[{"data":1,"prerenderedAt":828},["ShallowReactive",2],{"/en-us/blog/beautifying-our-ui-enhancing-gitlabs-deployment-experience":3,"navigation-en-us":43,"banner-en-us":464,"footer-en-us":474,"blog-post-authors-en-us-Emily Bauman":715,"blog-related-posts-en-us-beautifying-our-ui-enhancing-gitlabs-deployment-experience":730,"blog-promotions-en-us":765,"next-steps-en-us":818},{"id":4,"title":5,"authorSlugs":6,"authors":8,"body":10,"category":11,"categorySlug":11,"config":12,"content":16,"date":25,"description":17,"extension":26,"externalUrl":27,"featured":15,"heroImage":19,"isFeatured":15,"meta":28,"navigation":29,"path":30,"publishedDate":25,"rawbody":31,"seo":32,"slug":14,"stem":36,"tagSlugs":37,"tags":41,"template":13,"updatedDate":27,"__hash__":42},"blogPosts/en-us/blog/beautifying-our-ui-enhancing-gitlabs-deployment-experience.md","Beautifying our UI: Enhancing GitLab's deployment experience",[7],"emily-bauman",[9],"Emily Bauman","At GitLab, we’ve implemented an innovative approach to improving our experience called [Beautifying our UI](https://handbook.gitlab.com/handbook/product/ux/product-design/#beautifying-our-ui). This unique initiative pairs one product designer with a frontend engineer for a milestone or two, and empowers them to make self-directed usability improvements across the platform. Ultimately, this helps build a more polished product experience, as these pairs can quickly address pain points, refine interactions, and deliver thoughtful improvements that make the platform more efficient and enjoyable to use.\n\nIn this iteration, [Anna Vovchenko](https://gitlab.com/anna_vovchenko) and I decided to focus on the continuous deployment ([CD](https://about.gitlab.com/topics/ci-cd/#what-is-continuous-deployment)) area of the product. Here is how we did it and what we learned.\n\n## Trying something new\n\nAs this was our second round going through the process, we wanted to make several small adjustments that in the end helped us deliver even more quality improvements to the product. These process improvements included:\n\n* **Extended timeline:** We decided this time around we wanted to extend the initiative to span two milestones. This gave us the time to tackle more complex problems, but also gave us space for additional planning at the start.\n* **Structured planning:** While it was encouraged in the past to work directly in merge requests, we found it helped to use the initial issue as a place to plan and seek out problems ahead of time. Rather than purely focusing on the ad-hoc, we incorporated a planning phase similar to milestone planning, helping the partnership identify and prioritize potential improvements beforehand.\n* **Product manager integration:** As we focused on one area for this round of the project, we also decided to involve the product manager of the team more actively in the process. This ensured alignment on larger changes, reduced surprises when MRs were merged and allowed us to gather valuable feedback throughout the implementation.\n* **Engaging the community:** We expanded our improvement efforts by inviting contributions from community members, accelerating our ability to implement fixes and enhancements across the platform.\n* **Strategic timing:** We chose to run this iteration during a traditionally slower period, allowing teams to focus more deeply on these improvements without competing priorities.\n\nThese refinements maintained the initiative's core strength of direct designer-engineer collaboration, while adding structure that helped our pair work more effectively.\n\n## What were the main improvements?\n\nDuring the two milestones, our pairing implemented several significant improvements that enhance the user experience across the CD space. Here's a look at what we accomplished:\n\n### Enhanced environment list view\n\nOne of the larger changes made during this cycle of \"Beautifying our UI\" was a redesigned Environment List page to make deployment information more accessible. Previously, users had to click through collapsible sections to view crucial deployment details, and viewing important details at a glance was difficult. Now, this information is immediately visible, bringing the most important deployment information to the forefront where users need it.\n\n![Beautifying UI - Environments page before](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Before_Environments_Page_aHR0cHM6_1750097793301.png)\n\n**Before:** The original design relied on collapsible sections, requiring users to click to reveal deployment information. This meant that users couldn't immediately see the status of their deployments, making it harder to quickly assess the state of their environments.