Service Overview: The Performance Intelligence Service provides advanced analytics, KPI monitoring, predictive insights, and prescriptive recommendations through machine learning models, real-time dashboards, and automated alerting for operational excellence.
Architecture: Lambda Architecture (Batch + Stream Processing)
Technology Stack: Spring Boot 3.2, PostgreSQL, TimescaleDB, Redis, Apache Kafka, Apache Spark, ML Platform
Domain Model: Metrics aggregation with ML-driven insights and anomaly detection
L1: Data-Driven Operational Excellence
L1.1: Strategic Value
- Visibility: Real-time operational metrics across all domains
- Proactivity: Predictive alerts 2-4 hours before issues occur
- Optimization: 15% efficiency gain through ML recommendations
- Decision Support: Data-driven insights for strategic planning
L2: Core Capabilities
L2.1: Real-Time Analytics & KPIs
- Executive dashboard with drill-down capabilities
- Operational metrics (throughput, accuracy, productivity)
- Financial KPIs (cost per order, labor efficiency)
- Custom metric definitions and calculations
L2.2: Predictive Analytics
- Demand forecasting with ML models
- Anomaly detection (performance degradation, outliers)
- Capacity constraint prediction
- Equipment failure prediction
L2.3: Prescriptive Recommendations
- Process optimization suggestions
- Resource reallocation recommendations
- Root cause analysis automation
- A/B testing framework for process changes
L2.4: Reporting & Alerting
- Scheduled report generation
- Ad-hoc query interface
- Threshold-based alerting
- Trend analysis and pattern recognition
Key Metrics
- Dashboard refresh rate: real-time (< 5 seconds)
- Prediction accuracy: 90%+
- Alert precision: 85% (true positive rate)
- Data completeness: 99%+
- Metric calculation: < 1 second
- Predictive model inference: < 500ms
- Report generation: < 10 seconds
- System availability: 99.95%