gke-basics
このスキルは、ユーザーが本番環境対応のGoogle Kubernetes Engine (GKE) クラスターを計画、作成、構成するのに役立ち、特にゴールデンパスのAutopilot構成に重点を置いています。Day-0チェックリスト、AutopilotとStandardの比較から、ネットワーキング、セキュリティ、可観測性、スケーリング、コスト最適化、AI/ML推論まで、重要な側面をカバーしています。GKE環境のデプロイと管理を簡素化し、効率的で安全なクラスター運用を保証することを目的としています。
npx skills add https://github.com/google/skills --skill gke-basicsBefore / After 効果比較
1 组ネットワーキング、セキュリティ、監視、スケーリングポリシーを含む本番環境レベルのGKEクラスターを手動で構成するには、通常数時間から数日かかり、構成ミスによるセキュリティ脆弱性やパフォーマンス問題が発生しやすいです。
GKE BasicsスキルのゴールデンパスAutopilot構成を利用することで、ユーザーはベストプラクティスに準拠したGKEクラスターを迅速にデプロイでき、構成時間を大幅に短縮し、人為的なエラーを最小限に抑え、本番環境への準備を確実にします。
Google Kubernetes Engine (GKE) Basics
GKE is a managed Kubernetes platform on Google Cloud for deploying, scaling, and operating containerized applications. This skill defaults to the golden path Autopilot configuration — see gke-golden-path.md for defaults, rules, and guardrails.
Quick Start
gcloud services enable container.googleapis.com --quiet
gcloud container clusters create-auto my-cluster --region=us-central1 --quiet
gcloud container clusters get-credentials my-cluster --region=us-central1 --quiet
kubectl create deployment hello-server \
--image=us-docker.pkg.dev/google-samples/containers/gke/hello-app:1.0
Reference Directory
Load the relevant reference based on trigger keywords. Prefer the most specific match; if ambiguous, ask the user to clarify.
| Scenario | Trigger Keywords | Reference |
|---|---|---|
| Core Concepts | Autopilot vs Standard, architecture, pricing, what is GKE | core-concepts.md |
| Golden Path & Defaults | golden path, Day-0 checklist, production defaults, cluster defaults | gke-golden-path.md |
| Cluster Creation | create cluster, new cluster, provision GKE | gke-cluster-creation.md |
| Networking | private cluster, VPC, subnet, Gateway API, DNS, ingress, egress, datapath | gke-networking.md |
| Security & IAM | Workload Identity, Secret Manager, RBAC, Binary Auth, hardening, audit, gVisor, IAM roles | gke-security.md |
| Scaling | HPA, VPA, autoscaler, autoscaling, NAP, scale pods, scale nodes | gke-scaling.md |
| Compute Classes | ComputeClass, machine family, Spot fallback, GPU node pool, node selection | gke-compute-classes.md |
| Cost | cost, savings, Spot VMs, rightsizing, CUD, optimize spend, budget | gke-cost.md |
| AI/ML Inference | inference, model serving, LLM, GPU, TPU, GIQ, vLLM | gke-inference.md |
| Upgrades | upgrade, maintenance window, release channel, patching, version | gke-upgrades.md |
| Observability | monitoring, logging, Prometheus, Grafana, metrics, alerts, dashboards | gke-observability.md |
| Multi-tenancy | multi-tenant, namespace isolation, team access, enterprise, RBAC planning | gke-multitenancy.md |
| Batch & HPC | batch, HPC, job queue, high performance, MPI, parallel | gke-batch-hpc.md |
| App Onboarding | containerize, deploy app, Dockerfile, onboard, migrate to GKE | gke-app-onboarding.md |
| Backup & DR | backup, restore, disaster recovery, CMEK | gke-backup-dr.md |
| Storage | storage, PVC, persistent volume, StorageClass, Filestore, GCS FUSE | gke-storage.md |
| Reliability | PDB, health probe, liveness, readiness, topology spread, graceful shutdown | gke-reliability.md |
| Client Libraries | client library, client-go, kubernetes python, kubernetes java, kubernetes SDK | client-library-usage.md |
| Infrastructure as Code | Terraform, IaC, HCL, infrastructure as code | iac-usage.md |
| MCP Server | MCP tools, MCP server, MCP setup | mcp-usage.md |
| CLI / Tools | gcloud, kubectl, commands, how to | cli-reference.md |
| Production Audit | production readiness, compliance, golden path check | gke-cluster-creation.md |
If you need product information not found in these references, use the Developer Knowledge MCP server search_documents tool.
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