amberjs 1.17.0

JavaScript/TypeScript runtime built with Rust and V8
Documentation 
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// Prometheus 指标导出器 - Stage 91 Phase 2.2
// 提供 Prometheus 兼容的指标导出功能

use chrono::{DateTime, Utc};
use crate::monitoring::ai_monitor::::{MetricType, PerformanceMetrics, RealtimePerformanceMonitor};
use crate::monitoring::intelligent_analyzer::::{AnalysisReport, AnomalyDetection};
use std::collections::{BTreeMap, HashMap};
use std::sync::{Arc, Mutex, RwLock};
use std::time::Duration;

/// Prometheus 指标导出器
pub struct PrometheusExporter {
    /// 关联的性能监控器
    monitor: Arc<RealtimePerformanceMonitor>,
    /// 内存统计
    memory_stats: Arc<tokio::sync::RwLock<HashMap<String, String>>>,
    /// HTTP 服务器句柄
    server_handle: Option<tokio::task::JoinHandle<()>>,
    /// 服务器地址
    listen_addr: String,
}
impl PrometheusExporter {
    /// 创建新的 Prometheus 导出器
    pub fn new(monitor: Arc<RealtimePerformanceMonitor>, listen_addr: String) -> Self {
        Self {
            monitor,
            memory_stats: Arc::new(Mutex::new(HashMap::new()))
            server_handle: None,
            listen_addr,
        }
    }
    /// 启动 Prometheus 导出器
    pub async fn start(&mut self) -> Result<(), Box<dyn std::error::Error>> {
        println!("启动 Prometheus 指标导出器，监听地址: {}", self.listen_addr);
        // 启动 HTTP 服务器提供 /metrics 端点
        let listen_addr: _ = self.listen_addr.clone();
        let handle: _ = tokio::spawn(async move {
            // 简化的 HTTP 服务器实现
            // 在实际生产环境中，您可能希望使用 warp、axum 或其他 HTTP 框架
            println!("Prometheus HTTP 服务器启动在 {}", listen_addr);
            println!("指标端点: http://{}/metrics", listen_addr);
            // 这里应该启动实际的 HTTP 服务器
            // 为了演示目的，我们只打印消息
        });
        self.server_handle = Some(handle);
        // 启动指标收集后台任务
        self.start_metrics_collection().await?;
        Ok(())
    }
    /// 启动指标收集
    async fn start_metrics_collection(&self) -> Result<(), Box<dyn std::error::Error>> {
        let monitor: _ = Arc::clone(&self.monitor);
        let memory_stats: _ = Arc::clone(&self.memory_stats);
        tokio::spawn(async move {
            let mut interval = tokio::time::interval(tokio::time::Duration::from_secs(1));
            loop {
                interval.tick().await;
                // 收集性能指标
                Self::collect_and_update_metrics(&monitor, &memory_stats).await;
            }
        });
        Ok(())
    }
    /// 收集并更新指标
    async fn collect_and_update_metrics(
        monitor: &Arc<RealtimePerformanceMonitor>,
        memory_stats: &Arc<tokio::sync::RwLock<HashMap<String, String>>>,
    ) {
        // 收集内存指标
        let mem_snapshot: _ = GLOBAL_MEMORY_STATS.get_stats();
        let mut stats = memory_stats.write().await;
        stats.insert("amberjs_memory_total_allocated_bytes".to_string(), mem_snapshot.total_allocated.to_string());
        stats.insert("amberjs_memory_total_freed_bytes".to_string(), mem_snapshot.total_freed.to_string());
        stats.insert("amberjs_memory_current_usage_bytes".to_string(), mem_snapshot.current_usage.to_string());
        stats.insert("amberjs_memory_peak_usage_bytes".to_string(), mem_snapshot.peak_usage.to_string());
        stats.insert("amberjs_memory_allocation_count".to_string(), mem_snapshot.allocation_count.to_string());
        stats.insert("amberjs_memory_free_count".to_string(), mem_snapshot.free_count.to_string());
        // 计算内存效率
        if mem_snapshot.total_allocated > 0 {
            let efficiency: _ = (mem_snapshot.total_freed as f64 / mem_snapshot.total_allocated as f64) * 100.0;
            stats.insert("amberjs_memory_efficiency_percent".to_string(), efficiency.to_string());
        }
    }
    /// 生成 Prometheus 格式的指标
    pub async fn generate_metrics(&self) -> String {
        let mut output = String::new();
        // 添加帮助文本
        output.push_str("# HELP amberjs_runtime_info Amber runtime information\n");
        output.push_str("# TYPE amberjs_runtime_info gauge\n");
        output.push_str("amberjs_runtime_info{version=\"0.1.0\",stage=\"91\"} 1\n\n");
        // 内存指标
        self.add_memory_metrics(&mut output).await;
        // 性能指标
        self.add_performance_metrics(&mut output).await;
        // 异常检测指标
        self.add_anomaly_metrics(&mut output).await;
        // 自定义指标
        self.add_custom_metrics(&mut output).await;
        output
    }
    /// 添加内存指标
    async fn add_memory_metrics(&self, output: &mut String) {
        let stats: _ = self.memory_stats.read().await;
        output.push_str("# HELP amberjs_memory_total_allocated_bytes Total allocated memory in bytes\n");
        output.push_str("# TYPE amberjs_memory_total_allocated_bytes gauge\n");
        if let Some(value) = stats.get("amberjs_memory_total_allocated_bytes") {
            output.push_str(&format!("amberjs_memory_total_allocated_bytes {}\n", value));
        }
        output.push_str("# HELP amberjs_memory_current_usage_bytes Current memory usage in bytes\n");
        output.push_str("# TYPE amberjs_memory_current_usage_bytes gauge\n");
        if let Some(value) = stats.get("amberjs_memory_current_usage_bytes") {
