368 lines
8.3 KiB
Markdown
368 lines
8.3 KiB
Markdown
# Example: K3s Deployment Skill
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This is a complete example of a DevOps skill for K3s/Kubernetes deployments.
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---
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```yaml
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---
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name: k3s-deploy
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description: Generates K3s deployment manifests with proper resource limits, probes, and HPA. Use when deploying applications to Kubernetes.
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argument-hint: [app-name] [replicas] [image]
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allowed-tools: Read, Write, Edit, Glob, Grep, Bash
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disable-model-invocation: true
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---
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# K3s Deployment Generator
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Generate production-ready Kubernetes manifests for K3s clusters with proper resource limits, health probes, and autoscaling.
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## When to Use
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- Deploying new applications to K3s
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- Creating or updating Deployment manifests
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- Setting up Services and Ingress
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- Configuring Horizontal Pod Autoscaling
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## Prerequisites
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- K3s cluster running and accessible
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- kubectl configured with cluster access
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- Container image available in registry
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## Instructions
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### Step 1: Parse Arguments
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Extract from `$ARGUMENTS`:
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- **app-name**: Name for the deployment (kebab-case)
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- **replicas**: Initial replica count (default: 2)
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- **image**: Container image with tag
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### Step 2: Generate Deployment
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Create `deployment.yaml`:
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```yaml
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apiVersion: apps/v1
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kind: Deployment
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metadata:
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name: ${APP_NAME}
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namespace: default
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labels:
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app: ${APP_NAME}
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version: v1
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spec:
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replicas: ${REPLICAS}
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revisionHistoryLimit: 3
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strategy:
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type: RollingUpdate
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rollingUpdate:
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maxSurge: 1
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maxUnavailable: 0
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selector:
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matchLabels:
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app: ${APP_NAME}
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template:
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metadata:
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labels:
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app: ${APP_NAME}
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version: v1
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annotations:
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prometheus.io/scrape: "true"
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prometheus.io/port: "8000"
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prometheus.io/path: "/metrics"
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spec:
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serviceAccountName: ${APP_NAME}
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securityContext:
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runAsNonRoot: true
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runAsUser: 1000
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fsGroup: 1000
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containers:
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- name: ${APP_NAME}
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image: ${IMAGE}
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imagePullPolicy: IfNotPresent
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ports:
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- name: http
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containerPort: 8000
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protocol: TCP
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env:
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- name: POD_NAME
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valueFrom:
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fieldRef:
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fieldPath: metadata.name
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- name: POD_NAMESPACE
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valueFrom:
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fieldRef:
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fieldPath: metadata.namespace
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envFrom:
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- configMapRef:
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name: ${APP_NAME}-config
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- secretRef:
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name: ${APP_NAME}-secrets
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resources:
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requests:
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memory: "128Mi"
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cpu: "100m"
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limits:
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memory: "256Mi"
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cpu: "500m"
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livenessProbe:
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httpGet:
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path: /health/live/
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port: http
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initialDelaySeconds: 30
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periodSeconds: 10
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timeoutSeconds: 5
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failureThreshold: 3
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readinessProbe:
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httpGet:
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path: /health/ready/
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port: http
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initialDelaySeconds: 5
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periodSeconds: 5
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timeoutSeconds: 3
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failureThreshold: 3
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startupProbe:
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httpGet:
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path: /health/live/
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port: http
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initialDelaySeconds: 10
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periodSeconds: 5
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failureThreshold: 30
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securityContext:
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allowPrivilegeEscalation: false
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readOnlyRootFilesystem: true
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capabilities:
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drop:
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- ALL
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volumeMounts:
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- name: tmp
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mountPath: /tmp
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volumes:
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- name: tmp
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emptyDir: {}
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affinity:
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podAntiAffinity:
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preferredDuringSchedulingIgnoredDuringExecution:
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- weight: 100
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podAffinityTerm:
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labelSelector:
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matchLabels:
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app: ${APP_NAME}
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topologyKey: kubernetes.io/hostname
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topologySpreadConstraints:
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- maxSkew: 1
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topologyKey: kubernetes.io/hostname
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whenUnsatisfiable: ScheduleAnyway
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labelSelector:
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matchLabels:
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app: ${APP_NAME}
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```
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### Step 3: Generate Service
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Create `service.yaml`:
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```yaml
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apiVersion: v1
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kind: Service
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metadata:
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name: ${APP_NAME}
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namespace: default
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labels:
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app: ${APP_NAME}
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spec:
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type: ClusterIP
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ports:
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- name: http
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port: 80
