Resources
Developer resources
Developer tools and artifacts for Quake AI, distinct from the product documentation. Templates you copy, graphs you explore, and surfaces that load platform context into AI assistants.
Ways to Build
Map of the common ways to build on Quake AI: the Console, CLI and API, infrastructure as code, containers, Kubernetes, and AI-assisted development, with the rationale for each and who it fits.
Open →IaC Templates
Validated OpenTofu and Heat templates for the most common Quake AI infrastructure patterns: VMs, networks, Kubernetes, object storage, full stacks.
Open →Deployments
Real workloads you stand up from a validated template and keep running: multi-tier apps, Kubernetes, datastores, media workers, and self-hosted platforms. Each card shows a price estimate derived from the validated pricing dataset, plus the tier the workload wants.
Open →Solutions
Architecture briefs for common workloads: reference architectures that compose several services, and self-hosted apps for open-source stacks you operate yourself. Each card shows the build path, plan tier, and a monthly cost band from a representative starting footprint.
Open →AI-Assisted Development
Four surfaces for loading Quake AI documentation as context for AI coding assistants: llms.txt, per-page markdown, llms-full.txt, and the MCP server. Includes setup for Cursor, Claude Desktop, and VS Code.
Open →Migration
Evaluate Quake AI against your current provider, then move workloads. Per-provider concept translation and phased migration guides for AWS, Azure, DigitalOcean, GCP, and Hetzner.
Open →OpenStack
Quake AI runs on OpenStack. Reference for how each Quake AI service maps to its backing OpenStack project (Nova, Neutron, Cinder, Swift, Magnum, Heat, Keystone), with orientation for new users, OpenStack veterans, and engineers migrating from another cloud.
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