get free trial",{"href":46,"dataGaName":47,"dataGaLocation":42},"https://gitlab.com/-/trial_registrations/new?glm_source=about.gitlab.com&glm_content=default-saas-trial/","free trial",{"text":49,"config":50},"Talk to sales",{"href":51,"dataGaName":52,"dataGaLocation":42},"/sales/","sales",{"text":54,"config":55},"Sign in",{"href":56,"dataGaName":57,"dataGaLocation":42},"https://gitlab.com/users/sign_in/","sign in",[59,86,181,186,287,347],{"text":60,"config":61,"cards":63},"Platform",{"dataNavLevelOne":62},"platform",[64,70,78],{"title":60,"description":65,"link":66},"The intelligent orchestration platform for DevSecOps",{"text":67,"config":68},"Explore our Platform",{"href":69,"dataGaName":62,"dataGaLocation":42},"/platform/",{"title":71,"description":72,"link":73},"GitLab Duo Agent Platform","Agentic AI for the entire software lifecycle",{"text":74,"config":75},"Meet GitLab Duo",{"href":76,"dataGaName":77,"dataGaLocation":42},"/gitlab-duo-agent-platform/","gitlab duo agent platform",{"title":79,"description":80,"link":81},"Why GitLab","See the top reasons enterprises choose GitLab",{"text":82,"config":83},"Learn more",{"href":84,"dataGaName":85,"dataGaLocation":42},"/why-gitlab/","why gitlab",{"text":87,"left":11,"config":88,"link":90,"lists":94,"footer":163},"Product",{"dataNavLevelOne":89},"solutions",{"text":91,"config":92},"View all Solutions",{"href":93,"dataGaName":89,"dataGaLocation":42},"/solutions/",[95,119,142],{"title":96,"description":97,"link":98,"items":103},"Automation","CI/CD and automation to accelerate deployment",{"config":99},{"icon":100,"href":101,"dataGaName":102,"dataGaLocation":42},"AutomatedCodeAlt","/solutions/delivery-automation/","automated software delivery",[104,108,111,115],{"text":105,"config":106},"CI/CD",{"href":107,"dataGaLocation":42,"dataGaName":105},"/solutions/continuous-integration/",{"text":71,"config":109},{"href":76,"dataGaLocation":42,"dataGaName":110},"gitlab duo agent platform - product menu",{"text":112,"config":113},"Source Code Management",{"href":114,"dataGaLocation":42,"dataGaName":112},"/solutions/source-code-management/",{"text":116,"config":117},"Automated Software Delivery",{"href":101,"dataGaLocation":42,"dataGaName":118},"Automated software delivery",{"title":120,"description":121,"link":122,"items":127},"Security","Deliver code faster without compromising security",{"config":123},{"href":124,"dataGaName":125,"dataGaLocation":42,"icon":126},"/solutions/application-security-testing/","security and compliance","ShieldCheckLight",[128,132,137],{"text":129,"config":130},"Application Security Testing",{"href":124,"dataGaName":131,"dataGaLocation":42},"Application security testing",{"text":133,"config":134},"Software Supply Chain Security",{"href":135,"dataGaLocation":42,"dataGaName":136},"/solutions/supply-chain/","Software supply chain security",{"text":138,"config":139},"Software Compliance",{"href":140,"dataGaName":141,"dataGaLocation":42},"/solutions/software-compliance/","software compliance",{"title":143,"link":144,"items":149},"Measurement",{"config":145},{"icon":146,"href":147,"dataGaName":148,"dataGaLocation":42},"DigitalTransformation","/solutions/visibility-measurement/","visibility and measurement",[150,154,158],{"text":151,"config":152},"Visibility & Measurement",{"href":147,"dataGaLocation":42,"dataGaName":153},"Visibility and Measurement",{"text":155,"config":156},"Value Stream Management",{"href":157,"dataGaLocation":42,"dataGaName":155},"/solutions/value-stream-management/",{"text":159,"config":160},"Analytics & Insights",{"href":161,"dataGaLocation":42,"dataGaName":162},"/solutions/analytics-and-insights/","Analytics and insights",{"title":164,"items":165},"GitLab for",[166,171,176],{"text":167,"config":168},"Enterprise",{"href":169,"dataGaLocation":42,"dataGaName":170},"/enterprise/","enterprise",{"text":172,"config":173},"Small Business",{"href":174,"dataGaLocation":42,"dataGaName":175},"/small-business/","small business",{"text":177,"config":178},"Public Sector",{"href":179,"dataGaLocation":42,"dataGaName":180},"/solutions/public-sector/","public sector",{"text":182,"config":183},"Pricing",{"href":184,"dataGaName":185,"dataGaLocation":42,"dataNavLevelOne":185},"/pricing/","pricing",{"text":187,"config":188,"link":190,"lists":194,"feature":274},"Resources",{"dataNavLevelOne":189},"resources",{"text":191,"config":192},"View all resources",{"href":193,"dataGaName":189,"dataGaLocation":42},"/resources/",[195,228,246],{"title":196,"items":197},"Getting started",[198,203,208,213,218,223],{"text":199,"config":200},"Install",{"href":201,"dataGaName":202,"dataGaLocation":42},"/install/","install",{"text":204,"config":205},"Quick start guides",{"href":206,"dataGaName":207,"dataGaLocation":42},"/get-started/","quick setup checklists",{"text":209,"config":210},"Learn",{"href":211,"dataGaLocation":42,"dataGaName":212},"https://university.gitlab.com/","learn",{"text":214,"config":215},"Product documentation",{"href":216,"dataGaName":217,"dataGaLocation":42},"https://docs.gitlab.com/","product documentation",{"text":219,"config":220},"Best practice videos",{"href":221,"dataGaName":222,"dataGaLocation":42},"/getting-started-videos/","best practice videos",{"text":224,"config":225},"Integrations",{"href":226,"dataGaName":227,"dataGaLocation":42},"/integrations/","integrations",{"title":229,"items":230},"Discover",[231,236,241],{"text":232,"config":233},"Customer success stories",{"href":234,"dataGaName":235,"dataGaLocation":42},"/customers/","customer success stories",{"text":237,"config":238},"Blog",{"href":239,"dataGaName":240,"dataGaLocation":42},"/blog/","blog",{"text":242,"config":243},"Remote",{"href":244,"dataGaName":245,"dataGaLocation":42},"https://handbook.gitlab.com/handbook/company/culture/all-remote/","remote",{"title":247,"items":248},"Connect",[249,254,259,264,269],{"text":250,"config":251},"GitLab Services",{"href":252,"dataGaName":253,"dataGaLocation":42},"/services/","services",{"text":255,"config":256},"Community",{"href":257,"dataGaName":258,"dataGaLocation":42},"/community/","community",{"text":260,"config":261},"Forum",{"href":262,"dataGaName":263,"dataGaLocation":42},"https://forum.gitlab.com/","forum",{"text":265,"config":266},"Events",{"href":267,"dataGaName":268,"dataGaLocation":42},"/events/","events",{"text":270,"config":271},"Partners",{"href":272,"dataGaName":273,"dataGaLocation":42},"/partners/","partners",{"backgroundColor":275,"textColor":276,"text":277,"image":278,"link":282},"#2f2a6b","#fff","Insights for the future of software development",{"altText":279,"config":280},"the source promo card",{"src":281},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1758208064/dzl0dbift9xdizyelkk4.svg",{"text":283,"config":284},"Read the latest",{"href":285,"dataGaName":286,"dataGaLocation":42},"/the-source/","the