[{"data":1,"prerenderedAt":790},["ShallowReactive",2],{"/en-us/blog/a-guide-to-the-breaking-changes-in-gitlab-19-0":3,"navigation-en-us":33,"banner-en-us":443,"footer-en-us":453,"blog-post-authors-en-us-Martin Brümmer":695,"blog-related-posts-en-us-a-guide-to-the-breaking-changes-in-gitlab-19-0":710,"assessment-promotions-en-us":741,"next-steps-en-us":780},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":24,"isFeatured":11,"meta":25,"navigation":26,"path":27,"publishedDate":15,"seo":28,"stem":30,"tagSlugs":31,"__hash__":32},"blogPosts/en-us/blog/a-guide-to-the-breaking-changes-in-gitlab-19-0.yml","A Guide To The Breaking Changes In Gitlab 19 0",[7],"martin-brmmer",null,"product",{"featured":11,"template":12,"slug":13},false,"BlogPost","a-guide-to-the-breaking-changes-in-gitlab-19-0",{"date":15,"body":16,"category":9,"tags":17,"authors":19,"title":21,"description":22,"heroImage":23},"2026-04-15","GitLab 17.0 shipped with 80 breaking changes. GitLab 18.0 had 27. The upcoming GitLab 19.0 release is projected to include 15.\n\nWe know that managing breaking changes across a major upgrade is time-consuming: It requires investigation and coordination across your organization. In response, we introduced a [breaking change approval requirement](https://docs.gitlab.com/development/deprecation_guidelines/#how-do-i-get-approval-to-move-forward-with-a-breaking-change) that mandates impact mitigation and leadership sign-off before any breaking change can proceed. That process is working, and we're committed to continuing to drive that number down.\n\nBelow you'll find every breaking change in GitLab 19.0, organized by deployment type and impact, alongside the mitigation steps you need to upgrade with confidence.\n\n## Deployment windows\n\nHere are the deployment windows you need to know.\n \n### GitLab.com\n \nBreaking changes for GitLab.com will be limited to these two windows:\n \n- **May 4–6, 2026** (09:00–22:00 UTC) — primary window\n- **May 11–13, 2026** (09:00–22:00 UTC) — contingency fallback\n \nMany other changes will continue to roll out throughout the month. You can learn more about the breaking changes occurring within each of these windows in the [breaking changes documentation](https://docs.gitlab.com/update/breaking_windows/).\n \n**Note:** Breaking changes may fall slightly outside of these windows in exceptional circumstances.\n \n### GitLab Self-Managed\n \nGitLab 19.0 will be available starting on May 21, 2026.\n\n> Learn more about the [release schedule](https://about.gitlab.com/releases/).\n \n### GitLab Dedicated\n \nThe upgrade to GitLab 19.0 will take place during your assigned maintenance window. You can learn more and find your assigned maintenance window in your Switchboard portal. GitLab Dedicated instances are kept on release N-1, so the upgrade to GitLab 19.0 will take place in the maintenance window during the week of June 22, 2026.\n\nVisit the [Deprecations page](https://docs.gitlab.com/update/deprecations/?removal_milestone=19.0&breaking_only=true) to see a full list of items scheduled for removal in GitLab 19.0. Read on to learn what's coming and how to prepare for this year's release based on your specific deployment.\n \n## Breaking changes\n\nHere are the breaking changes that are high impact.\n \n### High impact\n \n**1. Support for NGINX Ingress replaced by Gateway API with Envoy Gateway**\n \n_GitLab Self-Managed (Helm chart)_\n \nThe GitLab Helm chart has bundled NGINX Ingress as the default networking component. NGINX Ingress reached end-of-life in March 2026, and GitLab is now transitioning to Gateway API with Envoy Gateway as the new default.\n \nStarting with GitLab 19.0, Gateway API and the bundled Envoy Gateway become the default networking configuration. If migration to Envoy Gateway is not immediately feasible for your deployment, you can explicitly re-enable the bundled NGINX Ingress, which remains available until its planned removal in GitLab 20.0.\n \nThis change does not impact:\n- The NGINX used in the Linux package\n- GitLab Helm chart and GitLab Operator instances that use an externally managed Ingress or Gateway API controller\n \nGitLab will provide best-effort security maintenance for the forked NGINX Ingress chart and builds until full removal. To ensure a smooth transition, plan your migration to the provided Gateway API solution or an externally managed Ingress controller ahead of the 19.0 upgrade.\n \n[Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/work_items/590800)\n \n\n**2. Removal of bundled PostgreSQL, Redis, and MinIO from the GitLab Helm chart**\n \n_GitLab Self-Managed (Helm chart)_\n \nThe GitLab Helm chart has long bundled Bitnami PostgreSQL, Bitnami Redis, and a fork of the official MinIO chart to make setting up GitLab easier in proof-of-concept and test environments. Due to changes in licensing, project maintenance, and public image availability, these components will be removed from the GitLab Helm chart and GitLab Operator with no replacement.