ReddRadar
Agent skill
gke-basics
Plan, create, and configure production-ready Google Kubernetes Engine (GKE) clusters using the golden path Autopilot configuration. Covers Day-0 checklist, Autopilot vs Standard, networking (private clusters, VPC-native, Gateway API), security (Workload Identity, Secret Manager, RBAC hardening), observability, scaling, cost optimization, and AI/ML inference. WHEN: create GKE cluster, provision GKE environment, design GKE networking, secure GKE, optimize GKE cost, GKE autoscaling, GKE inference, GKE upgrade, GKE observability, GKE multi-tenancy, GKE batch, GKE HPC, GKE compute class.
Install this agent skill to your Project
npx add-skill https://github.com/google/skills/tree/main/skills/cloud/gke-basics
Metadata
Additional technical details for this skill
- author
- Google Cloud
- version
- 1.0.0
SKILL.md
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
gcloud container clusters create-auto my-cluster --region=us-central1
gcloud container clusters get-credentials my-cluster --region=us-central1
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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