
GKE Basics & Critical Gotchas
SkillGoogle's official GKE basics skill: creating clusters, choosing Autopilot or Standard, getting kubectl credentials, configuring Workload Identity and deploying workloads, plus a list of common gotchas. Needs gcloud and a GCP project.
name: gke-basics
metadata:
version: "1.1.1"
category: Containers
description: >-
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).
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), opengke-platform-security/SKILL.md. For cluster upgrades or maintenance windows, opengke-upgrades/SKILL.md. For generating Kubernetes YAML manifests (Deployment,StatefulSet,Service,HTTPRoute,PodDisruptionBudget), opengke-manifest-generation/SKILL.md.
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
hostPathmounts to the host OS filesystem.
- Custom node OS kernel parameters (
- 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-nodesfor private node IP addresses. - Use
--enable-private-endpointto disable public IP access to the control plane. - Restrict control plane access with
--enable-master-authorized-networksand--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
- Use
-
Workload Identity (IAM Binding):
- Never mount raw GCP Service Account JSON keys in Pods; open
gke-workload-identity/SKILL.mdfor KSA/GSA setup.
- Never mount raw GCP Service Account JSON keys in Pods; open
-
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
limitsto allow Autopilot to set defaults matchingrequests.
-
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
- Always explicitly specify
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 containercommands, 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.
関連リソース

kubectl-ai
CLIManage Kubernetes clusters in natural language: translates intent into kubectl operations and runs them, and can serve as an MCP server for other agents. Uses Gemini by default (API key required) and also supports OpenAI and local models. Maintained by Google Cloud.
GoogleCloudPlatform/kubectl-ai7.6k
Google Agent Skills
SkillGoogle's official skill library, focused on Google Cloud: 100+ skills for gcloud, Cloud Run, GKE, BigQuery, IAM, monitoring and logging, and the Well-Architected Framework, plus Ads and Analytics.
google/skills21.4k
Amazon EKS MCP Server
MCPOfficial AWS MCP to create and manage EKS clusters, deploy apps, manage Kubernetes resources, and read pod logs and events for troubleshooting. Read-only by default; writes need --allow-write and reading logs needs --allow-sensitive-data-access.
awslabs/mcp9.8k
Kubernetes MCP Server
MCPA native Go MCP server for Kubernetes and OpenShift: talks to the API server directly to create, read, update and delete any resource, view pod logs, exec commands and install Helm charts, without needing kubectl. Supports multiple clusters.
containers/kubernetes-mcp-server2.2k
Azure Skills
SkillMicrosoft's official Azure skill set: deployment prep and validation, deployment, production diagnostics, AKS, quota lookup, compliance audits, cloud migration and Foundry; the plugin version also connects the Azure MCP Server. Needs an Azure account and az login.
microsoft/azure-skills1.6k
Kubernetes Operations
PluginKubernetes operations plugin from the wshobson/agents marketplace: a kubernetes-architect subagent plus four skills for manifest generation, Helm chart scaffolding, GitOps workflows and security policies. Community-maintained.
wshobson/agents40.9k