\n \nThese charts are explicitly documented as not recommended for production usage. Their sole purpose was to enable quick-start test environments.\n \nIf you are running an instance with the bundled PostgreSQL, Redis, or MinIO, follow the [migration guide](https://docs.gitlab.com/charts/installation/migration/bundled_chart_migration/) to configure external services before upgrading to GitLab 19.0. The Redis and PostgreSQL provided by the Linux package are not impacted by this change.\n \n[Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/work_items/590797)\n \n\n**3. Resource Owner Password Credentials (ROPC) OAuth grant removed**\n \n_GitLab.com | Self-Managed | Dedicated_\n \nSupport for the Resource Owner Password Credentials (ROPC) grant as an OAuth flow will be fully removed in GitLab 19.0. This aligns with the OAuth RFC Version 2.1 standard, which removes ROPC due to its inherent security limitations.\n \nGitLab has already required client authentication for ROPC on GitLab.com since April 8, 2025. An administrator setting was added in 18.0 to allow controlled opt-out ahead of the removal.\n \nAfter the 19.0 upgrade, ROPC cannot be used under any circumstances, even with client credentials. Any applications or integrations using this grant type must migrate to a supported OAuth flow — such as the Authorization Code flow — before upgrading.\n \n[Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/issues/457353)\n \n**4. PostgreSQL 16 no longer supported — PostgreSQL 17 is the new minimum**\n \n_GitLab Self-Managed_\n \nGitLab follows an [annual upgrade cadence for PostgreSQL](https://handbook.gitlab.com/handbook/engineering/infrastructure-platforms/data-access/database-framework/postgresql-upgrade-cadence/). In GitLab 19.0, PostgreSQL 17 becomes the minimum required version, and support for PostgreSQL 16 is removed.\n \nPostgreSQL 17 is available as of GitLab 18.9, so you can upgrade at any time before the 19.0 release.\n \nFor instances running a single PostgreSQL instance installed via the Linux package, an automatic upgrade to PostgreSQL 17 may be attempted during the 18.11 upgrade. Ensure you have sufficient disk space to accommodate the upgrade.\n \nFor instances using PostgreSQL Cluster, or those that opt out of the automated upgrade, a manual upgrade to PostgreSQL 17 is required before upgrading to GitLab 19.0.\n \n[Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/issues/589774) | [Upgrade guide](https://docs.gitlab.com/omnibus/settings/database/#upgrade-packaged-postgresql-server)\n \n\n \n### Medium impact\n\nHere are the breaking changes that are medium impact.\n \n**1. Linux package support for Ubuntu 20.04 discontinued**\n \n_GitLab Self-Managed_\n \nUbuntu standard support for Ubuntu 20.04 ended in May 2025. In accordance with GitLab's [Linux package supported platforms policy](https://docs.gitlab.com/install/package/#supported-platforms), packages are dropped once a vendor stops supporting the operating system.\n \nFrom GitLab 19.0, packages will no longer be provided for Ubuntu 20.04. GitLab 18.11 will be the last release with Linux packages for this distribution.\n \nIf you currently run GitLab on Ubuntu 20.04, you must upgrade to Ubuntu 22.04 or another [supported operating system](https://docs.gitlab.com/install/package/#supported-platforms) before upgrading to GitLab 19.0. Canonical provides an [upgrade guide](https://documentation.ubuntu.com/server/how-to/software/upgrade-your-release/) to help with the migration.\n \n[Deprecation notice](https://gitlab.com/gitlab-org/omnibus-gitlab/-/issues/8915)\n \n\n**2. Support for Redis 6 removed**\n \n_GitLab Self-Managed_\n \nIn GitLab 19.0, support for Redis 6 is removed. Before upgrading, instances using an external Redis 6 deployment must migrate to either Redis 7.2 or Valkey 7.2, which is available in beta from GitLab 18.9 with general availability planned for GitLab 19.0.\n \nThe bundled Redis included with the Linux package has used Redis 7 since GitLab 16.2 and is not affected. Only instances using an external Redis 6 deployment must act.\n \nMigration resources are available for common platforms:\n \n- **AWS ElastiCache:** Upgrade to [Redis 7.2 or Valkey 7.2](https://docs.aws.amazon.com/AmazonElastiCache/latest/dg/supported-engine-versions.html)\n- **GCP Memorystore:** Upgrade to [Redis 7.2 or Valkey 7.2](https://cloud.google.com/memorystore/docs/redis/supported-versions)\n- **Azure Cache for Redis:** Managed Redis 7.2 or Valkey 7.2 is not yet available on Azure. You can self-host on Azure VMs or AKS, or use the Linux package installation, which will support Valkey 7.2 with GitLab 19.0 GA.