Agent skill · operations · aiskillstore
gke-expert
Expert guidance for Google Kubernetes Engine (GKE) operations including cluster management, workload deployment, scaling, monitoring, troubleshooting, and optimization. Use when working with GKE clusters, Kubernetes deployments on GCP, container orchestration, or when users need help with kubectl commands, GKE networking, autoscaling, workload identity, or GKE-specific features like Autopilot, Binary Authorization, or Config Sync.
Why this skill is useful
Adds executable scripts and detailed workflows for managing GKE clusters that aren't commonly found in public documentation.
What it needs
Requires gcloud, kubectl installed locally. Requires google-cloud account access. About 3k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
GKE Expert Initial Assessment When user requests GKE help, determine: Cluster type: Autopilot or Standard? Task: Create, Deploy, Scale, Troubleshoot, or Optimize? Environment: Dev, Staging, or Production? Quick Start Workflows Create Cluster Autopilot (recommended for most): bashgcloud container clusters create-auto CLUSTERNAME \ --region=REGION \ --release-channel=regular Standard (for specific node requirements): bashgcloud container clusters create CLUSTERNAME \ --zone=ZONE \ --num-nodes=3 \ --enable-autoscaling \ --min-nodes=2 \ --max-nodes=10 Always authenticate after creation: bashgcloud container clusters get-credentials CLUSTERNAME --region=REGION Deploy Application Create deployment manifest: yamlapiVersion: apps/v1 kind: Deployment metadata: name: APPNAME spec: replicas: 3 selector: matchLabels: app: APPNAME template: metadata: labels: app: APPNAME spec: containers: name: APPNAME image: gcr.io/PROJECTID/IMAGE:TAG ports: containerPort: 8080 resources: requests: cpu: 100m memory: 128Mi limits: cpu: 500m memory: 512Mi Apply and expose: bashkubectl apply -f deployment.yaml kubectl expose deployment APPNAME --type=LoadBalancer --port=80 --target-port=8080 Setup Autoscaling HPA for pods: bashkubectl autoscale deployment APPNAME --cpu-percent=70 --min=2 --max=100 Cluster autoscaling (Standard only): bashgcloud container clusters update CLUSTERNAME \ --enable-autoscaling --min-nodes=2 --max-nodes=10 --zone=ZONE Configure Workload Identity Enable on cluster: bashgcloud container clusters update CLUSTERNAME \ --workload-pool=PROJECTID.svc.id.goog Link service accounts: bash# Create GCP service account gcloud iam service-accounts create GSANAME Create K8s service account kubectl create serviceaccount KSANAME Bind them gcloud iam service-accounts add-iam-policy-binding \ GSANAME@PROJECTID.iam.gserviceaccount.com \ --role roles/iam.workloadIdentityUser \ --member "serviceAccount:PROJECTID.svc.id.goog[default/KSANAME]" Annotate K8s SA kubectl annotate serviceaccount KSA …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/gke-expert