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GitHub Copilot Analytics: Zero-Configuration Local Usage Dashboard Revealed

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GitHub Copilot Usage Metrics Viewer: A Zero-Configuration Local Analytics Dashboard

What is the GitHub Copilot Usage Metrics Viewer?

This web-based interactive dashboard visualizes GitHub Copilot usage metrics and analytics. It provides insights into request patterns, model distribution, user activity, and hourly trends—all running completely in your browser. No installation, servers, or data transmission required. Just open and use.

✨ Why Developers Need This Tool

Solving Key Pain Points

  • 🔒 Zero Privacy Compromises: All data processing happens locally—sensitive data never leaves your device
  • ⚡ 3-Second Setup: Double-click the HTML file or open via GitHub Pages
  • 📊 Decision Support: Reveals team model preferences, peak hours, and active user rankings
  • 💸 Cost Optimization: Identifies accounts exceeding quotas for better license allocation

🚀 5-Minute Setup Guide

Method 1: GitHub Pages Deployment (Recommended)

1. Go to your GitHub repository
2. Navigate to Settings > Pages
3. Select branch and save
4. Access via `https://[username].github.io/[repository-name]/`

Method 2: Local Execution

1. Download repository ZIP and extract
2. Double-click `index.html`
3. Click [📁 Load Data] on dashboard
4. Select your Copilot CSV file

Method 3: Custom Deployment

1. Fork the repository
2. Push modifications to main branch
3. GitHub Actions auto-deploys to Pages
4. Check `.github/workflows/deploy.yml` for configuration

📊 Core Features Explained

Global Data Overview

| Metric Type     | Analysis Dimension       | Business Value               |
|-----------------|--------------------------|------------------------------|
| Total Requests  | Time-period comparison   | Assess team usage intensity  |
| User Distribution | Active user ranking     | Identify power vs low users  |
| Model Usage %   | GPT-4o vs GPT-3.5 etc.  | Optimize model procurement   |
| Quota Status    | Over-limit accounts      | Prevent budget overruns      |

Advanced Analytics

  • Hourly Heatmaps: Identify developer activity peaks
  • Dynamic Filters: Real-time filtering by date/user/model
  • Data Export: Download filtered datasets as CSV


▲ Request distribution heatmap by hour

🧪 Data Preparation Guide

Step 1: Export Raw Data

Download CSV usage reports from GitHub Copilot admin portal

Step 2: Verify Data Format

Timestamp,User,Model,Requests Used,Exceeds Monthly Quota,Total Monthly Quota
2025-06-18T10:43:41.8378480Z,User41,gpt-4o-2024-11-20,1,FALSE,Unlimited

Note: Must contain these exact 6 columns

Step 3: Data Loading Demo

1. Click [📁 Load Data] top-right
2. Select CSV file
3. Wait for progress bar (3-10 seconds)
4. Charts auto-update with insights

🛠️ Technical Architecture

Core Components

Technology Function Advantage
Chart.js Data visualization Interactive dynamic charts
FileReader Local CSV parsing No server uploads needed
IndexedDB Browser data caching Handles 100K+ records fast

Performance Benchmarks

✅ 10,000 rows: Loads in <3s
✅ 50,000 rows: Filters in <1s
✅ Compatible with Chrome/Firefox/Safari/Edge

💼 Real-World Use Cases

Development Team Scenarios

1. **License Optimization**: 15-person team discovered:
   - 3 accounts consumed 40% of requests
   - 5 accounts used <10 requests/month
   ⇒ Saved $600/month in licenses

2. **Efficiency Boost**: Hourly analysis revealed:
   - Code generation peaked at 10:00-12:00
   - Afternoon response times slowed 30%
   ⇒ Scheduled critical tasks for mornings

Individual Developer Value

  • Compare model response quality
  • Analyze personal coding time patterns
  • Measure Copilot’s productivity impact

❓ Frequently Asked Questions (FAQ)

Q1: Does it require internet?

No. All processing happens locally. Works offline with loaded data.

Q2: What data size is supported?

Tested with 50,000+ rows. Performance depends on device RAM. Split large datasets.

Q3: Is my data stored?

Never. Data clears when browser closes. Reload required next use.

Q4: Format mismatch errors?

Verify these 6 exact columns exist:

  1. Timestamp
  2. User
  3. Model
  4. Requests Used
  5. Exceeds Monthly Quota
  6. Total Monthly Quota

Q5: Can I analyze historical data?

Yes. Supports any timeframe in exported CSV format.

🌟 Best Practice Recommendations

Team Administrators Should:

1. **Quarterly Reviews**: Analyze usage trends
2. **Model Cost Audits**: Compare GPT-4o vs GPT-3.5 ROI
3. **Anomaly Monitoring**: Set 50% usage spike alerts

Individual Developer Tips:

  • Correlate with time-tracking tools
  • Export monthly reports for performance reviews
  • Compare efficiency across IDEs

Final Note: Includes sample data_example.csv. Licensed under MIT for enterprise integration.

This dependency-free tool delivers:

- 🔍 Deep Copilot usage insights
- 💡 Data-driven optimization decisions
- ⏱️ Hours saved monthly on manual analysis

Access the repository now → GitHub Copilot Usage Metrics Viewer

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