source",{"text":288,"config":289,"lists":291},"Company",{"dataNavLevelOne":290},"company",[292],{"items":293},[294,299,305,307,312,317,322,327,332,337,342],{"text":295,"config":296},"About",{"href":297,"dataGaName":298,"dataGaLocation":42},"/company/","about",{"text":300,"config":301,"footerGa":304},"Jobs",{"href":302,"dataGaName":303,"dataGaLocation":42},"/jobs/","jobs",{"dataGaName":303},{"text":265,"config":306},{"href":267,"dataGaName":268,"dataGaLocation":42},{"text":308,"config":309},"Leadership",{"href":310,"dataGaName":311,"dataGaLocation":42},"/company/team/e-group/","leadership",{"text":313,"config":314},"Team",{"href":315,"dataGaName":316,"dataGaLocation":42},"/company/team/","team",{"text":318,"config":319},"Handbook",{"href":320,"dataGaName":321,"dataGaLocation":42},"https://handbook.gitlab.com/","handbook",{"text":323,"config":324},"Investor relations",{"href":325,"dataGaName":326,"dataGaLocation":42},"https://ir.gitlab.com/","investor relations",{"text":328,"config":329},"Trust Center",{"href":330,"dataGaName":331,"dataGaLocation":42},"/security/","trust center",{"text":333,"config":334},"AI Transparency Center",{"href":335,"dataGaName":336,"dataGaLocation":42},"/ai-transparency-center/","ai transparency center",{"text":338,"config":339},"Newsletter",{"href":340,"dataGaName":341,"dataGaLocation":42},"/company/contact/#contact-forms","newsletter",{"text":343,"config":344},"Press",{"href":345,"dataGaName":346,"dataGaLocation":42},"/press/","press",{"text":348,"config":349,"lists":350},"Contact us",{"dataNavLevelOne":290},[351],{"items":352},[353,356,361],{"text":49,"config":354},{"href":51,"dataGaName":355,"dataGaLocation":42},"talk to sales",{"text":357,"config":358},"Support portal",{"href":359,"dataGaName":360,"dataGaLocation":42},"https://support.gitlab.com","support portal",{"text":362,"config":363},"Customer portal",{"href":364,"dataGaName":365,"dataGaLocation":42},"https://customers.gitlab.com/customers/sign_in/","customer portal",{"close":367,"login":368,"suggestions":375},"Close",{"text":369,"link":370},"To search repositories and projects, login to",{"text":371,"config":372},"gitlab.com",{"href":56,"dataGaName":373,"dataGaLocation":374},"search login","search",{"text":376,"default":377},"Suggestions",[378,380,384,386,390,394],{"text":71,"config":379},{"href":76,"dataGaName":71,"dataGaLocation":374},{"text":381,"config":382},"Code Suggestions (AI)",{"href":383,"dataGaName":381,"dataGaLocation":374},"/solutions/code-suggestions/",{"text":105,"config":385},{"href":107,"dataGaName":105,"dataGaLocation":374},{"text":387,"config":388},"GitLab on AWS",{"href":389,"dataGaName":387,"dataGaLocation":374},"/partners/technology-partners/aws/",{"text":391,"config":392},"GitLab on Google Cloud",{"href":393,"dataGaName":391,"dataGaLocation":374},"/partners/technology-partners/google-cloud-platform/",{"text":395,"config":396},"Why GitLab?",{"href":84,"dataGaName":395,"dataGaLocation":374},{"freeTrial":398,"mobileIcon":403,"desktopIcon":408,"secondaryButton":411},{"text":399,"config":400},"Start free trial",{"href":401,"dataGaName":47,"dataGaLocation":402},"https://gitlab.com/-/trials/new/","nav",{"altText":404,"config":405},"Gitlab Icon",{"src":406,"dataGaName":407,"dataGaLocation":402},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1758203874/jypbw1jx72aexsoohd7x.svg","gitlab icon",{"altText":404,"config":409},{"src":410,"dataGaName":407,"dataGaLocation":402},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1758203875/gs4c8p8opsgvflgkswz9.svg",{"text":412,"config":413},"Get Started",{"href":414,"dataGaName":415,"dataGaLocation":402},"https://gitlab.com/-/trial_registrations/new?glm_source=about.gitlab.com/get-started/","get started",{"freeTrial":417,"mobileIcon":421,"desktopIcon":423},{"text":418,"config":419},"Learn more about GitLab Duo",{"href":76,"dataGaName":420,"dataGaLocation":402},"gitlab duo",{"altText":404,"config":422},{"src":406,"dataGaName":407,"dataGaLocation":402},{"altText":404,"config":424},{"src":410,"dataGaName":407,"dataGaLocation":402},{"button":426,"mobileIcon":431,"desktopIcon":433},{"text":427,"config":428},"/switch",{"href":429,"dataGaName":430,"dataGaLocation":402},"#contact","switch",{"altText":404,"config":432},{"src":406,"dataGaName":407,"dataGaLocation":402},{"altText":404,"config":434},{"src":435,"dataGaName":407,"dataGaLocation":402},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1773335277/ohhpiuoxoldryzrnhfrh.png",{"freeTrial":437,"mobileIcon":442,"desktopIcon":444},{"text":438,"config":439},"Back to pricing",{"href":184,"dataGaName":440,"dataGaLocation":402,"icon":441},"back to pricing","GoBack",{"altText":404,"config":443},{"src":406,"dataGaName":407,"dataGaLocation":402},{"altText":404,"config":445},{"src":410,"dataGaName":407,"dataGaLocation":402},{"title":447,"button":448,"config":453},"See how agentic AI transforms software delivery",{"text":449,"config":450},"Watch GitLab Transcend now",{"href":451,"dataGaName":452,"dataGaLocation":42},"/events/transcend/virtual/","transcend event",{"layout":454,"icon":455,"disabled":11},"release","AiStar",{"data":457},{"text":458,"source":459,"edit":465,"contribute":470,"config":475,"items":480,"minimal":686},"Git is a trademark of Software Freedom Conservancy and our use of 'GitLab' is under license",{"text":460,"config":461},"View page source",{"href":462,"dataGaName":463,"dataGaLocation":464},"https://gitlab.com/gitlab-com/marketing/digital-experience/about-gitlab-com/","page source","footer",{"text":466,"config":467},"Edit this page",{"href":468,"dataGaName":469,"dataGaLocation":464},"https://gitlab.com/gitlab-com/marketing/digital-experience/about-gitlab-com/-/blob/main/content/","web ide",{"text":471,"config":472},"Please contribute",{"href":473,"dataGaName":474,"dataGaLocation":464},"https://gitlab.com/gitlab-com/marketing/digital-experience/about-gitlab-com/-/blob/main/CONTRIBUTING.md/","please contribute",{"twitter":476,"facebook":477,"youtube":478,"linkedin":479},"https://twitter.com/gitlab","https://www.facebook.com/gitlab","https://www.youtube.com/channel/UCnMGQ8QHMAnVIsI3xJrihhg","https://www.linkedin.com/company/gitlab-com",[481,528,581,625,652],{"title":182,"links":482,"subMenu":497},[483,487,492],{"text":484,"config":485},"View plans",{"href":184,"dataGaName":486,"dataGaLocation":464},"view plans",{"text":488,"config":489},"Why Premium?",{"href":490,"dataGaName":491,"dataGaLocation":464},"/pricing/premium/","why premium",{"text":493,"config":494},"Why Ultimate?",{"href":495,"dataGaName":496,"dataGaLocation":464},"/pricing/ultimate/","why ultimate",[498],{"title":499,"links":500},"Contact Us",[501,504,506,508,513,518,523],{"text":502,"config":503},"Contact sales",{"href":51,"dataGaName":52,"dataGaLocation":464},{"text":357,"config":505},{"href":359,"dataGaName":360,"dataGaLocation":464},{"text":362,"config":507},{"href":364,"dataGaName":365,"dataGaLocation":464},{"text":509,"config":510},"Status",{"href":511,"dataGaName":512,"dataGaLocation":464},"https://status.gitlab.com/","status",{"text":514,"config":515},"Terms