Installation (Kubernetes)

Last updated: Jul 15, 2025

This guide explains how to deploy Tyk AI Studio, a secure and extensible AI gateway, using pure Kubernetes manifests.

Prerequisites

Kubernetes 1.16+
kubectl configured with access to your cluster
A TYK_AI_LICENSE string from Tyk Technologies (contact support@tyk.io or your account manager to obtain)
A securely generated TYK_AI_SECRET_KEY string for secrets encryption
If using SSL/TLS: cert-manager installed in your cluster

Note: The following examples use placeholder values (e.g., your-domain.com, your-secret-key). Remember to replace these with your actual configuration values.

Installation Options

Tyk AI Studio can be deployed in several configurations:

Local Development
Production without TLS
Production with TLS
Production with External Database

Option 1: Local Development Setup

Create a local-deployment.yaml file:

apiVersion: v1
kind: Namespace
metadata:
  name: tyk-ai-studio
---
apiVersion: v1
kind: Secret
metadata:
  name: tyk-ai-config
  namespace: tyk-ai-studio
type: Opaque
stringData:
  ALLOW_REGISTRATIONS: "true"
  ADMIN_EMAIL: "admin@localhost"
  SITE_URL: "http://localhost:32580"
  FROM_EMAIL: "noreply@localhost"
  DEV_MODE: "true"
  DATABASE_TYPE: "postgres"
  TYK_AI_SECRET_KEY: "your-secret-key"
  TYK_AI_LICENSE: "your-license"
  DATABASE_URL: "postgres://postgres:localdev123@postgres:5432/tyk-ai-studio"
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: postgres
  namespace: tyk-ai-studio
spec:
  replicas: 1
  selector:
    matchLabels:
      app: postgres
  template:
    metadata:
      labels:
        app: postgres
    spec:
      containers:
      - name: postgres
        image: postgres:13
        env:
        - name: POSTGRES_DB
          value: "tyk-ai-studio"
        - name: POSTGRES_USER
          value: "postgres"
        - name: POSTGRES_PASSWORD
          value: "localdev123"
        ports:
        - containerPort: 5432
        volumeMounts:
        - name: postgres-data
          mountPath: /var/lib/postgresql/data
      volumes:
      - name: postgres-data
        emptyDir: {}
---
apiVersion: v1
kind: Service
metadata:
  name: postgres
  namespace: tyk-ai-studio
spec:
  selector:
    app: postgres
  ports:
  - port: 5432
    targetPort: 5432
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: tyk-ai-studio
  namespace: tyk-ai-studio
spec:
  replicas: 1
  selector:
    matchLabels:
      app: tyk-ai-studio
  template:
    metadata:
      labels:
        app: tyk-ai-studio
    spec:
      containers:
      - name: ai-studio
        image: tykio/ai-studio:latest
        envFrom:
        - secretRef:
            name: tyk-ai-config
        ports:
        - containerPort: 8080
        - containerPort: 9090
---
apiVersion: v1
kind: Service
metadata:
  name: tyk-ai-studio
  namespace: tyk-ai-studio
spec:
  type: NodePort
  selector:
    app: tyk-ai-studio
  ports:
  - name: http
    port: 8080
    targetPort: 8080
    nodePort: 32580
  - name: gateway
    port: 9090
    targetPort: 9090
    nodePort: 32590

Deploy the application:

kubectl apply -f local-deployment.yaml

Access the application:

Web Interface: http://localhost:32580
Gateway: http://localhost:32590

Option 2: Production without TLS

For a production deployment without TLS certificates:

Create production-no-tls.yaml:

