docs/configs/ANALYTICS_SPEC.md

Advanced Analytics Agent Specification

Overview

The Advanced Analytics Agent provides comprehensive monitoring, custom metrics, role-based reporting, and system health tracking. This module integrates with UI interfaces and backend services for real-time analytics and historical trend analysis.

Configuration

Analytics configuration is defined in docs/configs/analytics_config.json

Features

Custom Metrics

• User Engagement Score: Composite metric tracking active user ratios and session duration
  • Formula: (active_users * avg_session_duration) / total_users
  • Warning threshold: 0.3
  • Critical threshold: 0.15
• API Response Time (P95): Performance metric for API latency monitoring
  • Unit: milliseconds
  • Warning threshold: 500ms
  • Critical threshold: 1000ms
• Error Rate: Reliability metric tracking system errors
  • Unit: percentage
  • Warning threshold: 2%
  • Critical threshold: 5%
• Resource Utilization: System metrics for CPU, memory, disk, and network usage
  • Components: cpu, memory, disk, network
  • Warning threshold: 75%
  • Critical threshold: 90%

Notifications

Multi-channel notification system with severity-based routing:

• Email: Alerts sent to admin and ops team for warning/critical events
• Slack: Critical alerts posted to #analytics-alerts channel
• Webhooks: All severity levels sent to configured webhook endpoint
• Rate Limiting: Maximum 10 notifications per hour with 15-minute cooldown

Role-Based Views

Four distinct role configurations with tailored permissions and dashboards:

Administrator

• Permissions: view_all, configure, export, delete
• Default Dashboard: system_overview
• Visible Metrics: All metrics (*)

Data Analyst

• Permissions: view_all, export
• Default Dashboard: analytics_deep_dive
• Visible Metrics: user_engagement_score, custom_metrics, historical_trends

Developer

• Permissions: view_technical, export
• Default Dashboard: api_performance
• Visible Metrics: api_response_time_p95, error_rate, system_health

Read-Only Viewer

• Permissions: view_summary
• Default Dashboard: executive_summary
• Visible Metrics: user_engagement_score

Batch Processing

Scheduled operations for data aggregation and reporting:

• Daily Aggregation: Runs at 2:00 AM, outputs parquet format, 365-day retention
• Weekly Report: Runs Monday 3:00 AM, generates PDF for leadership
• Data Cleanup: Runs Sunday 1:00 AM, purges data older than 90 days

Historical Analysis

Advanced analytics capabilities:

Trend Detection

• Moving average
• Exponential smoothing
• Seasonal decomposition

Anomaly Detection

• Isolation forest algorithm
• Statistical outliers
• Prophet forecasting

Forecasting

• 30-day horizon
• 95% confidence intervals

Comparative Analysis

• Day-over-day
• Week-over-week
• Month-over-month
• Year-over-year

System Health Monitoring

Real-time monitoring with 30-second intervals:

Database Monitoring

• Connection pool status
• Query performance metrics
• Replication lag tracking

Cache Monitoring

• Hit rate analysis
• Memory usage tracking
• Eviction rate monitoring

Queue Monitoring

• Queue depth tracking
• Processing rate analysis
• Dead-letter queue monitoring

External Services

• API availability checks
• Response time monitoring
• Rate limit tracking

Auto-Recovery

• Service restart capability
• Cache clearing
• Resource scaling

API Endpoints

Base path: /api/v1/analytics Authentication: Bearer token Rate limiting: 100 requests per minute

GET /metrics

Description: Retrieve current metrics Parameters:

• metric_id: Specific metric identifier
• start_time: Query start time
• end_time: Query end time
• granularity: Data granularity (minute, hour, day)

POST/PUT/DELETE /metrics/custom

Description: Manage custom metrics Permissions: Admin only

GET /dashboards

Description: Get dashboard configurations for user role

GET/POST /alerts

Description: Manage alert configurations

POST /export

Description: Export analytics data Parameters:

