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Availability

EditionDeployment Type
Community & EnterpriseSelf-Managed, Hybrid

Deployment Models

Tyk AI Studio supports two deployment modes:

Standalone

Standalone mode operates as a single AI Studio instance with embedded gateway functionality. It is suitable for development, testing, and small teams. Characteristics:
  • Single instance deployment
  • Built-in gateway functionality
  • SQLite database (or PostgreSQL)
  • No external dependencies

Hub and Spoke (Control + Edge)

Control Plane with Edge Gateways uses AI Studio as the central control plane managing edge gateways for distributed request processing. This approach uses lightweight Edge Gateways instances that connect to the control plane. It is suitable for production, enterprise, and multi-region deployments. Characteristics:
  • Centralized configuration management
  • Distributed request processing
  • Regional edge deployments
  • High availability and fault tolerance
  • Namespace-based multi-tenancy

Choosing Your Deployment

ScenarioRecommended ModeWhy
Local developmentStandaloneSimple, fast setup
Single office/locationStandaloneNo distribution needed
Multiple regionsHub-and-SpokeLow latency for users
High availabilityHub-and-SpokeFault tolerance
Multi-tenant SaaSHub-and-SpokeNamespace isolation
Compliance (data locality)Hub-and-SpokeRegional data processing

Requirements

Tyk AI Studio and Edge Gateway requires a persistent datastore for its operations. By default, SQLite is used, while PostgreSQL is recommended for production deployments.

Required Components

ComponentAI Studio (Hub)Edge Gateway (Edge)
SQLiteSupported (default)Supported (default)
PostgreSQLSupportedSupported

Optional Components

Tyk AI Studio uses a message queue for chat interface. By default, an in-memory queue is used, which is suitable for development and single-instance deployments. For production and multi-instance deployments, you can configure AI Studio to use NATS JetStream as the message queue backend. For development, testing, and proof of concept purposes, we recommend using our Docker installation, which allows you to quickly spin up AI Studio on your local machine.

Alternative Installation Methods