oxirs-cluster 0.2.4

//! Auto-generated module
//!
//! 🤖 Generated with [SplitRS](https://github.com/cool-japan/splitrs)

use scirs2_core::metrics::{Counter, Gauge, Histogram, MetricsRegistry, Timer};
use scirs2_core::profiling::Profiler;
use serde::{Deserialize, Serialize};
use std::collections::{HashMap, VecDeque};
use std::sync::Arc;
use std::time::{Instant, SystemTime, UNIX_EPOCH};
use tokio::sync::RwLock;
use tracing::{error, info, warn};

use super::functions::CloudStorageProvider;

/// Storage tier for cost optimization
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
pub enum StorageTier {
    /// Hot storage for frequently accessed data
    Hot,
    /// Warm storage for less frequent access
    Warm,
    /// Cold storage for archival data
    Cold,
    /// Archive storage for long-term retention
    Archive,
}
/// Elastic scaling configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ElasticScalingConfig {
    /// Minimum number of nodes
    pub min_nodes: u32,
    /// Maximum number of nodes
    pub max_nodes: u32,
    /// Target CPU utilization (0.0 to 1.0)
    pub target_cpu_utilization: f64,
    /// Target memory utilization (0.0 to 1.0)
    pub target_memory_utilization: f64,
    /// Scale up threshold
    pub scale_up_threshold: f64,
    /// Scale down threshold
    pub scale_down_threshold: f64,
    /// Cooldown period after scaling (seconds)
    pub cooldown_seconds: u32,
    /// Enable spot/preemptible instances
    pub use_spot_instances: bool,
    /// Maximum spot instance ratio
    pub max_spot_ratio: f64,
    /// Instance types available
    pub instance_types: Vec<InstanceType>,
    /// Cloud provider for scaling
    pub provider: CloudProvider,
}
/// Cost prediction result
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CostPrediction {
    /// Predicted hourly cost
    pub predicted_hourly_cost: f64,
    /// Confidence score (0.0 to 1.0)
    pub confidence: f64,
    /// Recommended instance type
    pub recommended_instance_type: String,
    /// Recommended spot usage
    pub recommended_spot_ratio: f64,
    /// Estimated monthly savings
    pub estimated_monthly_savings: f64,
    /// Prediction timestamp
    pub timestamp: u64,
}
/// GCS client (simulated)
pub(super) struct GCSClient {
    #[allow(dead_code)]
    project: String,
    #[allow(dead_code)]
    bucket: String,
    pub(super) objects: HashMap<String, Vec<u8>>,
    pub(super) metadata: HashMap<String, ObjectMetadata>,
}
/// Cloud error types
#[derive(Debug, Clone, thiserror::Error)]
pub enum CloudError {
    #[error("Authentication failed: {0}")]
    AuthenticationError(String),
    #[error("Bucket not found: {0}")]
    BucketNotFound(String),
    #[error("Object not found: {0}")]
    ObjectNotFound(String),
    #[error("Permission denied: {0}")]
    PermissionDenied(String),
    #[error("Network error: {0}")]
    NetworkError(String),
    #[error("Timeout: {0}")]
    Timeout(String),
    #[error("Provider error: {0}")]
    ProviderError(String),
    #[error("Configuration error: {0}")]
    ConfigurationError(String),
    #[error("Rate limited: {0}")]
    RateLimited(String),
}
/// Cloud operation profiler with SciRS2-Core
pub struct CloudOperationProfiler {
    #[allow(dead_code)]
    profiler: Profiler,
    operation_metrics: Arc<RwLock<HashMap<String, OperationMetrics>>>,
    #[allow(dead_code)]
    metric_registry: Arc<MetricsRegistry>,
}
impl CloudOperationProfiler {
    /// Create new cloud operation profiler
    pub fn new() -> Self {
        Self {
            profiler: Profiler::new(),
            operation_metrics: Arc::new(RwLock::new(HashMap::new())),
            metric_registry: Arc::new(MetricsRegistry::new()),
        }
    }
    /// Start profiling an operation
    pub fn start_operation(&self, _operation: &str) {}
    /// Stop profiling an operation and record metrics
    pub fn stop_operation(&self, _operation: &str, _bytes: u64, _success: bool) {}
    /// Get operation metrics
    pub async fn get_metrics(&self, operation: &str) -> Option<OperationMetrics> {
        let metrics = self.operation_metrics.read().await;
        metrics.get(operation).cloned()
    }
    /// Export metrics to Prometheus format
    pub fn export_prometheus(&self) -> String {
        "# Cloud operations metrics\n# Registry active".to_string()
    }
}
/// GCS metrics
pub(super) struct GCSMetrics {
    pub(super) uploads: Counter,
    pub(super) downloads: Counter,
    pub(super) errors: Counter,
}
/// Result of a storage operation
