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google/gke-productionize

google

gke-productionize

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).

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v1.0Saved Jul 24, 2026

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.
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Overall Score

82/100

Grade

B

Good

Safety

88

Quality

82

Clarity

84

Completeness

76

Summary

The gke-productionize skill is a meta/orchestrator skill that guides agents through a comprehensive production readiness assessment for GKE clusters and workloads. It spans eight key domains (app onboarding, scalability, observability, reliability, security, backup/DR, edge security, and cost optimization) and delegates to specialized domain skills rather than implementing each area directly. The skill provides cluster and workload discovery commands, assessment phases with clear references to delegated skills, and a RAG-based scoring framework for remediation prioritization.

Detected Capabilities

kubectl command executiongcloud cluster inspectionworkload configuration analysisYAML introspectionmeta-skill orchestrationassessment framework execution

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

gke production readinesskubernetes cluster auditproductionize gke workloadpre-production checklistgke security assessmentcluster hardening planreadiness review workflow

Risk Signals

INFO

No destructive or privilege-escalation commands detected

global
INFO

No credential access or secrets harvesting patterns detected

global
INFO

No command injection or pipe-to-shell patterns detected

global
INFO

All commands are read-only kubectl and gcloud inspect operations

Discovery Phase section
INFO

No file writes or local modifications attempted by this skill

global
INFO

Skill explicitly delegates state-changing implementations to specialized skills

Proactive Execution subsection

Referenced Domains

External domains referenced in skill content, detected by static analysis.

www.apache.org

Use Cases

  • Assess GKE cluster readiness before production deployment
  • Conduct comprehensive security and reliability audit of existing workloads
  • Plan and execute multi-domain production migration for Kubernetes applications
  • Prioritize production hardening efforts across scalability, observability, and security
  • Coordinate production readiness work across multiple specialized teams and skills

Quality Notes

  • ✓ Clear orchestrator role explicitly stated in frontmatter and IMPORTANT callout
  • ✓ Well-structured workflow with three clear phases: Discovery, Assessment, Scoring
  • ✓ Comprehensive discovery commands provided for both cluster and workload inspection
  • ✓ Explicit delegation to eight specialized domain skills with inline action references
  • ✓ RAG-based scoring framework provides clear prioritization guidance for remediation
  • ✓ Scope explicitly bounded — identifies when NOT to use this skill (single-domain deep dives)
  • ✓ Adaptability guidelines for single-app, cluster-wide, and proactive scenarios
  • ✓ Security guardrails in place — recommends confirmation before state-changing implementations
  • ⚠ Missing: explicit error handling guidance for kubectl/gcloud command failures
  • ⚠ Missing: detailed example output from Discovery Phase commands for reference
  • ⚠ Missing: specific metrics or thresholds for RAG status determination (Red/Amber/Green boundaries)
  • ⚠ Missing: template or concrete format for the production readiness summary report
  • ⚠ Minor: skill references gke-app-onboarding and eight other skills without noting fallback behavior if those skills are unavailable
Model: claude-haiku-4-5-20251001Analyzed: Jul 24, 2026

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