\n\n![Beautifying UI - Environments page after](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/After_Environments_Page_aHR0cHM6_1750097793301.png)\n\n**After:** The new design surfaces critical deployment information directly in the list view, including:\n\n* Deployment status with clear visual indicators\n* Who triggered the deployment along with timestamps\n* Commit information and version tags\n* Actions to take on the environment\n* Latest deployment indicators\n\nThis redesign eliminates the need for extra clicks and gives users immediate visibility into their deployment and environment statuses. The new layout maintains a clean interface while presenting more actionable information upfront.\n\n### Improved deploy keys filtering\n\nAnother larger enhancement was made to our deploy keys interface to improve searchability while maintaining performance. This change addresses a critical user need for quickly finding specific deploy keys in large repositories, which was broken when pagination was introduced earlier last year.\n\n![Beautifying UI - Deploy key before](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Deploy_Key_Before_aHR0cHM6_1750097793303.png)\n\n**Before:** The previous interface displayed deploy keys in a paginated list without a dedicated search function. While pagination helped with performance when handling thousands of keys, users had lost the ability to quickly search through their deploy keys using the browser search functionality, forcing them to manually scan through multiple pages.\n\n![Beautifying UI - Deploy key after](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Deploy_Key_After_aHR0cHM6_1750097793306.png)\n\n**After:** The new design introduces a dedicated search field at the top of the deploy keys list, allowing users to:\n\n* Quickly filter deploy keys by name or SHA\n* Maintain the performance benefits of pagination\n* Find specific keys without browsing through multiple pages\n\nThis improvement strikes the right balance between performance and usability, especially beneficial for teams managing numerous deploy keys across multiple projects.\n\n### Better Kubernetes agent management\n\nWe made significant improvements to the Kubernetes agent experience by simplifying the registration process and providing better visibility into agent status. These enhancements work together to create a smoother onboarding experience for teams getting started.\n\nOur first area of focus was streamlining how users register agents when they have configuration files ready to use. Previously, this process had several pain points that we wanted to address.\n\n![Beautifying UI - Agent before](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Agent_Before_aHR0cHM6_1750097793309.png)\n\n**Before:**\n\n* Only showed connected and previously connected agents\n* Connection status was limited to \"Never connected\" or \"Not connected\"\n* No clear path to register new agents\n\n![Beautifying UI - Agent after](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Agent_After_aHR0cHM6_1750097793310.png)\n\n**After:**\n\n* Added a new Available configurations tab showing all potential agent configurations\n* Clear \"Register an agent\" call-to-action button for each available configuration\n\nNext, we turned our attention to making the agent registration modal more intuitive. The previous design created some confusion that we wanted to resolve.\n\n![Beautifying UI - Registration before](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Registration_Before_aHR0cHM6_1750097793311.png)\n\n**Before:**\n\n* Users faced a confusing dual-purpose search box that both found existing agents and created new ones\n* The workflow had too many decision points instead of a clear path forward\n* The process for creating vs. selecting an agent wasn't clearly separated\n\n![Beautifying UI - Registration after](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Registration_After_aHR0cHM6_1750097793312.png)\n\n**After:**\n\n* Separated the interface into two clear options: bootstrap with Flux or create an agent through the UI\n* Streamlined the workflow into a more linear process\n* Made the distinction between creating new agents and selecting existing ones more obvious\n* Added a success message that clearly shows where to create the optional config file\n\nThese improvements make it immediately clear which agents need attention and provide a straightforward path to register new agents. The reorganized interface better supports both new users setting up their first agent and experienced users managing multiple agents.