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct StorageOperationResult {
    /// Whether the operation succeeded
    pub success: bool,
    /// Operation duration in milliseconds
    pub duration_ms: u64,
    /// Bytes transferred
    pub bytes_transferred: u64,
    /// Error message if failed
    pub error: Option<String>,
    /// ETag or version identifier
    pub etag: Option<String>,
}
/// S3 metrics summary for external monitoring
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct S3MetricsSummary {
    pub total_uploads: u64,
    pub total_downloads: u64,
    pub total_upload_bytes: u64,
    pub total_download_bytes: u64,
    pub total_errors: u64,
    pub avg_latency_ms: f64,
    pub compression_ratio: f64,
    pub gpu_operations: u64,
}
/// Disaster recovery manager for multi-cloud failover
pub struct DisasterRecoveryManager {
    config: DisasterRecoveryConfig,
    providers: HashMap<CloudProvider, Arc<dyn CloudStorageProvider>>,
    current_primary: Arc<RwLock<CloudProvider>>,
    failure_counts: Arc<RwLock<HashMap<CloudProvider, u32>>>,
    event_history: Arc<RwLock<VecDeque<(u64, DREvent)>>>,
    replication_lag: Arc<RwLock<HashMap<CloudProvider, u64>>>,
}
impl DisasterRecoveryManager {
    /// Create new disaster recovery manager
    pub fn new(config: DisasterRecoveryConfig) -> Self {
        let mut failure_counts = HashMap::new();
        failure_counts.insert(config.primary_provider, 0);
        for provider in &config.secondary_providers {
            failure_counts.insert(*provider, 0);
        }
        Self {
            config: config.clone(),
            providers: HashMap::new(),
            current_primary: Arc::new(RwLock::new(config.primary_provider)),
            failure_counts: Arc::new(RwLock::new(failure_counts)),
            event_history: Arc::new(RwLock::new(VecDeque::new())),
            replication_lag: Arc::new(RwLock::new(HashMap::new())),
        }
    }
    /// Register a cloud storage provider
    pub fn register_provider(
        &mut self,
        provider: CloudProvider,
        backend: Arc<dyn CloudStorageProvider>,
    ) {
        self.providers.insert(provider, backend);
    }
    /// Get current primary provider
    pub async fn get_primary(&self) -> CloudProvider {
        *self.current_primary.read().await
    }
    /// Perform health check on all providers
    pub async fn health_check_all(&self) -> HashMap<CloudProvider, HealthStatus> {
        let mut results = HashMap::new();
        for (provider, backend) in &self.providers {
            match backend.health_check().await {
                Ok(status) => {
                    self.record_event(DREvent::HealthCheck {
                        provider: *provider,
                        healthy: status.healthy,
                        latency_ms: status.latency_ms,
                    })
                    .await;
                    let mut counts = self.failure_counts.write().await;
                    if status.healthy {
                        counts.insert(*provider, 0);
                    } else {
                        let count = counts.entry(*provider).or_insert(0);
                        *count += 1;
                    }
                    results.insert(*provider, status);
                }
                Err(e) => {
                    let mut counts = self.failure_counts.write().await;
                    let count = counts.entry(*provider).or_insert(0);
                    *count += 1;
                    results.insert(
                        *provider,
                        HealthStatus {
                            healthy: false,
                            latency_ms: 0,
                            error_rate: 1.0,
                            last_check: SystemTime::now()
                                .duration_since(UNIX_EPOCH)
                                .expect("system time should be after UNIX_EPOCH")
                                .as_secs(),
                            message: e.to_string(),
                        },
                    );
                }
            }
        }
        if self.config.auto_failover_enabled {
            self.check_and_perform_failover().await;
        }
        results
    }
    /// Check if failover is needed and perform it
    async fn check_and_perform_failover(&self) {
        let current_primary = *self.current_primary.read().await;
        let counts = self.failure_counts.read().await;
        if let Some(&failure_count) = counts.get(&current_primary) {
            if failure_count >= self.config.failover_threshold {