apiVersion: v1
kind: Namespace
metadata:
  name: tyk-ai-studio
---
apiVersion: v1
kind: Secret
metadata:
  name: tyk-ai-config
  namespace: tyk-ai-studio
type: Opaque
stringData:
  ALLOW_REGISTRATIONS: "true"
  ADMIN_EMAIL: "admin@yourdomain.com"
  SITE_URL: "http://app.yourdomain.com"
  FROM_EMAIL: "noreply@yourdomain.com"
  DEV_MODE: "false"
  DATABASE_TYPE: "postgres"
  TYK_AI_SECRET_KEY: "your-production-key"
  TYK_AI_LICENSE: "your-production-license"
  DATABASE_URL: "postgres://your-db-user:your-db-password@your-db-host:5432/tyk-ai-studio"
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: tyk-ai-studio
  namespace: tyk-ai-studio
spec:
  replicas: 2
  selector:
    matchLabels:
      app: tyk-ai-studio
  template:
    metadata:
      labels:
        app: tyk-ai-studio
    spec:
      containers:
      - name: ai-studio
        image: tykio/ai-studio:latest
        envFrom:
        - secretRef:
            name: tyk-ai-config
        ports:
        - containerPort: 8080
        - containerPort: 9090
        resources:
          requests:
            cpu: 500m
            memory: 1Gi
          limits:
            cpu: 1000m
            memory: 2Gi
---
apiVersion: v1
kind: Service
metadata:
  name: tyk-ai-studio
  namespace: tyk-ai-studio
spec:
  selector:
    app: tyk-ai-studio
  ports:
  - name: http
    port: 8080
    targetPort: 8080
  - name: gateway
    port: 9090
    targetPort: 9090
---
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: tyk-ai-studio-ingress
  namespace: tyk-ai-studio
  annotations:
    kubernetes.io/ingress.class: nginx
spec:
  rules:
  - host: app.yourdomain.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: tyk-ai-studio
            port:
              number: 8080
  - host: gateway.yourdomain.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: tyk-ai-studio
            port:
              number: 9090

Deploy:

kubectl apply -f production-no-tls.yaml

Option 3: Production with TLS

For a secure production deployment with TLS:

Create production-tls.yaml:

apiVersion: v1
kind: Namespace
metadata:
  name: tyk-ai-studio
---
apiVersion: v1
kind: Secret
metadata:
  name: tyk-ai-config
  namespace: tyk-ai-studio
type: Opaque
stringData:
  ALLOW_REGISTRATIONS: "true"
  ADMIN_EMAIL: "admin@yourdomain.com"
  SITE_URL: "https://app.yourdomain.com"
  FROM_EMAIL: "noreply@yourdomain.com"
  DEV_MODE: "false"
  DATABASE_TYPE: "postgres"
  TYK_AI_SECRET_KEY: "your-production-key"
  TYK_AI_LICENSE: "your-production-license"
  DATABASE_URL: "postgres://user:password@your-production-db:5432/tyk-ai-studio"
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: tyk-ai-studio
  namespace: tyk-ai-studio
spec:
  replicas: 2
  selector:
    matchLabels:
      app: tyk-ai-studio
  template:
    metadata:
      labels:
        app: tyk-ai-studio
    spec:
      containers:
      - name: ai-studio
        image: tykio/ai-studio:latest
        envFrom:
        - secretRef:
            name: tyk-ai-config
        ports:
        - containerPort: 8080
        - containerPort: 9090
        resources:
          requests:
            cpu: 500m
            memory: 1Gi
          limits:
            cpu: 1000m
            memory: 2Gi
---
apiVersion: v1
kind: Service
metadata:
  name: tyk-ai-studio
  namespace: tyk-ai-studio
spec:
  selector:
    app: tyk-ai-studio
  ports:
  - name: http
    port: 8080
    targetPort: 8080
  - name: gateway
    port: 9090
    targetPort: 9090
---
apiVersion: cert-manager.io/v1
kind: Certificate
metadata:
  name: app-tls-certificate
  namespace: tyk-ai-studio
spec:
  secretName: app-tls-secret
  issuerRef:
    name: letsencrypt-prod
    kind: ClusterIssuer
  dnsNames:
  - app.yourdomain.com
---
apiVersion: cert-manager.io/v1
kind: Certificate
metadata:
  name: gateway-tls-certificate
  namespace: tyk-ai-studio
spec:
  secretName: gateway-tls-secret
  issuerRef:
    name: letsencrypt-prod
    kind: ClusterIssuer
  dnsNames:
  - gateway.yourdomain.com
---
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: tyk-ai-studio-ingress
  namespace: tyk-ai-studio
  annotations:
    kubernetes.io/ingress.class: nginx
    nginx.ingress.kubernetes.io/ssl-redirect: "true"
spec:
  tls:
  - hosts:
    - app.yourdomain.com
    secretName: app-tls-secret
  - hosts:
    - gateway.yourdomain.com
    secretName: gateway-tls-secret
  rules:
  - host: app.yourdomain.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: tyk-ai-studio
            port:
              number: 8080
  - host: gateway.yourdomain.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: tyk-ai-studio
            port:
              number: 9090

Deploy:

kubectl apply -f production-tls.yaml

Optional Components

Reranker Service

The Reranker service improves RAG result relevance. Add it to your deployment:

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: reranker
  namespace: tyk-ai-studio
spec:
  replicas: 1
  selector:
    matchLabels:
      app: reranker
  template:
    metadata:
      labels:
        app: reranker
    spec:
      containers:
      - name: reranker
        image: tykio/reranker_cpu:latest
        ports:
        - containerPort: 8080
        resources:
          requests:
            cpu: 500m
            memory: 1Gi
          limits:
            cpu: 1000m
            memory: 2Gi
---
apiVersion: v1
kind: Service
metadata:
  name: reranker
  namespace: tyk-ai-studio
spec:
  selector:
    app: reranker
  ports:
  - port: 8080
    targetPort: 8080

Transformer Server

The Transformer Server handles embedding generation and model inference. Add it to your deployment:

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: transformer-server
  namespace: tyk-ai-studio
spec:
  replicas: 1
  selector:
    matchLabels:
      app: transformer-server
  template:
    metadata:
      labels:
        app: transformer-server
    spec:
      containers:
      - name: transformer-server
        image: tykio/transformer_server_cpu:latest
        ports:
        - containerPort: 8080
        resources:
          requests:
            cpu: 500m
            memory: 1Gi
          limits:
            cpu: 1000m
            memory: 2Gi
---
apiVersion: v1
kind: Service
metadata:
  name: transformer-server
  namespace: tyk-ai-studio
spec:
  selector:
    app: transformer-server
  ports:
  - port: 8080
    targetPort: 8080

Database Options

Using Internal PostgreSQL

For development or small deployments, you can deploy PostgreSQL within your cluster:

---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: postgres-pvc
  namespace: tyk-ai-studio
spec:
  accessModes:
    - ReadWriteOnce
  resources:
    requests:
      storage: 10Gi
  storageClassName: standard
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: postgres
  namespace: tyk-ai-studio
spec:
  replicas: 1
  selector:
    matchLabels:
      app: postgres
  template:
    metadata:
      labels:
        app: postgres
    spec:
      containers:
      - name: postgres
        image: postgres:13
        env:
        - name: POSTGRES_DB
          value: "tyk-ai-studio"
        - name: POSTGRES_USER
          value: "postgres"
        - name: POSTGRES_PASSWORD
          value: "secure-password"
        ports:
        - containerPort: 5432
        volumeMounts:
        - name: postgres-storage
          mountPath: /var/lib/postgresql/data
        resources:
          requests:
            cpu: 250m
            memory: 512Mi
          limits:
            cpu: 500m
            memory: 1Gi
      volumes:
      - name: postgres-storage
        persistentVolumeClaim:
          claimName: postgres-pvc
---
apiVersion: v1
kind: Service
metadata:
  name: postgres
  namespace: tyk-ai-studio
spec:
  selector:
    app: postgres
  ports:
  - port: 5432
    targetPort: 5432

Using External Database

For production environments, configure your external database connection in the Secret:

apiVersion: v1
kind: Secret
metadata:
  name: tyk-ai-config
  namespace: tyk-ai-studio
type: Opaque
stringData:
  DATABASE_URL: "postgres://user:password@your-db-host:5432/tyk-ai-studio"
  # ... other config values

Maintenance

Upgrading

To upgrade an existing installation:

# Update the deployment with new configuration
kubectl apply -f your-deployment.yaml

# Or update just the image
kubectl set image deployment/tyk-ai-studio ai-studio=tykio/ai-studio:new-version -n tyk-ai-studio

Uninstalling

To remove the deployment:

# Delete all resources in the namespace
kubectl delete namespace tyk-ai-studio

# Or delete specific resources
kubectl delete -f your-deployment.yaml

Viewing Logs

# Main application logs
kubectl logs -l app.kubernetes.io/name=tyk-ai-studio

# Database logs (if using internal database)
kubectl logs -l app=postgres

# Optional component logs
kubectl logs -l app=reranker
kubectl logs -l app=transformer

Troubleshooting

Check pod status:

kubectl get pods

Check ingress configuration:

kubectl get ingress

View pod details:

kubectl describe pod <pod-name>

Common issues:

Database connection failures: Check credentials and network access
Ingress not working: Verify DNS records and TLS configuration
Resource constraints: Check pod resource limits and node capacity

First User Registration

After deployment, you need to create your first admin user:

Access the application: Navigate to your configured SITE_URL (e.g., https://app.yourdomain.com)
Register with admin email: Use the EXACT email address you set in the ADMIN_EMAIL environment variable in your Secret
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.

Next Steps

Once deployed and you’ve registered your first user, proceed to the First Steps guide to configure Tyk AI Studio.