of use",{"href":516,"dataGaName":517,"dataGaLocation":464},"/terms/","terms of use",{"text":519,"config":520},"Privacy statement",{"href":521,"dataGaName":522,"dataGaLocation":464},"/privacy/","privacy statement",{"text":524,"config":525},"Cookie preferences",{"dataGaName":526,"dataGaLocation":464,"id":527,"isOneTrustButton":11},"cookie preferences","ot-sdk-btn",{"title":87,"links":529,"subMenu":537},[530,533],{"text":25,"config":531},{"href":69,"dataGaName":532,"dataGaLocation":464},"devsecops platform",{"text":534,"config":535},"AI-Assisted Development",{"href":76,"dataGaName":536,"dataGaLocation":464},"ai-assisted development",[538],{"title":539,"links":540},"Topics",[541,546,551,556,561,566,571,576],{"text":542,"config":543},"CICD",{"href":544,"dataGaName":545,"dataGaLocation":464},"/topics/ci-cd/","cicd",{"text":547,"config":548},"GitOps",{"href":549,"dataGaName":550,"dataGaLocation":464},"/topics/gitops/","gitops",{"text":552,"config":553},"DevOps",{"href":554,"dataGaName":555,"dataGaLocation":464},"/topics/devops/","devops",{"text":557,"config":558},"Version Control",{"href":559,"dataGaName":560,"dataGaLocation":464},"/topics/version-control/","version control",{"text":562,"config":563},"DevSecOps",{"href":564,"dataGaName":565,"dataGaLocation":464},"/topics/devsecops/","devsecops",{"text":567,"config":568},"Cloud Native",{"href":569,"dataGaName":570,"dataGaLocation":464},"/topics/cloud-native/","cloud native",{"text":572,"config":573},"AI for Coding",{"href":574,"dataGaName":575,"dataGaLocation":464},"/topics/devops/ai-for-coding/","ai for coding",{"text":577,"config":578},"Agentic AI",{"href":579,"dataGaName":580,"dataGaLocation":464},"/topics/agentic-ai/","agentic ai",{"title":582,"links":583},"Solutions",[584,586,588,593,597,600,604,607,609,612,615,620],{"text":129,"config":585},{"href":124,"dataGaName":129,"dataGaLocation":464},{"text":118,"config":587},{"href":101,"dataGaName":102,"dataGaLocation":464},{"text":589,"config":590},"Agile development",{"href":591,"dataGaName":592,"dataGaLocation":464},"/solutions/agile-delivery/","agile delivery",{"text":594,"config":595},"SCM",{"href":114,"dataGaName":596,"dataGaLocation":464},"source code management",{"text":542,"config":598},{"href":107,"dataGaName":599,"dataGaLocation":464},"continuous integration & delivery",{"text":601,"config":602},"Value stream management",{"href":157,"dataGaName":603,"dataGaLocation":464},"value stream management",{"text":547,"config":605},{"href":606,"dataGaName":550,"dataGaLocation":464},"/solutions/gitops/",{"text":167,"config":608},{"href":169,"dataGaName":170,"dataGaLocation":464},{"text":610,"config":611},"Small business",{"href":174,"dataGaName":175,"dataGaLocation":464},{"text":613,"config":614},"Public sector",{"href":179,"dataGaName":180,"dataGaLocation":464},{"text":616,"config":617},"Education",{"href":618,"dataGaName":619,"dataGaLocation":464},"/solutions/education/","education",{"text":621,"config":622},"Financial services",{"href":623,"dataGaName":624,"dataGaLocation":464},"/solutions/finance/","financial services",{"title":187,"links":626},[627,629,631,633,636,638,640,642,644,646,648,650],{"text":199,"config":628},{"href":201,"dataGaName":202,"dataGaLocation":464},{"text":204,"config":630},{"href":206,"dataGaName":207,"dataGaLocation":464},{"text":209,"config":632},{"href":211,"dataGaName":212,"dataGaLocation":464},{"text":214,"config":634},{"href":216,"dataGaName":635,"dataGaLocation":464},"docs",{"text":237,"config":637},{"href":239,"dataGaName":240,"dataGaLocation":464},{"text":232,"config":639},{"href":234,"dataGaName":235,"dataGaLocation":464},{"text":242,"config":641},{"href":244,"dataGaName":245,"dataGaLocation":464},{"text":250,"config":643},{"href":252,"dataGaName":253,"dataGaLocation":464},{"text":255,"config":645},{"href":257,"dataGaName":258,"dataGaLocation":464},{"text":260,"config":647},{"href":262,"dataGaName":263,"dataGaLocation":464},{"text":265,"config":649},{"href":267,"dataGaName":268,"dataGaLocation":464},{"text":270,"config":651},{"href":272,"dataGaName":273,"dataGaLocation":464},{"title":288,"links":653},[654,656,658,660,662,664,666,670,675,677,679,681],{"text":295,"config":655},{"href":297,"dataGaName":290,"dataGaLocation":464},{"text":300,"config":657},{"href":302,"dataGaName":303,"dataGaLocation":464},{"text":308,"config":659},{"href":310,"dataGaName":311,"dataGaLocation":464},{"text":313,"config":661},{"href":315,"dataGaName":316,"dataGaLocation":464},{"text":318,"config":663},{"href":320,"dataGaName":321,"dataGaLocation":464},{"text":323,"config":665},{"href":325,"dataGaName":326,"dataGaLocation":464},{"text":667,"config":668},"Sustainability",{"href":669,"dataGaName":667,"dataGaLocation":464},"/sustainability/",{"text":671,"config":672},"Diversity, inclusion and belonging (DIB)",{"href":673,"dataGaName":674,"dataGaLocation":464},"/diversity-inclusion-belonging/","Diversity, inclusion and belonging",{"text":328,"config":676},{"href":330,"dataGaName":331,"dataGaLocation":464},{"text":338,"config":678},{"href":340,"dataGaName":341,"dataGaLocation":464},{"text":343,"config":680},{"href":345,"dataGaName":346,"dataGaLocation":464},{"text":682,"config":683},"Modern Slavery Transparency Statement",{"href":684,"dataGaName":685,"dataGaLocation":464},"https://handbook.gitlab.com/handbook/legal/modern-slavery-act-transparency-statement/","modern slavery transparency statement",{"items":687},[688,691,694],{"text":689,"config":690},"Terms",{"href":516,"dataGaName":517,"dataGaLocation":464},{"text":692,"config":693},"Cookies",{"dataGaName":526,"dataGaLocation":464,"id":527,"isOneTrustButton":11},{"text":695,"config":696},"Privacy",{"href":521,"dataGaName":522,"dataGaLocation":464},[698],{"id":699,"title":19,"body":8,"config":700,"content":702,"description":8,"extension":26,"meta":706,"navigation":11,"path":707,"seo":708,"stem":709,"__hash__":710},"blogAuthors/en-us/blog/authors/bill-staples.yml",{"template":701},"BlogAuthor",{"name":19,"config":703,"role":705},{"headshot":704},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1750434080/glxv59lh9qftpdbsb4ph.png","CEO",{},"/en-us/blog/authors/bill-staples",{},"en-us/blog/authors/bill-staples","K-ulWVa7KOFAxgiGSmeiIjz3KeQyIkhm95lIRX_r6Zc",[712,728,741],{"content":713,"config":726},{"title":714,"description":715,"authors":716,"body":719,"heroImage":720,"date":721,"category":9,"tags":722},"GitLab and Vertex AI on Google Cloud: Advancing agentic software development","Learn how Google Cloud customers are standardizing on GitLab and Vertex AI for foundation models, enterprise controls, and Model Garden breadth.\n",[717,718],"Regnard Raquedan","Rajesh Agadi","GitLab Duo Agent Platform is helping redefine how organizations build, secure, and deliver software. Since its general availability in January 2026, the platform is bringing agentic AI to every phase of the software development lifecycle. Duo Agent Platform is an intelligent orchestration layer where software teams, and their specialized agents plan, code, review, and remediate security vulnerabilities together.