realopslabs/kubeledger

开发工具

本页由 AI 翻译，技术细节请以原文为准。查看原文

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Repository Install

realopslabs/kubeledger 是一个从 https://github.com/realopslabs/kubeledger. 导入的 MCP 服务器候选

概览

realopslabs/kubeledger 是一个从 https://github.com/realopslabs/kubeledger. 导入的 MCP 服务器候选

概述（AI 翻译）

KubeLedger 是跟踪 Kubernetes 成本全貌的记录系统，揭示了隐藏在不可分配开销中的 30%，以便精确、按命名空间进行核算。

注： KubeLedger 以前被称为 Kubernetes Opex Analytics，又名 kube-opex-analytics。在我们的公告博客文章中了解更多关于此变更的信息。为了以简便的方式处理迁移，我们提供了迁移流程。

概述

KubeLedger 是一款使用会计工具，帮助组织跟踪、分析和优化 Kubernetes 集群上的 CPU、内存和 GPU 资源，随时间（小时、每日、每月）。

它作为集群资源的记录系统，提供有洞察力的使用分析和图表，工程和财务团队可以作为成本优化决策的关键指标。

**v26.05 新增内容：问问你的 AI 助手。

本页由 AI 翻译，技术细节请以原文为准。

README

以下为原文 README 节选，完整内容请查看原文。

KubeLedger

KubeLedger is the System of Record that tracks the full picture of Kubernetes costs, revealing the 30% hidden in non-allocatable overhead for precise, per-namespace accounting.

Note: KubeLedger was formerly known as Kubernetes Opex Analytics aka kube-opex-analytics. Read more about this change in our announcement blog post. To handle the migration in a straightforward way, we have provided a migration procedure.

Overview
Key Features
Quick Start
MCP Integration (AI Assistant) / Requires v26.05.0+
Architecture
Documentation
Configuration
Troubleshooting
License
Support & Contributions

Overview

KubeLedger is a usage accounting tool that helps organizations track, analyze, and optimize CPU, Memory, and GPU resources on Kubernetes clusters over time (hourly, daily, monthly).

It acts as a System of Record for your cluster resources, providing insightful usage analytics and charts that engineering and financial teams can use as key indicators for cost optimization decisions.

New in v26.05: ask your AI assistant. KubeLedger ships an optional Model Context Protocol (MCP) server that exposes the same analytics to AI tools such as Claude, Gemini, Mistral, Cursor, Windsurf, MCP Inspector and other MCP-aware clients. Ten read-only tools let an assistant rank consumers, group namespaces, assess efficiency or compare periods in plain language, unlocking investigations beyond what predefined dashboards can show.

Tracked Resources

CPU - Core usage and requests per namespace
Memory - RAM consumption and requests per namespace
GPU - NVIDIA GPU utilization via DCGM integration

Multi-cluster Integration: KubeLedger tracks usage for a single Kubernetes cluster. For centralized multi-cluster analytics, see Krossboard Kubernetes Operator (demo video).

Key Features

在 GitHub 查看完整 README

安装

npx -y mcp-remote@latest http://localhost:5484/mcp --transport http-only

新手？先看 mcpskill.org 教程 →

配置

{
  "mcpServers": {
    "kubeledger": {
      "type": "http",
      "url": "http://localhost:5484/mcp"
    }
  }
}