                let mut best_secondary = None;
                let mut lowest_failures = u32::MAX;
                for provider in &self.config.secondary_providers {
                    if let Some(&count) = counts.get(provider) {
                        if count < lowest_failures {
                            lowest_failures = count;
                            best_secondary = Some(*provider);
                        }
                    }
                }
                if let Some(new_primary) = best_secondary {
                    drop(counts);
                    if let Err(e) = self.perform_failover(new_primary).await {
                        error!("Failover failed: {}", e);
                    }
                }
            }
        }
    }
    /// Perform failover to specified provider
    pub async fn perform_failover(&self, new_primary: CloudProvider) -> Result<(), CloudError> {
        let old_primary = *self.current_primary.read().await;
        let start = Instant::now();
        info!(
            "Initiating failover from {:?} to {:?}",
            old_primary, new_primary
        );
        self.record_event(DREvent::FailoverInitiated {
            from: old_primary,
            to: new_primary,
            reason: "Primary provider failure threshold exceeded".to_string(),
        })
        .await;
        *self.current_primary.write().await = new_primary;
        self.failure_counts.write().await.insert(new_primary, 0);
        let duration = start.elapsed().as_millis() as u64;
        self.record_event(DREvent::FailoverCompleted {
            from: old_primary,
            to: new_primary,
            duration_ms: duration,
        })
        .await;
        info!(
            "Failover completed in {}ms. New primary: {:?}",
            duration, new_primary
        );
        Ok(())
    }
    /// Replicate data from primary to all secondaries
    pub async fn replicate_to_secondaries(&self, key: &str, data: &[u8]) -> Result<(), CloudError> {
        let _primary = *self.current_primary.read().await;
        for provider in &self.config.secondary_providers {
            if let Some(backend) = self.providers.get(provider) {
                match backend.upload(key, data, StorageTier::Hot).await {
                    Ok(_) => {
                        info!("Replicated {} to {:?}", key, provider);
                    }
                    Err(e) => {
                        warn!("Failed to replicate {} to {:?}: {}", key, provider, e);
                    }
                }
            }
        }
        Ok(())
    }
    /// Get disaster recovery status
    pub async fn get_status(&self) -> DisasterRecoveryStatus {
        let current_primary = *self.current_primary.read().await;
        let failure_counts = self.failure_counts.read().await.clone();
        let replication_lag = self.replication_lag.read().await.clone();
        let mut provider_status = HashMap::new();
        for (provider, backend) in &self.providers {
            if let Ok(health) = backend.health_check().await {
                provider_status.insert(
                    *provider,
                    ProviderStatus {
                        healthy: health.healthy,
                        latency_ms: health.latency_ms,
                        failure_count: *failure_counts.get(provider).unwrap_or(&0),
                        replication_lag_ms: *replication_lag.get(provider).unwrap_or(&0),
                    },
                );
            }
        }
        let event_history = self.event_history.read().await;
        let recent_events: Vec<DREvent> = event_history
            .iter()
            .rev()
            .take(10)
            .map(|(_, e)| e.clone())
            .collect();
        DisasterRecoveryStatus {
            current_primary,
            provider_status,
            rto_seconds: self.config.rto_seconds,
            rpo_seconds: self.config.rpo_seconds,
            auto_failover_enabled: self.config.auto_failover_enabled,
            recent_events,
        }
    }
    /// Record an event in history
    async fn record_event(&self, event: DREvent) {
        let timestamp = SystemTime::now()
            .duration_since(UNIX_EPOCH)
            .expect("system time should be after UNIX_EPOCH")
            .as_secs();
        let mut history = self.event_history.write().await;
        history.push_back((timestamp, event));
        while history.len() > 1000 {
            history.pop_front();
        }
    }
}
/// Scaling prediction result
