[{"data":1,"prerenderedAt":780},["ShallowReactive",2],{"/en-us/blog/reduce-the-load-on-gitlab-gitaly-with-bundle-uri":3,"navigation-en-us":34,"banner-en-us":434,"footer-en-us":444,"blog-post-authors-en-us-Olivier Campeau":684,"blog-related-posts-en-us-reduce-the-load-on-gitlab-gitaly-with-bundle-uri":698,"assessment-promotions-en-us":731,"next-steps-en-us":770},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":25,"isFeatured":11,"meta":26,"navigation":27,"path":28,"publishedDate":18,"seo":29,"stem":30,"tagSlugs":31,"__hash__":33},"blogPosts/en-us/blog/reduce-the-load-on-gitlab-gitaly-with-bundle-uri.yml","Reduce The Load On Gitlab Gitaly With Bundle Uri",[7],"olivier-campeau",null,"product",{"featured":11,"template":12,"slug":13},false,"BlogPost","reduce-the-load-on-gitlab-gitaly-with-bundle-uri",{"title":15,"description":16,"heroImage":17,"date":18,"body":19,"category":9,"tags":20,"authors":23},"Reduce the load on GitLab Gitaly with bundle URI","Discover what the bundle URI Git feature is, how it is integrated into Gitaly, configuration best practices, and how GitLab users can benefit from it.","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099013/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2814%29_6VTUA8mUhOZNDaRVNPeKwl_1750099012960.png","2025-06-24","Gitaly plays a vital role in the GitLab ecosystem — it is the server component that handles all Git operations. Every push and pull made to/from a repository is handled by Gitaly, which has direct access to the disk where the actual repositories are stored. As a result, when Gitaly is under heavy load, some operations like CI/CD pipelines and browsing a repository in the\nGitLab UI can become quite slow. This is particularly true when serving clones and fetches for large and busy monorepos, which can consume large amounts of CPU and memory.\n\n[Bundle URI](https://docs.gitlab.com/administration/gitaly/bundle_uris/) takes significant load off of Gitaly servers during clones by allowing Git to pre-download a bundled repository from object storage before calling the Gitaly servers to fetch the remaining objects.\n\nHere is a graph that shows the difference between clones without and with bundle URI.\n\n![Graph that shows the difference between clones without and with bundle URI](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750705069/rvbm4ru1w58msd6zv4x7.png)\n\nThis graph shows the results of a small test we ran on an isolated GitLab installation, with Gitaly running on a machine with 2 CPUs. We wanted to test bundle URI with a large repository, so we pushed the [GitLab repository](https://gitlab.com/gitlab-org/gitlab) to the instance. We also generated a bundle beforehand.\n\nThe big CPU spike is from when we performed a single clone of the GitLab repository with bundle URI disabled. It's quite noticeable. A little later, we turned on bundle URI and launched three concurrent clones of the GitLab repository. Sure enough, turning on bundle URI provides massive performance gain. We can't even distinguish the CPU usage of the three clones from normal usage.\n\n## Configure Gitaly to use bundle URI\n\nTo enable bundle URI on your GitLab installation, there are a couple of things you need to configure.\n\n### Create a cloud bucket\n\nBundles need to be stored somewhere. The ideal place is in a cloud storage bucket. Gitaly uses the [gocloud.dev](https://pkg.go.dev/gocloud.dev) library to read and write from cloud storage. Any cloud storage solution supported by this library can be used. Once you have a cloud bucket URL, you can add it in the Gitaly configuration here:\n\n```toml\n[bundle_uri]\ngo_cloud_url = \"\u003Cbucket-uri>\"\n```\n\nIt must be noted that Gitaly does not manage the lifecycle of the bundles stored in the bucket. To avoid cost issues, object lifecycle policies must be enabled on the bucket in order to delete unused or old objects.\n\n### Enable the feature flags\n\nThere are two feature flags to enable:\n\n- `gitaly_bundle_generation` enables [auto-generation](#auto-generated) of bundles.\n\n- `gitaly_bundle_uri` makes Gitaly advertise bundle URIs when they are available (either manually created or auto-generated) and allows the user to [manually](#manual) generate bundles.\n\nThese feature flags can be enabled at-large on a GitLab installation, or per repository. See the [documentation on how to enable a GitLab feature behind a feature flag](https://docs.gitlab.com/administration/feature_flags/#how-to-enable-and-disable-features-behind-flags).\n\n### How to generate bundles\n\nGitaly offers two ways for users to use bundle URI: a [manual](#manual) way and an [auto-generated](#auto-generated) way.\n\n#### Manual\n\nIt is possible to create a bundle manually by connecting over SSH with the Gitaly node that stores the repository you want to create a bundle for, and run the following command:\n\n```shell\nsudo -u git -- /opt/gitlab/embedded/bin/gitaly bundle-uri \n--config=\u003Cconfig-file>\n--storage=\u003Cstorage-name>\n--repository=\u003Crelative-path>\n```\n\nThis command will create a bundle for the given repository and store it into the bucket configured above. When a subsequent `git clone` request will reach Gitaly for the same repository, the bundle URI mechanism described above will come into play.