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GitLab

Google Antigravity agents get full context with GitLab Orbit GitLab Patch Release: 19.1.1, 19.0.3, 18.11.6 GitLab 19.1 release notes | GitLab Docs AI Catalog updates for governance and operations One vulnerability view: From scanner coverage to AI governance GitLab named a Leader in the 2026 Gartner® Magic Quadrant™ for DevSecOps Platforms GitLab and Capgemini accelerate DevSecOps transformation Introducing the 2026 EMEA GitLab Partner Award winners GitLab Patch Release: 19.0.2, 18.11.5, 18.10.8 Introducing GitLab Orbit GitLab Flex: Commit once, reshape your seats and AI spend GitLab: Built for the agentic engineering era Shai-Hulud copycat campaign targets Python developers through PyPI typosquatting Mythos-class Claude Fable 5 arrives on GitLab Duo Agent Platform GitLab Patch Release: 19.0.1, 18.11.4, 18.10.7 Claude Opus 4.8 on GitLab: Complex agentic work, less disruption Agentic coding is only as good as its context GitLab Patch Release: 18.9.8, 18.8.10, 18.7.7, 18.6.8, 18.5.7 Full security scanner coverage of your codebase in minutes Reduce supply chain risk with SBOM-based dependency scanning Transform MRs from manual tasks to an automated workflow Track CI component usage across your organization Manage CI/CD credentials with GitLab Secrets Manager More AI models for GitLab Duo Agent Platform Self-Hosted GitLab 19.0 | GitLab Docs GitLab Dedicated for Government now GovRAMP-authorized Beyond BYOK: Why governance matters for AI agents Fix bugs with Codex and GitLab 5 ways to fix misleading vulnerability severities with policy Harden your pipeline perimeter for the era of AI-assisted coding GitLab Patch Release: 18.11.3, 18.10.6, 18.9.7 GitLab Act 2 Consolidate your GitLab stack with Gitaly on Kubernetes Limit token exposure with fine-grained PATs Automate deployment processes with GitLab Duo Agent Platform Claude Code and GitLab: Three workflows that ship 8 Agentic AI patterns reshaping team collaboration How to detect and prevent Contagious Interview IDE attacks Atlassian will train on your data: Opt out with GitLab Automate detection testing with GitLab CI/CD and Duo
GitLab on Google Cloud: Fully managed, compliant, and AI-ready
Regnard Raquedan · 2026-06-10 · via GitLab

You can now run GitLab as a fully managed platform on Google Cloud, delivered by GitLab-certified managed service providers (MSPs) — with the latest Google AI models built in. Through MSP partners, including Beyond and Digital Future, your team can move to a scalable, reliable DevSecOps architecture on GitLab and Google Cloud, keep full control over where your code, pipelines, and security data live, and put Google's newest Gemini and Gemma models to work inside the same governed platform.

This builds on our April 2026 collaboration, which lets you call Google models through GitLab Duo Agent Platform and count that usage toward your existing Google Cloud commitment. Today, you also get a fully managed way to run the platform itself — and a deeper, faster model roadmap.

Why this matters

Running software development at scale puts two things in tension: you want access to the strongest, newest AI models, and you need control over your code, pipelines, and security data — ideally in the same platform, not bolted together from separate tools. Most teams end up trading one for the other: sovereignty without modern AI, or modern AI without governance. This collaboration is built to give you both. Here's what you can now do.

Run GitLab fully managed on Google Cloud

You don't have to be your own integrator. GitLab-certified MSP partners, including Beyond and Digital Future, now deliver a fully managed GitLab offering on Google Cloud, built for organizations subject to country-specific sovereignty, data residency, and other regulated requirements.

  • Your data stays where you need it. You keep full control over where your code, pipelines, and security data reside, while running the full GitLab platform on Google Cloud infrastructure.
  • No operational burden. Your MSP partner runs the platform to a high service-level agreement, so your team doesn't carry the work of managing the underlying infrastructure.
  • Auditable by design. Your compliance teams keep visibility into every agent action, merge request, and security finding through GitLab's built-in audit and policy controls. Governance doesn't stop when an agent takes over a workflow.

Match the model to the task

The latest Gemini models, including Gemini 3.5 Flash, are now available in GitLab Duo Agent Platform via Gemini Enterprise Agent Platform, and because GitLab is in Google's Gemini early-access program, new Gemini models keep landing in Duo as they ship, with no procurement work on your side. Different software tasks need different models, so the lineup gives you a clear choice:

ModelUse it forAvailability
Latest Gemini models (incl. Gemini 3.5 Flash)The full range — high-throughput, low-latency work like code completion and fast review suggestions, through deep reasoning for architectural decisions, multi-file refactors, and complex security analysisManaged (GitLab.com + Self-Managed), available now
Gemma 4Open weights you self-host and fully controlGitLab Duo Self-Hosted, available now

For self-hosted and regulated teams, Gemma 4 is now available for GitLab Duo Self-Hosted — an open-weight option beyond Gemini. It plugs into GitLab's self-hosted models architecture, so you run your own AI Gateway and keep every request and response inside your environment, on-premises or in a private cloud.

Leverage your existing Google Cloud commitment

Buy GitLab and Duo Agent Platform through Google Cloud Marketplace, and you can draw down your existing Google Cloud commitment to fund it:

  • No new budget cycle. Scale agentic AI against a commitment you've already made, instead of re-opening procurement every quarter.
  • One bill, one view. Platform, inference, and infrastructure spend land in the same Google Cloud billing surface — nothing to reconcile across vendors.

On top of that, you keep GitLab's own cost controls: usage dashboards, policy over which models run where, and the GitLab Credits model that gives your finance team predictable consumption. So you can answer the question your board is already asking — what did we spend on AI this quarter, and what did we get for it.

One governed platform, less fragmentation

Strong models bring better reasoning, faster tool calling, and long-context handling. GitLab Duo Agent Platform brings the software-delivery context a standalone coding assistant doesn't have — the merge request, the pipeline, the deployment target — which is what keeps a multi-step agent from stalling, and what makes monorepo-scale review workable at all. Put them together and your deployment, model choice, governance, and spend stay aligned inside the platform you already ship from, instead of fragmenting across separate assistants, security tools, and disconnected endpoints.

That's the whole point of doing this with Google Cloud: the right deployment option, the right models, and the right cost controls to run DevSecOps at scale, on infrastructure you control, with governance your compliance teams can audit.

If you are not using GitLab Duo Agent Platform today, you can start with a free trial.

If you are already using GitLab in the free tier, you can sign up for GitLab Duo Agent Platform by following a few simple steps.

And if you are an existing GitLab Premium or Ultimate subscriber, you can get started by turning on Duo Agent Platform and using the GitLab Credits that are included with your subscription.