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Kubesphere Gateway Api

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kubesphere
kubesphere-gateway-api

KubeSphere Gateway API extension management Skill (Traefik based, uses Kubernetes Gateway API + GatewayProxy CRD gatewayapi.kubesphere.io/v1alpha1). This is the newer Kubernetes Gateway API standard. For the older Ingress API based gateway (ingress-nginx + Gateway CRD gateway.kubesphere.io/v2alpha2), see the kubesphere-gateway skill instead. Covers installation, uninstallation, status checks, GatewayProxy status inspection, and troubleshooting.

Overview

Publisherkubesphere
Repositorykubesphere
Skill namekubesphere-gateway-api
Stars
17.1K
Forks
2.8K
Bundled files
3
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.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Kubesphere Gateway Api 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.
  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/kubesphere/kubesphere.git /tmp/kubesphere
mkdir -p .claude/skills
cp -r /tmp/kubesphere/skills/kubesphere-gateway-api .claude/skills/kubesphere-gateway-api
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Kubesphere Gateway Api 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 Kubesphere Gateway Api 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 Kubesphere Gateway Api 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.

KubeSphere Gateway API

Overview

Provides external access management using Kubernetes Gateway API with Traefik as the underlying proxy implementation. Supports three-tier gatewayproxy management:

TierScopeName PatternNamespaceDescription
ClusterEntire clustergatewayproxy-clusterkubesphere-controls-systemCluster-scoped GatewayProxy
WorkspaceSingle workspacegatewayproxy-workspace-{workspace}kubesphere-controls-systemWorkspace-scoped GatewayProxy
ProjectSingle project/namespacegatewayproxy-namespace-{namespace}kubesphere-controls-systemNamespace-scoped GatewayProxy

Each GatewayProxy (gatewayproxies.gatewayapi.kubesphere.io) deploys a Traefik instance (the proxy implementation). It auto-creates a GatewayClass, and users can then create standard Gateway (gateways.gateway.networking.k8s.io) resources that reference that GatewayClass. The extension consists of three components:

  • backend-extension — API server on the host cluster
  • backend-agent — API server + controller-manager on every cluster (including the host cluster if selected)
  • frontend — React SPA served via Nginx

Key Differentiator from kubesphere-gateway

Aspectkubesphere-gatewaykubesphere-gateway-api
Underlying proxyingress-nginxTraefik
API standardCustom Gateway CRD (gateway.kubesphere.io/v2alpha2)Kubernetes Gateway API (gateway.networking.k8s.io) + GatewayProxy CRD
Core resourceGateway + standard IngressClass/IngressGatewayProxy + standard Gateway/GatewayClass/HTTPRoute
Lifecycle managementHelm release per gatewayHelm release per GatewayProxy

Core CRDs

  • GatewayProxy (gatewayapi.kubesphere.io/v1alpha1) — the proxy implementation (e.g. Traefik). When created, the controller deploys Traefik via Helm SDK and auto-creates a GatewayClass. Key fields:

    • spec.type — proxy type (currently only Traefik)
    • spec.traefik.rawValues — raw Helm values passed to the Traefik chart
    • spec.traefik.deployment.replicas — replica count
    • spec.traefik.service.type — Service type (ClusterIP, NodePort, LoadBalancer)
    • spec.traefik.createDefaultGateway — whether to auto-create a default Gateway
    • spec.paused — pause reconciliation
    • status.conditions — condition types: Ready, Progressing, NewVersionDetected
    • status.service — Service type, ports, external IPs, load balancer status
    • status.entrypoints — exposed entrypoints with ports and protocols
    • status.gatewayClass.name — auto-created GatewayClass name
    • status.helmRelease.name — Helm release name
  • GatewayClass (gateway.networking.k8s.io/v1) — standard Kubernetes Gateway API class, auto-created by the GatewayProxy controller

  • Gateway (gateway.networking.k8s.io/v1) — standard Kubernetes Gateway API gateway, associated with a GatewayClass

  • HTTPRoute / GRPCRoute / TLSRoute / TCPRoute / UDPRoute — standard Kubernetes Gateway API route resources

Multi-Tenant Scoping

GatewayProxy and Gateway are scoped via labels:

  • gatewayapi.kubesphere.io/scope-typecluster, workspace, or namespace
  • gatewayapi.kubesphere.io/scope-workspace — workspace name (for workspace scope)
  • gatewayapi.kubesphere.io/scope-namespace — namespace name (for namespace scope)

Monitoring Integration

GatewayProxy exposes Traefik metrics via Prometheus. Requires the whizard-monitoring extension (optional dependency). Log search requires the whizard-logging extension.


