What is Qovery?
Qovery provisions and manages application environments, including the underlying Kubernetes cluster, inside a customer's own cloud account rather than hosting workloads itself (a "bring your own cloud" model). Its documentation describes it as the Kubernetes control plane for humans and AI agents, running on your own infrastructure, whether on a public cloud or on-premise. Qovery gives developers a self-service platform without the cost of building and maintaining one.
Developers deploy from git, and Qovery handles environment provisioning, preview environments, and infrastructure lifecycle so teams avoid building this tooling themselves. Deployments can be triggered from the console, CLI, API, Terraform provider or an AI tool, and build and deploy logs can be followed live with rollback to a previous version. Preview environments are created per pull request and torn down automatically. Cluster upgrades and security patches are handled by Qovery.
For AI agents, Qovery offers Policy API tokens that limit what each agent can do, plus an MCP server and skills for tools such as Claude Code. Every human and AI action is attributed and logged for audits. Pricing is subscription based: the Starter plan is for startups shipping a first production app on their own cloud at $299 per month billed yearly, and the Enterprise plan adds bring-your-own Kubernetes and a self-hosted control plane.
Key capabilities
- Clusters in your cloud account Managed production-grade clusters that run on your own cloud, with Qovery keeping them up to date.
- Multiple ways to deploy Console, CLI, API, or an AI tool through the deploy Qovery skill.
- Live logs and rollback Follow build and deploy logs in real time and roll back to a previous version.
- Built-in Copilot Reads logs, events and config to explain a failed deploy.
- Agent access Drive Qovery from Claude Code or Codex through its MCP server and skills.
- Security support A SOC 2 Type II report, a DPA and help with security reviews on the Scale plan.
Where Qovery fits
- Application deployment from git or a container registry
- Managed Kubernetes cluster provisioning and upgrades on AWS, GCP, Scaleway or Azure accounts
- Preview and multi-cloud environments
- Policy-controlled access for AI agents that deploy and debug
- Migration from PaaS platforms and self-managed clusters
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