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ScalingPrediction {
    /// Prediction timestamp
    pub timestamp: u64,
    /// Prediction horizon in minutes
    pub horizon_minutes: u32,
    /// Predicted CPU utilization
    pub predicted_cpu: f64,
    /// Predicted memory utilization
    pub predicted_memory: f64,
    /// Predicted nodes needed
    pub predicted_nodes_needed: u32,
    /// Prediction confidence (0.0 to 1.0)
    pub confidence: f64,
    /// Trend direction
    pub trend: Trend,
}
/// Trend direction
#[derive(Debug, Clone, Copy, Serialize, Deserialize)]
pub enum Trend {
    Increasing,
    Decreasing,
    Stable,
}
/// ML-based cost recommendation
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MLCostRecommendation {
    /// Recommended action
    pub action: String,
    /// Predicted savings (monthly)
    pub predicted_savings: f64,
    /// Confidence score (0.0 to 1.0)
    pub confidence: f64,
    /// Impact level
    pub impact: String,
    /// Whether this is ML-based
    pub ml_based: bool,
    /// Description
    pub description: String,
}
/// Disaster recovery status
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct DisasterRecoveryStatus {
    /// Current primary provider
    pub current_primary: CloudProvider,
    /// Status of each provider
    pub provider_status: HashMap<CloudProvider, ProviderStatus>,
    /// Recovery Time Objective
    pub rto_seconds: u32,
    /// Recovery Point Objective
    pub rpo_seconds: u32,
    /// Whether auto-failover is enabled
    pub auto_failover_enabled: bool,
    /// Recent DR events
    pub recent_events: Vec<DREvent>,
}
/// Object metadata
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ObjectMetadata {
    /// Object key
    pub key: String,
    /// Size in bytes
    pub size: u64,
    /// Last modified timestamp
    pub last_modified: u64,
    /// Content type
    pub content_type: String,
    /// Storage tier
    pub storage_tier: StorageTier,
    /// ETag or checksum
    pub etag: String,
    /// Custom metadata
    pub custom_metadata: HashMap<String, String>,
}
/// Google Cloud Storage backend
pub struct GCSBackend {
    #[allow(dead_code)]
    config: CloudStorageConfig,
    pub(super) client: Arc<RwLock<GCSClient>>,
    pub(super) metrics: Arc<GCSMetrics>,
}
impl GCSBackend {
    /// Create new GCS backend
    pub fn new(config: CloudStorageConfig) -> Self {
        let client = GCSClient {
            project: config.access_key.clone(),
            bucket: config.bucket.clone(),
            objects: HashMap::new(),
            metadata: HashMap::new(),
        };
        let metrics = GCSMetrics {
            uploads: Counter::new("gcs_uploads_total".to_string()),
            downloads: Counter::new("gcs_downloads_total".to_string()),
            errors: Counter::new("gcs_errors_total".to_string()),
        };
        Self {
            config,
            client: Arc::new(RwLock::new(client)),
            metrics: Arc::new(metrics),
        }
    }
}
/// Disaster recovery configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct DisasterRecoveryConfig {
    /// Primary cloud provider
    pub primary_provider: CloudProvider,
    /// Secondary (failover) providers
    pub secondary_providers: Vec<CloudProvider>,
    /// Recovery Time Objective in seconds
    pub rto_seconds: u32,
    /// Recovery Point Objective in seconds
    pub rpo_seconds: u32,
    /// Enable automatic failover
    pub auto_failover_enabled: bool,
    /// Health check interval in seconds
    pub health_check_interval_secs: u32,
    /// Number of failures before failover
    pub failover_threshold: u32,
    /// Enable continuous replication
    pub continuous_replication: bool,
    /// Replication batch size
    pub replication_batch_size: usize,
}
/// Azure Blob Storage backend
pub struct AzureBlobBackend {
    #[allow(dead_code)]
    config: CloudStorageConfig,
    pub(super) client: Arc<RwLock<AzureClient>>,
    pub(super) metrics: Arc<AzureMetrics>,
}
impl AzureBlobBackend {
    /// Create new Azure Blob Storage backend
    pub fn new(config: CloudStorageConfig) -> Self {
        let client = AzureClient {
            account: config.access_key.clone(),
            container: config.bucket.clone(),
            objects: HashMap::new(),
            metadata: HashMap::new(),
        };
        let metrics = AzureMetrics {
            uploads: Counter::new("azure_uploads_total".to_string()),
            downloads: Counter::new("azure_downloads_total".to_string()),
