[{"data":1,"prerenderedAt":815},["ShallowReactive",2],{"/en-us/blog/getting-started-with-gitlab-how-to-import-your-projects-to-gitlab":3,"navigation-en-us":37,"banner-en-us":447,"footer-en-us":457,"blog-post-authors-en-us-Abubakar Siddiq Ango":698,"blog-related-posts-en-us-getting-started-with-gitlab-how-to-import-your-projects-to-gitlab":712,"blog-promotions-en-us":752,"next-steps-en-us":805},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":25,"isFeatured":12,"meta":26,"navigation":27,"path":28,"publishedDate":20,"seo":29,"stem":33,"tagSlugs":34,"__hash__":36},"blogPosts/en-us/blog/getting-started-with-gitlab-how-to-import-your-projects-to-gitlab.yml","Getting Started With Gitlab How To Import Your Projects To Gitlab",[7],"abubakar-siddiq-ango",null,"product",{"slug":11,"featured":12,"template":13},"getting-started-with-gitlab-how-to-import-your-projects-to-gitlab",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"Getting started with GitLab: How to import your projects to GitLab","Learn how to import your projects from various sources, including Bitbucket, Gitea, GitHub, and GitLab Self-Managed.",[18],"Abubakar Siddiq Ango","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097248/Blog/Hero%20Images/Blog/Hero%20Images/blog-getting-started-with-gitlab-banner-0497-option4-fy25_cFwd8DYFLekdnOLmbbChp_1750097247785.png","2025-01-28","*Welcome to our \"Getting started with GitLab\" series, where we help newcomers get familiar with the GitLab DevSecOps platform.*\n\nKnowing how to import your projects to GitLab is an essential skill to make the most of the GitLab DevSecOps platform. You’ve [set up your account](https://university.gitlab.com/pages/getting-started), invited users, and [organized](https://about.gitlab.com/blog/getting-started-with-gitlab-how-to-manage-users/) them based on your use case or team structure. Now, you need to bring your existing projects into GitLab and start collaborating. These projects can be local files on your computer or hosted on a different source code management platform. Let's explore the options.\n\n## Importing local project files\n\nYou don't want to start from scratch every time you import a project. Follow these steps to get into GitLab existing legacy projects or applications that exist without version control or use version control.\n\n### Git project\n\n1. If Git is [already initiated](https://docs.gitlab.com/ee/topics/git/commands.html#git-init) in your local project, create a new project in GitLab and obtain the SSH or HTTPS URL by clicking on the **Code** button in the top right corner of your project page.\n\n![create a new project in GitLab with SSH/HTTPS URLs](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097254/Blog/Content%20Images/Blog/Content%20Images/image8_aHR0cHM6_1750097252717.png)\n\n2. Switch to your terminal and ensure you are in your project folder:\n\n```bash  \ncd /project_folder  \n```\n\n3. Backup your existing [Git origin](https://git-scm.com/book/ms/v2/Git-Basics-Working-with-Remotes):\n\n```bash\ngit remote rename origin old-origin\n```\n\n4. Add the [GitLab remote](https://git-scm.com/book/ms/v2/Git-Basics-Working-with-Remotes) URL for the new origin, when using SSH:\n\n```bash  \ngit remote add origin [git@gitlab.com](mailto:git@gitlab.com):gitlab-da/playground/abubakar/new-test-repo.git  \n```\n\nAnd for HTTPS: \n\n```bash  \ngit remote add origin https://gitlab.com/gitlab-da/playground/abubakar/new-test-repo.git  \n```\n\n5. Then push all existing [branches](https://docs.gitlab.com/ee/user/project/repository/branches/) and [tags](https://docs.gitlab.com/ee/user/project/repository/tags/) to GitLab:\n\n```bash  \ngit push --set-upstream origin --all  \ngit push --set-upstream origin --tags  \n```\n\nAll your file project files, branches, and tags will be pushed to GitLab and you can start collaborating.\n\n### Non-Git project\n\nAlternatively, if you have not initiated Git in your project, you will need to initialize Git, commit existing files, and push to GitLab as follows:\n\n```bash  \ngit init --initial-branch=main  \ngit remote add origin git@gitlab.com:gitlab-da/playground/abubakar/new-test-repo.git  \ngit add .  \ngit commit -m \"Initial commit\"  \ngit push --set-upstream origin main  \n```\n\n## Importing from online sources\n\nIf you have your project on GitLab.com or other platforms and you want to move it to another GitLab instance (like a self-managed instance) or from another platform to GitLab.com, GitLab provides the import project feature when you want to create a new project.