Automation & Ops ✓ Google · Official gke-networkingprivate-clustersvpc-nativedataplane-v2cloud-natip-planningcloud-dns

GKE Cluster Networking Planner

Design private, VPC-native GKE networks with practical IP and egress guidance.

FollowSkills review · FSRS-2.0
Not recommended
49/ 100 5-point scale 2.5 / 5
Trust13 / 25 · 2.6/5

The skill clearly concerns private clusters, network policy, ingress, and egress, but its listed MCP tools include update_cluster and apply_k8s_manifest without documenting least privilege, pre-execution confirmation, data flows, sensitive-data handling, rollback, or recovery. This supports 13/25.

Reliability8 / 20 · 2.0/5

Defaults, gcloud commands, and YAML examples make the happy path understandable. However, there are no version prerequisites, parameter validation, tests, abnormal-input handling, or diagnosable failure messages, and several product behaviors are not verified within the files. Score: 8/20, within the static-review ceiling.

Adaptability10 / 15 · 3.3/5

The description clearly targets GKE network design, private clusters, Gateway API, IP planning, and ingress/egress, while excluding basic routing without dedicated network configuration. Inputs, outputs, non-fit boundaries, semantic trigger details, Chinese support, and mainland-China reachability are not sufficiently specified. Score: 10/15.

Convention8 / 15 · 2.7/5

The skill is readable and organized progressively around defaults, access patterns, IP planning, ingress, egress, and security. The README supplies installation, support, active-development, and contribution information, and the repository states Apache-2.0 licensing. The skill lacks its own version, changelog, named maintainer, dependency versions, FAQ, explicit limitations, and detailed post-install configuration notes. Score: 8/15.

Effectiveness7 / 15 · 2.3/5

It covers common GKE networking tasks and offers reusable commands, Gateway, BackendConfig, and sizing examples that can support core planning. Static files contain no execution evidence or tests; examples depend on environment-specific prerequisites and network changes require substantial review. Score: 7/15, constrained by static calibration.

Verifiability3 / 10 · 1.5/5

The fixed revision, official organization provenance, README, license, and inspectable configuration examples provide some traceability. The skill has no official-document citations, committed test suite, CI coverage, or independent corroboration, so key claims cannot be independently reproduced from the supplied files. Score: 3/10.

Evidence confidence:Low Reviewed Jul 20, 2026 Reviewed revision 513a7a51e85f
The upstream repository has new commits since this review. The score still applies to the reviewed revision shown and may not cover the latest changes.
Before you use it
  • Before executing update_cluster or apply_k8s_manifest, confirm the target cluster, change scope, required permissions, impact, and rollback plan.
  • Private clusters, DNS endpoints, Cloud NAT, IP ranges, and Gateway settings may depend on GKE version, region, existing VPC design, and organization policy; golden-path defaults should not be treated as universally applicable.
  • The files do not address mainland-China reachability or Chinese-language operation. Validate access to Google Cloud control-plane and supporting services before relying on the skill in that environment.
Review evidence [1][2][3][4]
See the full review method →

What does this skill do, and when should you use it?

This skill focuses on core networking for GKE clusters, excluding application ingress, load balancing, and service networking. Its recommended path uses private nodes, private control-plane access, Dataplane V2, Cloud DNS, and automatic IP management. It covers private-cluster access, existing VPC integration, VPC-native networking, IP sizing, egress, and network policy. It is most suitable for teams making GKE network decisions during cluster design and creation.

It plans and configures private GKE clusters, VPC-native networking, Dataplane V2, Cloud DNS, node egress, and Pod, Service, and node-subnet address ranges. It provides gcloud container clusters create-auto and get-credentials examples for cluster creation and access, including DNS endpoint, private endpoint, and authorized-network patterns. It identifies get_cluster, update_cluster, apply_k8s_manifest, and get_k8s_resource as MCP tools for reading or changing cluster and Kubernetes resources. It recommends Cloud NAT for internet access from private nodes, with options for manually allocated static egress IPs or firewall-appliance routing.

  1. A platform engineer needs to size Pod, Service, and node-subnet ranges before creating a GKE cluster.
  2. A cloud architect is designing a private GKE cluster whose nodes have no public IP addresses.
  3. A GKE administrator needs to choose DNS endpoint, private endpoint, or authorized-network control-plane access.
  4. A network engineer must connect GKE to an existing VPC and subnet using existing secondary ranges.
  5. A security or operations team needs Cloud NAT, static egress IPs, or inspected outbound traffic for private nodes.

What are this skill's strengths and limitations?

Pros
  • Covers private clusters, VPC-native mode, Dataplane V2, DNS, egress, and IP planning in one focused reference.
  • Provides concrete golden-path defaults, including private nodes, Cloud DNS, automatic IP management, and 48 Pods per node.
  • Includes actionable access commands for DNS and private control-plane endpoints.
  • Highlights irreversible Day-0 network decisions before cluster creation.
Limitations
  • Does not cover application ingress, load balancing, or service networking.
  • The source provides no test suite, version compatibility matrix, or detailed troubleshooting procedure.
  • Its recommended IP sizes and defaults may need adjustment for actual cluster scale and density.
  • It assumes access to gcloud or MCP tooling but does not document authentication, permissions, or a complete runtime setup.