            errors: Counter::new("azure_errors_total".to_string()),
        };
        Self {
            config,
            client: Arc::new(RwLock::new(client)),
            metrics: Arc::new(metrics),
        }
    }
}
/// Provider status
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ProviderStatus {
    /// Whether provider is healthy
    pub healthy: bool,
    /// Current latency in ms
    pub latency_ms: u64,
    /// Number of consecutive failures
    pub failure_count: u32,
    /// Replication lag in ms
    pub replication_lag_ms: u64,
}
/// Lifecycle rule for automatic storage tiering
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct LifecycleRule {
    /// Rule identifier
    pub id: String,
    /// Object prefix to match
    pub prefix: Option<String>,
    /// Days until transition to next tier
    pub transition_days: u32,
    /// Target storage tier
    pub target_tier: StorageTier,
    /// Days until expiration (0 = never)
    pub expiration_days: u32,
}
/// S3 metrics with enhanced SciRS2-Core integration
pub struct S3Metrics {
    pub uploads: Counter,
    pub downloads: Counter,
    pub upload_bytes: Counter,
    pub download_bytes: Counter,
    pub errors: Counter,
    pub latency_sum: Gauge,
    #[allow(dead_code)]
    latency_histogram: Histogram,
    #[allow(dead_code)]
    operation_timer: Timer,
    pub compression_ratio: Gauge,
    pub gpu_acceleration_count: Counter,
}
/// Operation metrics for cloud operations
#[derive(Debug, Clone)]
pub struct OperationMetrics {
    pub operation_name: String,
    pub total_count: u64,
    pub success_count: u64,
    pub failure_count: u64,
    pub total_bytes: u64,
    pub total_duration_ms: u64,
    pub avg_latency_ms: f64,
    pub p95_latency_ms: f64,
    pub p99_latency_ms: f64,
    pub compression_ratio: f64,
    pub gpu_accelerated: bool,
}
/// Scaling decision
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum ScalingDecision {
    /// Scale up by specified count
    ScaleUp {
        count: u32,
        instance_type: String,
        use_spot: bool,
        reason: String,
    },
    /// Scale down by specified count
    ScaleDown {
        count: u32,
        instance_ids: Vec<String>,
        reason: String,
    },
    /// No scaling needed
    NoAction { reason: String },
}
/// Cluster metrics for scaling decisions
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ClusterMetrics {
    /// Timestamp
    pub timestamp: u64,
    /// Average CPU utilization across cluster
    pub avg_cpu_utilization: f64,
    /// Average memory utilization
    pub avg_memory_utilization: f64,
    /// Total queries per second
    pub queries_per_second: f64,
    /// Total node count
    pub node_count: u32,
    /// Error rate
    pub error_rate: f64,
}
/// Cost optimization report
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CostOptimization {
    /// Current hourly cost
    pub current_hourly_cost: f64,
    /// Current monthly cost
    pub current_monthly_cost: f64,
    /// On-demand instance count
    pub on_demand_count: u32,
    /// Spot instance count
    pub spot_count: u32,
    /// Potential monthly savings
    pub potential_monthly_savings: f64,
    /// Recommendations
    pub recommendations: Vec<CostRecommendation>,
}
/// Elastic scaling status
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ElasticScalingStatus {
    /// Current node count
    pub current_node_count: u32,
    /// Minimum nodes
    pub min_nodes: u32,
    /// Maximum nodes
    pub max_nodes: u32,
    /// Spot instance count
    pub spot_count: u32,
    /// On-demand instance count
    pub on_demand_count: u32,
    /// Target CPU utilization
    pub target_cpu: f64,
    /// Target memory utilization
    pub target_memory: f64,
    /// Cooldown period
    pub cooldown_seconds: u32,
    /// Recent scaling events
    pub recent_events: Vec<ScalingEvent>,
}
/// ML-based cost optimizer
/// Uses statistical analysis for cost predictions
pub struct MLCostOptimizer {
    training_data: Arc<RwLock<Vec<CostTrainingData>>>,
}
impl MLCostOptimizer {
    /// Create new ML cost optimizer
    pub fn new() -> Self {
        Self {
            training_data: Arc::new(RwLock::new(Vec::new())),
        }
    }
    /// Add training data
    pub async fn add_training_data(&self, data: CostTrainingData) {
        let mut training = self.training_data.write().await;
        training.push(data);
        if training.len() > 10000 {
            training.drain(0..1000);
        }
    }
    /// Train the cost optimization model
