[{"data":1,"prerenderedAt":781},["ShallowReactive",2],{"/en-us/blog/optimize-gitlab-object-storage-for-scale-and-performance":3,"navigation-en-us":34,"banner-en-us":434,"footer-en-us":444,"blog-post-authors-en-us-Tim Rizzi":686,"blog-related-posts-en-us-optimize-gitlab-object-storage-for-scale-and-performance":700,"assessment-promotions-en-us":732,"next-steps-en-us":771},{"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":23,"seo":29,"stem":31,"tagSlugs":32,"__hash__":33},"blogPosts/en-us/blog/optimize-gitlab-object-storage-for-scale-and-performance.yml","Optimize Gitlab Object Storage For Scale And Performance",[7],"tim-rizzi",null,"product",{"featured":11,"template":12,"slug":13},false,"BlogPost","optimize-gitlab-object-storage-for-scale-and-performance",{"title":15,"description":16,"authors":17,"category":9,"tags":19,"heroImage":22,"date":23,"body":24},"Optimize GitLab object storage for scale and performance","Configure GitLab object storage for maximum performance and cost savings. Learn consolidated forms, direct downloads, and identity-based authentication.",[18],"Tim Rizzi",[9,20,21],"tutorial","features","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749665151/Blog/Hero%20Images/blog-image-template-1800x945__27_.png","2025-10-08","Managing GitLab at scale requires strategic object storage configuration.\nHere's how to configure object storage for maximum performance, security, and reliability across your GitLab components.\n## Use consolidated form for GitLab components\nFor artifacts, LFS, uploads, packages, and other GitLab data, eliminate credential duplication with the consolidated form:\n```text gitlab_rails['object_store']['enabled'] = true\ngitlab_rails['object_store']['connection'] = {\n  'provider' => 'AWS',\n  'region' => 'us-east-1',\n  'use_iam_profile' => true\n}\ngitlab_rails['object_store']['objects']['artifacts']['bucket'] = 'gitlab-artifacts'\ngitlab_rails['object_store']['objects']['lfs']['bucket'] = 'gitlab-lfs'\n# ... additional buckets for each object type\n``` This reduces complexity while enabling encrypted S3 buckets and proper Content-MD5 headers.\n## Configure container registry separately\nThe container registry requires its own configuration since it doesn't support the consolidated form:\n```text registry['storage'] = {\n  's3_v2' => {  # Use the new v2 driver\n    'bucket' => 'gitlab-registry',\n    'region' => 'us-east-1',\n    # Omit access keys to use IAM roles\n  }\n}\n```\n**Note:** The s3_v1 driver is deprecated and will be removed in GitLab 19.0. Migrate to s3_v2 for better performance and reliability.\n## Disable proxy download for performance\nSet `proxy_download` to **false** (default) for direct downloads:\n```text # For GitLab objects - can be set globally\ngitlab_rails['object_store']['proxy_download'] = false\n# Or configure per bucket for granular control\ngitlab_rails['object_store']['objects']['artifacts']['proxy_download'] = false\ngitlab_rails['object_store']['objects']['lfs']['proxy_download'] = false\ngitlab_rails['object_store']['objects']['uploads']['proxy_download'] = true  # Example: keep proxy for uploads\n# Container registry defaults to redirect mode (direct downloads)\n# Only disable if your environment requires it:\nregistry['storage']['redirect']['disable'] = false  # Keep as false\n```\n**Important:** The `proxy_download` option can be configured globally at the object-store level or individually per bucket. This gives you flexibility to optimize based on your specific use case — for example, you might want direct downloads for large artifacts and LFS files, but proxy smaller uploads through GitLab for additional security controls.\nThis dramatically reduces server load and egress costs by letting clients download directly from object storage.\n## Choose identity-based authentication\n**AWS:** Use IAM roles instead of access keys:\n```text # GitLab objects\ngitlab_rails['object_store']['connection'] = {\n  'provider' => 'AWS',\n  'use_iam_profile' => true\n}\n# Container registry\nregistry['storage'] = {\n  's3_v2' => {\n    'bucket' => 'gitlab-registry',\n    'region' => 'us-east-1'\n    # No access keys = IAM role authentication\n  }\n}\n```\n**Google Cloud Platform:** Enable application default credentials:\n```text\ngitlab_rails['object_store']['connection'] = {\n  'provider' => 'Google',\n  'google_application_default' => true\n}\n```\n**Azure:** Use workload identities by omitting storage access keys.\n## Add encryption layers\nEnable server-side encryption for additional security:\n```text # GitLab objects\ngitlab_rails['object_store']['storage_options'] = {\n  'server_side_encryption' => 'AES256'\n}\n# Container registry\nregistry['storage'] = {\n  's3_v2' => {\n    'bucket' => 'gitlab-registry',\n    'encrypt' => true\n  }\n}\n```\nFor AWS KMS encryption, specify the key ARN in `server_side_encryption_kms_key_id`.\n## Use separate buckets for organization\nCreate dedicated buckets for each component:\n* **gitlab-artifacts** - CI/CD job artifacts\n* **gitlab-lfs** - Git LFS objects\n* **gitlab-uploads** - User uploads\n* **gitlab-packages** - Package registry\n* **gitlab-registry** - Container images\nThis isolation improves security, enables granular access controls, and simplifies cost tracking.\n## Key configuration differences\n| Component | Consolidated Form | Identity Auth | Encryption | Direct Downloads |\n| --- | --- | --- | --- | ---|\n| Artifacts, LFS, Packages | ✅ Supported | ✅ use_iam_profile | ✅ storage_options | ✅ proxy_download: false |\n| Container Registry | ❌ Separate config | ✅ Omit access keys | ✅ encrypt: true | ✅ redirect enabled by default |\n## Migration path\n1. **Start with GitLab objects:** Use the consolidated form for immediate complexity reduction.\n2. **Configure registry separately:** Use s3_v2 driver with IAM authentication.\n3. **Enable encryption:** Add server-side encryption for both components.\n4. **Optimize performance:** Ensure direct downloads are enabled with appropriate `proxy_download` settings.\n5. **Set up lifecycle policies:** Configure S3 lifecycle rules to clean up incomplete multipart uploads.\n## Additional resources\nFor a complete AWS S3 configuration example, see the [GitLab documentation on AWS S3 object storage setup](https://docs.gitlab.com/administration/object_storage/#aws-s3).\nFor more details on configuring proxy_download parameters per bucket, refer to the [GitLab object storage configuration documentation](https://docs.gitlab.com/administration/object_storage/#configure-the-parameters-of-each-object).\n*These configurations will scale with your growth while maintaining security and performance. 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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.",[706],"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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