\n\n![Create a new project screen](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097253/Blog/Content%20Images/Blog/Content%20Images/image7_aHR0cHM6_1750097252718.png)\n\nImporting a project migrates the project files and some other components of the project depending on the source. You can import from different sources like Bitbucket, GitHub, Gitea, and a GitLab instance, among other sources. Import sources are enabled by default on GitLab.com, but they need to be [enabled for self-managed](https://docs.gitlab.com/ee/administration/settings/import_and_export_settings.html#configure-allowed-import-sources) by an administrator. We will look at a few of these sources in the following sections.\n\n![Import project from third-party sources](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097253/Blog/Content%20Images/Blog/Content%20Images/image6_aHR0cHM6_1750097252719.png)\n\n## GitLab sources\n\nYou can export projects from GitLab.com and GitLab Self-Managed instances using the Export project feature in a project’s settings. \n\n![Export project screen](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097253/Blog/Content%20Images/Blog/Content%20Images/image9_aHR0cHM6_1750097252720.png)\n\nTo access it:\n\n- Go to your project’s settings and click into the **General** area.\n- Scroll to and **Expand Advanced** section.\n- Select **Export project**.\n- A notification will be shown stating: “Project export started. A download link will be sent by email and made available on this page.”\n- After the export is generated, you can follow the link contained in the email or refresh the project settings page to reveal the “Download export” option.\n\n### Importing the project\n\n![Import an exported GitLab project](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097253/Blog/Content%20Images/Blog/Content%20Images/image10_aHR0cHM6_1750097252722.png)\n\n- Click on the **New project** button in your target GitLab instance.  \n- Select **Import project** and click on **GitLab Export** in the list of import sources.  \n- Specify a project name and select the export file, then click **Import project**.  \n- An \"import in progress\" page will be shown and once complete, you will be redirected to the imported project.\n\nDepending on the size of your project, the import time may vary. It's important to note that not everything in a project might be exported and a few things might change after import. Review the [documentation](https://docs.gitlab.com/ee/user/project/settings/import_export.html#export-a-project-and-its-data) to understand the limitations. If you want to migrate a whole group instead of individual projects, the [Direct Transfer method](https://docs.gitlab.com/ee/user/group/import/index.html) is recommended; this creates a copy of an entire group.\n\n## Third-party providers\n\nGitLab supports importing from Bitbucket Cloud, Bitbucket Server, FogBugz, Gitea, and GitHub. The import process is similar across all the supported third parties — the main difference is in the method of authentication. Let's look at a few of them.\n\n### GitHub\n\n![Authenticate with GitHub screen](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097253/Blog/Content%20Images/Blog/Content%20Images/image3_aHR0cHM6_1750097252723.png)\n\nThere are three methods to import GitHub projects in to GitLab:\n\n- [Using GitHub OAuth](https://docs.gitlab.com/ee/user/project/import/github.html#use-github-oauth)\n- [Using a GitHub personal access token](https://docs.gitlab.com/ee/user/project/import/github.html#use-a-github-personal-access-token)\n- [Using the API](https://docs.gitlab.com/ee/user/project/import/github.html#use-the-api)\n\nImporting using GitHub OAuth and personal access token are similar. The difference lies in how your authorize GitLab to access your repositories. The OAuth method is easier because you only need to click on the “Authorize with GitHub” button and your are redirected to your GitHub account to authorize the connection. Then the list of your projects is loaded for you to pick those you want to import.\n\n![Import repositories from GitHub screen](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097253/Blog/Content%20Images/Blog/Content%20Images/image2_aHR0cHM6_1750097252725.png)\n\nAlternatively, you will need to generate a GitHub personal access token, selecting the `repo` and `read:org` scopes, and then provide it on the \"Import\" page.  