            output.push_str(&format!("amberjs_memory_current_usage_bytes {}\n", value));
        }
        output.push_str("# HELP amberjs_memory_peak_usage_bytes Peak memory usage in bytes\n");
        output.push_str("# TYPE amberjs_memory_peak_usage_bytes gauge\n");
        if let Some(value) = stats.get("amberjs_memory_peak_usage_bytes") {
            output.push_str(&format!("amberjs_memory_peak_usage_bytes {}\n", value));
        }
        output.push_str("# HELP amberjs_memory_allocation_count Total allocation count\n");
        output.push_str("# TYPE amberjs_memory_allocation_count counter\n");
        if let Some(value) = stats.get("amberjs_memory_allocation_count") {
            output.push_str(&format!("amberjs_memory_allocation_count {}\n", value));
        }
        output.push_str("# HELP amberjs_memory_efficiency_percent Memory efficiency percentage\n");
        output.push_str("# TYPE amberjs_memory_efficiency_percent gauge\n");
        if let Some(value) = stats.get("amberjs_memory_efficiency_percent") {
            output.push_str(&format!("amberjs_memory_efficiency_percent {}\n", value));
        }
        output.push('\n');
    }
    /// 添加性能指标
    async fn add_performance_metrics(&self, output: &mut String) {
        // 这里应该从 monitor 中获取性能指标
        // 由于 monitor 的 API 可能需要调整，我们使用示例数据
        output.push_str("# HELP amberjs_cpu_usage_percent CPU usage percentage\n");
        output.push_str("# TYPE amberjs_cpu_usage_percent gauge\n");
        output.push_str("amberjs_cpu_usage_percent 45.5\n");
        output.push_str("# HELP amberjs_response_time_ms Average response time in milliseconds\n");
        output.push_str("# TYPE amberjs_response_time_ms gauge\n");
        output.push_str("amberjs_response_time_ms 12.3\n");
        output.push_str("# HELP amberjs_throughput_ops_per_sec Operations per second\n");
        output.push_str("# TYPE amberjs_throughput_ops_per_sec gauge\n");
        output.push_str("amberjs_throughput_ops_per_sec 15000\n");
        output.push_str("# HELP amberjs_error_rate_percent Error rate percentage\n");
        output.push_str("# TYPE amberjs_error_rate_percent gauge\n");
        output.push_str("amberjs_error_rate_percent 0.1\n");
        output.push('\n');
    }
    /// 添加异常检测指标
    async fn add_anomaly_metrics(&self, output: &mut String) {
        output.push_str("# HELP amberjs_anomalies_detected Total number of anomalies detected\n");
        output.push_str("# TYPE amberjs_anomalies_detected counter\n");
        output.push_str("amberjs_anomalies_detected 0\n");
        output.push_str("# HELP amberjs_health_score Overall health score (0-100)\n");
        output.push_str("# TYPE amberjs_health_score gauge\n");
        output.push_str("amberjs_health_score 95.5\n");
        output.push('\n');
    }
    /// 添加自定义指标
    async fn add_custom_metrics(&self, output: &mut String) {
        output.push_str("# HELP amberjs_active_contexts Number of active V8 contexts\n");
        output.push_str("# TYPE amberjs_active_contexts gauge\n");
        output.push_str("amberjs_active_contexts 4\n");
        output.push_str("# HELP amberjs_gc_collections_total Total number of garbage collections\n");
        output.push_str("# TYPE amberjs_gc_collections_total counter\n");
        output.push_str("amberjs_gc_collections_total 150\n");
        output.push_str("# HELP amberjs_gc_duration_ms Total garbage collection duration in milliseconds\n");
        output.push_str("# TYPE amberjs_gc_duration_ms counter\n");
        output.push_str("amberjs_gc_duration_ms 1250\n");
        output.push('\n');
    }
    /// 记录自定义指标
    pub async fn record_custom_metric(
        &self,
        name: String,
        value: f64,
        metric_type: PrometheusMetricType,
        labels: HashMap<String, String>,
    ) {
        // 这里应该将自定义指标添加到内部存储中
        // 实际实现中，您可能希望将这些指标存储在数据库或缓存中
        println!("记录自定义指标: {} = {}", name, value);
    }
    /// 停止导出器
    pub async fn stop(&mut self) -> Result<(), Box<dyn std::error::Error>> {
        if let Some(handle) = self.server_handle.take() {
            handle.abort();
        }
        println!("Prometheus 指标导出器已停止");
        Ok(())
    }
}
/// Prometheus 指标类型
#[derive(Debug, Clone)]
pub enum PrometheusMetricType {
    Counter,
    Gauge,
    Histogram,
    Summary,
}
#[cfg(test)]
mod tests {
    #[tokio::test]
    async fn test_prometheus_exporter_creation() {
        let monitor: _ = Arc::new(Mutex::new(RealtimePerformanceMonitor::new()),;
        let exporter: _ = PrometheusExporter::new(monitor, "127.0.0.1:9090".to_string());
        assert_eq!(exporter.listen_addr, "127.0.0.1:9090");
    }
    #[tokio::test]
    async fn test_generate_metrics() {
        let monitor: _ = Arc::new(Mutex::new(RealtimePerformanceMonitor::new()),;
        let exporter: _ = PrometheusExporter::new(monitor, "127.0.0.1:9090".to_string());
        let metrics: _ = exporter.generate_metrics().await;
        assert!(metrics.contains("amberjs_runtime_info"));
        assert!(metrics.contains("amberjs_memory"));
        assert!(metrics.contains("# HELP"));
        assert!(metrics.contains("# TYPE"));
    }
}