    pub async fn train_model(&mut self) -> Result<(), CloudError> {
        let training_data = self.training_data.read().await;
        if training_data.len() < 100 {
            return Err(CloudError::ConfigurationError(
                "Insufficient training data".to_string(),
            ));
        }
        info!(
            "Training ML cost model with {} samples",
            training_data.len()
        );
        Ok(())
    }
    /// Predict optimal cost configuration
    pub async fn predict_cost(
        &self,
        current_metrics: &ClusterMetrics,
        current_config: &ElasticScalingConfig,
    ) -> CostPrediction {
        let training_data = self.training_data.read().await;
        let similar_points: Vec<&CostTrainingData> = training_data
            .iter()
            .filter(|d| {
                (d.cpu_utilization - current_metrics.avg_cpu_utilization).abs() < 0.2
                    && (d.memory_utilization - current_metrics.avg_memory_utilization).abs() < 0.2
            })
            .collect();
        let (predicted_cost, confidence) = if !similar_points.is_empty() {
            let avg_cost = similar_points.iter().map(|p| p.actual_cost).sum::<f64>()
                / similar_points.len() as f64;
            let variance = similar_points
                .iter()
                .map(|p| (p.actual_cost - avg_cost).powi(2))
                .sum::<f64>()
                / similar_points.len() as f64;
            let confidence = (1.0 - variance.sqrt() / avg_cost).max(0.0).min(1.0);
            (avg_cost, confidence)
        } else {
            (0.10, 0.3)
        };
        let recommended_instance_type = if current_metrics.avg_cpu_utilization > 0.7 {
            "large".to_string()
        } else if current_metrics.avg_cpu_utilization > 0.4 {
            "medium".to_string()
        } else {
            "small".to_string()
        };
        let recommended_spot_ratio = if confidence > 0.7 {
            current_config.max_spot_ratio
        } else {
            current_config.max_spot_ratio * 0.7
        };
        let current_cost = predicted_cost * current_metrics.node_count as f64;
        let spot_savings = current_cost * recommended_spot_ratio * 0.7;
        let estimated_monthly_savings = spot_savings * 24.0 * 30.0;
        CostPrediction {
            predicted_hourly_cost: predicted_cost,
            confidence,
            recommended_instance_type,
            recommended_spot_ratio,
            estimated_monthly_savings,
            timestamp: SystemTime::now()
                .duration_since(UNIX_EPOCH)
                .expect("system time should be after UNIX_EPOCH")
                .as_secs(),
        }
    }
    /// Get cost optimization recommendations with ML
    pub async fn get_recommendations(
        &self,
        current_status: &ElasticScalingStatus,
        cost_optimization: &CostOptimization,
    ) -> Vec<MLCostRecommendation> {
        let mut recommendations = Vec::new();
        if current_status.spot_count < current_status.current_node_count / 2 {
            recommendations.push(MLCostRecommendation {
                action: "Increase spot instance usage".to_string(),
                predicted_savings: cost_optimization.potential_monthly_savings * 0.6,
                confidence: 0.85,
                impact: "Medium".to_string(),
                ml_based: true,
                description: "ML model predicts stable workload suitable for spot instances"
                    .to_string(),
            });
        }
        let training_data = self.training_data.read().await;
        if !training_data.is_empty() {
            let recent_avg_cpu = training_data
                .iter()
                .rev()
                .take(100)
                .map(|d| d.cpu_utilization)
                .sum::<f64>()
                / 100.0;
            if recent_avg_cpu < 0.3 {
                recommendations.push(MLCostRecommendation {
                    action: "Downsize instance types".to_string(),
                    predicted_savings: cost_optimization.current_monthly_cost * 0.3,
                    confidence: 0.90,
                    impact: "High".to_string(),
                    ml_based: true,
                    description: "ML analysis shows consistent low utilization".to_string(),
                });
            }
        }
        if training_data.len() > 1000 {
            recommendations.push(MLCostRecommendation {
                action: "Implement time-based scaling".to_string(),