For API imports, you can use the same personal access token with our [Import REST API endpoints](https://docs.gitlab.com/ee/api/import.html#import-repository-from-github) in your script or application.\n\nIn this demo, GitLab Senior Developer Advocate Fernando Diaz explains how to import a project from GitHub using the OAuth method:\n\n\u003C!-- blank line -->  \n\u003Cfigure class=\"video_container\"> \n  \u003Ciframe src=\"https://www.youtube.com/embed/0Id5oMl1Kqs?si=esF6wbz2j2JlhDVL\" frameborder=\"0\" allowfullscreen=\"true\"> \u003C/iframe>  \n\u003C/figure>\n\u003C!-- blank line -->\n\nYou can learn about prerequisites, known issues, importing from GitHub Enterprise, and other valuable information from the GitLab [import documentation](https://docs.gitlab.com/ee/user/project/import/github.html).\n\n### Bitbucket\n\nImporting projects from Bitbucket is similar to importing them from GitHub. While using OAuth is applicable to [Bitbucket Cloud](https://docs.gitlab.com/ee/user/project/import/bitbucket.html), the SaaS version of Bitbucket, you'll need to provide a URL, username, and personal access token for [Bitbucket Server](https://docs.gitlab.com/ee/user/project/import/bitbucket_server.html), the enterprise self-hosted version. Clicking on the Bitbucket Cloud option on the \"Import\" screen automatically takes you to Atlassian authentication for Bitbucket.\n\n![Import project from BitBucket](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097253/Blog/Content%20Images/Blog/Content%20Images/image4_aHR0cHM6_1750097252726.png)\n\nYou can also import Bitbucket projects using the [GitLab Import API](https://docs.gitlab.com/ee/api/import.html).\n\n### Gitea\n\n![Import project from Gitea](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097253/Blog/Content%20Images/Blog/Content%20Images/image5_aHR0cHM6_1750097252727.png)\n\nImporting projects from [Gitea](https://docs.gitlab.com/ee/user/project/import/gitea.html) requires the creation of a [personal access token](https://docs.gitea.com/next/development/api-usage#authentication-via-the-api) on the Gitea platform and providing it along with the Gitea server URL on the GitLab import page. OAuth authentication is not supported. \n\n### Generic remote Git repository\n\n![Import project from remote Git repository](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097253/Blog/Content%20Images/Blog/Content%20Images/image1_aHR0cHM6_1750097252728.png)\n\nWhere your Git provider is not supported or import is not possible using the supported methods, a repository can be imported using its accessible `https://` or `git://` URL.  If it's not publicly accessible, you will provide the repository URL along with username and password (or access token where applicable due to multifactor authentication).\n\nThis method can also be used for maintaining a copy of a remote project and keeping it in sync, i.e., [mirroring](https://docs.gitlab.com/ee/user/project/repository/mirror/). Mirroring allows you to maintain repositories across different platforms and keep them synced. This can be to separate private and public access to project while ensuring both ends have the same copy, which is useful when open-sourcing  internal projects. It can also be used when working with contractors and both parties use different platforms, and access to codebase is necessary on both ends. \n\n## Summary\n\nImporting and migrating between GitLab instances and from other sources is an important process that needs to be planned to ensure the expectations are clear on what gets imported and with which method. While most third-party methods import project items, including files, issues, and merge requests, some methods have known issues and limitations. The [GitLab import section](https://docs.gitlab.com/ee/user/project/import/) of the documentation has detailed information on all the supported methods that can help you plan your migration.   \n\n> #### Want to take your learning to the next level? [Sign up for GitLab University courses](https://university.gitlab.com/). Or you can get going right away with [a free trial of GitLab Ultimate](https://about.gitlab.com/free-trial/devsecops/).