\n\n## Additional usability enhancements\n\nWhile working on major interface improvements, we also addressed several focused usability issues that significantly improve the day-to-day experience:\n\n* **Enhanced Kubernetes pod search:** Added search functionality for Kubernetes pods on the environment page, making it easier to locate specific pods in large deployments. This was showcased in the [GitLab 17.8 release post](https://docs.gitlab.com/releases/17/gitlab-17-8-released/#search-for-pods-on-the-dashboard-for-kubernetes).\n* **Improved Flux status visibility:** Added a \"stopped\" badge to the dashboard view when Flux sync is stopped, providing immediate visibility into sync status. This was also showcased in the [GitLab 17.8 release post](https://docs.gitlab.com/releases/17/gitlab-17-8-released/#view-paused-flux-reconciliations-on-the-dashboard-for-kubernetes).\n* **Better release information:** Implemented a clear view of deployments related to a release, improving deployment tracking and visibility.\n* **Streamlined environment search:** Fixed an issue where users couldn't effectively search the Environments page, improving navigation in large environment lists.\n* **Enhanced error message display:** Resolved issues with viewing Flux details when long error messages were present, making troubleshooting more straightforward.\n\n## Looking forward\n\nThe success of these improvements demonstrates the value of empowering our teams to make direct, meaningful changes to our experience. Beyond the product enhancements, one of the most valuable outcomes has been the strengthened relationship between our Frontend and Design teams. Working together closely on these improvements has fostered better understanding of each other's perspectives, workflows, and constraints, leading to more effective collaboration.\n\nThis deepened partnership has created a foundation for even better collaboration in our regular workflow, as team members now have stronger working relationships and shared understanding of each other's domains. We're excited to continue this initiative in future iterations, not just for the product improvements it generates, but also for its role in building stronger, more cohesive teams.\n\n> [Follow along with the \"Beautifying our UI\" project](https://handbook.gitlab.com/handbook/product/ux/product-design/#beautifying-our-ui) as we continue to make improvements to GitLab.\n\n## Read more\n\n- [How we overhauled GitLab navigation](https://about.gitlab.com/blog/navigation-research-blog-post/)\n- [GitLab dark mode is getting a new look](https://about.gitlab.com/blog/gitlab-dark-mode-is-getting-a-new-look/)\n- [Beautifying our UI: Giving GitLab build features a fresh look](https://about.gitlab.com/blog/beautifying-of-our-ui/)","product",{"template":13,"slug":14,"featured":15},"BlogPost","beautifying-our-ui-enhancing-gitlabs-deployment-experience",false,{"title":5,"description":17,"authors":18,"heroImage":19,"tags":20,"category":11,"date":25,"body":10},"Go inside our innovative approach to improving our user interface, including pairing product designers and frontend engineers to make usability improvements across the platform.",[9],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097783/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%288%29_5KLUrr4DkY2u0JTMA12FVm_1750097783460.png",[21,22,23,11,24],"design","UX","UI","DevSecOps platform","2025-03-06","md",null,{},true,"/en-us/blog/beautifying-our-ui-enhancing-gitlabs-deployment-experience","---\nseo:\n  title: \"Beautifying our UI: Enhancing GitLab's deployment experience\"\n  description: >-\n    Go inside our innovative approach to improving our user interface, including\n    pairing product designers and frontend engineers to make usability\n    improvements across the platform.\n  ogTitle: \"Beautifying our UI: Enhancing GitLab's deployment experience\"\n  ogDescription: >-\n    Go inside our innovative approach to improving our user interface, including\n    pairing product designers and frontend engineers to make usability\n    improvements across the platform.\n  noIndex: false\n  ogImage: >-\n    https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097783/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%288%29_5KLUrr4DkY2u0JTMA12FVm_1750097783460.png\n  ogUrl: >-\n    https://about.gitlab.com/blog/beautifying-our-ui-enhancing-gitlabs-deployment-experience\n  ogSiteName: https://about.gitlab.com\n  ogType: article\n  canonicalUrls: >-\n    https://about.gitlab.com/blog/beautifying-our-ui-enhancing-gitlabs-deployment-experience\ntitle: \"Beautifying our UI: Enhancing GitLab's deployment experience\"\ndescription: Go inside our innovative approach to improving our user interface, including pairing product designers and frontend engineers to make usability improvements across the platform.