foxhunt/crates/ml-observability/src/dashboards.rs

//! Dashboard system for ML metrics visualization

use anyhow::Result;
use serde::{Deserialize, Serialize};

/// Dashboard configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct DashboardConfig {
    pub name: String,
    pub description: String,
    pub refresh_interval_seconds: u64,
    pub widgets: Vec<DashboardWidget>,
}

/// Dashboard widget configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct DashboardWidget {
    pub id: String,
    pub title: String,
    pub widget_type: WidgetType,
    pub metrics: Vec<String>,
    pub time_range_minutes: u64,
    pub position: WidgetPosition,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct WidgetPosition {
    pub row: u32,
    pub column: u32,
    pub width: u32,
    pub height: u32,
}

/// Widget types for different visualizations
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum WidgetType {
    LineChart,
    Histogram,
    Gauge,
    Counter,
    Table,
    Heatmap,
}

/// Metrics dashboard
#[derive(Debug)]
pub struct MetricsDashboard {
    config: DashboardConfig,
}

impl MetricsDashboard {
    pub const fn new(config: DashboardConfig) -> Self {
        Self { config }
    }

    /// Generate dashboard JSON for Grafana/similar tools
    pub fn generate_grafana_json(&self) -> Result<String> {
        let dashboard = serde_json::json!({
            "dashboard": {
                "title": self.config.name,
                "description": self.config.description,
                "refresh": format!("{}s", self.config.refresh_interval_seconds),
                "panels": self.config.widgets.iter().map(|w| {
                    serde_json::json!({
                        "id": w.id,
                        "title": w.title,
                        "type": match w.widget_type {
                            WidgetType::LineChart => "graph",
                            WidgetType::Histogram => "histogram",
                            WidgetType::Gauge => "gauge",
                            WidgetType::Counter => "stat",
                            WidgetType::Table => "table",
                            WidgetType::Heatmap => "heatmap",
                        },
                        "gridPos": {
                            "h": w.position.height,
                            "w": w.position.width,
                            "x": w.position.column,
                            "y": w.position.row
                        }
                    })
                }).collect::<Vec<_>>()
            }
        });

        Ok(serde_json::to_string_pretty(&dashboard)?)
    }
}

/// Create default HFT ML dashboard
pub fn create_hft_ml_dashboard() -> DashboardConfig {
    DashboardConfig {
        name: "HFT ML Performance".to_owned(),
        description: "Real-time monitoring of ML models in HFT trading environment".to_owned(),
        refresh_interval_seconds: 5,
        widgets: vec![
            DashboardWidget {
                id: "inference_latency".to_owned(),
                title: "Inference Latency (us)".to_owned(),
                widget_type: WidgetType::LineChart,
                metrics: vec!["ml_inference_latency_microseconds".to_owned()],
                time_range_minutes: 15,
                position: WidgetPosition {
                    row: 0,
                    column: 0,
                    width: 12,
                    height: 6,
                },
            },
            DashboardWidget {
                id: "prediction_rate".to_owned(),
                title: "Predictions per Second".to_owned(),
                widget_type: WidgetType::LineChart,
                metrics: vec!["ml_predictions_total".to_owned()],
                time_range_minutes: 15,
                position: WidgetPosition {
                    row: 6,
                    column: 0,
                    width: 6,
                    height: 6,
                },
            },
            DashboardWidget {
                id: "error_rate".to_owned(),
                title: "Error Rate".to_owned(),
                widget_type: WidgetType::Gauge,
                metrics: vec!["ml_error_rate".to_owned()],
                time_range_minutes: 15,
                position: WidgetPosition {
                    row: 6,
                    column: 6,
                    width: 6,
                    height: 6,
                },
            },
        ],
    }
}