cluster-planning

Analyzes surveyed cluster hardware and creates a phased K3s deployment roadmap.

1|Updated Apr 3, 2026
One-click install
npx skills add https://github.com/villadalmine/infra --skill cluster-planning
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cluster-planning
Source: https://github.com/villadalmine/infra/tree/main/skills/cluster-planning
Command: npx skills add https://github.com/villadalmine/infra --skill cluster-planning

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you turn raw homelab cluster survey data into a clear deployment strategy, showing what your hardware can support today and what to add next.

Core Features & Use Cases

  • Hardware profiling: Classifies a cluster into practical tiers based on node count, RAM, storage, and readiness for K3s workloads.
  • Phased planning: Recommends an ordered rollout for foundations, services, observability, AI, security, and high-availability control planes.
  • Node assignment: Suggests which machines should host control-plane, AI, and worker roles based on latency, memory, and storage performance.
  • Buying guidance: Translates gaps in capability into concrete purchase recommendations for more RAM, faster storage, HA control-plane, or local inference.
  • Learning roadmap: Maps infrastructure maturity to skill-building paths so the cluster doubles as an education platform.

Quick Start

Use the cluster-planning skill to analyze my surveyed nodes and generate a phased deployment roadmap with node role assignments, tier recommendations, and what hardware I should buy next.

Frequently Asked Questions about cluster-planning

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I plan a K3s homelab deployment from surveyed hardware data?

Plan a K3s homelab deployment by analyzing surveyed cluster hardware to produce a phased deployment roadmap. The skill classifies nodes into practical tiers based on RAM, storage, and readiness, then recommends what to deploy now and what to defer.

What is the best way to assign K3s control-plane nodes for an ARM64 cluster?

Assign K3s control-plane nodes by evaluating ARM64 hardware latency, memory, and storage performance from survey data. The skill suggests which machines should host control-plane, AI, and worker roles to ensure a safe and stable high-availability setup.

How do I know what hardware to buy next for my homelab cluster?

Determine what hardware to buy next by translating capability gaps from your cluster survey into concrete purchase recommendations. The skill advises on acquiring more RAM, faster storage, or additional nodes for a high-availability control plane.

Can I generate a phased deployment roadmap for existing ARM64 nodes?

Generate a phased deployment roadmap for existing ARM64 nodes by applying planning rules to your survey data. The skill maps infrastructure maturity to an ordered rollout for foundations, services, observability, AI, and security.

Do I need survey data to get a cluster hardware profiling recommendation?

Survey data is required to receive cluster hardware profiling and node assignment recommendations. The skill analyzes your surveyed node count, RAM, and storage to classify cluster tiers and generate a safe deployment strategy.

When should I defer deploying K3s workloads in my homelab?

Defer deploying K3s workloads when your surveyed hardware lacks the RAM, storage, or node count to support them safely. The skill identifies capability gaps and recommends deferring services until your cluster matures or hardware is upgraded.