\nauthors:\n  - Emily Bauman\nheroImage: https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097783/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%288%29_5KLUrr4DkY2u0JTMA12FVm_1750097783460.png\ntags:\n  - design\n  - UX\n  - UI\n  - product\n  - DevSecOps platform\ncategory: product\ndate: '2025-03-06'\nslug: beautifying-our-ui-enhancing-gitlabs-deployment-experience\nfeatured: false\ntemplate: BlogPost\n---\n\nAt GitLab, we’ve implemented an innovative approach to improving our experience called [Beautifying our UI](https://handbook.gitlab.com/handbook/product/ux/product-design/#beautifying-our-ui). This unique initiative pairs one product designer with a frontend engineer for a milestone or two, and empowers them to make self-directed usability improvements across the platform. Ultimately, this helps build a more polished product experience, as these pairs can quickly address pain points, refine interactions, and deliver thoughtful improvements that make the platform more efficient and enjoyable to use.\n\nIn this iteration, [Anna Vovchenko](https://gitlab.com/anna_vovchenko) and I decided to focus on the continuous deployment ([CD](https://about.gitlab.com/topics/ci-cd/#what-is-continuous-deployment)) area of the product. Here is how we did it and what we learned.\n\n## Trying something new\n\nAs this was our second round going through the process, we wanted to make several small adjustments that in the end helped us deliver even more quality improvements to the product. These process improvements included:\n\n* **Extended timeline:** We decided this time around we wanted to extend the initiative to span two milestones. This gave us the time to tackle more complex problems, but also gave us space for additional planning at the start.\n* **Structured planning:** While it was encouraged in the past to work directly in merge requests, we found it helped to use the initial issue as a place to plan and seek out problems ahead of time. Rather than purely focusing on the ad-hoc, we incorporated a planning phase similar to milestone planning, helping the partnership identify and prioritize potential improvements beforehand.\n* **Product manager integration:** As we focused on one area for this round of the project, we also decided to involve the product manager of the team more actively in the process. This ensured alignment on larger changes, reduced surprises when MRs were merged and allowed us to gather valuable feedback throughout the implementation.\n* **Engaging the community:** We expanded our improvement efforts by inviting contributions from community members, accelerating our ability to implement fixes and enhancements across the platform.\n* **Strategic timing:** We chose to run this iteration during a traditionally slower period, allowing teams to focus more deeply on these improvements without competing priorities.\n\nThese refinements maintained the initiative's core strength of direct designer-engineer collaboration, while adding structure that helped our pair work more effectively.\n\n## What were the main improvements?\n\nDuring the two milestones, our pairing implemented several significant improvements that enhance the user experience across the CD space. Here's a look at what we accomplished:\n\n### Enhanced environment list view\n\nOne of the larger changes made during this cycle of \"Beautifying our UI\" was a redesigned Environment List page to make deployment information more accessible. Previously, users had to click through collapsible sections to view crucial deployment details, and viewing important details at a glance was difficult. Now, this information is immediately visible, bringing the most important deployment information to the forefront where users need it.\n\n![Beautifying UI - Environments page before](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Before_Environments_Page_aHR0cHM6_1750097793301.png)\n\n**Before:** The original design relied on collapsible sections, requiring users to click to reveal deployment information. This meant that users couldn't immediately see the status of their deployments, making it harder to quickly assess the state of their environments.