[{"data":1,"prerenderedAt":825},["ShallowReactive",2],{"/en-us/blog/next-generation-gitlab-container-registry-goes-ga":3,"navigation-en-us":41,"banner-en-us":462,"footer-en-us":472,"blog-post-authors-en-us-Tim Rizzi":712,"blog-related-posts-en-us-next-generation-gitlab-container-registry-goes-ga":727,"blog-promotions-en-us":762,"next-steps-en-us":815},{"id":4,"title":5,"authorSlugs":6,"authors":8,"body":10,"category":11,"categorySlug":11,"config":12,"content":16,"date":24,"description":17,"extension":25,"externalUrl":26,"featured":15,"heroImage":19,"isFeatured":15,"meta":27,"navigation":15,"path":28,"publishedDate":24,"rawbody":29,"seo":30,"slug":14,"stem":35,"tagSlugs":36,"tags":39,"template":13,"updatedDate":26,"__hash__":40},"blogPosts/en-us/blog/next-generation-gitlab-container-registry-goes-ga.md","Next-generation GitLab container registry goes GA",[7],"tim-rizzi",[9],"Tim Rizzi","Last year, we embarked on an ambitious journey to [re-architect the GitLab container registry](https://gitlab.com/gitlab-org/container-registry/-/issues/199) and unlock powerful new capabilities like zero-downtime garbage collection. After successfully migrating GitLab.com to this next-generation registry, we [opened up a beta program](https://about.gitlab.com/blog/gitlabs-next-generation-container-registry-is-now-available/) for self-managed customers to test out the new architecture and provide feedback.\n\nThe results from the beta program have been outstanding – participants are already realizing major benefits, including the following:\n\n- significant storage cost and maintenance time savings from efficient zero-downtime garbage collection, with no required downtime or manual interventions\n- improved performance and reliability for tag cleanup policies and the container registry API and UI\n- early access to new features like better sorting/filtering and storage usage visibility\n\nBased on the positive feedback and successful migrations during the beta, we are excited to announce that the next-generation GitLab container registry will become generally available – but off by default – for self-managed deployments starting with GitLab 17.3.\n\nBelow are the goals and non-goals for reaching this point. The goals are what we need to have in place to officially call this feature GA. The non-goals clarify what will not be present or required at the start of GA support for bringing your own database; however, these features may be added later.\n\n__Goals__\n- The import process is free of known bugs.\n- Import documentation reflects known best practices and addresses feedback from the [beta program](https://gitlab.com/gitlab-org/gitlab/-/issues/423459).\n- Registry API, metadata database, and zero-downtime garbage collection are stable and reliable.\n- Able to automatically apply database schema migrations for Charts installs during upgrades.\n- Provide registry database as an opt-in improvement.\n\n__Non-goals__\n- Automatically provision registry database.\n- Automatically apply database schema migrations for omnibus installs during upgrades.\n- Automatically import object storage data.\n- Provide Geo support to ensure your registry is highly available.\n\nFor existing self-managed instances, here's what you can expect:\n\n- In GitLab 17.3, the new registry will be included, but disabled by default to allow time for planning migrations.\n- Enabling the database will be an opt-in process outlined in the [documentation](https://docs.gitlab.com/administration/packages/container_registry_metadata_database/).\n- The legacy container registry will still receive security updates, but new features and improvements will only be developed for the next-gen version.\n- We will target GitLab 19.0 for the legacy registry to stop being supported after over a year of co-existence.\n- Our goal is to make this transition as seamless as possible while putting customers in control of their migration timeline. The [documentation](https://docs.gitlab.com/administration/packages/container_registry_metadata_database/) covers all the details on how to plan and execute the move to the next-gen registry.\n\nThis architectural investment lays the foundation for an even more powerful container registry experience in the years ahead. Some of the significant improvements on our roadmap include:\n\n- protected repositories and immutable tags\n- improved Helm chart management\n- improved support for signing and attestations\n- many more UX/UI enhancements are only possible with the database architecture\n\nWe couldn't have reached this GA milestone without the valuable feedback from our beta participants. As always, please continue to share your experiences so we can make the GitLab container registry an indispensable part of your DevSecOps toolchain.\n\n> You can try the container registry today with a [free trial of GitLab Ultimate](https://gitlab.com/-/trial_registrations/new?glm_source=about.gitlab.com/blog&glm_content=default-saas-trial).","product",{"template":13,"slug":14,"featured":15},"BlogPost","next-generation-gitlab-container-registry-goes-ga",true,{"title":5,"description":17,"authors":18,"heroImage":19,"tags":20,"category":11,"date":24,"body":10},"Starting in GitLab 17.3, GitLab self-managed instances can access the generally available container registry, which features efficient zero-downtime garbage collection and other benefits.",[9],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749662332/Blog/Hero%20Images/blog-image-template-1800x945__23_.png",[21,22,23,11],"DevSecOps platform","features","cloud native","2024-07-23","md",null,{},"/en-us/blog/next-generation-gitlab-container-registry-goes-ga","---\nseo:\n  title: Next-generation GitLab container registry goes GA\n  description: >-\n    Starting in GitLab 17.3, GitLab self-managed instances can access the\n    generally available container registry, which features efficient\n    zero-downtime garbage collection and other benefits.\n  ogTitle: Next-generation GitLab container registry goes GA\n  ogDescription: >-\n    Starting in GitLab 17.3, GitLab self-managed instances can access the\n    generally available container registry, which features efficient\n    zero-downtime garbage collection and other benefits.