\n\nThrough this exciting partnership, [GitLab Duo Agent Platform](https://about.gitlab.com/gitlab-duo-agent-platform/) automates software development orchestration and lifecycle context via its integration with Vertex AI on Google Cloud, which powers the model tier for agent calls. Software teams keep working on issues, merge requests, pipelines, and security workflows while inference follows the Google Cloud posture they already defined. \n\nAdvances in Google Cloud’s Vertex AI models expand how Google Cloud customers can use GitLab Duo Agent Platform in their environment. Customers get an AI-powered DevSecOps control plane in GitLab, backed by a rapidly advancing AI infrastructure foundation in Vertex AI and Duo Agent Platform’s flexible deployment and integration options. The combination enables more capable, governed agentic workflows that operate at enterprise scale.\n\n![Conceptual illustration of the GitLab Duo Agent Platform integrated with Google Cloud's Vertex AI to power agentic software development and governed AI workflows](https://res.cloudinary.com/about-gitlab-com/image/upload/v1776165990/b7jlux9kydafncwy8spc.png)\n\n## Agents that work across the full lifecycle\n\nMany AI tools focus on a single task: generating code faster. GitLab Duo Agent Platform goes further. It orchestrates AI agents across the entire software development lifecycle (SDLC), from planning through security review to delivery, across many teams with many projects and releases. At this scale, AI coding assistants are necessary for continuous innovation but not sufficient. \n\nSingle-purpose coding assistants rarely see the full state of a project. Backlog shape, open merge requests, failing jobs, and security findings live in GitLab, but a separate chat window in a coding assistant does not inherit that full picture of the SDLC. The gap shows up as manual handoffs, duplicate explanations to an AI that lacks context, and governance teams trying to map data flows across tools that were never designed as one system.\n\nGitLab Duo Agent Platform helps close that gap by running agents and flows on the same objects engineers use every day. Vertex AI then supplies the models and services those agents call when Google Cloud is your chosen inference home, with GitLab’s AI Gateway mediating access so administrators keep a clear map of what connects to what. For instance, GitLab Duo Planner Agent analyzes backlogs, breaks epics into structured tasks, and applies prioritization frameworks to help teams decide what to build next. Security Analyst Agent triages vulnerabilities, details risks in plain language, and recommends remediation in priority order. Built-in flows connect these agents into end-to-end processes, without requiring developers to manage every handoff manually.\n\nAgentic Chat in GitLab Duo Agent Platform ties the experience together for developers. They query in natural language to get context-aware responses with multi-step reasoning that draws on the full state of a project: its issues, merge requests, pipelines, security findings, and codebase. Because GitLab serves as the system of record for the SDLC with a unified data model, GitLab Duo agents operate with lifecycle context that falls outside the reach of standalone, tool-specific AI assistants.\n\n### Amplified by Vertex AI\n\nGitLab Duo Agent Platform is designed to be model-flexible, routing different capabilities to different models based on what performs best for a given task. That architectural choice pays off on Google Cloud, where Vertex AI acts as the managed environment for foundation models and related services, providing a broad model ecosystem and managed infrastructure that helps push the platform's capabilities further.\n\nThe latest generations of AI models available through Vertex AI bring significant improvements in reasoning, tool use, and long-context understanding compared to previous iterations — the same properties that GitLab's agents rely on across many projects and teams with large, complex codebases. Longer context windows and richer tool integration in the underlying models expand what agents can accomplish in a single pass, which is especially important for workloads like deep backlog analysis or monorepo security review.\n\n[Vertex AI Model Garden](https://cloud.google.com/model-garden), with access to a wide range of foundation models, gives customers the breadth to make these choices based on performance, cost, and regulatory requirements rather than vendor lock-in.\n\nMoreover, GitLab customers can use Bring Your Own Model (BYOM) for Duo Agent Platform so approved providers and gateways land where your security model expects them. GitLab’s [18.9 launch coverage of self-hosted Duo Agent Platform and BYOM](https://about.gitlab.com/blog/agentic-ai-enterprise-control-self-hosted-duo-agent-platform-and-byom/) describes how that wiring works. With this deployment option, customers gain access to a wider set of model options they can tailor to their software development process: the right model for the right workflow, with the right guardrails.\n\nFor GitLab, the decision to build on Vertex AI was driven by the need for enterprise-grade reliability and unparalleled model breadth. Vertex AI and Model Garden completely abstract the heavy lifting of LLM hosting — meaning rapid version delivery, robust security, and strict governance are seamlessly built into the integration. Beyond offering Gemini models, Vertex AI provides global, low-latency access to a vast catalog of third-party and open-source models. \n\nCombined with Google Cloud's industry-leading approach to data privacy and model protection, Vertex AI emerged as the clear choice to power GitLab's next-generation developer experience. \n\nBy integrating Vertex AI Model Garden into its backend, GitLab supercharges its DevSecOps platform without passing any complexity on to users. Development teams are not burdened with evaluating or managing underlying LLMs; instead, they experience a streamlined, AI-assisted workflow for building their applications. \n\nGitLab completely abstracts cloud orchestration, enabling developers to focus entirely on writing great code, while Vertex AI powers the features and functionality that assist them.\n\n## What this means for customers on Google Cloud\n\nGitLab Duo Agent Platform already delivers AI agents that operate across the full software lifecycle within a single, governed system of record. On Google Cloud, it enables rapid innovation as Vertex AI continues to advance the model and infrastructure layers. \n\nFor Google Cloud customers, this integration means streamlined software delivery while maintaining strict enterprise governance. For platform engineering groups, it means normalizing which Vertex-backed models power suggestions, analysis, and remediation inside GitLab instead of cataloging dozens of client-side tools. Security programs benefit when agents propose and validate fixes in the same place developers already triage findings, cutting context switching and reducing work that would otherwise spill into unmanaged channels.