Before You Start

Check if Gateway API extension is already installed:

bash
kubectl get installplans.kubesphere.io gateway-api --ignore-not-found

If found, upgrading is supported — just select a newer version in Step 1.


Installation

Step 1: Detect and Select Version

bash
ALL_VERSIONS=$(kubectl get extensionversions.kubesphere.io \
  -l kubesphere.io/extension-ref=gateway-api \
  -o jsonpath='{range .items[*]}{.spec.version}{"\n"}{end}' | sort -V)

LATEST_STABLE=$(echo "$ALL_VERSIONS" | grep -v -E 'alpha|beta|rc' | tail -1)
if [ -z "$LATEST_STABLE" ]; then
  LATEST_STABLE=$(echo "$ALL_VERSIONS" | tail -1)
fi

echo "Available versions:"
echo "$ALL_VERSIONS"
echo ""
echo "Latest stable: $LATEST_STABLE"

This sets ALL_VERSIONS and LATEST_STABLE. Use SELECTED_VERSION for the version chosen.

Use the question tool:

  • $LATEST_STABLE (Recommended) — accept the auto-detected version
  • (custom) — type a specific version; validate it against the printed list

Step 2: Detect and Select Clusters

bash
CLUSTER_DATA=$(kubectl get clusters.cluster.kubesphere.io \
  -o jsonpath='{range .items[*]}{.metadata.name}{"\t"}{.status.conditions[?(@.type=="Ready")].status}{"\n"}{end}')

READY_CLUSTERS=$(echo "$CLUSTER_DATA" | awk -F'\t' '$2 == "True" {print $1}')
CLUSTER_COUNT=$(echo "$READY_CLUSTERS" | wc -l)

HOST_CLUSTER=$(kubectl get clusters.cluster.kubesphere.io \
  -l 'cluster-role.kubesphere.io/host' \
  -o jsonpath='{.items[0].metadata.name}' || echo "")

echo "Ready clusters:"
echo "$READY_CLUSTERS"
echo ""
echo "Cluster count: $CLUSTER_COUNT"
echo "Host cluster: $HOST_CLUSTER"

This sets READY_CLUSTERS, CLUSTER_COUNT, HOST_CLUSTER.

  • 1 cluster → skip selection, auto-use it. Set TARGET_CLUSTERS="$HOST_CLUSTER"
  • Multiple clusters → use question with multiple: true:
    • All clustersTARGET_CLUSTERS="$READY_CLUSTERS"
    • Host cluster onlyTARGET_CLUSTERS="$HOST_CLUSTER"
    • (custom) — validate each name against $READY_CLUSTERS

Step 3: Generate and Apply InstallPlan

bash
./scripts/generate-installplan.sh "$SELECTED_VERSION" "$TARGET_CLUSTERS"

This generates the YAML to /tmp/gateway-api-installplan.yaml, runs --dry-run=server, then prints the apply command.

Apply it:

bash
kubectl apply -f /tmp/gateway-api-installplan.yaml

Tell the user "Installing". Then ask if they want to check status. If yes:

bash
./scripts/check-status.sh poll

Status Checking

PurposeCommand
Single snapshot./scripts/check-status.sh quick
Wait until complete (5min timeout)./scripts/check-status.sh poll

Logic:

  • All Installed → ✓ success
  • Any Failed → ✗ prints full status
  • Timeout (300s) → ⚠ prints current status
  • In progress → prints every 10s

Uninstallation

Always confirm with the user before proceeding.

Uninstall from all clusters

bash
if ! kubectl get installplans.kubesphere.io gateway-api &>/dev/null; then
  echo "Gateway API is not installed."
  exit 0
fi

Confirm with the user, then delete:

bash
kubectl delete installplans.kubesphere.io gateway-api --ignore-not-found

Verify cleanup:

bash
./scripts/verify-uninstall.sh

Success criteria:

  1. InstallPlan is deleted
  2. No active pods remain in extension-gateway-api namespace

Uninstall from specific clusters

WARNING: Do NOT delete the InstallPlan. Only remove target clusters from the placement list.

