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kubernetes-specialist
用于 Kubernetes 集群管理、部署编排、Pod 调试与 Helm Chart 设计。来源:skills.sh 5K+ installs。
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用于 Kubernetes 集群管理、部署编排、Pod 调试与 Helm Chart 设计。来源:skills.sh 5K+ installs。
通过 GitHub CLI 自动化 Issue、PR、Review 与 CI 检查,适合工程协作闭环。
Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.
Plan, create, and configure production-ready Azure Kubernetes Service (AKS) clusters. Covers Day-0 checklist, SKU selection (Automatic vs Standard), networking options (private API server, Azure CNI Overlay, egress configuration), security, and operations (autoscaling, upgrade strategy, cost analysis). WHEN: create AKS environment, provision AKS, enable AKS observability, design AKS networking, choose AKS SKU, secure AKS, optimize AKS, AKS spot nodes, AKS cluster-autoscaler, rightsize AKS pod, pod rightsizing, over-provisioned AKS pod, pod resource requests and limits, Vertical Pod Autoscaler, VPA recommendations.
Guides and best practices for working with Neon Serverless Postgres. Covers setup, connection methods, branching, autoscaling, scale-to-zero, read replicas, connection pooling, Neon Auth, and the Neon CLI, MCP server, REST API, TypeScript SDK, and Python SDK. Use when users ask about "Neon setup", "connect to Neon", "Neon project", "DATABASE_URL", "serverless Postgres", "Neon CLI", "neonctl", "Neon MCP", "Neon Auth", "@neondatabase/serverless", "@neondatabase/neon-js", "scale to zero", "Neon autoscaling", "Neon read replica", or "Neon connection pooling".
Engineering observability and reliability through SLO/SLI design, distributed tracing, alerting, dashboards, capacity planning, toil automation, and reliability review. Use when designing observability instrumentation, defining SLOs/SLIs, building dashboards/alerts, or reviewing reliability posture.
Designing red team attack scenarios, building threat models, applying MITRE ATT&CK/OWASP frameworks, running Purple Team exercises, and performing AI/LLM red teaming. Use when adversarial security validation is needed.
| name | kubernetes-specialist |
| description | 用于 Kubernetes 集群管理、部署编排、Pod 调试与 Helm Chart 设计。来源:skills.sh 5K+ installs。 |
| version | 1.0.0 |
| author | seaworld008 |
| source | skills.sh |
| source_url | https://skills.sh/jeffallan/claude-skills/kubernetes-specialist |
| license | MIT |
| tags | ["development", "kubernetes", "specialist"] |
| created_at | 2026-03-27 |
| updated_at | 2026-03-27 |
| quality | 4 |
| complexity | intermediate |
kubectl get pods 确认状态(Pending, Error, CrashLoopBackOff)。kubectl describe pod <name> 查看事件日志(Events),定位调度失败或探针失败原因。kubectl logs <name> [-c container] [--previous] 查看标准输出/错误流。kubectl exec -it <name> -- /bin/sh 进入容器内部排查(如网络连通性)。kubectl debug 注入诊断容器。{{ .Values.xxx }} 提取配置,支持多环境部署(values-dev.yaml, values-prod.yaml)。Chart.yaml 管理子 Chart 依赖。pre-install, post-upgrade 等 Hooks 处理数据库迁移或清理任务。# 查看所有 Namespace 下异常的 Pod
kubectl get pods -A --field-selector=status.phase!=Running
# 追踪实时日志并显示时间戳
kubectl logs -f <pod-name> --timestamps
# 查看资源占用排行
kubectl top nodes
kubectl top pods
# 导出资源定义的干净版本(去除 runtime 信息)
kubectl get deployment <name> -o yaml | kubectl-neat > deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: my-app
spec:
replicas: 3
selector:
matchLabels:
app: my-app
template:
metadata:
labels:
app: my-app
spec:
containers:
- name: main
image: my-app:v1.2.3
resources:
requests:
cpu: "100m"
memory: "128Mi"
limits:
cpu: "500m"
memory: "512Mi"
livenessProbe:
httpGet:
path: /healthz
port: 8080
initialDelaySeconds: 15
periodSeconds: 20
readinessProbe:
httpGet:
path: /readyz
port: 8080
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: my-app-hpa
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: my-app
minReplicas: 2
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70