Kubernetes Deployment

KDeps can generate ready-to-apply Kubernetes manifests directly from your workflow.yaml using kdeps export k8s.

Quick Start

# Generate manifests and print to stdout
kdeps export k8s examples/chatbot

# Save to a file and apply
kdeps export k8s examples/chatbot --output k8s.yaml
kubectl apply -f k8s.yaml

Command Reference

kdeps export k8s [path] [flags]

Arguments:

• path - Directory containing workflow.yaml, a workflow.yaml file directly, or a .kdeps package

Flags:

Flag	Short	Description	Default
--image	-i	Container image to use	{name}:{version} from workflow
--output	-o	Output file path	stdout
--replicas	-r	Number of replicas (overrides workflow.yaml)	From workflow

Examples:

# Stdout output using default image name
kdeps export k8s examples/chatbot

# Custom image from a private registry
kdeps export k8s examples/chatbot --image registry.example.com/chatbot:v1.2.0

# Override replicas at export time
kdeps export k8s examples/chatbot --replicas 5

# Save directly to a file
kdeps export k8s examples/chatbot --output deploy/k8s.yaml

# Full example with all flags
kdeps export k8s examples/chatbot \
  --image registry.example.com/chatbot:v1.2.0 \
  --replicas 3 \
  --output deploy/k8s.yaml

Workflow Configuration

Configure Kubernetes-specific settings in workflow.yaml under agentSettings:

settings:
  apiServerMode: true
  portNum: 8080
  agentSettings:
    # Number of pod replicas
    replicas: 3

    # CPU and memory limits/requests
    resources:
      cpuLimit: "1000m"
      memoryLimit: "1Gi"
      cpuRequest: "250m"
      memoryRequest: "256Mi"

    # Env vars mapped to container environment
    env:
      APP_MODE: production
      DATABASE_URL: "postgres://user:pass@db-service:5432/mydb"

Ports

Ports are derived from your workflow settings:

Setting	Port name in manifest	Description
apiServerMode: true + portNum	api	REST API server
webServerMode: true + portNum	web	Web server
installOllama: true (or auto-detected)	backend	Ollama LLM backend (11434)

Ollama port is auto-detected when any resource uses run.chat.

Resources

When resources is set, the manifest includes both limits and requests:

agentSettings:
  resources:
    cpuLimit: "500m"
    memoryLimit: "512Mi"
    cpuRequest: "100m"
    memoryRequest: "128Mi"

When resources is absent, no resources: block is emitted (Kubernetes defaults apply).

Generated Manifests

kdeps export k8s produces a single YAML document with two resources separated by ---.

Deployment

apiVersion: apps/v1
kind: Deployment
metadata:
  name: chatbot
  labels:
    app: chatbot
    version: 1.0.0
    kdeps-component: "true"
spec:
  replicas: 3
  selector:
    matchLabels:
      app: chatbot
  template:
    metadata:
      labels:
        app: chatbot
    spec:
      containers:
      - name: chatbot
        image: registry.example.com/chatbot:v1.0.0
        ports:
        - containerPort: 8080
          name: api
        env:
        - name: APP_MODE
          value: "production"
        resources:
          limits:
            cpu: "1000m"
            memory: "1Gi"
          requests:
            cpu: "250m"
            memory: "256Mi"
        readinessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 10
          periodSeconds: 10
        livenessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 30
          periodSeconds: 30

Service

apiVersion: v1
kind: Service
metadata:
  name: chatbot
  labels:
    app: chatbot
spec:
  selector:
    app: chatbot
  ports:
  - name: api
    port: 8080
    targetPort: api
  type: ClusterIP

Health check probes are automatically generated from the configured port.

Typical Workflow

# 1. Build the Docker image
kdeps bundle build examples/chatbot --tag registry.example.com/chatbot:v1.0.0

# 2. Push to registry
docker push registry.example.com/chatbot:v1.0.0

# 3. Generate manifests with the pushed image
kdeps export k8s examples/chatbot \
  --image registry.example.com/chatbot:v1.0.0 \
  --output k8s.yaml

# 4. Apply to your cluster
kubectl apply -f k8s.yaml

# 5. Verify rollout
kubectl rollout status deployment/chatbot

Example: k8s-deployment

The examples/k8s-deployment/ directory contains a full workflow demonstrating Kubernetes settings:

kdeps export k8s examples/k8s-deployment --image my-registry/k8s-example:1.0.0

See examples/k8s-deployment/README.md for details.

Related

• Docker Deployment - Build Docker images for your workflows
• Standalone Executables - Self-contained binaries for edge deployment
• CLI Reference - Full command reference