\n\nFrom a cloud economics and policy angle, drawing agent inference toward Vertex from within GitLab keeps usage nearer to the agreements and controls you already run on Google Cloud, which helps avoid duplicate spend and shadow paths that bypass procurement.\n\nBecause Vertex AI is an underlying infrastructure provider for GitLab Duo Agent Platform, organizations are enabled to dramatically lift developer productivity without the overhead and risk of managing fragmented AI toolchains. Teams stay aligned within a single, secure system of record, helping them build applications faster and ship with confidence.\n\nThe GitLab and Google Cloud collaboration has been building since 2018. Today, it represents one of the most comprehensive paths for organizations moving from AI experiments to fully governed, agentic software development on Google Cloud. As both platforms continue to advance — GitLab expanding its agent orchestration and developer context, and Vertex AI pushing the boundaries of model capability and agent infrastructure — the value for joint customers will continue to grow.\n\n> [Start a free trial of GitLab Duo Agent Platform](https://about.gitlab.com/free-trial/) to experience the power of GitLab and Vertex AI on Google Cloud.","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749663121/Blog/Hero%20Images/LogoLockupPlusLight.png","2026-04-14",[723,273,724,725,24],"AI/ML","google","news",{"featured":11,"template":12,"slug":727},"gitlab-and-vertex-ai-on-google-cloud",{"content":729,"config":739},{"heroImage":730,"title":731,"description":732,"authors":733,"date":735,"category":9,"tags":736,"body":738},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643639/sapu29gmlgtwvhggmj6k.png","Extend GitLab Duo Agent Platform: Connect any tool with MCP","Learn how to connect external tools to GitLab Duo Agent Platform using MCP. Step-by-step setup with three practical workflow demos.",[734],"Albert Rabassa","2026-03-05",[9,24,737],"tutorial","Managing software development often means juggling multiple tools: tracking issues in Jira, writing code in your IDE, and collaborating through GitLab. Context switching between these platforms disrupts focus and slows down delivery.\n\nWith GitLab Duo Agent Platform's [MCP](https://about.gitlab.com/topics/ai/model-context-protocol/) support, you can now connect Jira or any tool that supports MCP directly to your AI-powered development environment. Query issues, update tickets, and sync your workflow — all through natural language, without ever leaving your IDE.\n\n## What you'll learn\n\nIn this tutorial, we'll walk you through:\n\n* **Setting up the Jira/Atlassian OAuth application** for secure authentication\n* **Configuring GitLab Duo Agent Platform** as an MCP client\n* **Three practical use cases** demonstrating real-world workflows\n\n## Prerequisites\n\nBefore getting started, ensure you have the following:\n\n| Requirement | Details |\n| ---- | ----- |\n| **GitLab instance** | GitLab 18.8+ with Duo Agent Platform enabled |\n| **Jira account** | Jira Cloud instance with admin access to create OAuth applications |\n| **IDE** | Visual Studio Code with GitLab Workflow extension installed |\n| **MCP support** | MCP support enabled in GitLab |\n\n\n## Understanding the architecture\n\nGitLab Duo Agent Platform acts as an **MCP client**, connecting to the Atlassian MCP server to access your Jira project management data. Atlassian  MCP server handles authentication, translates natural language requests into API calls, and returns structured data back to GitLab Duo Agent Platform — all while maintaining security and audit controls.\n\n## Part 1: Configure Jira OAuth application\n\nTo securely connect GitLab Duo Agent Platform to your Jira instance, you'll need to create an OAuth 2.0 application in the Atlassian Developer Console. This grants to GitLab the MCP server authorized access to your Jira data.\n\n### Setup steps\n\nIf you prefer to configure manually, follow these steps:\n\n1. **Navigate to the Atlassian Developer Console**\n\n   * Go to [developer.atlassian.com/console/myapps](https://developer.atlassian.com/console/myapps)\n\n   * Sign in with your Atlassian account\n\n2. **Create a new OAuth 2.0 app**\n\n   * Click **Create** → **OAuth 2.0 integration**\n\n   * Enter a name (e.g., \"gitlab-dap-mcp\")\n\n   * Accept the terms and click **Create**\n\n3. **Configure permissions**\n\n   * Navigate to **Permissions** in the left sidebar.\n\n   * Add **Jira API** and configure the following scopes:\n\n     * `read:jira-work` — Read issues, projects, and boards\n\n     * `write:jira-work` — Create and update issues\n\n     * `read:jira-user` — Read user information\n\n4. **Set up authorization**\n\n   * Go to **Authorization** in the left sidebar\n\n   * Add a callback URL for your environment (`https://gitlab.com/oauth/callback`)\n\n   * Save your changes\n\n5. **Retrieve credentials**\n\n   * Navigate to **Settings**\n\n   * Copy your **Client ID** and **Client Secret**\n\n   * Store these securely — you'll need them for the MCP configuration\n\n\n### Interactive walkthrough: Jira OAuth setup\n\nClick on the image below to get started.\n\n\n[![Jira OAuth setup tour](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772644850/wnzfoq43nkkfmgdqldmr.png)](https://gitlab.navattic.com/jira-oauth-setup)\n\n\n## Part 2: Configure GitLab Duo Agent Platform MCP client\n\nWith your OAuth credentials ready, you can now configure GitLab Duo Agent Platform to connect to the Atlassian MCP server.\n\n### Create your MCP configuration file\n\nCreate the MCP configuration file in your GitLab project at `.gitlab/duo/mcp.json`:\n\n\n```json\n{\n  \"mcpServers\": {\n    \"atlassian\": {\n      \"type\": \"http\",\n      \"url\": \"https://mcp.atlassian.com/v1/mcp\",\n      \"auth\": {\n        \"type\": \"oauth2\",\n        \"clientId\": \"YOUR_CLIENT_ID\",\n        \"clientSecret\": \"YOUR_CLIENT_SECRET\",\n        \"authorizationUrl\": \"https://auth.atlassian.com/oauth/authorize\",\n        \"tokenUrl\": \"https://auth.atlassian.com/oauth/token\"\n      },\n      \"approvedTools\": true\n    }\n  }\n}\n```\n\nReplace `YOUR_CLIENT_ID` and `YOUR_CLIENT_SECRET` with the credentials you generated in Part 1.\n\n### Enable MCP in GitLab\n\n1. Navigate to your **Group Settings** → **GitLab Duo** → **Configuration**\n2. Make sure “Allow external MCP tools” is checked\n\n### Verify the connection\n\nOpen your project in VS Code and ask in GitLab Duo Agent Platform chat:\n\n```text\nWhat MCP tools do you have access to?