What is the main purpose of the GKE Basics skill?

The GKE Basics skill helps users manage GKE cluster provisioning, workload deployment, and understand the differences between Autopilot and Standard modes.

When should I use Standard mode over Autopilot?

Standard mode should be used when custom node OS kernel parameters, specific hardware node pools, or raw hostPath mounts are required.

How do I configure Workload Identity in GKE?

To configure Workload Identity, annotate the Kubernetes ServiceAccount to bind to the Google Service Account without mounting raw JSON keys.

What are some critical gotchas to be aware of?

Key gotchas include using private clusters correctly and ensuring resource requests in Autopilot are specified in the correct increments.

Where can I find additional resources related to GKE?

The skill provides a reference directory with links to core concepts, CLI usage, client libraries, and Infrastructure as Code examples.

GKE Basics

Name: GKE Basics
Availability: InStock
Author: google

Free

Simplify GKE cluster management and deployment.

by google17.6k stars on google/skills

Updated Aug 10, 2026

Get this skill

Free · Opens the source repo

What GKE Basics does

GKE Basics is a skill designed for developers and DevOps engineers who are working with Google Kubernetes Engine (GKE). This skill provides essential commands and best practices for provisioning GKE clusters, managing workloads, and understanding the differences between Autopilot and Standard modes. It is particularly useful for those new to GKE or those who want to streamline their cluster management processes. The skill defaults to Autopilot mode, which is suitable for most workloads, but also provides guidance on when to opt for Standard mode based on specific requirements.

The skill includes critical gotchas and best practices that help prevent common pitfalls when setting up GKE clusters. For instance, it emphasizes the importance of using private clusters and configuring Workload Identity correctly to enhance security. Users will learn how to fetch kubectl credentials accurately and how to specify resource requests in Autopilot mode. The skill also clarifies the significance of adhering to resource request increments, which can impact workload performance and cost.

Moreover, GKE Basics offers a structured reference directory that links to additional resources, including core concepts of GKE, CLI usage, client libraries, and Infrastructure as Code examples. This makes it a comprehensive tool for anyone looking to deepen their understanding of GKE and improve their operational efficiency. Whether you are deploying applications or managing clusters, this skill equips you with the knowledge needed to navigate GKE effectively.

When to use it

Use this skill when creating GKE clusters, configuring workloads, or when you need to understand Autopilot vs Standard modes.

When not to use it

Avoid this skill for advanced networking configurations, security hardening, or cluster upgrades, as those require specialized skills.

What you can build with it

Setting Up a New GKE Cluster

Use GKE Basics to quickly provision a new GKE cluster with best practices for Autopilot mode.

Configuring Workload Identity

Follow the guidelines in GKE Basics to set up Workload Identity securely without exposing service account keys.

Fetching Cluster Credentials

Utilize the skill to fetch kubectl credentials accurately, ensuring you specify the correct region or zone.

How to install GKE Basics

View source

1. Install with the skills CLI

npx skills add google/skills/gke-basics --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by google

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

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
```
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
```
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.
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: Architecture, cluster modes (Autopilot vs Standard), networking, scaling, and security model.
CLI Usage & Tool Reference: Tool preference hierarchy (MCP vs gcloud vs kubectl), gcloud container commands, and user preference overrides.
Client Libraries: Official Kubernetes and Google Cloud Container client libraries in Python, Go, Node.js, and Java.
MCP Usage: Connecting to and using the 23 structured GKE MCP tools for cluster management, K8s resources, and diagnostics.
Infrastructure as Code: Terraform examples for google_container_cluster (Autopilot), Kubernetes provider resources, and YAML samples.

Frequently asked questions about GKE Basics

Similar skills

Turborepo

Optimized build system for JavaScript/TypeScript monorepos.

Azure Pipelines Validation

Streamline your Azure DevOps pipeline changes locally.

Azure Developer CLI

Streamline your Azure project workflows with best practices.

Azure Container Registry CLI

Manage Azure Container Registry resources with ease.

Aspire

Build and orchestrate polyglot distributed applications seamlessly.

Vercel CLI

Manage and deploy Vercel projects from the command line.