\n\n![Beautifying UI - Environments page after](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/After_Environments_Page_aHR0cHM6_1750097793301.png)\n\n**After:** The new design surfaces critical deployment information directly in the list view, including:\n\n* Deployment status with clear visual indicators\n* Who triggered the deployment along with timestamps\n* Commit information and version tags\n* Actions to take on the environment\n* Latest deployment indicators\n\nThis redesign eliminates the need for extra clicks and gives users immediate visibility into their deployment and environment statuses. The new layout maintains a clean interface while presenting more actionable information upfront.\n\n### Improved deploy keys filtering\n\nAnother larger enhancement was made to our deploy keys interface to improve searchability while maintaining performance. This change addresses a critical user need for quickly finding specific deploy keys in large repositories, which was broken when pagination was introduced earlier last year.\n\n![Beautifying UI - Deploy key before](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Deploy_Key_Before_aHR0cHM6_1750097793303.png)\n\n**Before:** The previous interface displayed deploy keys in a paginated list without a dedicated search function. While pagination helped with performance when handling thousands of keys, users had lost the ability to quickly search through their deploy keys using the browser search functionality, forcing them to manually scan through multiple pages.\n\n![Beautifying UI - Deploy key after](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Deploy_Key_After_aHR0cHM6_1750097793306.png)\n\n**After:** The new design introduces a dedicated search field at the top of the deploy keys list, allowing users to:\n\n* Quickly filter deploy keys by name or SHA\n* Maintain the performance benefits of pagination\n* Find specific keys without browsing through multiple pages\n\nThis improvement strikes the right balance between performance and usability, especially beneficial for teams managing numerous deploy keys across multiple projects.\n\n### Better Kubernetes agent management\n\nWe made significant improvements to the Kubernetes agent experience by simplifying the registration process and providing better visibility into agent status. These enhancements work together to create a smoother onboarding experience for teams getting started.\n\nOur first area of focus was streamlining how users register agents when they have configuration files ready to use. Previously, this process had several pain points that we wanted to address.\n\n![Beautifying UI - Agent before](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Agent_Before_aHR0cHM6_1750097793309.png)\n\n**Before:**\n\n* Only showed connected and previously connected agents\n* Connection status was limited to \"Never connected\" or \"Not connected\"\n* No clear path to register new agents\n\n![Beautifying UI - Agent after](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Agent_After_aHR0cHM6_1750097793310.png)\n\n**After:**\n\n* Added a new Available configurations tab showing all potential agent configurations\n* Clear \"Register an agent\" call-to-action button for each available configuration\n\nNext, we turned our attention to making the agent registration modal more intuitive. The previous design created some confusion that we wanted to resolve.\n\n![Beautifying UI - Registration before](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Registration_Before_aHR0cHM6_1750097793311.png)\n\n**Before:**\n\n* Users faced a confusing dual-purpose search box that both found existing agents and created new ones\n* The workflow had too many decision points instead of a clear path forward\n* The process for creating vs. selecting an agent wasn't clearly separated\n\n![Beautifying UI - Registration after](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097793/Blog/Content%20Images/Blog/Content%20Images/Registration_After_aHR0cHM6_1750097793312.png)\n\n**After:**\n\n* Separated the interface into two clear options: bootstrap with Flux or create an agent through the UI\n* Streamlined the workflow into a more linear process\n* Made the distinction between creating new agents and selecting existing ones more obvious\n* Added a success message that clearly shows where to create the optional config file\n\nThese improvements make it immediately clear which agents need attention and provide a straightforward path to register new agents. The reorganized interface better supports both new users setting up their first agent and experienced users managing multiple agents.\n\n## Additional usability enhancements\n\nWhile working on major interface improvements, we also addressed several focused usability issues that significantly improve the day-to-day experience:\n\n* **Enhanced Kubernetes pod search:** Added search functionality for Kubernetes pods on the environment page, making it easier to locate specific pods in large deployments. This was showcased in the [GitLab 17.8 release post](https://docs.gitlab.com/releases/17/gitlab-17-8-released/#search-for-pods-on-the-dashboard-for-kubernetes).