\n```\n\nThen\n\n```text\nTest the MCP JIRA configuration in this project\n```\n\nAt this point you'll be redirected from the IDE to the MCP Atlassian website to approve access:\n\n![Redirect to MCP Atlassian website](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643461/z5acqjgguh0damnnde9g.png \"Redirect to MCP Atlassian website\")\n\n\u003Cbr>\u003C/br>\n\n![Approve access](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643461/rwowamm8nsubhpixtn3i.png \"Approve access\")\n\n\u003Cbr>\u003C/br>\n\n![Select your JIRA instance and approve](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643461/chuzqd0jeptfwvoj7wjr.png \"Select your JIRA instance and approve\")\n\n\u003Cbr>\u003C/br>\n\n![Success!](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643462/bsgti5iste2bzck19o5y.png \"Success!\")\n\n\u003Cbr>\u003C/br>\n\n### Verify with the MCP Dashboard\n\nGitLab also provides a built-in **MCP Dashboard** directly in your IDE for this.\n\nIn VS Code or VSCodium, open the Command Palette (`Cmd+Shift+P` on macOS, `Ctrl+Shift+P` on Windows/Linux) and search for **\"GitLab: Show MCP Dashboard\"**. The dashboard opens in a new editor tab and gives you:\n\n* **Connection status** for each configured MCP server\n* **Available tools** exposed by the server (e.g., `jira_get_issue`, `jira_create_issue`)\n* **Server logs** so you can see exactly which tools are being called in real time\n\n![MCP servers dashboard and status](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643462/mmvdfchucacsydivowvn.png \"MCP servers dashboard and status\")\n\n\u003Cbr>\u003C/br>\n\n![Server details and permissions](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643462/tcocgdvovp2dl42pvfn8.png \"Server details and permissions\")\n\n\u003Cbr>\u003C/br>\n\n\n![MCP Server logs](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772643466/mougvqqk1bozchaufsci.png \"MCP Server logs\")\n\n\u003Cbr>\u003C/br>\n\n### Interactive walkthrough: Testing MCP\n\n\u003Ciframe src=\"https://player.vimeo.com/video/1170005495?badge=0&autopause=0& player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"Testing MCP\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\n## Part 3: Use cases in action\n\nNow that your integration is configured, let's explore three practical workflows that demonstrate the power of connecting Jira to GitLab Duo Agent Platform.\n\n### Planning assistant\n\n**Scenario:** You're preparing for sprint planning and need to quickly assess the backlog, understand priorities, and identify blockers.\n\nThis demo shows you how to:\n\n* Query the backlog\n* Identify unassigned high-priority issues\n* Get AI-powered sprint recommendations\n\n#### Example prompts\n\nTry these prompts in GitLab Duo Agent Platform Chat:\n\n```text\nList all the unassigned issues in JIRA for project GITLAB\n```\n\n```text\nSuggest the two top issues to prioritize and summarize them. Assign them to me.\n```\n\n### Interactive walkthrough: Project planning\n\n\u003Ciframe src=\"https://player.vimeo.com/video/1170005462?badge=0&autopause=0&player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"Project Planning\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player. js\">\u003C/script>\n\n### Issue triage and creation from code\n\n**Scenario:** While reviewing code, you discover a bug and want to create a Jira issue with relevant context — without leaving your IDE.\n\nThis demo walks you through:\n\n* Identifying a bug while coding\n* Creating a detailed Jira issue via natural language\n* Auto-populating issue fields with code context\n* Linking the issue to your current branch\n\n#### Example prompts\n\n```text\nSearch in JIRA for a bug related to: Null pointer exception in PaymentService.processRefund().\nIf it does not exist create it with all the context needed from the code. Find possible blockers that this bug may cause.\n```\n\n```text\nCreate a new branch called issue-gitlab-18, checkout, and link it to the issue we just created. Assign the JIRA issue to me and mark it as in-progress.\n```\n\n### Interactive walkthrough: Bug review and task automation\n\n\u003Ciframe src=\"https://player.vimeo.com/video/1170005368?badge=0&autopause=0& player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"Bug Review\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\n### Cross-system incident investigation\n\n**Scenario:** A production incident occurs, and you need to correlate information from Jira (incident ticket), GitLab Project Management, your codebase, and merge requests to identify the root cause.\n\nThis demo demonstrates:\n\n* Fetching incident details from Jira\n* Correlating with recent merge requests in GitLab\n* Identifying potentially related code changes\n* Generating an incident timeline\n* Design a remediation plan and create it as a work item in GitLab\n\n#### Example prompts\n\n```text\n\"We have a production incident INC-1 about checkout failures. Can you help me investigate with all available context?\"\n```\n\n```text\nCreate a timeline of events for incident INC-1 including related Jira issues and recent deployments\n```\n\n```text\nPropose a remediation plan\n```\n\n### Interactive walkthrough: Cross-system troubleshooting and remediation\n\n\u003Ciframe src=\"https://player.vimeo.com/video/1170005413?badge=0&autopause=0& player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"Cross System Investigation\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\n## Troubleshooting\n\nThese are some common setup issues and quick fixes:\n\n| Issue | Solution |\n| ----- | ----- |\n| \"MCP server not found\" | Verify the `mcp.json` file is in the correct location and properly formatted |\n| \"Authentication failed\" | Re-check your OAuth credentials and ensure scopes are correctly configured in Atlassian |\n| \"No Jira tools available\" | Restart VS Code after updating `mcp.json` and ensure MCP is enabled in GitLab |\n| \"Connection timeout\" | Check your network connectivity to `mcp.atlassian.com` |\n\n\u003Cbr/> For detailed troubleshooting, see the [GitLab MCP clients documentation](https://docs.gitlab.com/user/gitlab_duo/model_context_protocol/mcp_clients/).\n\n\n## Security considerations\n\nWhen integrating Jira with GitLab Duo Agent Platform:\n\n* **OAuth tokens** — Make sure credentials remain secure\n* **Principle of least privilege** — Only grant the minimum required Jira scopes\n* **Token rotation** — Regularly rotate your OAuth credentials as part of security hygiene\n\n\n## Summary\n\nConnecting GitLab Duo Agent Platform to different tools through MCP transforms how you interact with your development lifecycle. In this article, you have learned how to:\n\n* **Query issues naturally** — Ask questions about your backlog, sprints, and incidents in natural language.\n* **Create and update issues on all your DevSecOps environment** — File bugs and update tickets without leaving your IDE.