How do you install this skill?

Install the collection with: npx skills add google/skills. The installer lets you select individual skills from the repository; this skill is located at skills/cloud/gke-networking. The source does not document a separate command for installing only this subdirectory or a specific destination directory for a client.

How do you use this skill?

After loading the skill in an Agent Skills-compatible client, use a request such as: “Design a private VPC-native network for a GKE cluster, size the IP ranges, and configure Cloud NAT.” For actual operations, combine the documented gcloud commands with get_cluster, update_cluster, apply_k8s_manifest, and get_k8s_resource. Decide the VPC, subnet, and IP ranges before cluster creation because the source warns that they cannot be changed afterward.

How does this skill compare with similar options?

The skill explicitly excludes application ingress, load balancing, and service networking, directing those scenarios to gke-service-networking. It is therefore a core cluster-networking reference rather than a complete GKE traffic-management guide. For default-deny and team-specific network policies, it points to gke-workload-security and gke-multitenancy.

FAQ

Can I use this for application Ingress or load balancing?
No. Those areas are explicitly outside this skill's scope, as is service networking.
How do private nodes reach the internet?
The recommended method is Cloud NAT because private nodes have no public IPs. Manual NAT IP allocation can provide a stable source IP.
Can I change the VPC, subnet, or IP ranges after creation?
The source warns that these settings cannot be changed after cluster creation, so they must be planned at Day 0.
Does Dataplane V2 require another network-policy add-on?
According to the golden path, Dataplane V2 includes built-in network-policy enforcement and does not need an additional add-on.

More skills from this repository

All from google/skills

Automation & Ops ✓ Google · Official

Google Cloud Network Observability

Investigate Google Cloud network behavior with logs, metrics, and path diagnostics for VPC, NAT, and firewall issues.

Automation & Ops ✓ Google · Official

GKE Service Networking

Configure secure GKE traffic routing, load balancing, edge protection, and private service connectivity.

Automation & Ops ✓ Google · Official

GKE Production Golden Path

Set production-oriented GKE defaults, readiness checks, and decision guardrails for cluster design.

Automation & Ops ✓ Google · Official

GKE Enterprise RAG Search Architect

Designs and validates enterprise RAG search systems built on GKE and AlloyDB.

Automation & Ops ✓ Google · Official

GKE Cluster Autoscaler Guide

Configure, optimize, and troubleshoot automatic GKE node scaling.

Automation & Ops ✓ Google · Official

GKE GPU/TPU Disruption Diagnosis

Diagnose and mitigate GKE GPU/TPU node disruptions caused by host maintenance.

Automation & Ops ✓ Google · Official

AI Workload Migration to GKE Inference

Move existing AI inference workloads to self-hosted inference on Google Kubernetes Engine.

Automation & Ops ✓ Google · Official

GKE Cluster Creation Advisor

Plan, provision, and audit GKE clusters against production best practices.

Automation & Ops ✓ Google · Official

GKE Upgrade & Maintenance Advisor

Plans and validates upgrades and maintenance for Standard and Autopilot GKE clusters.

Automation & Ops ✓ Google · Official

GKE Cost Optimization

Reduce GKE spending through rightsizing, quotas, Spot VMs, and capacity planning.

Automation & Ops ✓ Google · Official

GKE AI Inference Deployment Assistant

Deploy, tune, and autoscale GPU/TPU AI inference services on GKE.

Automation & Ops ✓ Google · Official

GKE Basics Navigator

A focused entry point for discovering GKE cluster needs and routing each task to the right specialist skill.

Automation & Ops ✓ Google · Official

GKE Observability Configuration

Configure GKE logging, monitoring, and Prometheus metrics.

Dev & Engineering ✓ Google · Official

Google Agents CLI Agent Development Guide

Guides agents from specification through development, deployment, and monitoring.

Automation & Ops ✓ Google · Official

Google Cloud Secure Serverless Tiers

Guides agents to design, codify, deploy, and validate isolated multi-tier serverless web applications on Google Cloud.

Automation & Ops ✓ Google · Official

Google Cloud Authentication Guide

Choose secure Google Cloud authentication and authorization for local, production, and cross-cloud workloads.

Automation & Ops ✓ Google · Official

GKE ComputeClasses Advisor

Configure, optimize, and troubleshoot GKE ComputeClasses for cost, capacity, and workload placement.

Automation & Ops ✓ Google · Official

Google Cloud Solution Architect

Plan, validate, and package end-to-end architectures for complex multi-product Google Cloud workloads.

Automation & Ops ✓ Google · Official

Google Cloud Reliability Architect

Evaluate and improve Google Cloud workload reliability using the Well-Architected Framework.

Automation & Ops ✓ Google · Official

Google Cloud Workload Manager Evaluator

Evaluate Google Cloud workloads against best-practice rules and review actionable findings.

Related skills