\n- **Self-hosted:** Upgrade your Redis 6 instance to Redis 7.2 or Valkey 7.2.\n \n[Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/work_items/585839) | [Requirements documentation](https://docs.gitlab.com/install/requirements/)\n \n\n \n**3. `heroku/builder:22` image replaced by `heroku/builder:24`**\n \n_GitLab.com | Self-Managed | Dedicated_\n \nThe cloud-native buildpack (CNB) builder image used in Auto DevOps has been updated to `heroku/builder:24`. This affects pipelines that use the [`auto-build-image`](https://gitlab.com/gitlab-org/cluster-integration/auto-build-image) provided by the [Auto Build stage of Auto DevOps](https://docs.gitlab.com/topics/autodevops/stages/#auto-build).\n \nWhile most workloads will be unaffected, this may be a breaking change for some users. Before upgrading, review the [Heroku-24 stack release notes](https://devcenter.heroku.com/articles/heroku-24-stack#what-s-new) and [upgrade notes](https://devcenter.heroku.com/articles/heroku-24-stack#upgrade-notes) to assess your impact.\n \nIf you need to continue using `heroku/builder:22` after GitLab 19.0, set the CI/CD variable `AUTO_DEVOPS_BUILD_IMAGE_CNB_BUILDER` to `heroku/builder:22`.\n \n[Deprecation notice](https://gitlab.com/gitlab-org/cluster-integration/auto-build-image/-/issues/79)\n\n\n**4. Mattermost removed from the Linux package**\n \n_GitLab Self-Managed_\n \nIn GitLab 19.0, bundled Mattermost is removed from the Linux package. Mattermost was first bundled with GitLab in 2015, but has since matured its own standalone deployment options. Additionally, with Mattermost v11, [GitLab SSO was deprecated from their free offering](https://forum.mattermost.com/t/mattermost-v11-changes-in-free-offerings/25126), reducing the value of the bundled integration.\n \nCustomers not using the bundled Mattermost will not be impacted. If you currently use it, refer to [Migrating from GitLab Omnibus to Mattermost Standalone](https://docs.mattermost.com/administration-guide/onboard/migrate-gitlab-omnibus.html) in the Mattermost documentation for migration instructions.\n \n[Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/work_items/590798)\n \n\n \n**5. Linux package support for SUSE distributions discontinued**\n \n_GitLab Self-Managed_\n \nIn GitLab 19.0, Linux package support for SUSE distributions ends. This affects:\n \n- openSUSE Leap 15.6\n- SUSE Linux Enterprise Server 12.5\n- SUSE Linux Enterprise Server 15.6\n \nGitLab 18.11 will be the last version with Linux packages for these distributions. The recommended path forward is to migrate to a [Docker deployment of GitLab](https://docs.gitlab.com/install/docker/installation/) on your existing distribution, avoiding the need to change your underlying operating system to continue receiving upgrades.\n \n[Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/work_items/590801)\n \n\n \n### Low impact\n\nHere are the breaking changes that are low impact.\n \n**1. Spamcheck removed from Linux package and GitLab Helm chart**\n \n_GitLab Self-Managed_\n \nIn GitLab 19.0, [Spamcheck](https://docs.gitlab.com/administration/reporting/spamcheck/) is removed from the Linux package and GitLab Helm chart. It is primarily relevant to large public instances, which is an edge case in GitLab's customer base. The removal reduces package size and dependency footprint for the majority of customers.\n \nCustomers not currently using Spamcheck will not be impacted. If you currently use the bundled Spamcheck, you can deploy it separately using [Docker](https://gitlab.com/gitlab-org/gl-security/security-engineering/security-automation/spam/spamcheck). No data migration is required.\n \n[Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/work_items/590796)\n \n\n**2. Slack slash commands integration removed**\n \n_GitLab Self-Managed | Dedicated_\n \nThe [Slack slash commands integration](https://docs.gitlab.com/user/project/integrations/slack_slash_commands/) is deprecated in favor of the [GitLab for Slack app](https://docs.gitlab.com/user/project/integrations/gitlab_slack_application/), which provides a more secure integration with the same capabilities.\n \nFrom GitLab 19.0, users will no longer be able to configure or use Slack slash commands. This integration only exists on GitLab Self-Managed and GitLab Dedicated — GitLab.com users are not affected.\n \nTo check if your instance is impacted, see the [impact check guidance](https://gitlab.com/gitlab-org/gitlab/-/work_items/569345#am-i-impacted).