Qovery vs Ravion

Qovery is a Kubernetes control plane that runs on customers’ infrastructure and is designed for use by people and AI agents. It supports deployments on Kubernetes, AWS, Google Cloud, Scaleway, and Azure, with capabilities including GitOps, preview environments, rolling releases, rollback, and approval gates. Its documentation describes real-time logs, metrics, and Kubernetes events without setup. Qovery says its eight AI agent skills work across more than 30 tools, including Claude Code, OpenAI Codex, Gemini CLI, Cursor, and VS Code Copilot. The MCP Server starts in read-only mode; writes require enabling access in both a connection setting and a separate Console setting, and actions appear in an audit trail. Qovery says customer workloads, secrets, and application data stay in the customer’s cloud account. It reports encryption in transit and at rest, regular third-party penetration tests, and compliance coverage including SOC 2 Type II, HIPAA, GDPR, and DORA. Annual plans are listed at $299.00 per month for Team, $899.00 per month for Growth, and $2,999.00 per month for Business. Plans have deployment-minute allowances, and unused minutes do not roll over.

Ravion is a framework and governed execution layer for internal developer platforms. It lets developers and AI agents provision, deploy and operate applications in a customer's AWS account. Platform teams can package existing Terraform as reusable modules with typed inputs, which developers use through forms. Each module instance is tracked as a stack with reviewable plans, approval gates, managed state and versioned resource history. Ravion supports deployments for containers, Lambdas and static sites, including rollbacks and deployment visibility. It works with Terraform providers and connects to AWS CloudWatch logs and metrics, Systems Manager Parameter Store and Secrets Manager, plus external CI through its API and CLI. Ravion says it uses short-lived, operation-scoped credentials through AWS STS and OIDC rather than storing AWS access keys. Infrastructure, application traffic, runtime secrets, builds, Terraform runs and pipeline runners stay in the customer's AWS account. AI agents can propose configuration changes and review dry-run diffs, subject to plans, policies and approval gates. AWS is supported today; Cloudflare, GCP and Azure are planned. The Individuals plan is free; Team is pay as you go, with module prices and pipeline-minute costs listed.