From claude-code-toolkit
Provides Kubernetes manifests, Helm charts, autoscaling, troubleshooting commands, and resource management examples.
npx claudepluginhub rohitg00/awesome-claude-code-toolkitThis skill uses the workspace's default tool permissions.
```yaml
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.
Searches prompts.chat for AI prompt templates by keyword or category, retrieves by ID with variable handling, and improves prompts via AI. Use for discovering or enhancing prompts.
Guides MCP server integration in Claude Code plugins via .mcp.json or plugin.json configs for stdio, SSE, HTTP types, enabling external services as tools.
apiVersion: apps/v1
kind: Deployment
metadata:
name: api-server
labels:
app: api-server
version: v1
spec:
replicas: 3
strategy:
type: RollingUpdate
rollingUpdate:
maxSurge: 1
maxUnavailable: 0
selector:
matchLabels:
app: api-server
template:
metadata:
labels:
app: api-server
version: v1
spec:
containers:
- name: api
image: registry.example.com/api:1.2.0
ports:
- containerPort: 8080
resources:
requests:
cpu: 100m
memory: 128Mi
limits:
cpu: 500m
memory: 512Mi
livenessProbe:
httpGet:
path: /healthz
port: 8080
initialDelaySeconds: 10
periodSeconds: 15
readinessProbe:
httpGet:
path: /ready
port: 8080
initialDelaySeconds: 5
periodSeconds: 5
env:
- name: DATABASE_URL
valueFrom:
secretKeyRef:
name: db-credentials
key: url
topologySpreadConstraints:
- maxSkew: 1
topologyKey: kubernetes.io/hostname
whenUnsatisfiable: DoNotSchedule
labelSelector:
matchLabels:
app: api-server
Always set resource requests and limits. Use topology spread constraints for high availability.
chart/
Chart.yaml
values.yaml
values-staging.yaml
values-production.yaml
templates/
deployment.yaml
service.yaml
ingress.yaml
hpa.yaml
_helpers.tpl
# values.yaml
replicaCount: 2
image:
repository: registry.example.com/api
tag: "1.2.0"
pullPolicy: IfNotPresent
resources:
requests:
cpu: 100m
memory: 128Mi
limits:
cpu: 500m
memory: 512Mi
autoscaling:
enabled: true
minReplicas: 2
maxReplicas: 10
targetCPUUtilization: 70
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: api-server
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: api-server
minReplicas: 2
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70
- type: Resource
resource:
name: memory
target:
type: Utilization
averageUtilization: 80
behavior:
scaleDown:
stabilizationWindowSeconds: 300
# Pod diagnostics
kubectl describe pod <pod-name> -n <namespace>
kubectl logs <pod-name> -c <container> --previous
kubectl exec -it <pod-name> -- /bin/sh
# Resource usage
kubectl top pods -n <namespace> --sort-by=memory
kubectl top nodes
# Network debugging
kubectl run debug --image=nicolaka/netshoot --rm -it -- bash
nslookup <service-name>.<namespace>.svc.cluster.local
# Events sorted by time
kubectl get events -n <namespace> --sort-by='.lastTimestamp'
# Find pods not running
kubectl get pods -A --field-selector=status.phase!=Running
securityContext.runAsNonRoot: truelatest tag instead of pinned image versionsPodDisruptionBudget for critical workloadslatest