Confirm which clusters to remove, compute remaining clusters, then patch:

bash
kubectl patch installplans.kubesphere.io gateway-api --type='json' \
  -p='[{"op": "replace", "path": "/spec/clusterScheduling/placement/clusters", "value": ["<REMAINING_CLUSTER_1>", "<REMAINING_CLUSTER_2>"]}]'

Success: patch returns OK + removed clusters no longer in .status.clusterSchedulingStatuses.


GatewayProxy Operations

List GatewayProxies

GatewayProxies are organized by scope type. List them:

bash
echo "=== Cluster GatewayProxies ==="
kubectl get gatewayproxies.gatewayapi.kubesphere.io -A \
  -l gatewayapi.kubesphere.io/scope-type=cluster

echo -e "\n=== Workspace GatewayProxies ==="
kubectl get gatewayproxies.gatewayapi.kubesphere.io -A \
  -l gatewayapi.kubesphere.io/scope-type=workspace

echo -e "\n=== Namespace GatewayProxies ==="
kubectl get gatewayproxies.gatewayapi.kubesphere.io -A \
  -l gatewayapi.kubesphere.io/scope-type=namespace

Check GatewayProxy Status

Pick a gateway proxy name from the list above and run:

bash
GWP_NS="kubesphere-controls-system"
GWP_NAME="<gatewayproxy-name-from-list>"

# app.kubernetes.io/instance uses the Helm release name if available, otherwise the GatewayProxy name
GWP_INSTANCE=$(kubectl get gatewayproxies.gatewayapi.kubesphere.io -n $GWP_NS $GWP_NAME -o jsonpath='{.status.helmRelease.name}' 2>/dev/null)
if [ -z "$GWP_INSTANCE" ]; then
  GWP_INSTANCE="$GWP_NAME"
fi

kubectl get gatewayproxies.gatewayapi.kubesphere.io -n $GWP_NS $GWP_NAME -o wide
kubectl describe gatewayproxies.gatewayapi.kubesphere.io -n $GWP_NS $GWP_NAME
kubectl get gatewayproxies.gatewayapi.kubesphere.io -n $GWP_NS $GWP_NAME -o yaml
kubectl get pods -n $GWP_NS -l "app.kubernetes.io/instance=$GWP_INSTANCE"

GatewayProxy conditions:

Condition TypeStatus TrueMeaning
ReadyTrueFully operational
ProgressingTrueBeing created or updated
NewVersionDetectedTrueNew chart version available

List Associated Gateways

Each GatewayProxy may have associated standard Gateways and GatewayClasses. The GatewayProxy creates GatewayClasses with the label gatewayapi.kubesphere.io/gateway-class-name, and auto-created Gateways carry scope labels:

bash
# List GatewayClasses created by any GatewayProxy
kubectl get gatewayclass -l "gatewayapi.kubesphere.io/gateway-class-name"

# List Gateways associated with a specific GatewayProxy (by scope label)
kubectl get gateways.gateway.networking.k8s.io -n $GWP_NS \
  -l "gatewayapi.kubesphere.io/scope-type"

# Alternatively, list Gateways by the GatewayClass name they reference
GW_CLASS=$(kubectl get gatewayproxies.gatewayapi.kubesphere.io -n $GWP_NS $GWP_NAME \
  -o jsonpath='{.status.gatewayClass.name}')
kubectl get gateways.gateway.networking.k8s.io -A \
  -o jsonpath='{range .items[?(@.spec.gatewayClassName=="'"$GW_CLASS"'")]}{.metadata.namespace}{"\t"}{.metadata.name}{"\t"}{.spec.gatewayClassName}{"\n"}{end}'

View GatewayProxy Pods and Logs

bash
kubectl get pods -n $GWP_NS -l "app.kubernetes.io/instance=$GWP_INSTANCE"
kubectl logs -n $GWP_NS -l "app.kubernetes.io/instance=$GWP_INSTANCE" --tail=100

Troubleshooting

Set $GWP_NAME and $GWP_NS to the target GatewayProxy name and namespace (kubesphere-controls-system for all tiers). $GWP_INSTANCE is auto-resolved from status.helmRelease.name (falls back to $GWP_NAME).

