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gke-basics

Set up a managed Kubernetes environment on Google Cloud, from choosing Autopilot or Standard to creating a GKE cluster, obtaining kubectl connection credentials, and deploying workloads. Includes guidance on private clusters and resource requests.

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原文查看原文说明

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).

google/skills

集成工具Google Cloud Kubernetes

查看安装方法

适用场景

Choosing between Autopilot and Standard
Creating a private GKE cluster
Obtaining kubectl credentials for a cluster
Checking resource requests before deployment

包含的文件（6）

SKILL.md3.9 KB
references/cli-reference.md14.2 KB
references/client-library-usage.md2.4 KB
references/core-concepts.md3.2 KB
references/iac-usage.md2.1 KB
references/mcp-usage.md6.8 KB

SKILL.md（原文）

安装前可以查看交给 AI 代理的指令内容。

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.

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; open gke-workload-identity/SKILL.md for KSA/GSA setup.
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.

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中文简介正在准备中。当前显示英语简介。

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