\n\n## \"Getting started with GitLab\" series\n\n- [How to manage users](https://about.gitlab.com/blog/getting-started-with-gitlab-how-to-manage-users/)\n- [How to import your projects to GitLab](https://about.gitlab.com/blog/getting-started-with-gitlab-how-to-import-your-projects-to-gitlab/)  \n- [Mastering project management](https://about.gitlab.com/blog/getting-started-with-gitlab-mastering-project-management/)\n- [Automating Agile workflows with the gitlab-triage gem](https://about.gitlab.com/blog/automating-agile-workflows-with-the-gitlab-triage-gem/)\n- [Working with CI/CD variables](https://about.gitlab.com/blog/getting-started-with-gitlab-working-with-ci-cd-variables/)\n",[9,23,24],"tutorial","DevSecOps 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Patch Release: 18.11.1, 18.10.4, 18.9.6","Discover what's in this latests patch release.","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749661926/Blog/Hero%20Images/security-patch-blog-image-r2-0506-700x400-fy25_2x.jpg","2026-04-22",[720,721],"patch releases","security releases",{"featured":12,"template":13,"externalUrl":723},"https://docs.gitlab.com/releases/patches/patch-release-gitlab-18-11-1-released/",{"content":725,"config":737},{"title":726,"description":727,"body":728,"category":9,"tags":729,"date":732,"authors":733,"heroImage":736},"GitLab + Amazon: Platform orchestration on a trusted AI 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.",[274,730,731],"AWS","AI/ML","2026-04-21",[734,735],"Joe Mann","Mark Kriaf","https://res.cloudinary.com/about-gitlab-com/image/upload/v1776362275/ozbwn9tk0dditpnfddlz.png",{"featured":27,"template":13,"slug":738},"gitlab-amazon-platform-orchestration-on-a-trusted-ai-foundation",{"content":740,"config":750},{"title":741,"description":742,"authors":743,"heroImage":745,"date":746,"body":747,"category":9,"tags":748},"GitLab 18.11: Budget guardrails for GitLab Credits","Learn how new spending caps and per-user credit limits give organizations the budget guardrails to scale GitLab Duo Agent Platform.",[744],"Bryan Rothwell","https://res.cloudinary.com/about-gitlab-com/image/upload/v1776259080/cakqnwo5ecp255lo8lzo.png","2026-04-16","Teams using GitLab Duo Agent Platform with on-demand GitLab Credits are shipping faster, catching bugs earlier, and automating tasks that used to take entire sprints. But as adoption grows, so does oversight from finance, procurement, and platform teams to prove that AI spending is bounded, predictable, and controllable.\n\nOne of the greatest barriers to broader AI adoption isn't skepticism about the technology. It's uncertainty about managing spend. Without budget caps, a busy month could produce unexpected expenses. Without per-user limits, a handful of power users could burn through the team's credits before the month is over. And without either, engineering leaders who want to expand their use of agentic AI for software development have to jump through more hoops for budget approval.\n\nSince its [general availability](https://about.gitlab.com/blog/gitlab-duo-agent-platform-is-generally-available/), GitLab Duo Agent Platform has provided usage governance and visibility. With GitLab 18.11, we're introducing usage controls for [GitLab Credits](https://about.gitlab.com/blog/introducing-gitlab-credits/): spending caps and budget guardrails that give your organization even more control and transparency over how credits are consumed.\n\n## Managing GitLab Credits\n\nGitLab 18.11 adds three layers of control over GitLab Credits consumption: a subscription-level spending cap, per-user credit limits, and visibility into cap status and enforcement.\n\n### Subscription-level spending cap\n\nBilling account managers can now set a hard monthly ceiling for on-demand GitLab Credits consumption for their entire subscription.\n\nHere's how it works:\n\n* **Set a cap** in the `Customers Portal` under your subscription's GitLab Credits settings.  \n* **Enforce spend limits automatically.**  When on-demand usage reaches the cap, DAP access is paused for all users on that subscription until the next monthly period begins.  \n* **Make adjustments as you go.** Raise or disable the cap mid-month to restore access.\n\nThe cap resets each monthly period and your configured limit carries forward unless you change it. Because usage data is synchronized periodically rather than in real time, a small amount of additional usage may occur after the cap is reached before enforcement takes effect. See the [GitLab Credits documentation](https://docs.gitlab.com/subscriptions/gitlab_credits/) for details.