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targetPort: http
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protocol: TCP
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selector:
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app: ${APP_NAME}
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```
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### Step 4: Generate ConfigMap
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Create `configmap.yaml`:
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```yaml
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apiVersion: v1
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kind: ConfigMap
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metadata:
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name: ${APP_NAME}-config
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namespace: default
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data:
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LOG_LEVEL: "INFO"
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ENVIRONMENT: "production"
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```
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### Step 5: Generate HPA
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Create `hpa.yaml`:
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```yaml
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apiVersion: autoscaling/v2
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kind: HorizontalPodAutoscaler
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metadata:
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name: ${APP_NAME}
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namespace: default
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spec:
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scaleTargetRef:
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apiVersion: apps/v1
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kind: Deployment
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name: ${APP_NAME}
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minReplicas: 2
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maxReplicas: 10
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metrics:
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- type: Resource
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resource:
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name: cpu
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target:
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type: Utilization
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averageUtilization: 70
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- type: Resource
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resource:
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name: memory
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target:
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type: Utilization
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averageUtilization: 80
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behavior:
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scaleDown:
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stabilizationWindowSeconds: 300
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policies:
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- type: Percent
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value: 10
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periodSeconds: 60
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scaleUp:
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stabilizationWindowSeconds: 0
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policies:
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- type: Percent
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value: 100
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periodSeconds: 15
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- type: Pods
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value: 4
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periodSeconds: 15
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selectPolicy: Max
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```
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### Step 6: Generate ServiceAccount
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Create `serviceaccount.yaml`:
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```yaml
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apiVersion: v1
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kind: ServiceAccount
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metadata:
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name: ${APP_NAME}
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namespace: default
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```
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### Step 7: Generate Ingress (Traefik)
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Create `ingress.yaml`:
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```yaml
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apiVersion: traefik.io/v1alpha1
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kind: IngressRoute
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metadata:
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name: ${APP_NAME}
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namespace: default
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spec:
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entryPoints:
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- websecure
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routes:
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- match: Host(\`${APP_NAME}.example.com\`)
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kind: Rule
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services:
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- name: ${APP_NAME}
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port: 80
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middlewares:
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- name: ${APP_NAME}-ratelimit
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tls:
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certResolver: letsencrypt
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---
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apiVersion: traefik.io/v1alpha1
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kind: Middleware
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metadata:
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name: ${APP_NAME}-ratelimit
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namespace: default
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spec:
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rateLimit:
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average: 100
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burst: 50
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```
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## Patterns & Best Practices
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### Resource Sizing
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Start conservative and adjust based on metrics:
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| Workload Type | CPU Request | CPU Limit | Memory Request | Memory Limit |
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|---------------|-------------|-----------|----------------|--------------|
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| Web App | 100m | 500m | 128Mi | 256Mi |
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| API Server | 200m | 1000m | 256Mi | 512Mi |
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| Worker | 500m | 2000m | 512Mi | 1Gi |
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| Database | 1000m | 4000m | 1Gi | 4Gi |
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### Probe Configuration
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- **startupProbe**: Use for slow-starting apps (Django, Java)
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- **livenessProbe**: Detect deadlocks, restart if failed
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- **readinessProbe**: Detect temporary unavailability, remove from LB
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### Labels Convention
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```yaml
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labels:
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app: my-app # Required: app name
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version: v1.2.3 # Recommended: version
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component: api # Optional: component type
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part-of: platform # Optional: parent application
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managed-by: kubectl # Optional: management tool
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```
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## Validation
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```bash
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# Dry run to validate manifests
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kubectl apply --dry-run=client -f .
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# Show diff before applying
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kubectl diff -f .
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# Apply with record
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kubectl apply -f . --record
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# Watch rollout
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kubectl rollout status deployment/${APP_NAME}
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# Check events
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kubectl get events --field-selector involvedObject.name=${APP_NAME}
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```
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## Common Pitfalls
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- **No Resource Limits**: Can cause node resource exhaustion
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- **Missing Probes**: Leads to traffic to unhealthy pods
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- **Wrong Probe Paths**: Causes constant restarts
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- **No Anti-Affinity**: All pods on same node = single point of failure
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- **Aggressive HPA**: Causes thrashing; use stabilization windows
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## Rollback Procedure
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```bash
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# View rollout history
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kubectl rollout history deployment/${APP_NAME}
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# Rollback to previous version
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kubectl rollout undo deployment/${APP_NAME}
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# Rollback to specific revision
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kubectl rollout undo deployment/${APP_NAME} --to-revision=2
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```
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```
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