• format: json, csv, parquet, excel
• metrics: Array of metric IDs
• date_range: Date range for export

GET /health

Description: Get system health status Public: Yes (no authentication required)

GET /historical

Description: Access historical analysis and trends Parameters:

• analysis_type: trends, anomalies, forecast, comparison
• metric_id: Target metric
• time_range: Analysis time range

Failover Logging

Multi-tier logging system with automatic failover:

Primary Logger: Elasticsearch

• Endpoint: ${ELASTICSEARCH_URL}
• Index pattern: analytics-logs-%{+YYYY.MM.dd}

Failover Tier 1: CloudWatch

• Log group: strategystack-analytics
• Retention: 30 days

Failover Tier 2: File System

• Path: /var/log/analytics
• Rotation: Daily
• Max size: 100MB per file
• Retention: 7 days

Failover Tier 3: Syslog

• Endpoint: ${SYSLOG_ENDPOINT}
• Protocol: TCP

Health Checks: 60-second intervals Auto-Failover: Enabled Log Levels: DEBUG, INFO, WARNING, ERROR, CRITICAL Structured Logging: Enabled with correlation IDs and session tracking

Integration Points

UI Components (React)

MetricsDashboard

• Path: src/components/analytics/MetricsDashboard.tsx
• Props: roleId, dateRange, refreshInterval
• Description: Main dashboard showing role-based metrics

CustomMetricBuilder

• Path: src/components/analytics/CustomMetricBuilder.tsx
• Permissions: admin, analyst
• Description: UI for creating and editing custom metrics

AlertsPanel

• Path: src/components/analytics/AlertsPanel.tsx
• Realtime: Yes (WebSocket)
• Description: Real-time alert display

HistoricalAnalyzer

• Path: src/components/analytics/HistoricalAnalyzer.tsx
• Features: trends, forecasting, anomalies
• Description: Trend, forecasting, and anomaly visualization

SystemHealthMonitor

• Path: src/components/analytics/SystemHealthMonitor.tsx
• Update Interval: 10 seconds
• Description: Component status dashboard

Backend Integration

Strategy Engine

• Metrics export enabled
• Event hooks: strategy_execution, performance_update

User Service

• Metrics export enabled
• Event hooks: user_action, session_start, session_end

Notification Service

• Alert integration enabled
• Priority routing enabled

WebSocket Support

• Real-time metric updates via ${WEBSOCKET_URL}/analytics
• Redux state management for UI consistency

Performance Optimization

Caching

• Strategy: Redis
• TTL: 5 minutes (300 seconds)
• Cache Warmer: Enabled

Query Optimization

• Materialized views for frequently accessed aggregations
• Parallel query execution
• Query timeout: 30 seconds

Data Sampling

• High-cardinality threshold: 10,000 records
• Sampling rate: 10%

Usage

1. Configure analytics sources: Edit docs/configs/analytics_config.json to customize metrics, alerts, roles, and integration points.
2. Enable real-time monitoring: Deploy UI components and connect to analytics API.
3. Set up notifications: Configure email, Slack, and webhook endpoints for alert delivery.
4. Configure historical analysis: Enable trend detection, anomaly detection, and forecasting as needed.
5. Monitor system health: Use system health endpoint for infrastructure monitoring.

Implementation Status

• Configuration schema defined
• Custom metrics configuration
• Multi-channel notifications
• Role-based access control
• Batch processing schedules
• Historical analysis features
• System health monitoring
• API endpoint definitions
• Failover logging configuration
• UI component specifications
• Backend integration points
• Performance optimization strategies

Next Steps

1. Implement analytics agent Python module
2. Create UI components according to specifications
3. Set up database tables and materialized views
4. Configure notification channels
5. Deploy monitoring infrastructure
6. Set up failover logging systems
7. Create integration tests
8. Document API with OpenAPI/Swagger specs
9. Create user documentation and tutorials
10. Set up monitoring dashboards and alerts

---

Configuration file: analytics_config.json Last updated: 2025-11-05