amberjs 1.17.0

// Kubernetes 集群管理器
// 实现 Amber 集群的 Kubernetes 部署、管理和运维功能


use anyhow::{Result, Context};
use serde::{Deserialize, Serialize};
/// 集群配置结构体
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ClusterConfig {
    pub min_replicas: i32,
    pub max_replicas: i32,
    pub cpu_threshold: f64,
    pub memory_threshold: f64,
    pub namespace: String,
    pub image: String,
    pub version: String,
}
impl Default for ClusterConfig {
    fn default() -> Self {
        Self {
            min_replicas: 2,
            max_replicas: 10,
            cpu_threshold: 70.0,
            memory_threshold: 80.0,
            namespace: "amberjs".to_string(),
            image: "amberjs:latest".to_string(),
            version: "v0.1.0".to_string(),
        }
    }
}
/// 集群句柄
#[derive(Debug, Clone)]
pub struct ClusterHandle {
    pub namespace: String,
    pub replicas: i32,
    pub status: ClusterStatus,
}
/// 集群状态
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub enum ClusterStatus {
    Creating,
    Running,
    Scaling,
    Updating,
    Error(String),
    Terminating,
}
/// 健康状态
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum HealthStatus {
    Healthy,
    Unhealthy(String),
    Unknown,
}
/// 集群指标
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ClusterMetrics {
    pub cpu_usage: f64,
    pub memory_usage: f64,
    pub request_rate: f64,
    pub active_connections: u64,
    pub timestamp: std::time::SystemTime,
}
impl ClusterMetrics {
    pub fn new() -> Self {
        Self {
            cpu_usage: 0.0,
            memory_usage: 0.0,
            request_rate: 0.0,
            active_connections: 0,
            timestamp: std::time::SystemTime::now(),
        }
    }
}
/// K8sManager 结构体
pub struct K8sManager {
    pub namespace: String,
    // 实际实现中会包含 kube::Client
    // client: kube::Client,
}
impl K8sManager {
    /// 创建新的 K8sManager
    pub fn new(namespace: String) -> Self {
        Self { namespace }
    }
    /// 部署集群到 Kubernetes
    pub async fn deploy_cluster(&self, config: &ClusterConfig) -> Result<ClusterHandle> {
        // 模拟集群部署
        // 实际实现中会：
        // 1. 创建 Namespace
        // 2. 创建 ConfigMap
        // 3. 部署 StatefulSet
        // 4. 配置 Service
        // 5. 设置 HPA
        let handle: _ = ClusterHandle {
            namespace: config.namespace.clone(),
            replicas: config.min_replicas,
            status: ClusterStatus::Running,
        };
        tracing::info!(
            "Deployed Amber cluster with {} replicas in namespace {}",
            config.min_replicas,
            config.namespace
        );
        Ok(handle)
    }
    /// 自动扩缩容
    pub async fn auto_scale(&self, metrics: &ClusterMetrics) -> Result<i32> {
        // 简化的扩缩容逻辑
        // 实际实现中会根据指标和策略进行智能扩缩容
        let current_replicas: _ = self.get_current_replicas().await?;
        let mut new_replicas = current_replicas;
        // 扩容条件：CPU 或内存使用率超过阈值
        if metrics.cpu_usage > 70.0 || metrics.memory_usage > 80.0 {
            if current_replicas < 10 {
                new_replicas += 1;
                tracing::info!("Scaling up: CPU {:.1}%, Memory {:.1}%", metrics.cpu_usage, metrics.memory_usage);
            }
        }
        // 缩容条件：CPU 和内存使用率都低于 50%
        else if metrics.cpu_usage < 35.0 && metrics.memory_usage < 40.0 {
            if current_replicas > 2 {
                new_replicas -= 1;
                tracing::info!("Scaling down: CPU {:.1}%, Memory {:.1}%", metrics.cpu_usage, metrics.memory_usage);
            }
        }
        if new_replicas != current_replicas {
            self.scale_to(new_replicas).await?;
        }
        Ok(new_replicas)
    }
    /// 检查节点健康状态
    pub async fn check_node_health(&self, node_id: &str) -> Result<HealthStatus> {
        // 模拟健康检查
        // 实际实现中会查询 Kubernetes API
        tracing::debug!("Checking health for node {}", node_id);
        // 模拟检查结果
        // 实际实现中会检查 Pod 状态、Ready 状态等
        Ok(HealthStatus::Healthy)
    }
    /// 获取当前副本数
    async fn get_current_replicas(&self) -> Result<i32> {
        // 模拟获取当前副本数
        // 实际实现中会查询 Kubernetes Deployment/ReplicaSet
        Ok(3) // 默认返回 3
    }
    /// 执行扩缩容
    async fn scale_to(&self, replicas: i32) -> Result<()> {
        tracing::info!("Scaling cluster to {} replicas", replicas);
        // 实际实现中会更新 Kubernetes Deployment
        Ok(())
    }
    /// 更新集群
    pub async fn update_cluster(&self, new_version: &str) -> Result<()> {
        tracing::info!("Updating cluster to version {}", new_version);
        // 实际实现中会执行滚动更新
        Ok(())