\n* **Improved Flux status visibility:** Added a \"stopped\" badge to the dashboard view when Flux sync is stopped, providing immediate visibility into sync status. This was also showcased in the [GitLab 17.8 release post](https://docs.gitlab.com/releases/17/gitlab-17-8-released/#view-paused-flux-reconciliations-on-the-dashboard-for-kubernetes).\n* **Better release information:** Implemented a clear view of deployments related to a release, improving deployment tracking and visibility.\n* **Streamlined environment search:** Fixed an issue where users couldn't effectively search the Environments page, improving navigation in large environment lists.\n* **Enhanced error message display:** Resolved issues with viewing Flux details when long error messages were present, making troubleshooting more straightforward.\n\n## Looking forward\n\nThe success of these improvements demonstrates the value of empowering our teams to make direct, meaningful changes to our experience. Beyond the product enhancements, one of the most valuable outcomes has been the strengthened relationship between our Frontend and Design teams. Working together closely on these improvements has fostered better understanding of each other's perspectives, workflows, and constraints, leading to more effective collaboration.\n\nThis deepened partnership has created a foundation for even better collaboration in our regular workflow, as team members now have stronger working relationships and shared understanding of each other's domains. 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foundation","Pair GitLab Duo Agent Platform with Amazon Bedrock for agentic software development and orchestration.","If your team runs GitLab and has a strong AWS practice, a new combination of Duo Agent Platform and Amazon Bedrock is just for you. The model is simple: GitLab acts as your orchestration layer to help accelerate your entire software lifecycle with agentic AI, and Bedrock is designed to provide a secure, compliant foundation model layer with AI inference behind the scenes.\n\nGitLab Duo Agent Platform enables you to handle planning, merge pipelines, security scanning, vulnerability remediation, and more as part of your GitLab workflows, while the GitLab AI Gateway routes model calls to Bedrock (or GitLab-managed Bedrock-backed endpoints, depending on your setup). That means you can build on the identity and access management (IAM) policies, virtual private cloud (VPC) boundaries, regional controls, and cloud spend commitments you already have in AWS.\n\nIf you already use Amazon Bedrock and want AI to help inside the work you already do in GitLab, not in yet another standalone chat tool, this is the pairing for you.\n\n\nIn this article, we look at the real problem many teams face today: AI is fragmented, data paths are fuzzy, and Bedrock investment gets underused when AI sits outside the software development lifecycle. Then we break down your deployment options for GitLab Duo Agent Platform:\n\n* Integrated with self-hosted models on Amazon Bedrock for GitLab Self-Managed deployments and self-hosted AI gateway   \n* Integrated with GitLab-operated models on Amazon Bedrock (with GitLab-owned keys) for GitLab Self-Managed deployments and GitLab-hosted AI gateway  \n* Integrated with GitLab-operated models on Amazon Bedrock (with GitLab-owned keys) for GitLab.com instances and GitLab-hosted AI gateway\n\nWe wrap with a summary on how this approach helps avoid shadow AI and point-tool sprawl without creating a parallel tech stack for AI tooling.\n\n## AI everywhere, control nowhere\n\nSomewhere in your company right now, software teams might be using an AI tool that your security team hasn't approved. Prompt data might be leaving your environment through a path no one has fully mapped. And your organization’s Amazon Bedrock investment might be underused while individual teams expense separate AI tools, pulling workloads and cloud spend away from the platforms you’ve already committed to.\n\nInstead of being a people problem, this might be an architecture problem. And it surfaces the same three constraints in nearly every enterprise:\n\n**Operational fragmentation.** Each team, or sometimes even an individual developer, picks their own development toolset, including AI tooling and model selection. That fragmentation makes end-to-end governance within the software development lifecycle nearly impossible.\n\n**Security and sovereignty.