\n \n[Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/work_items/569345)\n \n\n**3. Bitbucket Cloud import via API no longer supports app passwords**\n \n_GitLab.com | Self-Managed | Dedicated_\n \nAtlassian has deprecated app passwords (username and password authentication) for Bitbucket Cloud and has announced that this authentication method will stop working on June 9, 2026.\n \nFrom GitLab 19.0, importing repositories from Bitbucket Cloud through the GitLab API requires [user API tokens](https://support.atlassian.com/organization-administration/docs/understand-user-api-tokens/) instead of app passwords. Users importing from Bitbucket Server, or from Bitbucket Cloud through the GitLab UI, are not affected.\n \n[Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/work_items/588961) | [Impact check](https://gitlab.com/gitlab-org/gitlab/-/work_items/588961#am-i-impacted)\n \n**4. Trending tab removed from Explore projects page**\n \n_GitLab.com | Self-Managed | Dedicated_\n \nThe **Trending** tab in **Explore > Projects** and its associated GraphQL arguments are removed in GitLab 19.0. The trending algorithm only considers public projects, making it ineffective for Self-Managed instances that primarily use internal or private project visibility.\n \nIn the month before the GitLab 19.0 release, the **Trending** tab on GitLab.com will redirect to the **Active** tab sorted by stars in descending order.\n \nAlso removed: the `trending` argument in the `Query.adminProjects`, `Query.projects`, and `Organization.projects` GraphQL types.\n \n[Deprecation notice](https://gitlab.com/groups/gitlab-org/-/work_items/18493)\n \n\n**5. Container registry storage driver updates**\n \n_GitLab Self-Managed_\n \nTwo legacy container registry storage drivers are being replaced in GitLab 19.0:\n \n- **Azure storage driver:** The legacy `azure` driver becomes an alias for the new `azure_v2` driver. No manual action is required, but proactive migration is recommended for improved reliability and performance. See the [object storage documentation](https://docs.gitlab.com/administration/packages/container_registry/#use-object-storage) for migration steps. [Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/issues/523096)\n \n- **S3 storage driver (AWS SDK v1):** The legacy `s3` driver becomes an alias for the new `s3_v2` driver. The `s3_v2` driver does not support Signature Version 2 — any `v4auth: false` configuration will be transparently ignored. Migrate to Signature Version 4 before upgrading. [Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/issues/523095)\n \n\n**6. `ciJobTokenScopeAddProject` GraphQL mutation removed**\n \n_GitLab.com | Self-Managed | Dedicated_\n \nThe `ciJobTokenScopeAddProject` GraphQL mutation is deprecated in favor of `ciJobTokenScopeAddGroupOrProject`, introduced alongside the CI/CD job token scope changes in GitLab 18.0. Update any automation or tooling using the deprecated mutation before upgrading.\n \n[Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/issues/474175)\n\n \n**7. `ci_job_token_scope_enabled` projects API attribute removed**\n \n_GitLab.com | Self-Managed | Dedicated_\n \nThe `ci_job_token_scope_enabled` attribute in the [Projects REST API](https://docs.gitlab.com/api/projects/) is removed in GitLab 19.0. This attribute was deprecated in GitLab 18.0 when the underlying setting was removed, and has since always returned `false`.\n \nTo control CI/CD job token access, use the [CI/CD job token project settings](https://docs.gitlab.com/ci/jobs/ci_job_token/#control-job-token-access-to-your-project).\n \n[Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/issues/423091)\n \n\n \n**8. Unauthenticated Projects API pagination limit enforced on GitLab.com**\n \n_GitLab.com_\n \nTo maintain platform stability and ensure consistent performance, a maximum offset limit of 50,000 will be enforced for all unauthenticated requests to the Projects List REST API on GitLab.com. For example, the `page` parameter will be limited to 2,500 pages when retrieving 20 results per page.\n \nWorkflows requiring access to more data must use keyset-based pagination parameters. This limit applies only to GitLab.com. On GitLab Self-Managed and GitLab Dedicated, the offset limit will be disabled by default behind a feature flag.\n \n[Deprecation notice](https://gitlab.com/gitlab-org/gitlab/-/work_items/585176)\n \n## Resources to manage your impact\n \nWe've developed specific tooling to help customers understand how these planned changes impact their GitLab instance(s). Once you've assessed your impact, we recommend reviewing the mitigation steps provided in the documentation relevant to each change to ensure a smooth transition to GitLab 19.0.\n \n**[GitLab Detective](https://gitlab.com/gitlab-com/support/toolbox/gitlab-detective) (Self-Managed only):** This experimental tool automatically checks a GitLab installation for known issues by looking at config files and database values. Note: it must run directly on your GitLab nodes.