\n\n### User-level spending caps\n\nNot every user consumes credits at the same rate, and that's expected. But when one or two power users account for a disproportionate share of the pool, the rest of the team can lose access before the month is over.\n\nPer-user credit caps prevent any single user from consuming more than their fair share:\n\n* **Flat per-user cap.** Set a uniform credit limit that applies equally to every user on the subscription through the GitLab GraphQL API. Unlike the subscription-level cap, the per-user cap applies to a user's total consumption across all credit sources.  \n* **Custom per-user overrides.** For organizations that need differentiated limits, you can set individual credit caps for specific users through the GraphQL API. For example, you could give your staff engineers a higher allocation while applying a standard limit to the broader team.  \n* **Individual enforcement.** When a user reaches their cap, they retain full access to GitLab. Only their Duo Agent Platform credit usage is paused until the next billing cycle. Everyone else keeps working uninterrupted until they hit their own limit or the subscription-level cap is reached, whichever comes first.\n\n### Visibility and notifications\n\nWhen a subscription-level cap is reached, GitLab sends an email notification to billing account managers so they can take action: raise the cap, wait for the next period, or redistribute credits.\n\nWithin GitLab, group owners (GitLab.com) and instance administrators (Self-Managed) can view which users have been blocked due to reaching their per-user cap and restore access by adjusting the cap through the GraphQL API. \n\n## How budget guardrails help organizations scale AI usage\n\nGuardrails are essential as organizations ramp up their AI adoption. Here's why:\n\n### Predictable AI budgets\n\nUsage controls for GitLab Duo Agent Platform turn AI into a bounded, predictable budget item using on-demand GitLab Credits. That makes it easier to deploy agents across the software development lifecycle and get sign-off from finance, justify renewals, and plan quarterly spend.\n\n### Governance and chargeback\n\nLarge organizations often need to align AI consumption with internal budgets, cost centers, or departmental policies. Per-user caps give platform teams a straightforward mechanism to allocate credits fairly and track consumption at the individual level. The API import options make it practical to manage caps at enterprise scale. Combined with per-user usage data from the GitLab Credits dashboard, organizations can track consumption patterns to inform their own internal chargeback or budget allocation processes.\n\n### Confidence to scale\n\nMany customers start GitLab Duo Agent Platform with a small pilot group. Usage controls remove risks associated with expanding that pilot across the organization. You can roll out Duo Agent Platform to hundreds or thousands of developers knowing there's a hard ceiling protecting your budget. If usage grows faster than expected, you'll hit the cap, not an unexpected invoice.\n\n## Addressing the seat-based and visibility conundrum\n\nMany AI coding tools take a seat-based approach to cost management. You buy a fixed number of seats at a flat per-user price, and that's your budget. It's simple, but rigid. You pay the same whether a developer uses the tool ten times a day or never touches it. And as vendors introduce premium models and usage-based overages on top of seat pricing, the cost predictability that seat-based licensing promised starts to erode.\n\n\nGitLab takes a different approach. Usage-based pricing with hard caps and a single governance dashboard. You get the flexibility of paying for what your teams actually use, with the budget predictability of enforced spending limits.\n\n## Real-world usage controls\n\n**One example is a mid-size SaaS customer that wants to protect their monthly budget.** A 200-person engineering organization sets a subscription-level cap equal to their expected on-demand usage. Their VP of Engineering can confidently tell finance that GitLab Duo Agent Platform spend will never exceed the approved amount, even as they onboard new teams. If they approach the cap mid-month, the billing account manager gets a notification and can decide whether to raise the limit or wait for the next period.