\n  noIndex: false\n  ogImage: >-\n    https://res.cloudinary.com/about-gitlab-com/image/upload/v1749662332/Blog/Hero%20Images/blog-image-template-1800x945__23_.png\n  ogUrl: >-\n    https://about.gitlab.com/blog/next-generation-gitlab-container-registry-goes-ga\n  ogSiteName: https://about.gitlab.com\n  ogType: article\n  canonicalUrls: >-\n    https://about.gitlab.com/blog/next-generation-gitlab-container-registry-goes-ga\ntitle: Next-generation GitLab container registry goes GA\ndescription: Starting in GitLab 17.3, GitLab self-managed instances can access the generally available container registry, which features efficient zero-downtime garbage collection and other benefits.\nauthors:\n  - Tim Rizzi\nheroImage: https://res.cloudinary.com/about-gitlab-com/image/upload/v1749662332/Blog/Hero%20Images/blog-image-template-1800x945__23_.png\ntags:\n  - DevSecOps platform\n  - features\n  - cloud native\n  - product\ncategory: product\ndate: '2024-07-23'\nslug: next-generation-gitlab-container-registry-goes-ga\nfeatured: true\ntemplate: BlogPost\n---\n\nLast year, we embarked on an ambitious journey to [re-architect the GitLab container registry](https://gitlab.com/gitlab-org/container-registry/-/issues/199) and unlock powerful new capabilities like zero-downtime garbage collection. After successfully migrating GitLab.com to this next-generation registry, we [opened up a beta program](https://about.gitlab.com/blog/gitlabs-next-generation-container-registry-is-now-available/) for self-managed customers to test out the new architecture and provide feedback.\n\nThe results from the beta program have been outstanding – participants are already realizing major benefits, including the following:\n\n- significant storage cost and maintenance time savings from efficient zero-downtime garbage collection, with no required downtime or manual interventions\n- improved performance and reliability for tag cleanup policies and the container registry API and UI\n- early access to new features like better sorting/filtering and storage usage visibility\n\nBased on the positive feedback and successful migrations during the beta, we are excited to announce that the next-generation GitLab container registry will become generally available – but off by default – for self-managed deployments starting with GitLab 17.3.\n\nBelow are the goals and non-goals for reaching this point. The goals are what we need to have in place to officially call this feature GA. The non-goals clarify what will not be present or required at the start of GA support for bringing your own database; however, these features may be added later.\n\n__Goals__\n- The import process is free of known bugs.\n- Import documentation reflects known best practices and addresses feedback from the [beta program](https://gitlab.com/gitlab-org/gitlab/-/issues/423459).\n- Registry API, metadata database, and zero-downtime garbage collection are stable and reliable.\n- Able to automatically apply database schema migrations for Charts installs during upgrades.\n- Provide registry database as an opt-in improvement.\n\n__Non-goals__\n- Automatically provision registry database.\n- Automatically apply database schema migrations for omnibus installs during upgrades.\n- Automatically import object storage data.\n- Provide Geo support to ensure your registry is highly available.\n\nFor existing self-managed instances, here's what you can expect:\n\n- In GitLab 17.3, the new registry will be included, but disabled by default to allow time for planning migrations.\n- Enabling the database will be an opt-in process outlined in the [documentation](https://docs.gitlab.com/administration/packages/container_registry_metadata_database/).\n- The legacy container registry will still receive security updates, but new features and improvements will only be developed for the next-gen version.\n- We will target GitLab 19.0 for the legacy registry to stop being supported after over a year of co-existence.\n- Our goal is to make this transition as seamless as possible while putting customers in control of their migration timeline. The [documentation](https://docs.gitlab.com/administration/packages/container_registry_metadata_database/) covers all the details on how to plan and execute the move to the next-gen registry.\n\nThis architectural investment lays the foundation for an even more powerful container registry experience in the years ahead. Some of the significant improvements on our roadmap include:\n\n- protected repositories and immutable tags\n- improved Helm chart management\n- improved support for signing and attestations\n- many more UX/UI enhancements are only possible with the database architecture\n\nWe couldn't have reached this GA milestone without the valuable feedback from our beta participants. 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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.",[289,753,754],"AWS","AI/ML","2026-04-21",[757,758],"Joe Mann","Mark Kriaf","https://res.cloudinary.com/about-gitlab-com/image/upload/v1776362275/ozbwn9tk0dditpnfddlz.png",{"featured":15,"template":13,"slug":761},"gitlab-amazon-platform-orchestration-on-a-trusted-ai-foundation",{"promotions":763},[764,778,789,801],{"id":765,"categories":766,"header":768,"text":769,"button":770,"image":775},"ai-modernization",[767],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":771,"config":772},"Get your AI maturity score",{"href":773,"dataGaName":774,"dataGaLocation":252},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":776},{"src":777},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":779,"categories":780,"header":781,"text":769,"button":782,"image":786},"devops-modernization",[11,581],"Are you just managing tools or shipping innovation?",{"text":783,"config":784},"Get your DevOps maturity score",{"href":785,"dataGaName":774,"dataGaLocation":252},"/assessments/devops-modernization-assessment/",{"config":787},{"src":788},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":790,"categories":791,"header":793,"text":769,"button":794,"image":798},"security-modernization",[792],"security","Are you trading speed for security?",{"text":795,"config":796},"Get your security maturity score",{"href":797,"dataGaName":774,"dataGaLocation":252},"/assessments/security-modernization-assessment/",{"config":799},{"src":800},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":802,"paths":803,"header":806,"text":807,"button":808,"image":813},"github-azure-migration",[804,805],"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. 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