\n* **Correlate across systems** — Combine Jira data with GitLab project management, merge requests, and pipelines for complete visibility.\n* **Reduce context switching** — Keep your focus on code while staying connected to project management.\n\nThis integration exemplifies the power of MCP: standardized, secure access to your tools through AI, enabling developers to work more efficiently without sacrificing governance or security.\n\n\n## Read more\n\n* [GitLab Duo Agent Platform adds support for Model Context Protocol](https://about.gitlab.com/blog/duo-agent-platform-with-mcp/)\n\n* [What is Model Context Protocol?](https://about.gitlab.com/topics/ai/model-context-protocol/)\n\n* [Agentic AI guides and resources](https://about.gitlab.com/blog/agentic-ai-guides-and-resources/)\n\n* [GitLab MCP clients documentation](https://docs.gitlab.com/user/gitlab_duo/model_context_protocol/mcp_clients/)\n\n* [Get started with GitLab Duo Agent Platform: The complete guide](https://about.gitlab.com/blog/gitlab-duo-agent-platform-complete-getting-started-guide/)",{"featured":31,"template":12,"slug":740},"extend-gitlab-duo-agent-platform-connect-any-tool-with-mcp",{"content":742,"config":752},{"title":743,"description":744,"authors":745,"heroImage":747,"date":748,"body":749,"category":9,"tags":750},"10 AI prompts to speed your team’s software delivery","Eliminate review backlogs, security delays, and coordination overhead with ready-to-use AI prompts covering every stage of the software lifecycle.",[746],"Chandler Gibbons","https://res.cloudinary.com/about-gitlab-com/image/upload/v1772632341/duj8vaznbhtyxxhodb17.png","2026-03-04","AI-assisted coding tools are helping developers generate code faster than ever. So why aren’t teams _shipping_ faster?\n\nBecause coding is only 20% of the software delivery lifecycle, the remaining 80% becomes the bottleneck: code review backlogs grow, security scanning can’t keep pace, documentation falls behind, and manual coordination overhead increases.\n\nThe good news is that the same AI capabilities that accelerate individual coding can eliminate these team-level delays. You just need to apply AI across your entire software lifecycle, not only during the coding phase.\n\nBelow are 10 ready-to-use prompts from the [GitLab Duo Agent Platform Prompt Library](https://about.gitlab.com/gitlab-duo/prompt-library/) that help teams overcome common obstacles to faster software delivery. Each prompt addresses a specific slowdown that emerges when individual productivity increases without corresponding improvements in team processes.\n\n## How do you move code review from bottleneck to accelerator?\nDevelopers generate merge requests faster with AI assistance, but human reviewers can quickly become overwhelmed as code review cycles stretch from hours to days. AI can handle routine review tasks, freeing reviewers to focus on architecture and business logic instead of catching basic logical errors and API contract violations.\n\n### Review MR for logical errors\n**Complexity**: Beginner\n\n**Category**: Code Review\n\n**Prompt from library**:\n\n\n```text\nReview this MR for logical errors, edge cases, and potential bugs: [MR URL or paste code]\n```\n\n**Why it helps**: Automated linters catch syntax issues, but logical errors require understanding intent. This prompt catches bugs before human reviewers even look at the code, reducing review cycles from multiple rounds to often just one approval.\n\n### Identify breaking changes in MR\n**Complexity**: Beginner\n\n**Category**: Code Review\n\n**Prompt from library**:\n\n\n```text\nDoes this MR introduce any breaking changes?\n\nChanges:\n[PASTE CODE DIFF]\n\nCheck for:\n1. API signature changes\n2. Removed or renamed public methods\n3. Changed return types\n4. Modified database schemas\n5. Breaking configuration changes\n```\n\n**Why it helps**: Breaking changes discovered during deployment can cause rollbacks and incidents. This prompt shifts that discovery left to the MR stage, when fixes are faster and less expensive.\n\n## How can you shift security left without slowing down?\nSecurity scans generate hundreds of findings. Security teams manually triage each one while developers wait for approval to deploy. Most findings are false positives or low-risk issues, but identifying the real threats requires expertise and time. AI can prioritize findings by actual exploitability and auto-remediate common vulnerabilities, allowing security teams to focus on the threats that matter.\n\n### Analyze security scan results\n**Complexity**: Intermediate\n\n**Category**: Security\n\n**Agent**: Duo Security Analyst\n\n**Prompt from library**:\n\n\n```text\n@security_analyst Analyze these security scan results:\n\n[PASTE SCAN OUTPUT]\n\nFor each finding:\n1. Assess real risk vs false positive\n2. Explain the vulnerability\n3. Suggest remediation\n4. Prioritize by severity\n```\n\n**Why it helps**: Most security scan findings are false positives or low-risk issues. This prompt helps security teams focus on the findings that actually matter, reducing remediation time from weeks to days.\n\n### Review code for security issues\n**Complexity**: Intermediate\n\n**Category**: Security\n\n**Agent**: Duo Security Analyst\n\n**Prompt from library**:\n\n```text\n@security_analyst Review this code for security issues:\n\n[PASTE CODE]\n\nCheck for:\n1. Injection vulnerabilities\n2. Authentication/authorization flaws\n3. Data exposure risks\n4. Insecure dependencies\n5. Cryptographic issues\n```\n\n**Why it helps**: Traditional security reviews happen after code is written. This prompt enables developers to find and fix security issues before creating an MR, eliminating the back and forth that delays deployments.\n\n## How do you keep documentation current as code changes?\nCode changes faster than documentation. Onboarding new developers takes weeks because docs are outdated or missing. Teams know documentation is important, but it always gets deferred when deadlines approach. Automating documentation generation and updates as part of your standard workflow ensures docs stay current without adding manual work.\n\n### Generate release notes from MRs\n**Complexity**: Beginner\n\n**Category**: Documentation\n\n**Prompt from library**:\n\n```text\nGenerate release notes for these merged MRs:\n[LIST MR URLs or paste titles]\n\nGroup by:\n1. New features\n2. Bug fixes\n3. Performance improvements\n4. Breaking changes\n5. Deprecations\n```\n\n**Why it helps**: Manual release note compilation takes hours and often includes errors or omissions. Automated generation ensures every release has comprehensive notes without adding work to your release process.