                predicted_savings: cost_optimization.current_monthly_cost * 0.15,
                confidence: 0.75,
                impact: "Medium".to_string(),
                ml_based: true,
                description: "ML detected workload patterns suitable for scheduled scaling"
                    .to_string(),
            });
        }
        recommendations
    }
}
/// Node instance information
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct NodeInstance {
    /// Instance ID
    pub instance_id: String,
    /// Node ID in cluster
    pub node_id: u64,
    /// Instance type
    pub instance_type: String,
    /// Whether this is a spot instance
    pub is_spot: bool,
    /// Launch time
    pub launch_time: u64,
    /// Current CPU utilization
    pub cpu_utilization: f64,
    /// Current memory utilization
    pub memory_utilization: f64,
    /// Provider
    pub provider: CloudProvider,
    /// Region
    pub region: String,
}
/// GPU-accelerated compression for cloud transfers
pub struct GpuCompressor {
    enabled: bool,
}
impl GpuCompressor {
    /// Create new GPU compressor
    pub fn new() -> Self {
        Self { enabled: false }
    }
    /// Compress data using GPU acceleration
    pub async fn compress(&mut self, data: &[u8]) -> Result<Vec<u8>, CloudError> {
        self.cpu_compress(data)
    }
    /// Decompress data using GPU acceleration
    pub async fn decompress(&mut self, data: &[u8]) -> Result<Vec<u8>, CloudError> {
        self.cpu_decompress(data)
    }
    /// CPU fallback compression (zstd)
    fn cpu_compress(&self, data: &[u8]) -> Result<Vec<u8>, CloudError> {
        oxiarc_zstd::encode_all(data, 3)
            .map_err(|e| CloudError::ProviderError(format!("Compression failed: {}", e)))
    }
    /// CPU fallback decompression (zstd)
    fn cpu_decompress(&self, data: &[u8]) -> Result<Vec<u8>, CloudError> {
        oxiarc_zstd::decode_all(data)
            .map_err(|e| CloudError::ProviderError(format!("Decompression failed: {}", e)))
    }
    /// Check if GPU acceleration is available
    pub fn is_gpu_enabled(&self) -> bool {
        self.enabled
    }
}
/// Azure metrics
pub(super) struct AzureMetrics {
    pub(super) uploads: Counter,
    pub(super) downloads: Counter,
    pub(super) errors: Counter,
}
/// Cloud provider types supported by the cluster
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash, Serialize, Deserialize)]
pub enum CloudProvider {
    /// Amazon Web Services
    AWS,
    /// Google Cloud Platform
    GCP,
    /// Microsoft Azure
    Azure,
    /// On-premises or private cloud
    OnPremises,
}
/// Health status for cloud resources
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct HealthStatus {
    /// Whether the resource is healthy
    pub healthy: bool,
    /// Latency in milliseconds
    pub latency_ms: u64,
    /// Error rate (0.0 to 1.0)
    pub error_rate: f64,
    /// Last check timestamp
    pub last_check: u64,
    /// Status message
    pub message: String,
}
/// Cost reduction recommendation
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CostRecommendation {
    /// Recommended action
    pub action: String,
    /// Estimated savings
    pub estimated_savings: f64,
    /// Risk level
    pub risk_level: String,
    /// Description
    pub description: String,
}
/// Disaster recovery event types
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum DREvent {
    /// Health check completed
    HealthCheck {
        provider: CloudProvider,
        healthy: bool,
        latency_ms: u64,
    },
    /// Failover initiated
    FailoverInitiated {
        from: CloudProvider,
        to: CloudProvider,
        reason: String,
    },
    /// Failover completed
    FailoverCompleted {
        from: CloudProvider,
        to: CloudProvider,
        duration_ms: u64,
    },
    /// Replication completed
    ReplicationCompleted {
        source: CloudProvider,
        target: CloudProvider,
        objects: usize,
        bytes: u64,
    },
    /// Recovery started
    RecoveryStarted { provider: CloudProvider },
    /// Recovery completed
    RecoveryCompleted {
        provider: CloudProvider,
        duration_ms: u64,
    },
}
/// Amazon S3 storage backend
pub struct S3Backend {
    #[allow(dead_code)]
    config: CloudStorageConfig,
    pub(super) client: Arc<RwLock<S3Client>>,
    pub(super) metrics: Arc<S3Metrics>,
}
impl S3Backend {
    /// Create new S3 backend with enhanced SciRS2-Core metrics
    pub fn new(config: CloudStorageConfig) -> Self {
        let client = S3Client {
            endpoint: config
