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Gke Networking

OrganizationPopular
google
gke-networking

Plans, configures, and manages core GKE cluster networking. Covers private clusters, VPC-native configurations, DNS, node egress, Dataplane V2, and IP planning. Use when designing GKE networking layouts, configuring private clusters, setting up Dataplane V2, planning GKE IP ranges, or managing VPC- native cluster modes. Don't use for application ingress, load balancing, or service networking (use gke-service-networking instead).

Overview

Publishergoogle
Repositoryskills
Skill namegke-networking
Stars
20.5K
Forks
1.7K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by google on GitHub. Read the source before you install it.

Installation

Install the Gke Networking AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/google/skills/tree/main/skills/cloud/gke-networking
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/google/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/cloud/gke-networking .claude/skills/gke-networking
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gke Networking in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Gke Networking on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Gke Networking is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

GKE Networking

This reference covers networking configuration for GKE clusters. The golden path enforces private, VPC-native clusters with Dataplane V2.

MCP Tools: get_cluster, update_cluster, apply_k8s_manifest, get_k8s_resource

Golden Path Networking Defaults

SettingGolden Path ValueDay-0/1Notes
privateClusterConfig.enablePrivateNodestrueDay-0Nodes have no public IPs
masterAuthorizedNetworksConfig.privateEndpointEnforcementEnabledtrueDay-0Control plane only reachable via private endpoint or DNS
controlPlaneEndpointsConfig.dnsEndpointConfig.allowExternalTraffictrueDay-0Allows DNS-based access from outside VPC
networkConfig.datapathProviderADVANCED_DATAPATH (Dataplane V2)Day-0eBPF-based, built-in Network Policy
networkConfig.dnsConfig.clusterDnsCLOUD_DNSDay-0Managed DNS, more reliable than kube-dns
networkConfig.enableIntraNodeVisibilitytrueDay-1VPC Flow Logs for intra-node traffic
ipAllocationPolicy.autoIpamConfig.enabledtrueDay-0Automatic IP range management
ipAllocationPolicy.createSubnetworktrueDay-0Auto-create dedicated subnet
defaultMaxPodsConstraint.maxPodsPerNode48Day-0Conservative default; 110 for high density

Private Cluster Access Patterns

The golden path creates a private cluster. Users access it via:

  1. DNS endpoint (default): allowExternalTraffic: true enables access via the cluster's DNS endpoint from outside the VPC. No VPN required.
  2. Private endpoint: Direct access from within the VPC or via Cloud VPN/Interconnect.
  3. Authorized networks: Add specific CIDRs to masterAuthorizedNetworksConfig for IP-based access control.
bash
# Access private cluster via DNS endpoint (golden path default)
gcloud container clusters get-credentials {cluster_name} \
  --region {region} --dns-endpoint \
  --quiet

# Access via private endpoint (from within VPC)
gcloud container clusters get-credentials {cluster_name} \
  --region {region} --internal-ip \
  --quiet

Bring-Your-Own VPC/Subnet

If the customer has existing network infrastructure:

bash
gcloud container clusters create-auto {cluster_name} \
  --region {region} \
  --network {vpc_name} \
  --subnetwork {subnet_name} \
  --cluster-secondary-range-name {pod_range} \
  --services-secondary-range-name {svc_range} \
  --enable-private-nodes \
  --enable-master-authorized-networks \
  --quiet

Day-0 Warning: VPC, subnet, and IP ranges cannot be changed after cluster creation.

VPC-Native Mode Benefits

VPC-native clusters route traffic natively using GCP Alias IP ranges. Key benefits to cover:

  1. Scalability: Traffic routes natively inside the VPC, bypassing the need for custom routes and avoiding custom route limit bottlenecks.
  2. Direct VPC Integration: Direct resource integration across GCP networks without complex bridging or routing tunnels.
  3. Avoiding IP Exhaustion: Supports discontiguous IP ranges and optimizes allocation, reducing the risk of exhausting subnet IP ranges.

IP Planning

ResourceGolden PathNotes
Pod CIDR/17 (auto)~32K pod IPs; size based on maxPodsPerNode
Service CIDR/20 (auto)~4K service IPs
Node subnetauto-created/20 recommended for growth
Max pods/node48Each node gets a /25 pod range; set to 110
: : : for /24 per node :

Pod CIDR sizing rule of thumb:

  • maxPodsPerNode=48 -> each node uses a /25 (128 IPs) from pod CIDR
  • maxPodsPerNode=110 -> each node uses a /24 (256 IPs) from pod CIDR
  • Larger maxPodsPerNode = fewer nodes fit in a given CIDR

Egress

  • Default: nodes use Cloud NAT for outbound internet access (private nodes have no public IPs) to allow private nodes to reach the internet without public IP exposure.
  • For static egress IPs: configure Cloud NAT with manual IP allocation to maintain a consistent source IP for external allowlists or partner firewalls.
  • For restricted egress: route through a firewall appliance via custom routes to inspect and filter outbound traffic according to organization security policies.

Network Policy

Dataplane V2 (golden path) provides built-in Network Policy enforcement — no additional addon needed. Apply default-deny per namespace, then allow specific flows.

See the gke-workload-security skill for default-deny policy and the gke-multitenancy skill for per-team allow policies.

Frequently asked questions

What does the Gke Networking AI skill do?

Plans, configures, and manages core GKE cluster networking. Covers private clusters, VPC-native configurations, DNS, node egress, Dataplane V2, and IP planning. Use when designing GKE networking layouts, configuring private clusters, setting up Dataplane V2, planning GKE IP ranges, or managing VPC- native cluster modes. Don't use for application ingress, load balancing, or service networking (use gke-service-networking instead).

Why use Gke Networking on TypingMind?

Because you install it once and use it with any model. Gke Networking is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Gke Networking in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/google/skills/tree/main/skills/cloud/gke-networking. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Gke Networking?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Gke Networking?

As many as you like. As long as a model supports skills, you can use Gke Networking with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Gke Networking AI skill free?

Yes. It is published on GitHub by google under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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