Gantry vs Ravion

Gantry is an open-source internal developer platform for teams that need a service catalog and self-service workflows without dedicated platform engineering staff. Its catalog brings together services, APIs, teams, infrastructure components, and environments, including ownership and dependency relationships. Teams can create executable runbooks and workflows with schema-driven forms for tasks such as deployments and environment provisioning. Catalog entities can be written in YAML and applied with `gantry apply`, supporting version control, review, diffs, and rollback. Search uses SQLite FTS5, so Elasticsearch is not required. Official integrations include Kubernetes, GitHub, and ArgoCD; PagerDuty, Datadog, Grafana, and Flux are planned. Gantry ships as a Go binary with embedded SQLite and no external runtime dependencies. It can be installed from a binary, run through Docker or Docker Compose, or built from source. The documentation describes JWT authentication and requires installers to set an admin password. Gantry is self-hosted, licensed under Apache 2.0, and free. Its documentation says it is in active development and that APIs and schemas may change before its first stable release.

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.