# Kubernetes Specialist > Kubernetes Specialist - Skill: `dnyoussef/kubernetes-specialist` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add dnyoussef/kubernetes-specialist` - Raw SKILL.md: https://api.skillmd.com/api/skills/dnyoussef/kubernetes-specialist/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: DevOps & Infra - Author: DNYoussef (https://skillmd.com/u/dnyoussef) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/dnyoussef/kubernetes-specialist --- /*============================================================================*/ /* KUBERNETES-SPECIALIST SKILL :: VERILINGUA x VERIX EDITION */ /*============================================================================*/ --- name: kubernetes-specialist version: 1.0.0 description: | [assert|neutral] Kubernetes orchestration expert for Helm chart development, custom operators and CRDs, service mesh (Istio/Linkerd), auto-scaling strategies (HPA/VPA/Cluster Autoscaler), multi-cluster management, and [ground:given] [conf:0.95] [state:confirmed] category: Cloud Platforms tags: - general author: system cognitive_frame: primary: aspectual goal_analysis: first_order: "Execute kubernetes-specialist workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic Cloud Platforms processes" --- /*----------------------------------------------------------------------------*/ /* S0 META-IDENTITY */ /*----------------------------------------------------------------------------*/ [define|neutral] SKILL := { name: "kubernetes-specialist", category: "Cloud Platforms", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S1 COGNITIVE FRAME */ /*----------------------------------------------------------------------------*/ [define|neutral] COGNITIVE_FRAME := { frame: "Aspectual", source: "Russian", force: "Complete or ongoing?" } [ground:cognitive-science] [conf:0.92] [state:confirmed] ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. /*----------------------------------------------------------------------------*/ /* S2 TRIGGER CONDITIONS */ /*----------------------------------------------------------------------------*/ [define|neutral] TRIGGER_POSITIVE := { keywords: ["kubernetes-specialist", "Cloud Platforms", "workflow"], context: "user needs kubernetes-specialist capability" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S3 CORE CONTENT */ /*----------------------------------------------------------------------------*/ # Kubernetes Specialist ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. Expert Kubernetes orchestration for cloud-native applications with production-grade deployments. ## Purpose Comprehensive Kubernetes expertise including Helm charts, custom operators, service mesh, auto-scaling, and GitOps. Ensures K8s deployments are resilient, secure, observable, and cost-effective. ## When to Use - Deploying microservices to Kubernetes - Creating Helm charts for reusable deployments - Implementing auto-scaling (HPA, VPA, Cluster Autoscaler) - Setting up service mesh for advanced networking - Building custom operators with Operator SDK - Implementing GitOps with ArgoCD or Flux - Optimizing pod scheduling and resource allocation ## Prerequisites **Required**: Docker, kubectl, basic K8s concepts (Pods, Services, Deployments) **Agents**: `system-architect`, `cicd-engineer`, `perf-analyzer`, `security-manager` ## Core Workflows ### Workflow 1: Production-Grade Deployment **Step 1: Create Deployment Manifest** ```yaml # deployment.yaml apiVersion: apps/v1 kind: Deployment metadata: name: my-app labels: app: my-app spec: replicas: 3 selector: matchLabels: app: my-app template: metadata: labels: app: my-app version: v1 spec: containers: - name: app image: myregistry/my-app:v1.0.0 ports: - containerPort: 8080 resources: requests: memory: "128Mi" cpu: "100m" limits: memory: "256Mi" cpu: "500m" livenessProbe: httpGet: path: /health port: 8080 initialDelaySeconds: 30 periodSeconds: 10 readinessProbe: httpGet: path: /ready port: 8080 initialDelaySeconds: 5 periodSeconds: 5 securityContext: runAsNonRoot: true readOnlyRootFilesystem: true allowPrivilegeEscalation: false capabilities: drop: - ALL affinity: podAntiAffinity: preferredDuringSchedulingIgnoredDuringExecution: - weight: 100 podAffinityTerm: labelSelector: matchExpressions: - key: app operator: In values: - my-app topologyKey: kubernetes.io/hostname ``` **Step 2: Create Service and Ingress** ```yaml # service.yaml apiVersion: v1 kind: Service metadata: name: my-app spec: selector: app: my-app ports: - protocol: TCP port: 80 targetPort: 8080 type: ClusterIP --- # ingress.yaml apiVersion: networking.k8s.io/v1 kind: Ingress metadata: name: my-app annotations: cert-manager.io/cluster-issuer: letsencrypt-prod nginx.ingress.kubernetes.io/rate-limit: "100" spec: ingressClassName: nginx tls: - hosts: - my-app.example.com secretName: my-app-tls rules: - host: my-app.example.com http: paths: - path: / pathType: Prefix backend: service: name: my-app port: number: 80 ``` ### Workflow 2: Helm Chart Development **Step 1: Create Helm Chart** ```bash helm create my-app cd my-app ``` **Step 2: Define Values.yaml** ```yaml # values.yaml replicaCount: 3 image: repository: myregistry/my-app tag: "v1.0.0" pullPolicy: IfNotPresent resources: requests: memory: "128Mi" cpu: "100m" limits: memory: "256Mi" cpu: "500m" autoscaling: enabled: true minReplicas: 2 maxReplicas: 10 targetCPUUtilizationPercentage: 70 ingress: enabled: true className: nginx hosts: - host: my-app.example.com paths: - path: / pathType: Prefix tls: - secretName: my-app-tls hosts: - my-app.example.com ``` **Step 3: Template Deployment** ```yaml # templates/depl /*----------------------------------------------------------------------------*/ /* S4 SUCCESS CRITERIA */ /*----------------------------------------------------------------------------*/ [define|neutral] SUCCESS_CRITERIA := { primary: "Skill execution completes successfully", quality: "Output meets quality thresholds", verification: "Results validated against requirements" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S5 MCP INTEGRATION */ /*----------------------------------------------------------------------------*/ [define|neutral] MCP_INTEGRATION := { memory_mcp: "Store execution results and patterns", tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"] } [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S6 MEMORY NAMESPACE */ /*----------------------------------------------------------------------------*/ [define|neutral] MEMORY_NAMESPACE := { pattern: "skills/Cloud Platforms/kubernetes-specialist/{project}/{timestamp}", store: ["executions", "decisions", "patterns"], retrieve: ["similar_tasks", "proven_patterns"] } [ground:system-policy] [conf:1.0] [state:confirmed] [define|neutral] MEMORY_TAGGING := { WHO: "kubernetes-specialist-{session_id}", WHEN: "ISO8601_timestamp", PROJECT: "{project_name}", WHY: "skill-execution" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S7 SKILL COMPLETION VERIFICATION */ /*----------------------------------------------------------------------------*/ [direct|emphatic] COMPLETION_CHECKLIST := { agent_spawning: "Spawn agents via Task()", registry_validation: "Use registry agents only", todowrite_called: "Track progress with TodoWrite", work_delegation: "Delegate to specialized agents" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S8 ABSOLUTE RULES */ /*----------------------------------------------------------------------------*/ [direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* PROMISE */ /*----------------------------------------------------------------------------*/ [commit|confident] KUBERNETES_SPECIALIST_VERILINGUA_VERIX_COMPLIANT [ground:self-validation] [conf:0.99] [state:confirmed]