ancoleman/ai-design-components/operating-kubernetes

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Operating production Kubernetes clusters effectively with resource management, advanced scheduling, networking, storage, security hardening, and autoscaling. Use when deploying workloads to Kubernetes, configuring cluster resources, implementing security policies, or troubleshooting operational issues.

Install

npx vskill@latest install ancoleman/ai-design-components/operating-kubernetes

SKILL.md

Kubernetes Operations

Purpose

Operating Kubernetes clusters in production requires mastery of resource management, scheduling patterns, networking architecture, storage strategies, security hardening, and autoscaling. This skill provides operations-first frameworks for right-sizing workloads, implementing high-availability patterns, securing clusters with RBAC and Pod Security Standards, and systematically troubleshooting common failures.

Use this skill when deploying applications to Kubernetes, configuring cluster resources, implementing NetworkPolicies for zero-trust security, setting up autoscaling (HPA, VPA, KEDA), managing persistent storage, or diagnosing operational issues like CrashLoopBackOff or resource exhaustion.

When to Use This Skill

Common Triggers:

  • "Deploy my application to Kubernetes"
  • "Configure resource requests and limits"
  • "Set up autoscaling for my pods"
  • "Implement NetworkPolicies for security"
  • "My pod is stuck in Pending/CrashLoopBackOff"
  • "Configure RBAC with least privilege"
  • "Set up persistent storage for my database"
  • "Spread pods across availability zones"

Operations Covered:

  • Resource management (CPU/memory, QoS classes, quotas)
  • Advanced scheduling (affinity, taints, topology spread)
  • Networking (NetworkPolicies, Ingress, Gateway API)
  • Storage operations (StorageClasses, PVCs, CSI)
  • Security hardening (RBAC, Pod Security Standards, policies)
  • Autoscaling (HPA, VPA, KEDA, cluster autoscaler)
  • Troubleshooting (systematic debugging playbooks)

Resource Management

Quality of Service (QoS) Classes

Kubernetes assigns QoS classes based on resource requests and limits:

Guaranteed (Highest Priority):

  • Requests equal limits for CPU and memory
  • Never evicted unless exceeding limits
  • Use for critical production services
yaml
resources:
requests:
memory: "512Mi"
cpu: "500m"
limits:
memory: "512Mi" # Same as request
cpu: "500m"

Burstable (Medium Priority):

  • Requests less than limits (or only requests set)
  • Can burst above requests
  • Evicted under node pressure
  • Use for web servers, most applications
yaml
resources:
requests:
memory: "256Mi"
cpu: "250m"
limits:
memory: "512Mi" # 2x request
cpu: "500m"

BestEffort (Lowest Priority):

  • No requests or limits set
  • First to be evicted under pressure
  • Use only for development/testing
Decision Framework: Which QoS Class?
Workload TypeQoS ClassConfiguration
Critical API/DatabaseGuaranteedrequests == limits
Web servers, servicesBurstablelimits 1.5-2x requests
Batch jobsBurstableLow requests, high limits
Dev/test environmentsBestEffortNo limits
Resource Quotas and LimitRanges

Enforce multi-tenancy with ResourceQuotas (namespace limits) and LimitRanges (per-container defaults):

yaml
# ResourceQuota: Namespace-level limits
apiVersion: v1
kind: ResourceQuota
metadata:
name: team-quota
namespace: team-alpha
spec:
hard:
requests.cpu: "10"
requests.memory: "20Gi"
limits.cpu: "20"
limits.memory: "40Gi"
pods: "50"

For detailed resource management patterns including Vertical Pod Autoscaler (VPA), see references/resource-management.md.