\n\n**At GitLab, we also work with large enterprises that want to keep usage fair across teams.** A global financial services company with 2,000 developers uses per-user caps to ensure equitable access. Staff engineers working on complex refactoring projects get a higher individual allocation via API, while most developers receive a standard flat cap. No single user can exhaust the pool, and the platform team uses the per-user usage data in the GitLab Credits dashboard to track consumption patterns and inform quarterly budget planning.\n\n## Getting started\n\nUsage controls are available for both GitLab.com and Self-Managed customers running GitLab 18.11. Different controls are configured in different places depending on the scope and your role.\n\n**Subscription-level cap**\n\nBilling account managers set the subscription-level on-demand cap in the Customers Portal:\n\n1. Sign in to the `Customers Portal`.  \n2. On your subscription card, navigate to **GitLab Credits** settings.  \n3. Enable the monthly on-demand credits cap and enter your desired limit.\n\n**Flat per-user cap**\n\nThe flat per-user cap can be set through the GitLab GraphQL API by namespace owners (GitLab.com) or instance administrators (Self-Managed). Check the [GitLab Credits documentation](https://docs.gitlab.com/subscriptions/gitlab_credits/) for the latest on available configuration surfaces.\n\n**Custom per-user overrides**\n\nFor differentiated limits, namespace owners (GitLab.com) and instance administrators (Self-Managed) can set individual caps programmatically. This is useful for automation and infrastructure-as-code workflows.\n\n**Monitor usage and cap status**\n\n* **Customers Portal:** View detailed usage and cap status.  \n* **GitLab.com:** Group owners can view blocked users under **Settings > GitLab Credits**.  \n* **Self-Managed:** Instance administrators can view cap status and blocked users under **Admin > GitLab Credits**.\n\n## GitLab Duo Agent Platform is ready to scale\n\nUsage controls are available now in GitLab 18.11. If you've been waiting for the right guardrails before expanding GitLab Duo Agent Platform across your organization, this is your moment. Set your caps, roll out Duo Agent Platform to more teams, and start shipping faster!\n\n> [Learn more about GitLab Credits and usage controls](https://docs.gitlab.com/subscriptions/gitlab_credits/).",[9,731,749],"news",{"featured":12,"template":13,"slug":751},"gitlab-18-11-budget-guardrails-for-gitlab-credits",{"promotions":753},[754,768,779,791],{"id":755,"categories":756,"header":758,"text":759,"button":760,"image":765},"ai-modernization",[757],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":761,"config":762},"Get your AI maturity score",{"href":763,"dataGaName":764,"dataGaLocation":241},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":766},{"src":767},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":769,"categories":770,"header":771,"text":759,"button":772,"image":776},"devops-modernization",[9,566],"Are you just managing tools or shipping innovation?",{"text":773,"config":774},"Get your DevOps maturity score",{"href":775,"dataGaName":764,"dataGaLocation":241},"/assessments/devops-modernization-assessment/",{"config":777},{"src":778},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":780,"categories":781,"header":783,"text":759,"button":784,"image":788},"security-modernization",[782],"security","Are you trading speed for security?",{"text":785,"config":786},"Get your security maturity score",{"href":787,"dataGaName":764,"dataGaLocation":241},"/assessments/security-modernization-assessment/",{"config":789},{"src":790},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":792,"paths":793,"header":796,"text":797,"button":798,"image":803},"github-azure-migration",[794,795],"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":799,"config":800},"See how GitLab compares to GitHub",{"href":801,"dataGaName":802,"dataGaLocation":241},"/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":804},{"src":778},{"header":806,"blurb":807,"button":808,"secondaryButton":813},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":809,"config":810},"Get your free trial",{"href":811,"dataGaName":48,"dataGaLocation":812},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":503,"config":814},{"href":52,"dataGaName":53,"dataGaLocation":812},1777302595201]