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GKE Basics & Critical Gotchas

GKE Basics & Critical Gotchas Skill

by Google google/skills skills/cloud/gke-basics

Google's official GKE skill — when Autopilot beats Standard, Workload Identity instead of JSON keys, Autopilot's 250m CPU rounding, and private-cluster flags.

GitHub Docs
DevOps & Infrastructure
Released
Apache-2.0

Install

Install with the skills CLI

One command for Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf and dozens of other agents. Needs Node.js; the skill is fetched straight from google/skills.

$ npx skills add google/skills --skill gke-basics

Run it in a terminal. The CLI finds the agents installed on your machine, asks which ones to add the skill to, and whether to install it into the folder you ran it from or for all your projects.

Other ways to install

Copy the whole skill folder — SKILL.md and any scripts or references beside it — into ~/.claude/skills/gke-basics/, where Claude Code picks it up in every project. Only git is needed.

tmp=$(mktemp -d) && \
  git clone --depth 1 --branch main https://github.com/google/skills.git "$tmp" && \
  mkdir -p ~/.claude/skills && \
  cp -R "$tmp"/skills/cloud/gke-basics ~/.claude/skills/gke-basics

No scripts or references next to it? Saving the SKILL.md alone as ~/.claude/skills/gke-basics/SKILL.md works too.

Using another agent? Its personal skills folder
Codex
~/.agents/skills/
Cursor
~/.cursor/skills/
GitHub Copilot
~/.copilot/skills/
Gemini CLI
~/.gemini/skills/
Windsurf
~/.codeium/windsurf/skills/
OpenCode
~/.config/opencode/skills/
Open folder on GitHub

About

  • Autopilot-by-default with the three explicit reasons to pick Standard
  • Workload Identity binding instead of mounted service-account keys
  • Autopilot's 250m CPU increment and requests-equal-limits behaviour
  • Private cluster and master-authorised-network flags in full
  • Explicit hand-off to the specialised GKE networking, security and upgrade skills

Most GKE mistakes are made in the first ten minutes: reaching for Standard mode out of habit, mounting a service-account JSON key into a pod, or requesting 300m of CPU on Autopilot and quietly paying for 500m.

This official Google skill is written as a decision guide rather than a tutorial. It defaults to Autopilot and names the only three reasons to choose Standard — custom sysctl kernel parameters, custom node taints or specific hardware node pools, and DaemonSets needing raw hostPath mounts — and asks the agent to cite which one applies. From there it covers private Autopilot clusters (--enable-private-nodes, --enable-private-endpoint, master authorised networks), Workload Identity binding a Kubernetes ServiceAccount to a Google Service Account via annotation, Autopilot's 250m CPU increment rule and its requests-equal-limits behaviour, and always passing --region or --zone when fetching credentials.

It is deliberately scoped: specialised networking, security hardening and upgrades live in sibling skills (gke-networking, gke-platform-security, gke-workload-security, gke-upgrades), so the agent knows when to hand off rather than guess.

Try it

Once installed, ask your agent something like:

"Create a private Autopilot cluster in us-central1, wire up Workload Identity for the billing service account, and deploy this manifest."

SKILL.md

The instructions your agent loads, as published by Google.

SKILL.md
name
gke-basics
metadata
category: Containers
description
Manages core GKE cluster provisioning, credentials, Autopilot vs Standard selection, and workload deployment. Use when creating GKE clusters, fetching kubectl credentials, configuring Workload Identity, or deciding between Autopilot and Standard modes. Don't use for specialized GKE networking (use gke-networking), advanced security hardening (use gke-platform-security or gke-workload-security), or cluster upgrades (use gke-upgrades).

GKE Basics & Critical Gotchas

Managed Kubernetes platform on Google Cloud. Defaults to Autopilot mode unless Standard is explicitly required.

Key Selection Rules: Autopilot vs. Standard
  • Default to Autopilot for almost all workloads.
  • Use Standard ONLY if:
  • Custom node OS kernel parameters (sysctl) are required.
  • Custom node taints or specific hardware node pools are required.
  • DaemonSets require raw hostPath mounts to the host OS filesystem.
  • When explaining why Standard is required over Autopilot, explicitly cite all matching restrictions (e.g., custom sysctls and custom node taints).
  • For advanced cluster architecture or complex node pool creation planning, refer to `gke-cluster-creation`.
Critical Gotchas & Best Practices
  1. Private Autopilot Clusters:
  • Use --enable-private-nodes for private node IP addresses.
  • Use --enable-private-endpoint to disable public IP access to the control plane.
  • Restrict control plane access with --enable-master-authorized-networks and --master-authorized-networks=CIDR_BLOCK:
     gcloud container clusters create-auto CLUSTER_NAME --region=REGION \
       --enable-private-nodes \
       --enable-private-endpoint \
       --enable-master-authorized-networks \
       --master-authorized-networks=CIDR_BLOCK
  1. Workload Identity (IAM Binding):
  • Never mount raw GCP Service Account JSON keys in Pods.
  • Annotate the Kubernetes ServiceAccount (KSA) to bind to the Google Service Account (GSA):
     metadata:
       annotations:
         iam.gke.io/gcp-service-account: GSA_NAME@PROJECT_ID.iam.gserviceaccount.com
  1. Autopilot Resource Requests:
  • In Autopilot, CPU requests must be specified in increments of 250m (0.25 vCPU). If an unaligned CPU request (e.g., 300m) is requested, round up to the nearest 250m increment (500m / 0.5 vCPU).
  • Resource requests equal limits automatically. Omit limits to allow Autopilot to set defaults matching requests.
  1. Cluster Credentials:
  • Always explicitly specify --region (for regional clusters) or --zone (for zonal clusters) when fetching credentials:
     gcloud container clusters get-credentials CLUSTER_NAME --region=REGION --quiet
Reference Directory
  • [Core Concepts](references/core-concepts.md): Architecture, cluster modes (Autopilot vs Standard), networking, scaling, and security model.
  • [CLI Usage & Tool Reference](references/cli-reference.md): Tool preference hierarchy (MCP vs gcloud vs kubectl), gcloud container commands, and user preference overrides.
  • [Client Libraries](references/client-library-usage.md): Official Kubernetes and Google Cloud Container client libraries in Python, Go, Node.js, and Java.
  • [MCP Usage](references/mcp-usage.md): Connecting to and using the 23 structured GKE MCP tools for cluster management, K8s resources, and diagnostics.
  • [Infrastructure as Code](references/iac-usage.md): Terraform examples for google_container_cluster (Autopilot), Kubernetes provider resources, and YAML samples.
Install

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