Observability✓ Mathematical
◆ The PatternPrediction health, feature drift, and system metrics in one view
A model monitoring dashboard tracks three layers: system metrics (latency, errors, throughput), data metrics (feature distributions, missing rates), and model metrics (prediction distribution, accuracy if labels are available). Grafana + Prometheus is the standard stack.
// Interactive — monitoring dashboard simulation
| Layer | Metrics | Alert When |
|---|---|---|
| System | Latency, error rate, throughput | p99 > SLO or error rate > 1% |
| Data | Feature distributions, null rates | PSI > 0.2 or null rate spikes |
| Model | Prediction distribution, confidence | Distribution shift or low confidence |
Pattern bridge: ML monitoring dashboards are structured like trading dashboards — layered views from system health down to individual signal quality. The learning curve concept extends to tracking model performance over time in production.