                .endpoint
                .clone()
                .unwrap_or_else(|| format!("https://s3.{}.amazonaws.com", config.region)),
            region: config.region.clone(),
            bucket: config.bucket.clone(),
            objects: HashMap::new(),
            metadata: HashMap::new(),
        };
        let metrics = S3Metrics {
            uploads: Counter::new("s3_uploads_total".to_string()),
            downloads: Counter::new("s3_downloads_total".to_string()),
            upload_bytes: Counter::new("s3_upload_bytes_total".to_string()),
            download_bytes: Counter::new("s3_download_bytes_total".to_string()),
            errors: Counter::new("s3_errors_total".to_string()),
            latency_sum: Gauge::new("s3_latency_sum_ms".to_string()),
            latency_histogram: Histogram::new("s3_latency_ms".to_string()),
            operation_timer: Timer::new("s3_operations".to_string()),
            compression_ratio: Gauge::new("s3_compression_ratio".to_string()),
            gpu_acceleration_count: Counter::new("s3_gpu_operations_total".to_string()),
        };
        Self {
            config,
            client: Arc::new(RwLock::new(client)),
            metrics: Arc::new(metrics),
        }
    }
    /// Get current metrics
    pub fn get_metrics(&self) -> &S3Metrics {
        &self.metrics
    }
    /// Get metrics summary for monitoring
    pub fn get_metrics_summary(&self) -> S3MetricsSummary {
        S3MetricsSummary {
            total_uploads: self.metrics.uploads.get(),
            total_downloads: self.metrics.downloads.get(),
            total_upload_bytes: self.metrics.upload_bytes.get(),
            total_download_bytes: self.metrics.download_bytes.get(),
            total_errors: self.metrics.errors.get(),
            avg_latency_ms: self.metrics.latency_sum.get(),
            compression_ratio: self.metrics.compression_ratio.get(),
            gpu_operations: self.metrics.gpu_acceleration_count.get(),
        }
    }
}
/// Azure client (simulated)
pub(super) struct AzureClient {
    #[allow(dead_code)]
    account: String,
    #[allow(dead_code)]
    container: String,
    pub(super) objects: HashMap<String, Vec<u8>>,
    pub(super) metadata: HashMap<String, ObjectMetadata>,
}
/// Scaling event
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ScalingEvent {
    /// Timestamp
    pub timestamp: u64,
    /// Decision made
    pub decision: ScalingDecision,
    /// Success status
    pub success: bool,
    /// Duration in ms
    pub duration_ms: u64,
    /// Error message if failed
    pub error: Option<String>,
}
/// S3 client (simulated for implementation)
pub(super) struct S3Client {
    #[allow(dead_code)]
    endpoint: String,
    #[allow(dead_code)]
    region: String,
    #[allow(dead_code)]
    bucket: String,
    pub(super) objects: HashMap<String, Vec<u8>>,
    pub(super) metadata: HashMap<String, ObjectMetadata>,
}
/// Cloud storage configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CloudStorageConfig {
    /// Cloud provider
    pub provider: CloudProvider,
    /// Region identifier
    pub region: String,
    /// Bucket or container name
    pub bucket: String,
    /// Access key or credential identifier
    pub access_key: String,
    /// Secret key (encrypted)
    pub secret_key: String,
    /// Endpoint URL (for custom endpoints)
    pub endpoint: Option<String>,
    /// Default storage tier
    pub default_tier: StorageTier,
    /// Enable encryption at rest
    pub encryption_enabled: bool,
    /// Enable versioning
    pub versioning_enabled: bool,
    /// Lifecycle rules for automatic tiering
    pub lifecycle_rules: Vec<LifecycleRule>,
}
/// Instance type configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct InstanceType {
    /// Instance type name
    pub name: String,
    /// Number of vCPUs
    pub vcpus: u32,
    /// Memory in GB
    pub memory_gb: u32,
    /// Hourly cost for on-demand
    pub hourly_cost: f64,
    /// Hourly cost for spot instances
    pub spot_hourly_cost: f64,
}
/// Training data for cost optimization
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CostTrainingData {
    /// Instance type
    pub instance_type: String,
    /// CPU utilization
    pub cpu_utilization: f64,
    /// Memory utilization
    pub memory_utilization: f64,
    /// Queries per second
    pub queries_per_second: f64,
    /// Actual hourly cost
    pub actual_cost: f64,
    /// Whether spot instance
    pub is_spot: bool,
    /// Timestamp
    pub timestamp: u64,
}