/gke-productionize

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-workload-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 the following block in the

describe output:

    autopilot:
      enabled: true

• 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.

I. Upgrades & Maintenance Posture

Ensure a safe, predictable upgrade posture.

• **Action**: You MUST run the `gke-upgrades` skill for release channel

selection, maintenance windows/exclusions, and node pool upgrade strategy.

J. Golden Path Defaults Audit

Ensure the cluster configuration matches recommended defaults.

• **Action**: You MUST run the `gke-golden-path` skill to compare the cluster

against golden path defaults and report deviations with severity and remediation.

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.

Apply this rubric deterministically so repeated assessments of the same environment produce the same result:

1. **Per-domain criteria**: For each assessed domain (A-J), list the concrete checks performed (from the domain skill's guidance) and classify each check as **pass**, **fail-critical** (production-blocking, e.g., no resource requests, no backups for stateful data, public control plane in a locked down environment), or **fail-minor** (improvement, e.g., missing VPA recommendations, no Spot usage for batch). 2. **RAG mapping (p