\n\n#### Auto-generated\n\nGitaly can also generate bundles automatically, using a heuristic to determine if it is currently handling frequent clones for the same repository.\n\nThe current heuristic keeps track of the number of times a `git fetch` request is issued for each repository. If the number of requests reaches a certain `threshold` in a given time `interval`, a bundle is automatically generated. Gitaly also keeps track of the last time it generated a bundle for a repository. When a new bundle should be regenerated, based on the `threshold` and `interval`, Gitaly looks at the last time a bundle was generated for the given repository. It will only generate a new bundle if the existing bundle is older than some `maxBundleAge` configuration. The old bundle is overwritten. There can only be one bundle per repository in cloud storage.\n\n## Using bundle URI\n\nWhen a bundle exists for a repository, it can be used by the `git clone` command.\n\n### Cloning from your terminal\n\nTo clone a repository from your terminal, make sure your Git configuration enables bundle URI. The configuration can be set like so:\n\n```shell\ngit config --global transfer.bundleuri true\n```\n\nTo verify that bundle URI is used during a clone, you can run the `git clone` command with `GIT_TRACE=1` and see if your bundle is being downloaded:\n```shell\n➜  GIT_TRACE=1 git clone https://gitlab.com/gitlab-org/gitaly\n...\n14:31:42.374912 run-command.c:667       trace: run_command: git-remote-https '\u003Cbundle-uri>'\n...\n```\n\n### Cloning during CI/CD pipelines\n\nOne scenario where using bundle URI would be beneficial is during a CI/CD pipeline, where each job needs a copy of the repository in order to run. Cloning a repository during a CI/CD pipeline is the same as cloning a repository from your terminal, except that the Git client in this case is the GitLab Runner. Thus, we need to configure the GitLab Runner in such a way that it can use bundle URI.\n\n**1. Update the helper-image**\n\nThe first thing to do to configure the GitLab Runner is to [overwrite the helper-image](https://docs.gitlab.com/runner/configuration/advanced-configuration/#override-the-helper-image) that your GitLab Runner instances use. The `helper-image` is the image that is used to run the process of cloning a repository before the job starts. To use bundle URI, the image needs the following:\n\n- Git Version 2.49.0 or later\n\n- [`GitLab Runner helper`](https://gitlab.com/gitlab-org/gitlab-runner/-/tree/main/apps/gitlab-runner-helper?ref_type=heads) Version 18.1.0 or later\n\nThe helper-images can be found [here](https://gitlab.com/gitlab-org/gitlab-runner/container_registry/1472754?orderBy=PUBLISHED_AT&sort=desc&search[]=v18.1.0). Select an image that corresponds to the OS distribution and the architecture you use for your GitLab Runner instances, and verify that the image satisfies the requirements.\n\nAt the time of writing, the `alpine-edge-\u003Carch>-v18.1.0*` tag meets all requirements.\n\nYou can validate the image meets all requirements with:\n\n```shell\ndocker run -it \u003Cimage:tag>\n$ git version ## must be 2.49.0 or newer\n$ gitlab-runner-helper -v ## must be 18.0 or newer\n```\n\nIf you do not find an image that meets the requirements, you can also use the helper-image as a base image and install the requirements yourself in a custom-built image that you can host on [GitLab Container Registry](https://docs.gitlab.com/user/packages/container_registry/).\n\nOnce you have found the image you need, you must configure your GitLab Runner instances to use it by updating your `config.toml` file:\n\n```toml\n[[runners]]\n  (...)\n  executor = \"docker\"\n  [runners.docker]\n    (...)\n    helper_image = \"image:tag\" ## \u003C-- put the image name and tag here\n```\n\nOnce the configuration is changed, you must restart the runners for the new configuration to take effect.\n\n**2. Turn on the feature flag**\n\nNext, you must enable the `FF_USE_GIT_NATIVE_CLONE` [GitLab Runner feature flags](https://docs.gitlab.com/runner/configuration/feature-flags/) in your `.gitlab-ci.yml` file. To do that, simply add it as a variable and set to `true` :\n\n```yaml\nvariables:\n  FF_USE_GIT_NATIVE_CLONE: \"true\"\n```\n\nThe `GIT_STRATEGY` must also be [set to `clone`](\u003Chttps://docs.gitlab.com/ci/runners/configure_runners/#git-strategy>), as Git bundle URI only works with `clone` commands.