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Gcp Networking

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BagelHole
gcp-networking

Configure VPCs, firewall rules, and Cloud NAT. Implement shared VPC and private service connect. Use when designing GCP network infrastructure.

Overview

PublisherBagelHole
RepositoryDevOps-Security-Agent-Skills
Skill namegcp-networking
Stars
1.1K
Forks
161
Bundled files
Instructions only
LicenseMIT
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 BagelHole on GitHub. Read the source before you install it.

Installation

Install the Gcp 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/BagelHole/DevOps-Security-Agent-Skills/tree/main/infrastructure/cloud-gcp/gcp-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/BagelHole/DevOps-Security-Agent-Skills.git /tmp/DevOps-Security-Agent-Skills
mkdir -p .claude/skills
cp -r /tmp/DevOps-Security-Agent-Skills/infrastructure/cloud-gcp/gcp-networking .claude/skills/gcp-networking
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gcp 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 Gcp 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 Gcp 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.

GCP Networking

Design, implement, and secure network infrastructure on Google Cloud Platform.

When to Use

  • Building VPC networks for new GCP projects or multi-project architectures
  • Configuring firewall rules to control traffic between services
  • Setting up Cloud NAT for outbound internet access from private instances
  • Deploying load balancers for HTTP(S), TCP/UDP, or internal traffic
  • Implementing Private Service Connect or Shared VPC

Prerequisites

  • Google Cloud SDK (gcloud) installed and authenticated
  • Compute Engine API enabled
  • IAM role roles/compute.networkAdmin for network management
bash
gcloud services enable compute.googleapis.com servicenetworking.googleapis.com

VPC Network Creation

bash
gcloud compute networks create prod-vpc \
  --subnet-mode=custom --bgp-routing-mode=regional --mtu=1460

gcloud compute networks subnets create us-subnet \
  --network=prod-vpc --region=us-central1 --range=10.0.0.0/20 \
  --enable-private-ip-google-access --enable-flow-logs \
  --logging-flow-sampling=0.5

gcloud compute networks subnets create eu-subnet \
  --network=prod-vpc --region=europe-west1 --range=10.1.0.0/20 \
  --enable-private-ip-google-access --enable-flow-logs

# Subnet with secondary ranges for GKE
gcloud compute networks subnets create gke-subnet \
  --network=prod-vpc --region=us-central1 --range=10.2.0.0/20 \
  --secondary-range=pods=10.4.0.0/14,services=10.8.0.0/20 \
  --enable-private-ip-google-access

# Proxy-only subnet (required for regional L7 LBs)
gcloud compute networks subnets create proxy-only-subnet \
  --network=prod-vpc --region=us-central1 --range=10.129.0.0/23 \
  --purpose=REGIONAL_MANAGED_PROXY --role=ACTIVE

Firewall Rules

bash
gcloud compute firewall-rules create allow-http-https \
  --network=prod-vpc --allow=tcp:80,tcp:443 \
  --source-ranges=0.0.0.0/0 --target-tags=http-server --priority=1000

gcloud compute firewall-rules create allow-internal \
  --network=prod-vpc --allow=tcp,udp,icmp \
  --source-ranges=10.0.0.0/8 --priority=1000

gcloud compute firewall-rules create allow-iap-ssh \
  --network=prod-vpc --allow=tcp:22 \
  --source-ranges=35.235.240.0/20 --priority=1000

gcloud compute firewall-rules create allow-health-checks \
  --network=prod-vpc --allow=tcp:80,tcp:443,tcp:8080 \
  --source-ranges=130.211.0.0/22,35.191.0.0/16 \
  --target-tags=http-server --priority=900

# List firewall rules
gcloud compute firewall-rules list --filter="network=prod-vpc" \
  --format="table(name,direction,priority,allowed[].map().firewall_rule().list():label=ALLOW)"

Cloud NAT

bash
gcloud compute routers create prod-router \
  --network=prod-vpc --region=us-central1

gcloud compute routers nats create prod-nat \
  --router=prod-router --region=us-central1 \
  --nat-all-subnet-ip-ranges --auto-allocate-nat-external-ips \
  --min-ports-per-vm=256 --max-ports-per-vm=4096 \
  --enable-logging --log-filter=ERRORS_ONLY

# Static NAT IPs (stable egress)
gcloud compute addresses create nat-ip-1 nat-ip-2 --region=us-central1
gcloud compute routers nats create prod-nat-static \
  --router=prod-router --region=us-central1 \
  --nat-all-subnet-ip-ranges --nat-external-ip-pool=nat-ip-1,nat-ip-2

External HTTP(S) Load Balancer

bash
gcloud compute addresses create web-lb-ip --global

gcloud compute health-checks create http web-hc \
  --port=80 --request-path=/healthz --check-interval=10s --timeout=5s

gcloud compute backend-services create web-backend \
  --protocol=HTTP --port-name=http --health-checks=web-hc \
  --global --enable-cdn --enable-logging

gcloud compute backend-services add-backend web-backend \
  --instance-group=web-mig --instance-group-region=us-central1 \
  --balancing-mode=UTILIZATION --max-utilization=0.8 --global

gcloud compute url-maps create web-url-map --default-service=web-backend

gcloud compute ssl-certificates create web-cert \
  --domains=app.example.com --global

gcloud compute target-https-proxies create web-proxy \
  --url-map=web-url-map --ssl-certificates=web-cert

gcloud compute forwarding-rules create web-https \
  --address=web-lb-ip --target-https-proxy=web-proxy --ports=443 --global

