# Unified Monitoring Dashboard Architecture

## Overview

The Unified Monitoring Dashboard consolidates real-time metrics, historical trends, and quality analytics into a single, comprehensive interface. It builds upon existing WebSocket infrastructure and quality baseline services to provide enterprise-grade monitoring capabilities.

## Architecture Components

### 1. Core Monitoring Stack

```
┌─────────────────────────────────────────┐
│           Web Dashboard                 │
│    (React + D3.js + WebSocket)         │
├─────────────────────────────────────────┤
│         WebSocket API Server           │
│      (FastAPI + Real-time Events)      │
├─────────────────────────────────────────┤
│        Metrics Collection Layer        │
│   (Enhanced Quality Baseline + Jobs)   │
├─────────────────────────────────────────┤
│          Data Persistence              │
│    (SQLite + JSON Cache + History)     │
└─────────────────────────────────────────┘
```

### 2. Data Flow Architecture

#### Real-time Metrics Pipeline

```
Quality Events → MetricCollector → WebSocket Stream → Dashboard Updates
     ↓
Historical Storage → Trend Analysis → Alert Generation → Notification System
```

#### Historical Analysis Pipeline

```
Stored Metrics → Trend Calculator → Prediction Engine → Visualization Data
     ↓
Alert Thresholds → Anomaly Detection → Performance Insights → Recommendations
```

## Dashboard Features

### 1. Real-time Monitoring Panel

- **Live Quality Score**: Current quality metrics with trend indicators
- **Active Jobs**: Running tests, hooks, and analysis tasks with progress bars
- **Resource Usage**: CPU, memory, and I/O metrics during operations
- **Error Stream**: Real-time error detection and categorization

### 2. Historical Analytics

- **Quality Trends**: 7, 30, 90-day quality score progression with statistical confidence
- **Performance Metrics**: Test execution times, hook duration analysis, coverage trends
- **Failure Analysis**: Error pattern recognition, recurring issue identification
- **Productivity Insights**: Development velocity, fix rates, quality improvement velocity

### 3. Interactive Visualizations

- **Time Series Charts**: Quality scores, test coverage, performance metrics over time
- **Heatmaps**: Error patterns by module, time-of-day development patterns
- **Network Graphs**: Dependency impact analysis, code complexity visualization
- **Comparison Views**: Before/after analysis, team member performance comparison

### 4. Alert & Notification System

- **Threshold Alerts**: Quality drops, coverage regression, performance degradation
- **Anomaly Detection**: Unusual patterns, unexpected behavior, system health issues
- **Predictive Warnings**: Trend-based predictions, potential failure forecasting
- **Integration Points**: Slack, email, webhooks for external notification systems

## Technical Implementation

### Enhanced WebSocket Endpoints

```python
# Real-time metrics streaming
/ws/metrics/live              # Live quality scores, job progress
/ws/metrics/historical/{days} # Historical data with configurable time ranges
/ws/alerts/subscribe          # Alert subscription with filtering
/ws/dashboard/overview        # Comprehensive dashboard data

# REST API endpoints
/api/metrics/summary          # Current system summary
/api/trends/quality           # Quality trend analysis
/api/alerts/configure         # Alert threshold configuration
/api/export/data             # Data export for external analysis
```

### Data Models

```python
@dataclass
class UnifiedMetrics:
    timestamp: datetime
    quality_score: int
    test_coverage: float
    hook_duration: float
    active_jobs: int
    error_count: int
    trend_direction: TrendDirection
    predictions: dict[str, Any]


@dataclass
class DashboardState:
    current_metrics: UnifiedMetrics
    historical_data: list[UnifiedMetrics]
    active_alerts: list[QualityAlert]
    system_health: SystemHealthStatus
    recommendations: list[str]
```

### Visualization Components

#### D3.js Chart Types

- **Line Charts**: Quality score trends, coverage progression
- **Bar Charts**: Error frequency, performance comparisons
- **Area Charts**: Resource usage over time, job completion rates
- **Scatter Plots**: Correlation analysis, outlier detection
- **Sankey Diagrams**: Process flow analysis, dependency mapping

