Agent Skillsgoogle/skills › gke-productionize

gke-productionize

GitHub

作为GKE生产就绪的元技能,协调对集群和负载的可扩展性、安全性、可靠性等维度的评估。通过发现当前状态并调用专用子技能,指导用户完成从测试到生产环境的全面准备与审计。

skills/cloud/gke-productionize/SKILL.md google/skills

Trigger Scenarios

需要对GKE集群或应用进行上线前的生产就绪评估 请求审查、审核或准备GKE环境以投入生产

Install

npx skills add google/skills --skill gke-productionize -g -y
More Options

Non-standard path

npx skills add https://github.com/google/skills/tree/main/skills/cloud/gke-productionize -g -y

Use without installing

npx skills use google/skills@gke-productionize

指定 Agent (Claude Code)

npx skills add google/skills --skill gke-productionize -a claude-code -g -y

安装 repo 全部 skill

npx skills add google/skills --all -g -y

预览 repo 内 skill

npx skills add google/skills --list

SKILL.md

Frontmatter
{
    "name": "gke-productionize",
    "metadata": {
        "category": "Containers"
    },
    "description": "Orchestrates comprehensive production readiness reviews and assessments for GKE clusters and workloads across scalability, security, reliability, observability, backup\/DR, and cost optimization. Use when asked to productionize, prepare, assess, audit, or review a GKE cluster or workload before going live to production. Don't use for deep-dive single-domain implementation (use specific domain skills like gke-scaling, gke-platform-security, gke-workload-security, gke-service-networking, gke-reliability instead)."
}

GKE Productionize Skill

This skill acts as a high-level orchestrator for preparing a GKE cluster and its workloads for production readiness.

[!IMPORTANT] This is a meta-skill or orchestrator skill. You are expected to invoke and run many other specialized skills listed in this document as part of the overall productionization process. Do not attempt to implement all production readiness features directly within this skill; instead, use this skill to assess the environment and then delegate to the specific skills for each domain.

Scope

This skill is adaptable to:

  • A single application (already on Kubernetes or not).
  • A set of applications.
  • A target cluster.

Workflow

1. Discovery Phase

Before making recommendations, discover the current state of the environment.

Cluster Discovery

Run these commands to understand the cluster setup:

  • Check cluster details: gcloud container clusters describe {cluster_name} --location {location} --project {project}
  • Check for Autopilot vs Standard: Look for autopilot: true in the describe output.
  • Check release channel: Look for releaseChannel.

Workload Discovery

If a specific application is targeted, discover its configuration:

  • Get deployment/statefulset details: kubectl get deployment {app_name} -n {namespace} -o yaml
  • Check for dedicated namespace and labels: kubectl get namespace {namespace} -o yaml (Look for Pod Security Standards labels).
  • Check for dedicated service account usage: kubectl get pods -n {namespace} -o custom-columns="NAME:.metadata.name,SERVICE_ACCOUNT:.spec.serviceAccountName"
  • Check for resource requests and limits.
  • Check for liveness, readiness, and startup probes.
  • Check for HPA: kubectl get hpa -n {namespace}
  • Check for PDB: kubectl get pdb -n {namespace}
  • Check for NetworkPolicies: kubectl get networkpolicy -n {namespace}

2. Production Readiness Assessment

Before implementation, you MUST run the skills for each relevant specialized area listed below and incorporate its guidance into your assessment and plan. Failure to do so will result in a non-compliant production configuration.

A. App Onboarding (Pre-Kubernetes)

If the application is not yet running on GKE, you MUST run the gke-app-onboarding skill for planning containerization, image building, and basic deployment.

B. Scalability & Resource Management

Ensure workloads have appropriate resources and autoscaling.

  • Action: You MUST run the gke-workload-scaling skill for configuring HPA, VPA, and resource limits.

C. Observability

Ensure adequate logging and monitoring are in place.

  • Action: You MUST run the gke-observability skill for setting up Cloud Logging, Monitoring, and Managed Prometheus.

D. Reliability

Ensure high availability and graceful degradation.

  • Action: You MUST run the gke-reliability skill for configuring regional clusters, PDBs, and health probes.

E. Security

Harden the cluster and workloads.

  • Action: You MUST run the gke-platform-security and gke-workload-security skills for Workload Identity, Network Policies, and Shielded Nodes.
  • Namespace Isolation: Ensure workloads run in dedicated namespaces with Pod Security Standards (PSS) enforced via labels.
  • Least Privilege: Ensure workloads use dedicated ServiceAccounts instead of the default ServiceAccount.

F. Backup & Disaster Recovery

Ensure stateful data is protected.

  • Action: You MUST run the gke-backup-dr skill for configuring Backup for GKE and restore procedures.

G. Edge Security & Ingress

Secure external access.

  • Action: You MUST run the gke-service-networking skill for Gateway API, Ingress, and Cloud Armor.

H. Cost Optimization

Ensure efficient use of resources.

  • Action: You MUST run the gke-cost-optimization skill for strategies on rightsizing, quotas, and Spot VMs.

3. Production Readiness Scoring

After the assessment, provide a summary report with a RAG (Red, Amber, Green) status for each area and an overall readiness score. This helps prioritize remediation efforts.

Adaptability Guidelines

  • Single App: Focus on Health Probes, HPA, Resource Limits, PDB, and Workload Identity for that specific app.
  • Cluster Wide: Focus on Cluster Autoscaler, Multi-zonal setup, Release Channels, Maintenance Windows, and default Network Policies.
  • Proactive Execution: Proactively execute relevant skills (e.g., observability, security, scaling, reliability) to assess and propose improvements, seeking user confirmation before applying state-changing implementations.

Version History

  • 05679aa Current 2026-07-31 07:59

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