A sophisticated Real User Monitoring (RUM) system that combines traditional performance monitoring with AI-powered analytics. The system collects, analyzes, and visualizes web performance metrics while providing intelligent insights and predictions.

• Core Web Vitals Monitoring
  • Largest Contentful Paint (LCP)
  • First Contentful Paint (FCP)
  • Cumulative Layout Shift (CLS)
• Element-Level Analysis
  • Detailed tracking of HTML elements
  • Class and ID-based performance correlation
  • DOM structure impact analysis

• Anomaly Detection
  • Real-time performance deviation analysis
  • Pattern recognition in metric trends
  • Automated alert generation
• Predictive Analytics
  • Performance trend forecasting
  • Resource utilization predictions
  • User experience impact analysis

• Dynamic Visualization
  • Real-time metric updates
  • Interactive performance charts
  • Customizable data views
• Smart Insights
  • Automated performance recommendations
  • Root cause analysis
  • Optimization suggestions

• Framework: Next.js 15.3.0 with React 19
• UI Components: NextUI v2.6.11
• Styling: TailwindCSS 3.4.0
• Charts: Recharts 2.15.2
• Theme Support: next-themes 0.4.6

• API Routes: Next.js API routes
• Data Processing: Node.js with TypeScript
• External Services:
  • Sitemap parsing (xml2js)
  • HTTP requests (node-fetch)

// RUM Metrics Collection
const metrics = {
  LCP: {
    value: number,
    element: string,
    tagName: string,
    classList: string[],
    id: string
  },
  FCP: {
    value: number,
    element: string,
    tagName: string,
    classList: string[],
    id: string
  },
  CLS: {
    value: number,
    element: string,
    tagName: string,
    classList: string[],
    id: string
  }
};

• Node.js (v18 or higher)
• npm or yarn
• TypeScript 5.0

# Clone the repository
git clone [repository-url]

# Install dependencies
npm install

# Start development server
npm run dev

Create a .env.local file with the following variables:

NEXT_PUBLIC_API_URL=http://localhost:3000

• Jest configuration for unit testing
• React Testing Library for component testing
• TypeScript for type safety

src/
├── app/
│   ├── api/           # API routes
│   ├── _components/   # Reusable components
│   ├── page.tsx       # Main dashboard
│   └── layout.tsx     # Root layout
├── utils/             # Utility functions
└── types/             # TypeScript definitions

The system uses PerformanceObserver to collect metrics:

const observer = new PerformanceObserver((list) => {
  list.getEntries().forEach((entry) => {
    // Process LCP, FCP, and CLS metrics
    // Send to backend for analysis
  });
});

1. Metric Analysis

   • Pattern recognition in performance data
   • Correlation analysis between metrics
   • Trend prediction models

2. Insight Generation

   • Automated performance recommendations
   • Root cause analysis
   • Optimization suggestions

3. Alert System

   • Smart threshold detection
   • Context-aware notifications
   • Priority-based alerting

1. Machine Learning Model Integration
2. Advanced Predictive Analytics
3. Automated Performance Optimization
4. Enhanced Visualization Capabilities
5. Integration with CI/CD Pipelines

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

[Specify License]

For support, please create an issue or contact the maintainers.