[{"data":1,"prerenderedAt":796},["ShallowReactive",2],{"/en-us/blog/gitlab-backs-99-9-availability-with-service-credits-for-ultimate-customers":3,"navigation-en-us":38,"banner-en-us":438,"footer-en-us":448,"blog-post-authors-en-us-Aathira Nair|Lyle Kozloff":688,"blog-related-posts-en-us-gitlab-backs-99-9-availability-with-service-credits-for-ultimate-customers":714,"assessment-promotions-en-us":747,"next-steps-en-us":786},{"id":4,"title":5,"authorSlugs":6,"body":9,"categorySlug":10,"config":11,"content":15,"description":9,"extension":27,"isFeatured":12,"meta":28,"navigation":12,"path":29,"publishedDate":21,"seo":30,"stem":34,"tagSlugs":35,"__hash__":37},"blogPosts/en-us/blog/gitlab-backs-99-9-availability-with-service-credits-for-ultimate-customers.yml","Gitlab Backs 99 9 Availability With Service Credits For Ultimate Customers",[7,8],"aathira-nair","lyle-kozloff",null,"product",{"featured":12,"template":13,"slug":14},true,"BlogPost","gitlab-backs-99-9-availability-with-service-credits-for-ultimate-customers",{"title":16,"description":17,"authors":18,"date":21,"body":22,"heroImage":23,"category":10,"tags":24},"GitLab backs 99.9% availability with service credits for Ultimate customers","Ultimate customers now receive service credits when platform availability falls below 99.9%, ensuring reliability for mission-critical DevSecOps workflows.",[19,20],"Aathira Nair","Lyle Kozloff","2026-02-18","GitLab now backs its 99.9% availability commitment with service credits for Ultimate customers on GitLab.com and GitLab Dedicated. When monthly availability falls below this threshold, eligible customers receive credits toward future invoices. This commitment ensures your DevSecOps workflows have the reliability they need.\n\n## We value your trust\n\nModern software delivery operates at a velocity where teams push code, open merge requests, and track issues continuously throughout the day. Git operations — push, pull, clone — happen thousands of times per hour across distributed teams. When any of these core experiences become unavailable, your entire software delivery workflow stops. \n\nThe 99.9% availability service-level agreement (SLA) ensures your accelerated development pace doesn't hit infrastructure walls. Service credits demonstrate our accountability — tying our success to platform reliability and aligning our interests with yours. We hold ourselves accountable to your business outcomes, not just availability targets.\n\nGitLab's SLA commitment covers the core platform services essential to your DevSecOps workflows.\n\nAt launch, the covered experiences are:\n\n\\* Issues and merge requests  \n\\* Git operations (push, pull, clone via HTTPS and SSH)  \n\\* Container Registry operations  \n\\* Package Registry operations  \n\\* API requests (limited to the above)\n\nThe most up-to-date list of covered and excluded experiences is available in the [GitLab handbook](https://handbook.gitlab.com/handbook/engineering/infrastructure-platforms/service-level-agreement/#covered-experiences).\n\nService availability is measured using automated monitoring across multiple geographic locations, providing an accurate representation of actual service availability experienced by customers. When availability falls below 99.9%, customers are eligible to claim credits based on the severity of the shortfall.\n\n## Understanding downtime minutes\n\nWhen the GitLab service experiences degraded availability of 5% or more of valid customer requests for covered experiences in a given minute, resulting in server errors, this is called a [downtime minute](https://handbook.gitlab.com/handbook/engineering/infrastructure-platforms/service-level-agreement/#downtime-minute-definition). Server errors are defined as HTTP 5xx status codes or connection timeouts exceeding 30 seconds as determined by GitLab's internal and external monitoring systems.\n\nThe SLA measures server-side failures, but some issues may not trigger 5xx errors, such as application bugs that make features unusable, Sidekiq job processing outages, or infrastructure problems that degrade performance without failing requests outright.\n\nHere’s how you can claim service credits when applicable: \n\n1. Submit a support request at support.gitlab.com within thirty (30) days after the end of the affected month to claim downtime credits. \n\n2. The GitLab team reviews the claim, validates the downtime, and processes the credit if applicable. \n\n3. Service credits will be applied against your next issued invoice.\n\n[Read the handbook](https://handbook.gitlab.com/handbook/engineering/infrastructure-platforms/service-level-agreement/#calculating-monthly-uptime-percentage) for more on how monthly uptime availability is calculated, the service credits offered when applicable, and the credit claim procedures. \n\nWhile our monitoring is designed to capture the vast majority of service disruptions, if your experience doesn't match reported availability, we encourage you to submit a service credit claim. 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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.",[720],"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&byline=0&portrait=0&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=\"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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