Platform Architecture Overview | Kamiwaza Docs
Documentation for Kamiwaza 0.13.0
This is documentation for Kamiwaza 0.13.0, which is no longer actively maintained. For the current GA release, see 1.0.1.
Version: 0.13.0
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Kamiwaza is a Kubernetes-based AI platform that combines model serving, governed data access, application deployment, and security controls behind a single customer-facing domain. This page provides a high-level view of the current architecture used in supported deployments.
System Architecture Diagram
Compute and Orchestration
- Kubernetes
- Ray and Serving Runtimes
- Extension Operator
- CPU and GPU Nodes
- Shared Platform Layer
- Traefik or Istio Ingress
- Identity Provider
- Postgres or SQLite in lite mode
- etcd
- DataHub and Catalog Services
- Object Storage
- Platform Services
- API and Auth Gateway
- Model and Serving Services
- DDE, Retrieval, and Catalog
- Workrooms and Collaboration
- Logger and Audit Services
- User Experience
- Kamiwaza Web UI
- SDK and API Clients
- App Garden and Tool Shed
Architecture Layers
Experience layer
This is how users and client applications interact with Kamiwaza.
- Kamiwaza Web UI for administration, models, workrooms, apps, tools, and logs
- SDK and API clients for programmatic access
- App Garden and Tool Shed for launching applications and tool servers behind managed routes
Services layer
This layer contains the platform APIs and business logic.
- API and Auth Gateway for authenticated access, routing, and policy enforcement
- Model and Serving Services for model lifecycle and inference
- DDE, Retrieval, and Catalog for ingestion, discovery, secret references, and retrieval flows
- Workrooms and Collaboration for shared workspace functionality
- Logger and Audit Services for runtime troubleshooting and security evidence
Shared platform layer
This layer provides the shared services the platform depends on.
- Traefik or Istio for ingress and routing, depending on environment
- Identity provider integration for authenticated deployments
- Postgres as the standard persistent database in auth-enabled deployments
- SQLite as a reduced-scope database option in lite mode
- etcd for cluster coordination and runtime configuration
- DataHub and related catalog services for metadata-backed catalog workflows
- Object storage for uploaded files, workroom context, and related assets
Compute and orchestration layer
This layer runs the workloads that power the platform.
- Kubernetes as the primary deployment target
- Ray and serving runtimes for model execution and distributed work
- Extension Operator for managed application and tool deployment workflows
- CPU and GPU nodes that host inference and platform workloads
Technology Stack
| Category | Technologies |
|---|---|
| Backend | Python, FastAPI, Ray |
| Frontend | React |
| Data and metadata | Postgres, SQLite in lite mode, etcd, DataHub |
| Routing and ingress | Traefik, optional Istio |
| Deployment | Kubernetes, Helm |
Design Principles
Single customer-facing domain with path-based runtime routing as the standard deployment model
Security by configuration through identity integration, access controls, consent, and auditability
Composable services so model serving, retrieval, catalog, apps, and tools can evolve independently
Operational visibility through deployment logs, cluster logs, and OTEL-compatible export paths