\n \nIf you have a paid plan and have questions or require assistance with these changes, please open a support ticket on the [GitLab Support Portal](https://support.gitlab.com/).\n \nIf you are a free GitLab.com user, you can access additional support through community sources such as [GitLab Documentation](https://docs.gitlab.com/), the [GitLab Community Forum](https://forum.gitlab.com/), and [Stack Overflow](https://stackoverflow.com/questions/tagged/gitlab).\n",[9,18],"news",[20],"Martin Brümmer","A guide to the breaking changes in GitLab 19.0","GitLab 19.0 removes several deprecated features. 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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/).",[9,721,18],"AI/ML",{"featured":11,"template":12,"slug":723},"gitlab-18-11-budget-guardrails-for-gitlab-credits",{"content":725,"config":728},{"title":726,"heroImage":717,"description":727,"date":718,"category":9},"GitLab 18.11 release","This release includes Agentic SAST Vulnerability Resolution, Data Analyst Foundational Agent, CI Expert Agent, and more.",{"featured":11,"template":12,"externalUrl":729},"https://docs.gitlab.com/releases/18/gitlab-18-11-released/",{"content":731,"config":739},{"title":732,"description":733,"authors":734,"heroImage":717,"date":718,"body":736,"category":9,"tags":737},"GitLab 18.11: CI Expert and Data Analyst AI agents target development gaps","Set up CI and query your software development lifecycle data with two new GitLab Duo Agent Platform foundational agents available in GitLab 18.11.",[735],"Corinne Dent","AI-generated code moves faster than the systems around it can keep up with. More code means more merge requests queued, more pipelines to configure, more questions about delivery that nobody has time to answer — and most of the tooling teams rely on wasn't built for this pace.\n\nIn GitLab 18.11, two new foundational agents for Duo Agent Platform address specific gaps in the development lifecycle that AI has largely left untouched:\n* CI Expert Agent (now in beta) focuses on the gap between writing code and getting it into a running pipeline\n* Data Analyst Agent (now generally available) focuses on the gap between shipping code and being able to answer basic questions about how that delivery is actually going.\n\n\nThese are problem areas that couldn't be solved by a general-purpose assistant. A tool running outside GitLab can generate a YAML file or answer a question, but it has no awareness of how your pipelines have historically performed, where failures cluster, or what your actual MR cycle times look like. That context lives in GitLab. These agents do too.\n## Fast CI setup with CI Expert Agent\n\nAI has made it easier than ever to write code. Getting that code into a running pipeline is still something most teams do days, or weeks, later — if at all. The blank-page problem isn't in the editor anymore. The blank page is now in `.gitlab-ci.yml`.\n\nDevelopers who have never configured CI don't know what language detection looks like in YAML, what their test commands should be, or how to validate the result before pushing. Teams either copy a config from a previous project that may not fit, stitch together examples from documentation, or wait for the one person who's done it before. If that person isn't available, CI becomes the thing you'll \"get to later.\" Later becomes never.\n\nWhen CI never happens, the impact shows up everywhere else. Changes ship without a reliable safety net, regressions surface in production instead of in pipelines, and work piles up in bigger, riskier batches because no one wants to be the person who “breaks the build.” Over time, teams normalize working in the dark, often relying on undocumented institutional knowledge and ad-hoc testing, instead of having a fast, predictable feedback loop baked into every change.\n\nCI Expert Agent, now available in beta, removes that friction. It inspects your repository, identifies your language and framework, and proposes a working build and test pipeline tailored to what's actually there — then explains every decision in plain language. The target: a running pipeline in minutes, with no YAML written by hand.\n\nWhat CI Expert Agent does:\n\n* Repo-aware pipeline generation detects language, framework, and test setup \n* Generates valid, runnable build and test configurations   \n* Guided first-pipeline flow with plain-language explanation of each step in Agentic Chat  \n* Native GitLab CI semantics with no config translation required\n\nBecause it runs inside GitLab and sees real pipeline behavior over time, each improvement can build on how teams actually work, not just on static examples.