GatewayProxy stuck in Progressing state

bash
kubectl describe gatewayproxies.gatewayapi.kubesphere.io -n $GWP_NS $GWP_NAME

kubectl logs -n extension-gateway-api -l app=gateway-api-controller-manager --tail=200 | grep -iE "(error|helm|install|upgrade|reconcile)"

kubectl get pods -n $GWP_NS -l "app.kubernetes.io/instance=$GWP_INSTANCE"

Common causes: Helm chart not found, invalid rawValues, Traefik image pull failure, Helm SDK timeout.

GatewayProxy shows Ready=False state

bash
kubectl describe gatewayproxies.gatewayapi.kubesphere.io -n $GWP_NS $GWP_NAME

kubectl get deployment -n $GWP_NS -l "app.kubernetes.io/instance=$GWP_INSTANCE" -o wide
kubectl describe deployment -n $GWP_NS -l "app.kubernetes.io/instance=$GWP_INSTANCE"
kubectl get pods -n $GWP_NS -l "app.kubernetes.io/instance=$GWP_INSTANCE" -o wide

POD_NAME=$(kubectl get pods -n $GWP_NS -l "app.kubernetes.io/instance=$GWP_INSTANCE" -o jsonpath='{.items[0].metadata.name}')
kubectl describe pod -n $GWP_NS $POD_NAME
kubectl logs -n $GWP_NS $POD_NAME --tail=100

Common causes: Image pull failure, resource constraints, port conflicts, missing ConfigMap/Secret, Helm release abnormal.

GatewayProxy pod crash-looping / CrashLoopBackOff

bash
kubectl logs -n $GWP_NS -l "app.kubernetes.io/instance=$GWP_INSTANCE" --tail=100 --previous
kubectl get events -n $GWP_NS --sort-by='.lastTimestamp' | tail -20
kubectl exec -n $GWP_NS -l "app.kubernetes.io/instance=$GWP_INSTANCE" -- cat /etc/traefik/traefik.yaml 2>/dev/null | head -50
kubectl get configmap -n $GWP_NS -l "app.kubernetes.io/instance=$GWP_INSTANCE" -o yaml

Common causes: Misconfigured Traefik config, port conflicts, resource limits (OOMKilled), missing dependencies (ConfigMap/Secret).

Controller not reconciling

bash
kubectl get pods -n extension-gateway-api -l app=gateway-api-controller-manager
kubectl logs -n extension-gateway-api -l app=gateway-api-controller-manager --tail=200
kubectl get validatingwebhookconfiguration -l "app.kubernetes.io/managed-by=Helm,kubesphere.io/extension-ref=gateway-api"
kubectl get deployment -n extension-gateway-api -l app=gateway-api-controller-manager -o yaml

Common causes: Controller pod not running, webhook configuration blocking updates, Helm release state mismatch, RBAC permission issues.

Log search / metrics not working

GatewayProxy observability proxies to whizard-telemetry-apiserver:

bash
kubectl get pods -n extension-whizard-telemetry
kubectl get svc -n extension-whizard-telemetry whizard-telemetry-apiserver
kubectl logs -n extension-gateway-api -l app=gateway-api-apiserver --tail=100 | grep -iE "(log|search|whizard|proxy|metric)"

Common causes: Whizard-telemetry not installed or not running, network policy blocking cross-namespace traffic.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Kubesphere Gateway Api AI skill do?

KubeSphere Gateway API extension management Skill (Traefik based, uses Kubernetes Gateway API + GatewayProxy CRD gatewayapi.kubesphere.io/v1alpha1). This is the newer Kubernetes Gateway API standard. For the older Ingress API based gateway (ingress-nginx + Gateway CRD gateway.kubesphere.io/v2alpha2), see the kubesphere-gateway skill instead. Covers installation, uninstallation, status checks, GatewayProxy status inspection, and troubleshooting.

Why use Kubesphere Gateway Api on TypingMind?

Because you install it once and use it with any model. Kubesphere Gateway Api 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 Kubesphere Gateway Api in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kubesphere/kubesphere/tree/master/skills/kubesphere-gateway-api. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Kubesphere Gateway Api?

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 Kubesphere Gateway Api?

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

Is the Kubesphere Gateway Api AI skill free?

It is published on GitHub by kubesphere. Check the repository for licensing terms. 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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