Kubernetes operations
Skill timdevai/proteus/skills/community/from-rohitg00/kubernetes-operations
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Kubernetes operations including manifests, Helm charts, operators, troubleshooting, and resource management
SKILL.md
4.2 KB, as published. Nobody here has run it
Kubernetes Operations
Deployment Manifest
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.
Helm Chart Structure
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
HorizontalPodAutoscaler
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
Troubleshooting Commands
# 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
Anti-Patterns
- Running containers as root without
securityContext.runAsNonRoot: true - Missing resource requests/limits (causes scheduling issues and noisy neighbors)
- Using
latesttag instead of pinned image versions - Not setting
PodDisruptionBudgetfor critical workloads - Storing secrets in ConfigMaps instead of Secrets (or external secret managers)
- Ignoring pod anti-affinity for replicated deployments
Checklist
- All containers have resource requests and limits
- Liveness and readiness probes configured
- Images use specific version tags, not
latest - Secrets stored in Kubernetes Secrets or external vault
- PodDisruptionBudget set for production workloads
- NetworkPolicies restrict traffic between namespaces
- Topology spread constraints or anti-affinity for HA
- Helm values split per environment (staging, production)