Internal Load Balancer

bash
gcloud compute backend-services create internal-backend \
  --protocol=TCP --region=us-central1 \
  --health-checks=web-hc --health-checks-region=us-central1 \
  --load-balancing-scheme=INTERNAL

gcloud compute forwarding-rules create internal-lb \
  --region=us-central1 --load-balancing-scheme=INTERNAL \
  --network=prod-vpc --subnet=us-subnet \
  --backend-service=internal-backend --ports=8080

Cloud Armor (DDoS and WAF)

bash
gcloud compute security-policies create web-armor

gcloud compute security-policies rules create 1000 \
  --security-policy=web-armor \
  --expression="origin.region_code == 'XX'" --action=deny-403

gcloud compute security-policies rules create 2000 \
  --security-policy=web-armor --expression="true" \
  --action=rate-based-ban \
  --rate-limit-threshold-count=100 \
  --rate-limit-threshold-interval-sec=60 --ban-duration-sec=600

gcloud compute backend-services update web-backend \
  --security-policy=web-armor --global

Private Service Connect

bash
gcloud compute addresses create psc-google-apis \
  --global --purpose=PRIVATE_SERVICE_CONNECT \
  --addresses=10.255.255.254 --network=prod-vpc

gcloud compute forwarding-rules create psc-google-apis \
  --global --network=prod-vpc --address=psc-google-apis \
  --target-google-apis-bundle=all-apis

Shared VPC

bash
gcloud compute shared-vpc enable $HOST_PROJECT_ID
gcloud compute shared-vpc associated-projects add $SERVICE_PROJECT_ID \
  --host-project=$HOST_PROJECT_ID

Terraform Configuration

hcl
resource "google_compute_network" "vpc" {
  name                    = "prod-vpc"
  auto_create_subnetworks = false
  routing_mode            = "REGIONAL"
}

resource "google_compute_subnetwork" "us" {
  name                     = "us-subnet"
  ip_cidr_range            = "10.0.0.0/20"
  region                   = "us-central1"
  network                  = google_compute_network.vpc.id
  private_ip_google_access = true
  log_config { aggregation_interval = "INTERVAL_5_SEC"; flow_sampling = 0.5 }
}

resource "google_compute_firewall" "allow_http" {
  name    = "allow-http-https"
  network = google_compute_network.vpc.name
  allow { protocol = "tcp"; ports = ["80", "443"] }
  source_ranges = ["0.0.0.0/0"]
  target_tags   = ["http-server"]
}

resource "google_compute_firewall" "allow_iap" {
  name    = "allow-iap-ssh"
  network = google_compute_network.vpc.name
  allow { protocol = "tcp"; ports = ["22"] }
  source_ranges = ["35.235.240.0/20"]
}

resource "google_compute_router" "router" {
  name    = "prod-router"
  region  = "us-central1"
  network = google_compute_network.vpc.id
}

resource "google_compute_router_nat" "nat" {
  name                               = "prod-nat"
  router                             = google_compute_router.router.name
  region                             = "us-central1"
  nat_ip_allocate_option             = "AUTO_ONLY"
  source_subnetwork_ip_ranges_to_nat = "ALL_SUBNETWORKS_ALL_IP_RANGES"
  min_ports_per_vm                   = 256
  log_config { enable = true; filter = "ERRORS_ONLY" }
}

resource "google_compute_security_policy" "waf" {
  name = "web-armor"
  rule {
    action   = "deny(403)"
    priority = 1000
    match { expr { expression = "evaluatePreconfiguredExpr('xss-v33-stable')" } }
  }
  rule {
    action   = "allow"
    priority = 2147483647
    match { versioned_expr = "SRC_IPS_V1"; config { src_ip_ranges = ["*"] } }
  }
}

Common Operations

bash
gcloud compute networks list
gcloud compute networks subnets list --network=prod-vpc
gcloud compute networks subnets describe us-subnet --region=us-central1
gcloud network-management connectivity-tests create test-web-to-db \
  --source-instance=projects/${PROJECT_ID}/zones/us-central1-a/instances/web \
  --destination-instance=projects/${PROJECT_ID}/zones/us-central1-a/instances/db \
  --destination-port=5432 --protocol=TCP

Troubleshooting

SymptomCauseFix
Instance cannot reach internetNo external IP and no Cloud NATConfigure Cloud NAT on the subnet's router
Firewall rule not taking effectWrong target tags or priorityVerify tags match instance; check priority ordering
Load balancer returns 502Backend failing health checksCheck health check path/port; allow 130.211.0.0/22, 35.191.0.0/16
Cannot reach Google APIs from private VMPrivate Google Access disabledEnable --enable-private-ip-google-access on subnet
Cloud NAT port exhaustionToo many connections per VMIncrease --min-ports-per-vm; enable dynamic port allocation
Shared VPC project cannot create VMsMissing compute.networkUser roleGrant roles/compute.networkUser on host project
SSL cert stuck PROVISIONINGDNS not pointing to LB IPUpdate A record to reserved static IP; wait up to 60 min

Related Skills

  • gcp-compute - Compute Engine instances that use VPC networks and firewall rules
  • gcp-gke - GKE clusters deployed in VPC subnets with secondary ranges
  • gcp-cloud-sql - Private IP database connectivity through VPC peering
  • terraform-gcp - Provision networking resources with Infrastructure as Code

Frequently asked questions

What does the Gcp Networking AI skill do?

Configure VPCs, firewall rules, and Cloud NAT. Implement shared VPC and private service connect. Use when designing GCP network infrastructure.

Why use Gcp Networking on TypingMind?

Because you install it once and use it with any model. Gcp 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 Gcp Networking in TypingMind?

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

Which AI models can use Gcp 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 Gcp Networking?

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

Is the Gcp Networking AI skill free?

Yes. It is published on GitHub by BagelHole under the MIT 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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