Agent skill · software engineering · davila7
gke-basics
Plans, creates, and configures production-ready Google Kubernetes Engine (GKE) clusters using the golden path Autopilot configuration. Covers networking, security, observability, scaling, cost optimization, and AI/ML inference on GKE.
Why this skill is useful
Provides specific commands and configurations for deploying production-ready GKE clusters that the AI wouldn't reliably generate on its own.
What it needs
Requires gcloud, kubectl installed locally. Requires google account access. About 2k tokens when loaded. Last updated 2026-08-06. 30,138 stars on the source repository.
What this skill does
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 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 …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills davila7/gke-basics