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k8s-cost

Analyze Kubernetes namespace costs to identify unused storage and right-sizing opportunities.

Updated Aug 27, 2026
Search Tags:#kubernetes#observability#cost optimization#capacity planning#resource right-sizing#unused pvc#cluster efficiency
One-click install
npx skills add https://github.com/spigell/my-agents --skill k8s-cost-spigell
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: k8s-cost
Source: https://github.com/spigell/my-agents/tree/main/agents/shared/src/tools/ask_kubernetes_expert/skills/k8s-cost
Command: npx skills add https://github.com/spigell/my-agents --skill k8s-cost-spigell

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Kubernetes clusters can become expensive through overprovisioned workloads, unused storage, and inefficient infrastructure utilization that accumulates over time.

Core Features & Use Cases

  • Unused resource detection: Identify orphaned PVCs to prevent paying for storage that no longer backs active workloads.
  • Right-sizing recommendations: Use resource recommendation signals to tune CPU/memory requests and limits for better fit and fewer inefficiencies.
  • Cost-focused cluster efficiency analysis: Evaluate idle or underutilized components such as services and node utilization to target the biggest savings first.

Quick Start

Use the k8s-cost skill to analyze namespace cost and identify right-sizing and unused PVC opportunities for namespace "production".

Frequently Asked Questions about k8s-cost

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

FAQPage Schema
How do I find orphaned PVCs and unused storage in Kubernetes to stop paying for them?▼

To find orphaned PVCs in Kubernetes, you analyze cluster cost summaries to identify unused storage that no longer backs active workloads. This cleanup process targets orphaned persistent volume claims to prevent paying for unneeded storage capacity.

What is Kubernetes resource right-sizing and how does it reduce cluster costs?▼

Kubernetes resource right-sizing reduces cluster costs by tuning CPU and memory requests and limits to match actual workload usage. Evaluating resource recommendation signals helps eliminate overprovisioning and improves overall workload efficiency.

How do I analyze Kubernetes cluster efficiency for capacity planning across staging and production namespaces?▼

You can analyze Kubernetes cluster efficiency for capacity planning by evaluating idle or underutilized components across staging and production namespaces. This cost-focused analysis highlights node utilization issues to target the biggest infrastructure savings first.

Do I need kubectl-mcp-server cost tooling to identify Kubernetes workload right-sizing recommendations?▼

Yes, you need kubectl-mcp-server cost tooling outputs to guide prioritized right-sizing actions. The skill requires namespace cost summaries, orphaned PVC discovery, and resource recommendation retrieval from this tooling to optimize Kubernetes spending effectively.

What's the best way to prioritize Kubernetes cost optimization actions for underutilized services?▼

The best way to prioritize Kubernetes cost optimization is evaluating cluster efficiency to find underutilized services and node components. Highlighting these idle infrastructure components allows you to target the biggest savings first before right-sizing workloads.

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