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claude-code-monitoring-guide

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파일 탐색기

최종 버전 다운로드 (.zip)

- - working-dashboard.json
- grafana_cost_per_model.png
- graphan_dashboard_cost_tokens_cost_per_user.png
- prometheus_cost_time_series.png
claude_code_roi_full.md
docker-compose.yml
otel-collector-config.yaml
prometheus.yml
README.md
report-generation-prompt.md
sample-report-output.md
troubleshooting.md

# 설치 가이드

1. 코드 내려받기

git clone https://github.com/anthropics/claude-code-monitoring-guide

깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.

cd claude-code-monitoring-guide

방금 내려받은 프로젝트 폴더 안으로 이동합니다.

2. Docker

쉬움 추천

사전 준비물

Git GitHub에서 프로젝트 코드를 내려받으려면 필요합니다.
Docker Desktop 컨테이너를 빌드하고 실행하려면 필요합니다. 설치 후 실행해서 백그라운드에 켜두세요.

docker compose up -d --build

정의된 모든 컨테이너(서버, DB 등)를 한 번에 빌드하고 백그라운드에서 실행합니다.

✅ 터미널에 docker compose ps 를 입력해 컨테이너들이 Up 상태인지 확인하세요. README에 포트 번호가 적혀있다면 브라우저에서 http://localhost:포트번호 로 접속해보세요.

// repository documentation

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# Claude Code ROI Measurement Guide

A comprehensive guide to measuring the return on investment for Claude Code implementation in your development organization.

## Overview

This repository contains a complete walkthrough for setting up telemetry, measuring costs, tracking productivity, and calculating ROI for Claude Code usage. Whether you're an individual developer or managing a large engineering team, this guide provides the tools and metrics needed to make data-driven decisions about AI coding assistance.

## What's Included

- **Telemetry Setup**: Complete Prometheus and OpenTelemetry configuration
- **Cost Analysis**: Real usage patterns and pricing breakdowns across different plans
- **Productivity Metrics**: Key indicators for measuring developer efficiency
- **ROI Calculations**: Framework for calculating return on investment
- **Automated Reporting**: Integration with Linear for comprehensive productivity reports

## Key Metrics Tracked

- **Cost Metrics**: Total spend, cost per session, cost by model
- **Token Usage**: Input/output tokens, cache efficiency
- **Productivity**: PR count, commit frequency, session duration
- **Team Analytics**: Usage by developer, adoption rates

## Contents

- [`claude_code_roi_full.md`](claude_code_roi_full.md) - Complete implementation guide
- [`docker-compose.yml`](docker-compose.yml), [`prometheus.yml`](prometheus.yml), [`otel-collector-config.yaml`](otel-collector-config.yaml) - Docker Compose and metrics collection setup
- [`sample-report-output.md`](sample-report-output.md) - Example automated reports
- [`report-generation-prompt.md`](report-generation-prompt.md) - Prompt template for generating productivity reports

## Getting Started

Read the complete guide in [`claude_code_roi_full.md`](claude_code_roi_full.md) for detailed setup instructions, real-world examples, and actionable insights for your organization.

## Contributing

This guide is based on real-world implementation experience. If you have additional insights or improvements, please feel free to create an issue / PR.

This guide was written by [Kashyap Coimbatore Murali](https://www.linkedin.com/in/kashyap-murali/)