** Where does prompt and code data actually flow? Who owns the logs?\n\n**Cloud spend optimization.** Commitments to key cloud providers like AWS are diluted as workloads and AI usage drift to point tools outside of customers’ existing agreements.\n\nGitLab Duo Agent Platform and Amazon Bedrock help solve this together. The division of labor is straightforward: Duo Agent Platform owns the workflow orchestration with agentic AI for software development, Bedrock owns the inference layer and hosts approved foundational models, and your organization has full control over the data and policy boundaries you already defined in AWS. Three jobs, three owners, no fragmentation.\n\n## GitLab Duo Agent Platform: The agentic control plane\n\nGitLab Duo Agent Platform is GitLab's agentic AI layer: a framework of specialized agents and flows that operate simultaneously and in-parallel, going beyond the traditional stage-based handoffs  and helping automate work across the entire software lifecycle. Rather than a single assistant responding to prompts, Duo Agent Platform enables teams to orchestrate many AI agents asynchronously using unified data and project context, including issues, merge requests, pipelines, and security findings. Linear workflows are turned into coordinated, continuous collaboration between software teams and their AI agents, at scale.\n\nWith that control plane in place, the natural next question is which AI foundation should power these agents. For customers who run GitLab Self-Managed on AWS and need inference traffic, prompt data, and logs to also stay within their AWS environment along with their software lifecycle data, Amazon Bedrock acting as the AI inference layer is the natural fit. \n\n## Amazon Bedrock: The trusted AI foundation\n\nAmazon Bedrock is a fully managed, serverless foundation model layer that runs entirely within your AWS environment. Customer data stays in the customer's AWS account: inputs and outputs are encrypted in transit and at rest, never shared with model providers, and never used to train base models. Bedrock carries compliance certifications across GDPR, HIPAA, and FedRAMP High, covering many regulated industry requirements out of the box. Teams can also bring fine-tuned models from elsewhere via Custom Model Import and deploy them alongside native Bedrock models through the same infrastructure, without managing separate deployment pipelines. Bedrock Guardrails adds configurable safeguards across all models for content filtering, hallucination detection, and sensitive data protection.\n\nTogether, GitLab Duo Agent Platform and Bedrock consolidate DevSecOps orchestration and AI model governance, helping eliminate the fragmentation that happens when teams roll out AI tools independently.\n\n## Choosing your deployment path\n\nThe integration delivers the same core GitLab Duo Agent Platform capabilities regardless of how it is deployed. What varies is who runs GitLab, who operates the AI Gateway, and whose Bedrock account the inference runs through. The right pattern depends on where your organization already operates.\n\nAt a high level, the integration has three main components:\n\n* **GitLab Duo Agent Platform:** agentic workflows embedded across the software development lifecycle  \n* **AI Gateway (GitLab-managed or self-hosted):** the abstraction layer between Duo Agent Platform and the foundational model backend   \n* **Amazon Bedrock:** the AI model and inference substrate\n\n![Deployment of GitLab and AWS Bedrock](https://res.cloudinary.com/about-gitlab-com/image/upload/v1776362365/udmvmv2efpmwtkxgydch.png)\n\nChoosing a deployment pattern is informed by where an organization wants to place the levers of control. The patterns below are designed to meet teams where they already are, whether that's SaaS-first, self-managed for compliance, or all-in on AWS with existing Bedrock investments.\n\n| Deployment Model | GitLab.com instance with GitLab-hosted AI Gateway with GitLab-operated Bedrock models   | GitLab Self-Managed with GitLab-hosted AI Gateway with GitLab-operated Bedrock models | GitLab Self-Managed  with self-hosted AI Gateway and customer-operated Bedrock models |\n| :---- | :---- | :---- | :---- |\n| **Ideal if you:** | Are primarily on GitLab.com and don’t want to self-host AI gateway and Bedrock models  | Need GitLab Self-Managed for compliance and operational reasons but don’t want to manage AI layer | Are AWS-centric with existing Bedrock usage and strict data/control needs  |\n| **Key Benefits** | Fastest, turnkey way to get Duo Agent Platform workflows: GitLab runs GitLab.com, the AI Gateway, integrated with Bedrock AI models. | Keep GitLab deployed