Advanced Scheduling

Node Affinity

Control which nodes pods schedule on with required (hard) or preferred (soft) constraints:

yaml
affinity:
nodeAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
nodeSelectorTerms:
- matchExpressions:
- key: node.kubernetes.io/instance-type
operator: In
values:
- g4dn.xlarge # GPU instance
Taints and Tolerations

Reserve nodes for specific workloads (inverse of affinity):

bash
# Taint GPU nodes to prevent non-GPU workloads
kubectl taint nodes gpu-node-1 workload=gpu:NoSchedule
yaml
# Pod tolerates GPU taint
tolerations:
- key: "workload"
operator: "Equal"
value: "gpu"
effect: "NoSchedule"
Topology Spread Constraints

Distribute pods evenly across failure domains (zones, nodes):

yaml
topologySpreadConstraints:
- maxSkew: 1 # Max difference in pod count
topologyKey: topology.kubernetes.io/zone
whenUnsatisfiable: DoNotSchedule
labelSelector:
matchLabels:
app: critical-app

For advanced scheduling patterns including pod priority and preemption, see references/scheduling-patterns.md.

Networking

NetworkPolicies (Zero-Trust Security)

Implement default-deny security with NetworkPolicies:

yaml
# Default deny all traffic
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
name: default-deny-all
namespace: production
spec:
podSelector: {}
policyTypes:
- Ingress
- Egress
yaml
# Allow specific ingress (frontend → backend)
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
name: backend-allow-frontend
spec:
podSelector:
matchLabels:
app: backend
ingress:
- from:
- podSelector:
matchLabels:
app: frontend
ports:
- protocol: TCP
port: 8080
Ingress vs. Gateway API

Ingress (Legacy):

  • Widely supported, mature ecosystem
  • Limited expressiveness
  • Use for existing applications

Gateway API (Modern):

  • Role-oriented design (cluster ops vs. app devs)
  • More expressive (HTTPRoute, TCPRoute, TLSRoute)
  • Recommended for new applications (GA in Kubernetes 1.29+)
yaml
# Gateway API example
apiVersion: gateway.networking.k8s.io/v1
kind: HTTPRoute
metadata:
name: app-routes
spec:
parentRefs:
- name: production-gateway
rules:
- matches:
- path:
type: PathPrefix
value: /api
backendRefs:
- name: backend
port: 8080

For detailed networking patterns including service mesh integration, see references/networking.md.

Storage

StorageClasses (Define Performance Tiers)

StorageClasses define storage tiers for different workload needs:

yaml
# AWS EBS SSD (high performance)
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
name: fast-ssd
provisioner: ebs.csi.aws.com
parameters:
type: gp3
iopsPerGB: "50"
encrypted: "true"
volumeBindingMode: WaitForFirstConsumer
allowVolumeExpansion: true
reclaimPolicy: Delete
Storage Decision Matrix
WorkloadPerformanceAccess ModeStorage Class
DatabaseHighReadWriteOnceSSD (gp3/io2)
Shared filesMediumReadWriteManyNFS/EFS
Logs (temp)LowReadWriteOnceStandard HDD
ML modelsHighReadOnlyManyObject storage (S3)

Access Modes:

  • ReadWriteOnce (RWO): Single node read-write (most common)
  • ReadOnlyMany (ROX): Multiple nodes read-only
  • ReadWriteMany (RWX): Multiple nodes read-write (requires network storage)

For detailed storage operations including volume snapshots and CSI drivers, see references/storage.md.

Security

RBAC (Role-Based Access Control)

Implement least-privilege access with RBAC:

yaml
# Role (namespace-scoped)
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
name: pod-reader
namespace: production
rules:
- apiGroups: [""]
resources: ["pods", "pods/log"]
verbs: ["get", "list", "watch"]
---
# RoleBinding (assign role to user)
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: read-pods
namespace: production
subjects:
- kind: User
name: jane@example.com
apiGroup: rbac.authorization.k8s.io
roleRef:
kind: Role
name: pod-reader
apiGroup: rbac.authorization.k8s.io
Pod Security Standards

Enforce secure pod configurations at the namespace level:

yaml
# Namespace with Restricted PSS (most secure)
apiVersion: v1
kind: Namespace
metadata:
name: production
labels:
pod-security.kubernetes.io/enforce: restricted
pod-security.kubernetes.io/audit: restricted
pod-security.kubernetes.io/warn: restricted

Pod Security Levels:

  • Restricted: Most secure, removes all privilege escalations (use for applications)
  • Baseline: Minimally restrictive, prevents known escalations
  • Privileged: Unrestricted (only for system workloads)

For detailed security patterns including policy enforcement (Kyverno/OPA) and secrets management, see references/security.md.