\n\n## How bundle URI works\n\nWhen a user clones a repository with the `git clone` command, a process called [`git-receive-pack`](https://git-scm.com/docs/git-receive-pack) is launched on the client's machine. This process communicates with the remote repository's server (it can be over HTTP/S, SSH, etc.) and asks to start a [`git-upload-pack`](https://git-scm.com/docs/git-receive-pack) process. Those two processes then exchange information using the Git protocol (it must be noted that bundle URI is only supported with [Git protocol v2](https://git-scm.com/docs/protocol-v2)). The capabilities both processes support and the references and objects the client needs are among the information exchanged. Once the Git server has determined which objects to send to the client, it must package them into a packfile, which, depending on the size of the data it must process, can consume a good amount of resources.\n\nWhere does bundle URI fit into this interaction? If bundle URI is advertised as a capability from the `upload-pack` process and the client supports bundle URI, the Git client will ask the server if it knows about any bundle URIs. The server sends those URIs back and the client downloads those bundles.\n\nHere is a diagram that shows those interactions:\n\n```mermaid\n\nsequenceDiagram\n\n\n    participant receive as Client\n\n\n    participant upload as Server\n\n\n    participant cloud as File server\n\n\n    receive ->> upload: issue git-upload-pack\n\n\n    upload -->> receive: list of server capabilities\n\n\n    opt if bundle URI is advertised as a capability\n\n\n    receive ->> upload: request bundle URI\n\n\n    upload -->> receive: bundle URI\n\n\n    receive ->> cloud: download bundle at URI\n\n\n    cloud -->> receive: bundle file\n\n\n    receive ->> receive: clone from bundle\n\n\n    end\n\n\n    receive ->> upload: requests missing references and objects\n\n\n    upload -->> receive: packfile data\n\n```\n\nAs such, Git [bundle URI](https://git-scm.com/docs/bundle-uri) is a mechanism by which, during a `git clone`, a Git server can advertise the URI of a bundle for the repository being cloned by the Git client. When that is the case, the Git client can clone the repository from the bundle and request from the Git server only the missing references or objects that were not part of the bundle. This mechanism really helps to alleviate pressure from the Git server.\n\n## Alternatives\n\nGitLab also has a feature [Pack-objects cache](https://docs.gitlab.com/administration/gitaly/configure_gitaly/#pack-objects-cache). This feature works slightly differently than bundle URI. When the server packs objects together into a so-called packfile, this feature will keep that file in the cache. When another client needs the same set of objects, it doesn't need to repack them, but it can just send the same packfile again.\n\nThe feature is only beneficial when many clients request the exact same set of objects. In a repository that is quick-changing, this feature might not give any improvements. With bundle URI, it doesn't matter if the bundle is slightly out-of-date because the client can request missing objects after downloading the bundle and apply those changes on top. Also bundle URI in Gitaly stores the bundles on external storage, which the Pack-objects Cache stores them on the Gitaly node, so using the latter doesn't reduce network and I/O load on the Gitaly server.\n\n## Try bundle URI today\n\nYou can try the bundle URI feature in one of the following ways:\n\n* Download a [free trial version of GitLab Ultimate](https://about.gitlab.com/free-trial/).\n\n* If you already run a self-hosted GitLab installation, upgrade to 18.1.\n\n* If you can't upgrade to 18.1 at this time, [download GitLab](https://about.gitlab.com/install/) to a local machine.",[9,21,22],"DevSecOps","git",[24],"Olivier 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GitLab metrics and registry features help reduce CI/CD bottlenecks","See how CI/CD Job Performance Metrics and Container Virtual Registry, currently in beta, help platform teams quickly spot slow jobs and simplify multi-registry container pulls.",[704],"Talia Armato-Helle","https://res.cloudinary.com/about-gitlab-com/image/upload/v1771438388/t6sts5qw4z8561gtlxiq.png","Platform and DevOps engineers spend too much time piecing together visibility across fragmented tools and managing infrastructure that should just work.\n\nTwo new GitLab features currently in beta tackle this from different angles but share the same goal: giving practitioners direct control over the CI/CD infrastructure they depend on, without adding another third-party tool. One surfaces job-level performance data right where you monitor pipelines. The other simplifies how you pull container images from multiple registries with built-in caching.\n\nBoth features are open for feedback now. Your input will help shape what ships next.\n\n## CI/CD Job Performance Metrics\n\n* **Available tiers:** GitLab Premium, GitLab Ultimate\n* **Status:** Limited-availability beta on GitLab.com; available on GitLab Self-Managed and GitLab Dedicated when ClickHouse is configured\n\nToday, there’s no simple way to see when a particular job’s duration starts increasing or which jobs are quietly dragging down your pipeline runtimes. Most teams either build custom dashboards or manually dig through logs to answer basic questions like:\n\n* Which jobs are slowest?  \n* Where are failure rates climbing?  \n* Which stage is the real bottleneck?\n\nCI/CD Job Performance Metrics changes that by adding a new job-focused panel to the CI/CD analytics page at the project level.\n\nFor each job in your pipelines, you can see:\n\n* Typical (P50, median) and worst‑case (P95) job duration, so you can quickly view normal versus slowest runs  \n* Failure rate, so you can spot fragile or flaky jobs  \n* Job name and stage, covering the last 30 days by default\n\nThe table is sortable, searchable by job name, and paginated, so platform teams get a single view to answer questions that previously required separate tools or custom reporting.\n\n**Try it now**\n\n* Navigate to your project and select **Analyze \\> CI/CD analytics**.  \n* Look for the CI/CD job performance metrics panel and sort by duration or failure rate to find your slowest or least reliable jobs.\n\n**Documentation**\n\n* [CI/CD analytics – CI/CD job performance metrics](https://docs.gitlab.com/user/analytics/ci_cd_analytics/#cicd-job-performance-metrics)\n\n**What’s coming next**\n\nWe’re working on stage-level grouping, so you can view aggregated metrics across your build, test, and deploy stages, and quickly understand where to focus optimization work.\n\n**Share your feedback:**\n\n* [CI/CD job performance metrics epic](https://gitlab.com/groups/gitlab-org/-/work_items/18548)\n\n## Container Virtual Registry\n\n**Tier:** GitLab Premium, GitLab Ultimate\n**Status:** Beta, API-ready in 18.9\n\nMost organizations pulling container images into CI/CD pipelines rely on multiple registries: Docker Hub, Harbor, Quay, and internal registries, to name a few. Managing authentication, availability, and caching across all of them is operational overhead that slows pipelines down and introduces fragility.\n\nThe Container Virtual Registry lets you create a single GitLab endpoint that pulls from multiple upstream container sources with built-in caching.\n\nInstead of configuring credentials and availability for each registry individually in your pipeline configuration, you can:\n\n* Point your pipelines at one GitLab virtual registry endpoint  \n* Configure multiple upstream registries (Docker Hub, Harbor, Quay, and others using long-lived token authentication)  \n* Let GitLab resolve image pulls automatically, with pull-through caching to reduce bandwidth costs and improve reliability\n\nFor teams evaluating GitLab as a container registry replacement, this closes a critical capability gap. For teams already managing multi-registry container workflows, it centralizes image management into GitLab and cuts down on repeated pulls.\n\n**What the beta supports today**\n\n* Upstream registries using long-lived token authentication: Docker Hub, Harbor, Quay, and other compatible registries  \n* Pull-through caching so commonly used images are served from GitLab after the first pull  \n* API-first configuration, with UI management in progress++\n\nCloud provider registries requiring IAM authentication (such as Amazon Elastic Container Registry, Google Artifact Registry, and Azure Container Registry) are being considered for future iterations.\n\n**Test it today**\n\n* The Container Virtual Registry is API-ready in 18.9.  \n* SaaS (GitLab.com): Request access through your CSM or by commenting on the feedback issue below to have the feature flag enabled for your group.  \n* Self-managed: Enable the feature flag and configure the virtual registry using the API.\n\n**Documentation**\n\n* [Container Virtual Registry API](https://docs.gitlab.com/api/container_virtual_registries/)  \n* [Pull container images from the virtual registry](https://docs.gitlab.com/user/packages/virtual_registry/container/#pull-container-images-from-the-virtual-registry)\n\n\n Watch this walkthrough of the Container Virtual Registry Beta:\n   \n\n  \u003Ciframe src=\"https://player.vimeo.com/video/1167512082?title=0&amp;byline=0&amp;portrait=0&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;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=\"20260223_Container Virtual Registry Beta_V1\">\u003C/iframe>\u003C\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\n  \u003Cbr>\u003C/br>\n\n\n\n**Share your feedback:**\n\n* [Container virtual registry feedback issue](https://gitlab.com/gitlab-org/gitlab/-/issues/589630)\n\n## Help us build what matters\n\nEveryone in the GitLab community is a contributor. We built these betas based on community requests.\n\n* **CI/CD Job Performance Metrics** came from teams who had no easy way to see when build times started trending in the wrong direction, or which jobs were hurting pipeline reliability.  \n* **Container Virtual Registry** came from enterprise customers managing multiple registries and looking to reduce tool sprawl and bandwidth costs while evaluating GitLab as a central registry.\n\nYour feedback shapes what we create next. Try one or both of these betas, and share your experience in the linked feedback issues.\n\nThis is the first in a series of Core DevOps betas we plan to highlight. 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