kubernetes-specialist
- Repo stars 0
- Author updated Live
- Author repo skills-registry
- Domain
- DevOps
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @tomevault-io · no license declared
- Token usage
- Lean
- Setup complexity
- Manual integration
- External API key
- Not required
- Operating systems
- Docker
- Runtime requirements
- Node.js · Docker
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: kubernetes-specialist
description: Expert Kubernetes Specialist with deep expertise in container orchestration, cluster management…
category: devops
runtime: Node.js / Docker
---
# kubernetes-specialist output preview
## PART A: Task fit
- Use case: Expert Kubernetes Specialist with deep expertise in container orchestration, cluster management, and cloud-native applications. Proficient in Kubernetes architecture, Helm charts, operators, and multi-cluster management across EKS, AKS, GKE, and on-premises deployments. Use when this capability is needed..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Purpose / When to Use / Quick Start” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Expert Kubernetes Specialist with deep expertise in container orchestration, cluster management, and cloud-native applications. Proficient in Kubernetes architecture, Helm charts, operators, and multi-cluster management across EKS, AKS, GKE, and on-premises deployments. Use when this capability is needed.”.
- **02** When the source has headings, the agent prioritizes “Purpose / When to Use / Quick Start” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Start with a small task and check whether the result follows “Purpose / When to Use / Quick Start”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: kubernetes-specialist
description: Expert Kubernetes Specialist with deep expertise in container orchestration, cluster management…
category: devops
source: tomevault-io/skills-registry
---
# kubernetes-specialist
## When to use
- Expert Kubernetes Specialist with deep expertise in container orchestration, cluster management, and cloud-native appl…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Purpose / When to Use / Quick Start” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "kubernetes-specialist" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Purpose / When to Use / Quick Start
rules -> SKILL.md triggers / order / output contract
runtime -> Node.js / Docker | read files, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} Kubernetes Specialist
Use this skill for Kubernetes design, architecture, implementation, optimization, and planned changes. For live incidents, unhealthy workloads, CrashLoopBackOff, stuck rollouts, ingress failures, or customer support triage, use k8s-sre-triage first.
Purpose
Provides expert Kubernetes orchestration and cloud-native application expertise with deep knowledge of container orchestration, cluster management, and production-grade deployments. Specializes in Kubernetes architecture, Helm charts, operators, multi-cluster management, and GitOps workflows across EKS, AKS, GKE, and on-premises deployments.
When to Use
- Designing Kubernetes cluster architecture for production workloads
- Implementing Helm charts, operators, or GitOps workflows (ArgoCD, Flux)
- Troubleshooting design-level or planned-change cluster issues after incident triage has narrowed the fault domain
- Planning Kubernetes upgrades or multi-cluster strategies
- Optimizing resource utilization and cost in Kubernetes environments
- Setting up service mesh (Istio, Linkerd) and observability
- Implementing Kubernetes security and RBAC policies
Quick Start
Invoke this skill when:
- Designing Kubernetes cluster architecture for production workloads
- Implementing Helm charts, operators, or GitOps workflows
- Troubleshooting design-level or planned-change cluster issues after
k8s-sre-triagehas narrowed the fault domain - Planning Kubernetes upgrades or multi-cluster strategies
- Optimizing resource utilization and cost in Kubernetes environments
Do NOT invoke when:
- Simple Docker container needs (use docker commands directly)
- Live Kubernetes incidents or customer support triage (use
k8s-sre-triagefirst) - Cloud infrastructure provisioning (use an installed cloud or infrastructure skill when available)
- Application code debugging (use an installed debugging or application skill when available)
- Database-specific issues (use a database-focused workflow or specialist when available)
Decision Framework
Deployment Strategy Selection
├─ Zero downtime required?
│ ├─ Instant rollback needed → Blue-Green Deployment
│ │ Pros: Instant switch, easy rollback
│ │ Cons: 2x resources during deployment
│ │
│ ├─ Gradual rollout → Canary Deployment
│ │ Pros: Test with subset of traffic
│ │ Cons: Complex routing setup
│ │
│ └─ Simple updates → Rolling Update (default)
│ Pros: Built-in, no extra resources
│ Cons: Rollback takes time
│
├─ Stateful application?
│ ├─ Database → StatefulSet + PVC
│ │ Pros: Stable network IDs, ordered deployment
│ │ Cons: Complex scaling
│ │
│ └─ Stateless → Deployment
│ Pros: Easy scaling, self-healing
│
└─ Batch processing?
├─ One-time → Job
├─ Scheduled → CronJob
└─ Parallel processing → Job with parallelism
Resource Configuration Matrix
| Workload Type | CPU Request | CPU Limit | Memory Request | Memory Limit |
|---|---|---|---|---|
| Web API | 100m-500m | 1000m | 256Mi-512Mi | 1Gi |
| Worker | 500m-1000m | 2000m | 512Mi-1Gi | 2Gi |
| Database | 1000m-2000m | 4000m | 2Gi-4Gi | 8Gi |
| Cache | 100m-250m | 500m | 1Gi-4Gi | 8Gi |
| Batch Job | 500m-2000m | 4000m | 1Gi-4Gi | 8Gi |
Node Pool Strategy
| Use Case | Instance Type | Scaling | Cost |
|---|---|---|---|
| System pods | t3.large (3 nodes) | Fixed | Low |
| Applications | m5.xlarge | Auto 3-20 | Medium |
| Batch/Spot | m5.large-2xlarge | Auto 0-50 | Very Low |
| GPU workloads | p3.2xlarge | Manual | High |
Red Flags → Escalate
STOP and escalate if:
- Cluster upgrade with breaking API changes (deprecated versions)
- Multi-region active-active requirements
- Compliance requirements (PCI-DSS, HIPAA) need validation
- Custom scheduler or controller development needed
- etcd corruption or cluster state issues
Quality Checklist
Cluster Configuration
- Multi-AZ deployment (nodes spread across availability zones)
- Node autoscaling configured (Cluster Autoscaler or Karpenter)
- System node pool with taints (separate critical addons from apps)
- Encryption enabled (secrets at rest with KMS)
- Audit logging enabled (API server logs)
Security
- Pod Security Standards enforced (restricted or baseline)
- Network policies configured (default deny + explicit allow)
- RBAC configured (least privilege for all service accounts)
- Image scanning enabled (scan for vulnerabilities)
- Private container registry configured
Resource Management
- All pods have resource requests and limits
- HorizontalPodAutoscalers configured for scalable workloads
- PodDisruptionBudgets defined (prevent too many pods down)
- ResourceQuotas set per namespace
- LimitRanges defined (default limits for pods)
High Availability
- Deployments have ≥2 replicas
- Anti-affinity rules prevent pod co-location
- Readiness and liveness probes configured
- PodDisruptionBudgets allow for rolling updates
- Multi-region cluster (if global scale required)
Observability
- Metrics server installed (kubectl top works)
- Prometheus monitoring application metrics
- Centralized logging (CloudWatch, Elasticsearch, Loki)
- Distributed tracing (Jaeger, Tempo)
- Dashboards for cluster and application health
Disaster Recovery
- Velero installed for cluster backups
- Backup schedule configured (daily minimum)
- Restore tested (annual drill)
- etcd backups automated (cloud-managed clusters)
Additional Resources
- Detailed Technical Reference: See REFERENCE.md
- Code Examples & Patterns: See EXAMPLES.md
Source: Canepro/codex-skills — distributed by TomeVault.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review