kubernetes-deployment
Deploy, manage, and scale containerized applications on Kubernetes clusters with best practices for production workloads, resource management, and rolling updates.
$ インストール
git clone https://github.com/aj-geddes/useful-ai-prompts /tmp/useful-ai-prompts && cp -r /tmp/useful-ai-prompts/skills/kubernetes-deployment ~/.claude/skills/useful-ai-prompts// tip: Run this command in your terminal to install the skill
SKILL.md
name: kubernetes-deployment description: Deploy, manage, and scale containerized applications on Kubernetes clusters with best practices for production workloads, resource management, and rolling updates.
Kubernetes Deployment
Overview
Master Kubernetes deployments for managing containerized applications at scale, including multi-container services, resource allocation, health checks, and rolling deployment strategies.
When to Use
- Container orchestration and management
- Multi-environment deployments (dev, staging, prod)
- Auto-scaling microservices
- Rolling updates and blue-green deployments
- Service discovery and load balancing
- Resource quota and limit management
- Pod networking and security policies
Implementation Examples
1. Complete Deployment with Resource Management
# kubernetes-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: api-service
namespace: production
labels:
app: api-service
version: v1
spec:
replicas: 3
strategy:
type: RollingUpdate
rollingUpdate:
maxSurge: 1
maxUnavailable: 0
selector:
matchLabels:
app: api-service
template:
metadata:
labels:
app: api-service
version: v1
annotations:
prometheus.io/scrape: "true"
prometheus.io/port: "8080"
spec:
# Service account for RBAC
serviceAccountName: api-service-sa
# Security context
securityContext:
runAsNonRoot: true
runAsUser: 1000
fsGroup: 1000
# Pod scheduling
affinity:
podAntiAffinity:
preferredDuringSchedulingIgnoredDuringExecution:
- weight: 100
podAffinityTerm:
labelSelector:
matchExpressions:
- key: app
operator: In
values:
- api-service
topologyKey: kubernetes.io/hostname
# Pod termination grace period
terminationGracePeriodSeconds: 30
# Init containers
initContainers:
- name: wait-for-db
image: busybox:1.35
command: ['sh', '-c', 'until nc -z postgres-service 5432; do echo waiting for db; sleep 2; done']
containers:
- name: api-service
image: myrepo/api-service:1.2.3
imagePullPolicy: IfNotPresent
# Ports
ports:
- name: http
containerPort: 8080
protocol: TCP
- name: metrics
containerPort: 9090
protocol: TCP
# Environment variables
env:
- name: NODE_ENV
value: "production"
- name: DATABASE_URL
valueFrom:
secretKeyRef:
name: api-secrets
key: database-url
- name: LOG_LEVEL
valueFrom:
configMapKeyRef:
name: api-config
key: log-level
- name: REPLICA_NUM
valueFrom:
fieldRef:
fieldPath: metadata.name
# Resource requests and limits
resources:
requests:
memory: "256Mi"
cpu: "100m"
limits:
memory: "512Mi"
cpu: "500m"
# Liveness probe
livenessProbe:
httpGet:
path: /health
port: 8080
scheme: HTTP
initialDelaySeconds: 30
periodSeconds: 10
timeoutSeconds: 5
failureThreshold: 3
# Readiness probe
readinessProbe:
httpGet:
path: /ready
port: 8080
scheme: HTTP
initialDelaySeconds: 10
periodSeconds: 5
timeoutSeconds: 3
failureThreshold: 2
# Volume mounts
volumeMounts:
- name: config
mountPath: /etc/config
readOnly: true
- name: cache
mountPath: /var/cache
- name: logs
mountPath: /var/log
# Security context
securityContext:
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
capabilities:
drop:
- ALL
# Volumes
volumes:
- name: config
configMap:
name: api-config
- name: cache
emptyDir:
sizeLimit: 1Gi
- name: logs
emptyDir:
sizeLimit: 2Gi
---
apiVersion: v1
kind: Service
metadata:
name: api-service
namespace: production
spec:
type: ClusterIP
selector:
app: api-service
ports:
- name: http
port: 80
targetPort: 8080
protocol: TCP
- name: metrics
port: 9090
targetPort: 9090
protocol: TCP
---
apiVersion: v1
kind: ConfigMap
metadata:
name: api-config
namespace: production
data:
log-level: "INFO"
max-connections: "100"
---
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: api-service-hpa
namespace: production
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: api-service
minReplicas: 3
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70
- type: Resource
resource:
name: memory
target:
type: Utilization
averageUtilization: 80
2. Deployment Script
#!/bin/bash
# deploy-k8s.sh - Deploy to Kubernetes cluster
set -euo pipefail
NAMESPACE="${1:-production}"
DEPLOYMENT="${2:-api-service}"
IMAGE="${3:-myrepo/api-service:latest}"
echo "Deploying $DEPLOYMENT to namespace $NAMESPACE..."
# Check cluster connectivity
kubectl cluster-info
# Create namespace if not exists
kubectl create namespace "$NAMESPACE" --dry-run=client -o yaml | kubectl apply -f -
# Apply configuration
kubectl apply -f kubernetes-deployment.yaml -n "$NAMESPACE"
# Wait for rollout
echo "Waiting for deployment to rollout..."
kubectl rollout status deployment/"$DEPLOYMENT" -n "$NAMESPACE" --timeout=5m
# Verify pods are running
echo "Verification:"
kubectl get pods -n "$NAMESPACE" -l "app=$DEPLOYMENT"
# Check service
kubectl get svc -n "$NAMESPACE" -l "app=$DEPLOYMENT"
echo "Deployment complete!"
3. Service Account and RBAC
apiVersion: v1
kind: ServiceAccount
metadata:
name: api-service-sa
namespace: production
---
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
name: api-service-role
namespace: production
rules:
- apiGroups: [""]
resources: ["configmaps"]
verbs: ["get", "list"]
- apiGroups: [""]
resources: ["secrets"]
verbs: ["get"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: api-service-rolebinding
namespace: production
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: api-service-role
subjects:
- kind: ServiceAccount
name: api-service-sa
namespace: production
Deployment Patterns
Rolling Update
- Gradually replace old pods with new ones
- Zero downtime deployments
- Automatic rollback on failure
Blue-Green
- Maintain two identical environments
- Switch traffic instantly
- Easier rollback capability
Canary
- Deploy to subset of users first
- Monitor metrics before full rollout
- Reduce risk of bad deployments
Best Practices
✅ DO
- Use resource requests and limits
- Implement health checks (liveness, readiness)
- Use ConfigMaps for configuration
- Apply security context restrictions
- Use service accounts and RBAC
- Implement pod anti-affinity
- Use namespaces for isolation
- Enable pod security policies
❌ DON'T
- Use latest image tags in production
- Run containers as root
- Set unlimited resource usage
- Skip readiness probes
- Deploy without resource limits
- Mix configurations in container images
- Use default service accounts
Resources
Repository

aj-geddes
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aj-geddes/useful-ai-prompts/skills/kubernetes-deployment
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