# Operate GKE Clusters with Expert Guidance

GKE operations can be complex across deployment, scaling, identity, and troubleshooting. This skill provides practical workflows, commands, and production patterns for reliable GKE management.

## Install

```bash
npx skillstore add adminturneddevops/gke-expert
```

## Metadata

- Status: approved
- Slug: adminturneddevops-gke-expert
- Skillstore revision: r1
- Version status: missing
- Tree hash: 87247740a85f3fe3086f948de223410b23894b93fe51d639deafb3de742d8de1
- Author: AdminTurnedDevOps
- GitHub username: AdminTurnedDevOps
- License: MIT
- Repository: https://github.com/AdminTurnedDevOps/agentic-demo-repo/tree/main/agentregistry/gke-expert/gke-expert/skills/gke-expert
- Ref: d46e62089a6dfc9e14ea02eebd9b8e2ad2dfe1f4
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: external\_commands, network
- Quality score: 75
- Public page: https://skillstore.pages.dev/skills/adminturneddevops-gke-expert
- Manifest: https://skillstore.pages.dev/api/skills/adminturneddevops-gke-expert/manifest

## Capabilities

- Provides GKE cluster creation workflows for Autopilot and Standard modes.
- Outlines deployment, service exposure, and autoscaling steps.
- Guides Workload Identity setup between Kubernetes and Google service accounts.
- Lists troubleshooting checks for pods, services, resources, logs, and events.
- Summarizes production patterns for ingress, disruption budgets, security context, and cost optimization.

## Use Cases

- Launch a GKE workload: Plan a cluster, deploy a container, expose a service, and verify the rollout.
- Troubleshoot Kubernetes failures: Investigate pod, service, event, and resource issues with focused GKE checks.
- Improve GKE security and cost: Apply Workload Identity, security contexts, autoscaling, and cost controls to a cluster.

## Prompt Templates

### Create a Basic Cluster Plan

```
Help me choose between GKE Autopilot and Standard for a small web service. Include the main commands and assumptions.
```

### Deploy and Expose an App

```
Create a GKE deployment plan for my container image. Include resource limits, service exposure, and verification steps.
```

### Diagnose Production Issues

```
Guide me through troubleshooting a GKE service with failing pods and no endpoints. Ask for missing context before recommending commands.
```

### Design a Secure GKE Platform

```
Review my GKE production design for Workload Identity, ingress, autoscaling, disruption budgets, and cost controls.
```

## Limitations

- Does not authenticate to Google Cloud or run commands for the user.
- Does not replace environment-specific review before production changes.
- Uses placeholder names that users must adapt to their clusters.
- May not cover every GKE feature or organization policy.

## Best Practices

- Confirm cluster type, environment, and risk before changing GKE resources.
- Replace placeholders with reviewed project, cluster, namespace, and service names.
- Use Workload Identity and least privilege instead of static credentials.

## Anti Patterns

- Running copied commands against production without checking context and namespace.
- Using broad cleanup commands without labels, backups, or rollback plans.
- Skipping resource requests, limits, and autoscaling configuration.

## Security Audit

- Audited at: 2026-07-07T19:10:00.289\+00:00
- Summary: The static findings are documentation examples, not executable code. The kubectl exec command uses a placeholder for interactive debugging, and the URLs point to official public documentation. No prompt injection, data exfiltration intent, or hidden unsafe behavior was found in the reviewed files.

## Stats

- Views: 173
- Downloads: 10
- Favorites: 0
- Popularity score: 0