AgentSkillsCN

kubernetes-basics

针对工作负载部署、服务发现与集群资源基础的专业化工作流。当容器、编排或基础设施运行时配置是核心关注点时,可选用此流程;但请勿将其用于 API 合约设计或需求优先级排序。

SKILL.md
--- frontmatter
name: kubernetes-basics
description: Specialized workflow for workload deployment, service discovery, and cluster resource basics. Use when container, orchestration, or infrastructure runtime configuration is central; do not use for API contract design or requirement prioritization.

Kubernetes Basics

Trigger Boundary

  • Use when runtime packaging, orchestration, or infrastructure controls must be defined.
  • Do not use for product requirement decomposition; use requirements-* or user-story-writing.
  • Do not use for post-incident review output; use incident-postmortem.

Goal

Establish reproducible, secure, and operable runtime platforms.

Inputs

  • Change scope and risk profile
  • Domain evidence for workload deployment, service discovery, and cluster resource basics
  • Operational, compliance, and rollout constraints

Outputs

  • Kubernetes workload baseline manifest set
  • Decision log for workload deployment, service discovery, and cluster resource basics
  • Verification checklist with measurable pass-fail criteria

Workflow

  1. Clarify outcomes and hard constraints for workload deployment, service discovery, and cluster resource basics.
  2. Produce options and select an approach for workload deployment, service discovery, and cluster resource basics.
  3. Evaluate trade-offs across security, performance, operability, and maintainability.
  4. Verify decisions using cluster deployment and health probe checks.
  5. Publish decisions, residual risks, and accountable follow-up actions.

Quality Gates

  • Scope and assumptions for workload deployment, service discovery, and cluster resource basics are explicit and reviewable.
  • Decision rationale is backed by evidence instead of preference.
  • Rollout and rollback criteria are defined when production impact exists.
  • Residual risks have owners, due dates, and verification steps.

Failure Handling

  • Stop when baseline workloads cannot be deployed reliably on target clusters.
  • Escalate when accepted risk exceeds team policy thresholds.