Deployment

This guide walks you through deploying Menatic AI on a Kubernetes cluster using kubectl and the provided manifests.

Prerequisites

Kubernetes cluster (1.28+) with kubectl access
Docker registry accessible from the cluster
Traefik ingress controller installed
cert-manager for TLS (optional but recommended)

Step 1: Clone the Repository

git clone https://github.com/menatic-ai/ftn-ai.git
cd ftn-ai

Step 2: Configure the Environment

Copy the example configuration and edit values for your environment:

cp k8s/config.example.yaml k8s/config.yaml

Key configuration values:

Variable	Description
`DOMAIN`	Base domain for ingress (e.g., `ai.example.com`)
`JWT_SECRET`	Secret key for JWT signing (generate with `openssl rand -hex 32`)
`DB_PASSWORD`	Database password
`ADMIN_PASSWORD`	Initial admin password

Step 3: Build and Push Images

# Build backend
docker build -t your-registry/ftn-ai-backend:latest ./backend
docker push your-registry/ftn-ai-backend:latest

# Build frontend
docker build -t your-registry/ftn-ai-frontend:latest ./frontend
docker push your-registry/ftn-ai-frontend:latest

Step 4: Create Namespaces

kubectl create namespace ftn-ai
kubectl create namespace apps

Step 5: Apply RBAC Manifests

kubectl apply -f k8s/rbac/

This creates the necessary ClusterRole and ClusterRoleBinding so the backend can manage workloads across namespaces.

Step 6: Deploy the Platform

kubectl apply -f k8s/

This deploys:

Backend API server
Frontend (Next.js)
PostgreSQL database
Traefik ingress rules

Step 7: Verify the Deployment

kubectl get pods -n ftn-ai

All pods should reach Running status within a few minutes.

Step 8: Install metrics-server

The dashboard requires metrics-server for real-time CPU and memory usage:

# For k3d / local clusters:
kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml

# For k3d, patch to disable TLS verification:
kubectl patch deployment metrics-server -n kube-system \
  --type=json \
  -p='[{"op":"add","path":"/spec/template/spec/containers/0/args/-","value":"--kubelet-insecure-tls"}]'

# For managed clusters (EKS, GKE, AKS):
# metrics-server is usually pre-installed or available via the cloud provider add-on

Step 9: Access the Platform

Navigate to https://your-domain and log in with the admin credentials configured in Step 2.

Local Development with k3d

For local development, use k3d to run a cluster with a local image registry:

# Create cluster with registry
k3d cluster create ftn-ai \
  --registry-create localhost:5050 \
  -p "80:80@loadbalancer" \
  -p "443:443@loadbalancer"

# Build and push to local registry
docker build -t localhost:5050/ftn-ai-backend:latest ./backend
docker push localhost:5050/ftn-ai-backend:latest

Upgrading

To upgrade the platform, rebuild and push new images, then roll out the deployments:

kubectl rollout restart deployment/ftn-ai-backend -n ftn-ai
kubectl rollout restart deployment/ftn-ai-frontend -n ftn-ai