#### Interactive Features

- **Zoom & Pan**: Detailed time range analysis
- **Brushing**: Multi-chart coordination, cross-filtering
- **Tooltips**: Contextual information, drill-down capabilities
- **Export**: PNG, SVG, PDF chart export functionality

## Integration Points

### Existing Systems Integration

- **Quality Baseline Service**: Real-time quality score streaming
- **WebSocket Server**: Bi-directional communication infrastructure
- **Job Manager**: Task progress tracking and status updates
- **Cache System**: Performance optimization and historical data storage

### External Integration Capabilities

- **CI/CD Pipelines**: Jenkins, GitHub Actions, GitLab CI integration
- **Monitoring Tools**: Prometheus, Grafana, DataDog integration
- **Communication**: Slack, Teams, Discord notification integration
- **Analytics**: Export to BI tools, custom reporting systems

## Performance Considerations

### Real-time Optimization

- **WebSocket Connection Pooling**: Efficient connection management
- **Data Compression**: Gzip compression for large data transfers
- **Selective Updates**: Only send changed data to reduce bandwidth
- **Client-side Caching**: Reduce server requests for static data

### Historical Data Management

- **Data Aggregation**: Automatic rollup of old data to reduce storage
- **Indexing Strategy**: Optimized queries for time-series data
- **Cleanup Policies**: Automatic purging of old data based on retention policies
- **Backup Strategy**: Regular exports for data protection

## Security & Privacy

### Access Control

- **Authentication**: Token-based authentication for dashboard access
- **Authorization**: Role-based access to different metrics and controls
- **Rate Limiting**: Prevent abuse of WebSocket and API endpoints
- **Audit Logging**: Track access and configuration changes

### Data Protection

- **Sensitive Data Masking**: Hide sensitive paths, credentials in logs
- **Encryption**: TLS for all communications, encrypted data storage
- **Privacy Compliance**: GDPR-compliant data handling and retention
- **Secure Defaults**: Conservative security settings out-of-the-box

## Implementation Phases

### Phase 1: Enhanced WebSocket API (Week 5)

- Extend existing WebSocket server with monitoring endpoints
- Implement real-time metrics streaming
- Add quality score broadcasting
- Create basic alert system

### Phase 2: Dashboard Frontend (Week 6)

- React-based dashboard with real-time updates
- D3.js chart integration for visualizations
- Responsive design for mobile/desktop access
- Basic interactivity and filtering

### Phase 3: Historical Analytics (Week 7)

- Historical data storage and retrieval
- Trend analysis and prediction algorithms
- Advanced alerting with anomaly detection
- Export capabilities and external integrations

### Phase 4: Advanced Features (Week 8)

- Machine learning-based insights
- Predictive analytics and recommendations
- Advanced visualization techniques
- Performance optimization and scaling

## Success Metrics

### Technical Metrics

- **Real-time Latency**: < 100ms for metric updates
- **Historical Query Performance**: < 2s for 90-day data queries
- **Dashboard Load Time**: < 3s initial load, < 1s subsequent navigation
- **Uptime**: 99.9% availability for monitoring infrastructure

### User Experience Metrics

- **Time to Insight**: < 30s to identify quality issues
- **Action Response Time**: < 5s from alert to actionable information
- **Data Export Speed**: < 30s for comprehensive data exports
- **Mobile Responsiveness**: Full functionality on mobile devices

### Business Impact Metrics

- **Quality Improvement Velocity**: 25% faster issue identification and resolution
- **Development Productivity**: 15% improvement in development cycle time
- **Error Reduction**: 40% reduction in production issues through early detection
- **Team Adoption**: 90% daily active usage by development team members

This unified monitoring architecture provides a comprehensive, scalable foundation for monitoring code quality, development productivity, and system health while building upon crackerjack's existing infrastructure.
