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Availability

This guide focuses on the Enterprise Edition of Tyk AI Studio. For the Community Edition, please refer to the Tyk AI Studio GitHub repository. The Community Edition uses different Docker images (tykio/tyk-ai-studio and tykio/tyk-microgateway) and does not require a license key.
This guide explains how to deploy Tyk AI Studio (control plane), an Edge Gateway (data plane), and PostgreSQL on Kubernetes using Helm. AI Studio manages configuration centrally and the Edge Gateway processes AI requests, receiving configuration via gRPC.

Prerequisites

  • Kubernetes 1.16+
  • Helm 3.0+
  • kubectl configured with access to your cluster
  • A Tyk AI License key (contact support@tyk.io or your account manager to obtain)
  • For production with TLS: cert-manager installed in your cluster
Running on Podman, containerd, or another container runtime? See Container Runtimes.

Generate Secrets

Before installing, generate three secret keys to secure communication and encrypt data:
Save these values — you will substitute them into the values file below.

Option 1: Testing / Quickstart

For local development or test clusters. Uses NodePort services, internal PostgreSQL, and no ingress.

1. Add the Helm Chart

2. Create values-testing.yaml

Replace the placeholder secrets with your generated values. The grpcAuthToken / edgeAuthToken and microgatewayEncryptionKey / encryptionKey pairs must match.
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3. Install

4. Set External Gateway URL

The Edge Gateway’s internal service URL is used for routing by default, but the portal needs to display the correct external URL for tools and datasources. After install, patch the config with your cluster’s node IP:
Tip: If you know your cluster’s external IP or hostname upfront, you can skip this step by setting config.toolDisplayUrl and config.datasourceDisplayUrl in your values file instead.

5. Verify

Access Points


Option 2: Production with TLS

For production deployments with Ingress, TLS via cert-manager, and an external database.

1. Create values-production.yaml

Replace all placeholder values with your actual configuration.
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2. Install

3. Verify


After Deployment

First User Registration

After deployment, you need to create your first admin user:
  1. Access the application: Navigate to your configured SITE_URL (e.g., https://studio.yourdomain.com)
  2. Register with admin email: Use the EXACT email address you set in the ADMIN_EMAIL environment variable in your configuration.
  3. Complete registration: The first user who registers with the admin email will automatically become the administrator.
Important: The first user registration must use the same email address specified in the ADMIN_EMAIL environment variable. This user will have full administrative privileges.

Add Your API Keys

AI Studio pre-populates OpenAI and Anthropic LLM configurations on first startup with placeholder secrets (OPENAI_KEY and ANTHROPIC_KEY). To start using them:
  1. Open AI Studio at the siteUrl you configured and log in with your admin account
  2. Navigate to Governance → Secrets in the sidebar
  3. Click on OPENAI_KEY and edit it to add your OpenAI API key
  4. Click on ANTHROPIC_KEY and edit it to add your Anthropic API key

Push Configuration to the Edge Gateway

  1. Navigate to AI Portal → Edge Gateways in the sidebar
  2. Verify your edge gateway (edge-1) shows as Connected
  3. Click Push Configuration to sync the latest settings to the Edge Gateway
Once the sync status shows Synced, the Edge Gateway is ready to proxy LLM requests. For further setup (additional LLMs, users, applications), see the Initial Configuration guide.

Shared Secrets Reference

These values must match between AI Studio and Edge Gateway configuration:

Port Reference


Advanced Configuration

Message Queue (NATS)

For distributed deployments with message persistence, add NATS configuration to your values file:

Optional Components

Reranker Service

Improves RAG result relevance:

Transformer Server

Handles embedding generation:

Scaling Edge Gateways

To deploy multiple edge gateways for different regions, override edgeId and edgeNamespace per instance. You can either deploy separate Helm releases or create additional Kubernetes Deployments with unique values:
Each edge instance registers independently with AI Studio and receives only the configuration assigned to its namespace.

Database Options

Internal PostgreSQL (testing/small deployments):
External Database (production):

Maintenance

Upgrading

Uninstalling

Viewing Logs

Troubleshooting

  • Database connection failures: Check credentials and network access
  • Ingress not working: Verify DNS records and TLS configuration
  • Login fails on HTTP: Set devMode: "true" — session cookies require this when not using HTTPS
  • Marketplace page is empty: Set ociCacheDir: "./data/cache/plugins" in your config values — the marketplace service will not start without it
  • Plugin signature verification: Docker images use distroless bases without cosign. Set ociRequireSignature: "false" to disable signature verification
  • Verify the Edge Gateway pod logs:
  • Check that CONTROL_ENDPOINT resolves to the AI Studio service (default: midsommar:50051)
  • Verify edgeAuthToken matches grpcAuthToken exactly
  • Verify encryptionKey matches microgatewayEncryptionKey exactly
  • Check that GATEWAY_MODE=control is set in AI Studio config