Autoscaling

Horizontal Pod Autoscaler (HPA)

Scale pod replicas based on CPU, memory, or custom metrics:

yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: web-app-hpa
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: web-app
minReplicas: 2
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70
behavior:
scaleDown:
stabilizationWindowSeconds: 300 # Wait 5min before scaling down
KEDA (Event-Driven Autoscaling)

Scale based on events beyond CPU/memory (queues, cron schedules, Prometheus metrics):

yaml
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
name: rabbitmq-scaler
spec:
scaleTargetRef:
name: message-processor
minReplicaCount: 0 # Scale to zero when queue empty
maxReplicaCount: 30
triggers:
- type: rabbitmq
metadata:
queueName: tasks
queueLength: "10" # Scale up when >10 messages
Autoscaling Decision Matrix
ScenarioUse HPAUse VPAUse KEDAUse Cluster Autoscaler
Stateless web app with traffic spikes✅❌❌Maybe
Single-instance database❌✅❌Maybe
Queue processor (event-driven)❌❌✅Maybe
Pods pending (insufficient nodes)❌❌❌✅

For detailed autoscaling patterns including VPA and cluster autoscaler configuration, see references/autoscaling.md.

Troubleshooting

Common Pod Issues

Pod Stuck in Pending:

bash
kubectl describe pod <pod-name>
# Common causes:
# - Insufficient CPU/memory: Reduce requests or add nodes
# - Node selector mismatch: Fix nodeSelector or add labels
# - PVC not bound: Create PVC or fix name
# - Taint intolerance: Add toleration or remove taint

CrashLoopBackOff:

bash
kubectl logs <pod-name>
kubectl logs <pod-name> --previous # Check previous crash
# Common causes:
# - Application crash: Fix code or configuration
# - Missing environment variables: Add to deployment
# - Liveness probe failing: Increase initialDelaySeconds
# - OOMKilled: Increase memory limit or fix leak

ImagePullBackOff:

bash
kubectl describe pod <pod-name>
# Common causes:
# - Image doesn't exist: Fix image name/tag
# - Authentication required: Create imagePullSecrets
# - Network issues: Check NetworkPolicies, firewall rules

Service Not Accessible:

bash
kubectl get endpoints <service-name> # Should list pod IPs
# If endpoints empty:
# - Service selector doesn't match pod labels
# - Pods aren't ready (readiness probe failing)
# - Check NetworkPolicies blocking traffic

For systematic troubleshooting playbooks including networking and storage issues, see references/troubleshooting.md.

Reference Documentation

Deep Dives
  • references/resource-management.md - Resource requests/limits, QoS classes, ResourceQuotas, VPA
  • references/scheduling-patterns.md - Node affinity, taints/tolerations, topology spread, priority
  • references/networking.md - NetworkPolicies, Ingress, Gateway API, service mesh integration
  • references/storage.md - StorageClasses, PVCs, CSI drivers, volume snapshots
  • references/security.md - RBAC, Pod Security Standards, policy enforcement, secrets
  • references/autoscaling.md - HPA, VPA, KEDA, cluster autoscaler configuration
  • references/troubleshooting.md - Systematic debugging playbooks for common failures

This is the start of the file. Read the full SKILL.md on GitHub.

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Source

Popularity

Repository stars
352
Repository forks
54
7-day trend score
29

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 7 May 2026, 5 months ago.

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