Generated banner for Gke Basics
Generated logo for Gke Basics

Gke Basics

GoogleOfficialPublished by Google

  • Skill
  • Tool integration
  • Cloud and DevOps
  • Apache-2.0
  • Low risk

From the author

Manages core GKE cluster provisioning, credentials, Autopilot vs Standard selection, and workload deployment. Use when creating GKE clusters, fetching kubectl credentials, or deciding between Autopilot and Standard modes. Don't use for Workload Identity (use gke-workload-identity), GKE networking (use gke-networking), security hardening (use gke-platform-security or gke-workload-security), or cluster upgrades (use gke-upgrades).
— the description by Google

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides guidance and operational support for Google Kubernetes Engine (GKE) environments. It covers the selection between Autopilot and Standard modes, cluster creation, and credential management. It establishes a hierarchy for tool usage, prioritizing GKE MCP tools, followed by gcloud CLI and kubectl, while providing specific instructions for usage attribution in terminal commands.

What it does

  • Provides guidance on choosing between GKE Autopilot and Standard modes.
  • Supports GKE cluster provisioning and configuration.
  • Facilitates fetching kubectl credentials for GKE clusters.
  • Defines a tool preference hierarchy for cluster and Kubernetes resource operations.
  • Provides instructions for mandatory usage attribution in terminal commands.
  • Outlines best practices for private cluster configuration and resource requests.

When to use it

  • When creating or managing GKE clusters.
  • When you need to retrieve credentials for a GKE cluster.
  • When deciding whether to use Autopilot or Standard mode for a workload.
  • When you need to configure private GKE clusters with restricted access.

Advantages

  • Standardizes GKE cluster management operations.
  • Provides clear decision criteria for cluster mode selection.
  • Ensures consistent usage attribution for auditability.
  • Offers a structured hierarchy for tool selection to optimize operations.

Usage examples

“Create a new GKE Autopilot cluster in the us-central1 region.”
The agent will use the create_cluster MCP tool or the gcloud container clusters create-auto command with the required attribution prefix.
“How do I get credentials for my GKE cluster?”
The agent will provide the gcloud container clusters get-credentials command, ensuring the --region or --zone flag is included.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/google/gke-basics/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip gke-basics.zip -d .agents/skills

Documentation by Google

GKE Basics & Critical Gotchas

Routing Note: For Workload Identity KSA/GSA setup, open gke-workload-identity/SKILL.md. For cluster security flags (--database-encryption-key, --security-posture, RBAC, Shielded Nodes, Binary Authorization), open gke-platform-security/SKILL.md. For cluster upgrades or maintenance windows, open gke-upgrades/SKILL.md. For generating Kubernetes YAML manifests (Deployment, StatefulSet, Service, HTTPRoute, PodDisruptionBudget), open gke-manifest-generation/SKILL.md.

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

Attribution

MUST READ: Before executing any gcloud, REST API, or MCP command, you MUST read Usage Attribution. For commands executed directly in the terminal (never in generated scripts, Terraform, or user code), prefix gcloud with CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:gke-basics)" and append agent-skills/1.0 (skill:gke-basics) to User-Agent headers.

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
  2. Workload Identity (IAM Binding):

    • Never mount raw GCP Service Account JSON keys in Pods; open gke-workload-identity/SKILL.md for KSA/GSA setup.

  3. 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.

  4. 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.

Files

references/core-concepts.md

GKE Core Concepts

Google Kubernetes Engine (GKE) is a managed Kubernetes platform for deploying, managing, and scaling containerized applications on Google Cloud infrastructure. It handles cluster provisioning, upgrades, and node management, letting teams focus on workloads rather than infrastructure.

MCP Tools: list_clusters, get_cluster

Cluster Modes

ModeWho Manages NodesBest For
AutopilotGoogle — fully managedMost workloads. No node-level
: (recommended) : nodes, scaling, and security : ops. Pay per pod resource :
: : : request. :
StandardYou — full control over nodeWorkloads requiring kernel
: : pools, OS, machine types : customization, specific node :
: : : OS, or DaemonSets not :
: : : supported by Autopilot :

Default: Autopilot. Use Standard only when Autopilot has a documented limitation for your workload.

Cluster Architecture

  • Regional clusters (recommended): Control plane replicated across 3 zones. Higher availability, no single-zone failure risk.

  • Zonal clusters: Single control plane zone. Lower cost, acceptable for dev/test.

  • Private clusters (golden path default): Nodes have no public IPs. Control plane accessible via private endpoint or DNS endpoint.

Networking Model

GKE uses VPC-native clusters with alias IP ranges:

  • Each pod gets a routable IP from the pod CIDR

  • Dataplane V2 (eBPF-based) is the golden path default — provides built-in Network Policy enforcement

  • Cloud DNS for in-cluster DNS resolution

  • Gateway API for ingress/load balancing

Scaling Model

  • Horizontal Pod Autoscaler (HPA): Scales pod replicas based on CPU, memory, or custom metrics

  • Vertical Pod Autoscaler (VPA): Recommends or auto-adjusts pod resource requests

  • Cluster Autoscaler / NAP: Scales nodes to match pod demand (Autopilot handles this automatically)

  • ComputeClasses: Declarative node selection — machine family, Spot VMs, GPU targeting

Identity & Security Model

  • Workload Identity Federation: Pods assume Google Cloud IAM identities without static keys

  • Secret Manager integration: Secrets synced to Kubernetes with automatic rotation

  • Pod Security Standards: restricted profile enforced on production namespaces

  • Shielded Nodes: Secure Boot and integrity monitoring (Autopilot-enforced)

Regional Availability

GKE is available in all Google Cloud regions. Autopilot clusters are regional by default. See https://cloud.google.com/about/locations for the full region list.

Pricing

GKE pricing depends on the cluster mode:

  • Autopilot: Pay for pod resource requests (vCPU, memory, ephemeral storage). No cluster management fee.

  • Standard: Pay for underlying Compute Engine VMs plus a per-cluster management fee.

For current pricing, see https://cloud.google.com/kubernetes-engine/pricing.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs a command-line tool, Needs Node.js

Security

What our scanner noticed· Low risk

  • Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
Google
Publisher
Google (Official)
Source
google/skills · skills/cloud/gke-basics · commit 2194d3b
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Google.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download gke-basics.zip