\n\n### Update documentation after code changes\n**Complexity**: Beginner\n\n**Category**: Documentation\n\n**Prompt from library**:\n\n```text\nI changed this code:\n\n[PASTE CODE CHANGES]\n\nWhat documentation needs updating? Check:\n1. README files\n2. API documentation\n3. Architecture diagrams\n4. Onboarding guides\n```\n\n**Why it helps**: Documentation drift happens because teams forget which docs need updates after code changes. This prompt makes documentation maintenance part of your development workflow, not a separate task that gets deferred.\n\n## How do you break down planning complexity?\nLarge features get stuck in planning. Teams spend weeks in meetings trying to scope work and identify dependencies. The complexity feels overwhelming, and it's hard to know where to start. AI can systematically decompose complex work into concrete, implementable tasks with clear dependencies and acceptance criteria, transforming weeks of planning into focused implementation.\n\n### Break down epic into issues\n**Complexity**: Intermediate\n\n**Category**: Documentation\n\n**Agent**: Duo Planner\n\n**Prompt from library**:\n\n```text\nBreak down this epic into implementable issues:\n\n[EPIC DESCRIPTION]\n\nConsider:\n1. Technical dependencies\n2. Reasonable issue sizes\n3. Clear acceptance criteria\n4. Logical implementation order\n```\n\n**Why it helps**: This prompt transforms a week of planning meetings into 30 minutes of AI-assisted decomposition followed by team review. Teams start implementation sooner with clearer direction.\n\n## How can you expand test coverage without expanding effort?\nDevelopers are writing code faster, but if testing doesn't keep pace, test coverage decreases and bugs slip through. Writing comprehensive tests manually is time-consuming, and developers often miss edge cases under deadline pressure. Generating tests automatically means developers can review and refine rather than write from scratch, maintaining quality without sacrificing velocity.\n\n### Generate unit tests\n**Complexity**: Beginner\n\n**Category**: Testing\n\n**Prompt from library**:\n\n```text\nGenerate unit tests for this function:\n\n[PASTE FUNCTION]\n\nInclude tests for:\n1. Happy path\n2. Edge cases\n3. Error conditions\n4. Boundary values\n5. Invalid inputs\n```\n\n**Why it helps**: Writing tests manually is time consuming, and developers often miss edge cases. This prompt generates thorough test suites in seconds, which developers can review and adjust rather than write from scratch.\n\n### Review test coverage gaps\n**Complexity**: Beginner\n\n**Category**: Testing\n\n**Prompt from library**:\n\n```text\nAnalyze test coverage for [MODULE/COMPONENT]:\n\nCurrent coverage: [PERCENTAGE]\n\nIdentify:\n1. Untested functions/methods\n2. Uncovered edge cases\n3. Missing error scenario tests\n4. Integration points without tests\n5. Priority areas to test next\n```\n\n**Why it helps**: This prompt reveals blind spots in your test suite before they cause production incidents. Teams can systematically improve coverage where it matters most.\n\n## How do you reduce mean time to resolution when debugging?\nProduction incidents take hours to diagnose. Developers wade through logs and stack traces while customers experience downtime. Every minute of debugging is a minute of lost productivity and potential revenue. AI can accelerate root cause analysis by parsing complex error messages and suggesting specific fixes, cutting diagnostic time from hours to minutes.\n\n### Debug failing pipeline\n**Complexity**: Beginner\n\n**Category**: Debugging\n\n**Prompt from library**:\n\n```text\nThis pipeline is failing:\n\nJob: [JOB NAME]\nStage: [STAGE]\nError: [PASTE ERROR MESSAGE/LOG]\n\nHelp me:\n1. Identify the root cause\n2. Suggest a fix\n3. Explain why it started failing\n4. Prevent similar issues\n```\n\n**Why it helps**: CI/CD failures block entire teams. This prompt diagnoses failures in seconds instead of the 15-30 minutes developers typically spend investigating, keeping deployment velocity high.\n\n## Moving from individual gains to team acceleration\nThese prompts represent a shift in how teams apply AI to software delivery. Rather than focusing solely on individual developer productivity, they address the coordination, quality, and knowledge-sharing challenges that actually constrain team velocity.\n\nThe [complete prompt library](https://about.gitlab.com/gitlab-duo/prompt-library/) contains more than 100 prompts across all stages of the software lifecycle: planning, development, security, testing, deployment, and operations. Each prompt is tagged by complexity level (Beginner, Intermediate, Advanced) and categorized by use case, making it easy to find the right starting point for your team.\n\nStart with prompts tagged “Beginner” that address your team’s most pressing obstacles. As your team builds confidence, explore intermediate and advanced prompts that enable more sophisticated workflows. The goal is not just faster coding — it's faster, safer, higher-quality software delivery from planning through production.",[723,751],"DevOps platform",{"featured":31,"template":12,"slug":753},"10-ai-prompts-to-speed-your-teams-software-delivery",{"promotions":755},[756,769,780,792],{"id":757,"categories":758,"header":759,"text":760,"button":761,"image":766},"ai-modernization",[9],"Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":762,"config":763},"Get your AI maturity score",{"href":764,"dataGaName":765,"dataGaLocation":240},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":767},{"src":768},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":770,"categories":771,"header":772,"text":760,"button":773,"image":777},"devops-modernization",[24,565],"Are you just managing tools or shipping innovation?",{"text":774,"config":775},"Get your DevOps maturity score",{"href":776,"dataGaName":765,"dataGaLocation":240},"/assessments/devops-modernization-assessment/",{"config":778},{"src":779},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":781,"categories":782,"header":784,"text":760,"button":785,"image":789},"security-modernization",[783],"security","Are you trading speed for security?",{"text":786,"config":787},"Get your security maturity score",{"href":788,"dataGaName":765,"dataGaLocation":240},"/assessments/security-modernization-assessment/",{"config":790},{"src":791},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":793,"paths":794,"header":797,"text":798,"button":799,"image":804},"github-azure-migration",[795,796],"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":800,"config":801},"See how GitLab compares to GitHub",{"href":802,"dataGaName":803,"dataGaLocation":240},"/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":805},{"src":779},{"header":807,"blurb":808,"button":809,"secondaryButton":814},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":810,"config":811},"Get your free trial",{"href":812,"dataGaName":47,"dataGaLocation":813},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":502,"config":815},{"href":51,"dataGaName":52,"dataGaLocation":813},1776443043106]