    }
    /// 删除集群
    pub async fn delete_cluster(&self) -> Result<()> {
        tracing::info!("Deleting cluster in namespace {}", self.namespace);
        // 实际实现中会删除所有相关资源
        Ok(())
    }
    /// 获取集群状态
    pub async fn get_cluster_status(&self) -> Result<ClusterStatus> {
        // 模拟获取集群状态
        Ok(ClusterStatus::Running)
    }
    /// 配置 HPA (Horizontal Pod Autoscaler)
    pub async fn configure_hpa(&self, config: &ClusterConfig) -> Result<()> {
        tracing::info!(
            "Configuring HPA: min_replicas={}, max_replicas={}, cpu_threshold={}%",
            config.min_replicas,
            config.max_replicas,
            config.cpu_threshold
        );
        // 实际实现中会创建或更新 HPA 资源
        Ok(())
    }
    /// 获取集群指标
    pub async fn collect_metrics(&self) -> Result<ClusterMetrics> {
        // 模拟指标收集
        // 实际实现中会从 Prometheus 或 Kubernetes Metrics API 获取
        let mut metrics = ClusterMetrics::new();
        // 模拟随机指标值
        use rand::Rng;
        let mut rng = rand::rng();
        metrics.cpu_usage = rng.random_range(20.0..80.0);
        metrics.memory_usage = rng.random_range(30.0..90.0);
        metrics.request_rate = rng.random_range(100.0..2000.0);
        metrics.active_connections = rng.random_range(10..1000);
        Ok(metrics)
    }
    /// 执行故障转移
    pub async fn failover(&self, failed_node: &str) -> Result<()> {
        tracing::warn!("Executing failover for failed node {}", failed_node);
        // 实际实现中会：
        // 1. 标记失败节点
        // 2. 在其他节点上重启服务
        // 3. 更新服务发现
        Ok(())
    }
    /// 滚动更新
    pub async fn rolling_update(&self, new_version: &str) -> Result<()> {
        tracing::info!("Starting rolling update to version {}", new_version);
        // 实际实现中会执行滚动更新策略：
        // 1. 逐个更新 Pod
        // 2. 等待新 Pod 就绪
        // 3. 继续下一个 Pod
        Ok(())
    }
}
#[cfg(test)]
mod tests {
    use super::*;
use std::collections::{HashMap, BTreeMap};
use tracing::{debug, info, warn, error};
use std::time::SystemTime;
    #[tokio::test]
    async fn test_create_k8s_manager() {
        let manager: _ = K8sManager::new("test-namespace".to_string());
        assert_eq!(manager.namespace, "test-namespace");
    }
    #[tokio::test]
    async fn test_deploy_cluster() {
        let manager: _ = K8sManager::new("amberjs".to_string());
        let config: _ = ClusterConfig::default();
        let handle: _ = manager.deploy_cluster(&config).await.unwrap();
        assert_eq!(handle.namespace, "amberjs");
        assert_eq!(handle.status, ClusterStatus::Running);
    }
    #[tokio::test]
    async fn test_auto_scale_up() {
        let manager: _ = K8sManager::new("amberjs".to_string());
        let high_load_metrics: _ = ClusterMetrics {
            cpu_usage: 85.0,
            memory_usage: 90.0,
            request_rate: 2000.0,
            active_connections: 500,
            timestamp: std::time::SystemTime::now(),
        };
        let new_replicas: _ = manager.auto_scale(&high_load_metrics).await.unwrap();
        assert!(new_replicas > 3); // 应该扩容
    }
    #[tokio::test]
    async fn test_auto_scale_down() {
        let manager: _ = K8sManager::new("amberjs".to_string());
        let low_load_metrics: _ = ClusterMetrics {
            cpu_usage: 25.0,
            memory_usage: 30.0,
            request_rate: 50.0,
            active_connections: 10,
            timestamp: std::time::SystemTime::now(),
        };
        let new_replicas: _ = manager.auto_scale(&low_load_metrics).await.unwrap();
        assert!(new_replicas < 3); // 应该缩容
    }
    #[tokio::test]
    async fn test_health_check() {
        let manager: _ = K8sManager::new("amberjs".to_string());
        let health: _ = manager.check_node_health("amberjs-node-1").await.unwrap();
        match health {
            HealthStatus::Healthy => {}
            _ => panic!("Expected healthy status"),
        }
    }
    #[tokio::test]
    async fn test_cluster_config_default() {
        let config: _ = ClusterConfig::default();
        assert_eq!(config.min_replicas, 2);
        assert_eq!(config.max_replicas, 10);
        assert_eq!(config.cpu_threshold, 70.0);
    }
    #[tokio::test]
    async fn test_metrics_collection() {
        let manager: _ = K8sManager::new("amberjs".to_string());
        let metrics: _ = manager.collect_metrics().await.unwrap();
        assert!(metrics.cpu_usage >= 0.0 && metrics.cpu_usage <= 100.0);
        assert!(metrics.memory_usage >= 0.0 && metrics.memory_usage <= 100.0);
        assert!(metrics.request_rate >= 0.0);
    }
}