\n\u003Ciframe src=\"https://player.vimeo.com/video/1183458036?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=\"CI/CD Expert Agent\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\u003Cbr>\u003C/br>\n\nCI Expert Agent is available on GitLab.com, Self-Managed, Dedicated; Free, Premium, Ultimate Editions with Duo Agent Platform enabled.\n\n## Query GitLab data in plain language with Data Analyst Agent\n\nAI has sped up how teams ship. Answering basic questions about how that work is going has gotten harder, not easier.\n\nHow long are MRs sitting in review? Which pipelines are slowing teams down? Are deployment targets actually being hit? These questions used to be answerable by glancing at a dashboard. Now, with more code, more teams, and more complexity, the data exists — it's in GitLab — but accessing it still means waiting on an analytics team, filing a dashboard request, or learning GLQL.\n\nData Analyst Agent targets that gap. Ask a natural-language question and get an instant visualization in Agentic Chat. No query language, no dashboard request, no waiting for the answers to be assembled by someone else.\n\nFor example, the agent can answer questions about the following topics for these roles:\n\n* Engineering managers: MR cycle time, throughput by project, where reviews get stuck  \n* Developers: Contribution patterns, flaky tests blocking their MRs, pipeline speed trends  \n* DevOps and platform engineers: Pipeline success/failure rates, runner utilization, deployment frequency  \n* Engineering leadership: Cross-portfolio deployment frequency, project health metrics, lead time comparisons\n\nNow generally available in 18.11, the agent covers MRs, issues, projects, pipelines, and jobs — full software development lifecycle coverage, expanded from the beta scope. Because Data Analyst Agent queries what's already in GitLab, the context is always current, and there's no pipeline to maintain or third-party tool to keep synchronized. Generated GitLab Query Language queries can be copied and used anywhere GitLab Flavored Markdown is supported, with direct export to work items and dashboards on the roadmap.\n\n\u003Ciframe src=\"https://player.vimeo.com/video/1183094817?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=\"Data Analyst agent demo\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\u003Cbr>\u003C/br>\n\nData Analyst Agent is available on GitLab.com, Self-Managed, Dedicated; Free, Premium and Ultimate Edition with Duo Agent Platform enabled.\n\n## One platform, connected context\n\nBoth agents run inside GitLab, with access to the code, pipelines, issues, and merge requests already there. That's what separates platform-native AI from a disconnected assistant: the context is always current, and it only gets more useful over time. CI Expert Agent and Data Analyst Agent represent two concrete steps toward a platform where AI doesn't just help you write code faster; it helps you understand, ship, and maintain what gets built.\n\n> [Start a free trial of GitLab Duo Agent Platform](https://about.gitlab.com/gitlab-duo/) to experience these foundational AI agents.",[721,738,9],"features",{"featured":26,"template":12,"slug":740},"ci-expert-and-data-analyst-ai-agents-target-development-gaps",{"promotions":742},[743,757,768],{"id":744,"categories":745,"header":747,"text":748,"button":749,"image":754},"ai-modernization",[746],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":750,"config":751},"Get your AI maturity score",{"href":752,"dataGaName":753,"dataGaLocation":237},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":755},{"src":756},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":758,"categories":759,"header":760,"text":748,"button":761,"image":765},"devops-modernization",[9,563],"Are you just managing tools or shipping innovation?",{"text":762,"config":763},"Get your DevOps maturity score",{"href":764,"dataGaName":753,"dataGaLocation":237},"/assessments/devops-modernization-assessment/",{"config":766},{"src":767},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":769,"categories":770,"header":772,"text":748,"button":773,"image":777},"security-modernization",[771],"security","Are you trading speed for security?",{"text":774,"config":775},"Get your security maturity score",{"href":776,"dataGaName":753,"dataGaLocation":237},"/assessments/security-modernization-assessment/",{"config":778},{"src":779},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":781,"blurb":782,"button":783,"secondaryButton":788},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":784,"config":785},"Get your free trial",{"href":786,"dataGaName":44,"dataGaLocation":787},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":499,"config":789},{"href":48,"dataGaName":49,"dataGaLocation":787},1776432864312]