in your own environment while consuming Bedrock models via a GitLab-managed AI Gateway, combining deployment control with simplified AI operations. | Run GitLab and AI Gateway in your AWS account, reuse existing IAM/VPC/regions, keep logs and data in your environment, and draw Bedrock usage from your existing AWS spend commitments. |\n\n## How customers use GitLab Duo Agent Platform with Amazon Bedrock\n\nPlatform teams can use GitLab Duo Agent Platform with Amazon Bedrock to standardize which models handle code suggestions, security analysis, and pipeline remediation. This helps enforce guardrails and logging centrally rather than letting individual teams adopt separate tools independently.\n\nSecurity workflows see particular benefit. GitLab Duo Agent Platform agents can propose and validate fixes for security findings within GitLab, helping reduce the manual triage work developers would otherwise handle outside the platform.\n\nFor enterprises already committed to AWS, routing AI workloads through Bedrock from within GitLab enables you to keep developer AI usage aligned with existing cloud agreements rather than generating separate, unplanned spend.\n\n## Closing the loop\n\nThe constraints that slow enterprise AI adoption are often not technical. They are organizational: fragmented tooling, ungoverned data flows, and cloud spend that never consolidates. Those are the problems that can stall AI programs even after the pilots succeed.\n\nGitLab Duo Agent Platform and Amazon Bedrock help address each one directly. Platform teams get consistent governance, auditability, and standardized paths for AI usage across the software development lifecycle. Development teams get streamlined, agentic workflows that feel native to GitLab. And AWS-centric organizations get to extend their existing Bedrock investment rather than build parallel AI infrastructure alongside it.\n\nThe result is an AI program that scales without fragmenting. Governance and velocity on the same stack, serving the same teams, under policies the organization already owns.\n\n\n> To explore which deployment pattern is right for your organization and how to align GitLab Duo Agent Platform and Amazon Bedrock with your existing AWS strategy, [contact the GitLab sales team](https://about.gitlab.com/sales/) and we’ll help you design and implement the best architecture for your environment. You can also [visit our AWS partner page](https://about.gitlab.com/partners/technology-partners/aws/) to learn more.",[291,756,757],"AWS","AI/ML","2026-04-21",[760,761],"Joe Mann","Mark Kriaf","https://res.cloudinary.com/about-gitlab-com/image/upload/v1776362275/ozbwn9tk0dditpnfddlz.png",{"featured":29,"template":13,"slug":764},"gitlab-amazon-platform-orchestration-on-a-trusted-ai-foundation",{"promotions":766},[767,781,792,804],{"id":768,"categories":769,"header":771,"text":772,"button":773,"image":778},"ai-modernization",[770],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":774,"config":775},"Get your AI maturity score",{"href":776,"dataGaName":777,"dataGaLocation":254},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":779},{"src":780},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":782,"categories":783,"header":784,"text":772,"button":785,"image":789},"devops-modernization",[11,583],"Are you just managing tools or shipping innovation?",{"text":786,"config":787},"Get your DevOps maturity score",{"href":788,"dataGaName":777,"dataGaLocation":254},"/assessments/devops-modernization-assessment/",{"config":790},{"src":791},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":793,"categories":794,"header":796,"text":772,"button":797,"image":801},"security-modernization",[795],"security","Are you trading speed for security?",{"text":798,"config":799},"Get your security maturity score",{"href":800,"dataGaName":777,"dataGaLocation":254},"/assessments/security-modernization-assessment/",{"config":802},{"src":803},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":805,"paths":806,"header":809,"text":810,"button":811,"image":816},"github-azure-migration",[807,808],"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":812,"config":813},"See how GitLab compares to GitHub",{"href":814,"dataGaName":815,"dataGaLocation":254},"/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":817},{"src":791},{"header":819,"blurb":820,"button":821,"secondaryButton":826},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":822,"config":823},"Get your free trial",{"href":824,"dataGaName":53,"dataGaLocation":825},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":520,"config":827},{"href":57,"dataGaName":58,"dataGaLocation":825},1777934898268]