quantrs2-device 0.1.3

//! Component types for enhanced monitoring

use super::types::*;
use async_trait::async_trait;
use chrono::{DateTime, Duration as ChronoDuration, Utc};
use serde::{Deserialize, Serialize};
use std::collections::{BTreeMap, HashMap, HashSet, VecDeque};
use std::sync::{Arc, Mutex, RwLock};
use std::time::Duration;
use uuid::Uuid;

use crate::performance_analytics_dashboard::NotificationDispatcher;
use crate::quantum_network::distributed_protocols::{NodeId, NodeInfo, PerformanceMetrics};
use crate::quantum_network::network_optimization::{
    FeatureVector, MLModel, NetworkOptimizationError, PredictionResult, Priority,
};

/// Real-time metrics collector
#[derive(Debug)]
pub struct RealTimeMetricsCollector {
    /// Metric data streams
    pub metric_streams: Arc<RwLock<HashMap<MetricType, MetricStream>>>,
    /// Collection schedulers
    pub schedulers: Arc<RwLock<HashMap<MetricType, MetricCollectionScheduler>>>,
    /// Data aggregation engine
    pub aggregation_engine: Arc<MetricsAggregationEngine>,
    /// Real-time data buffer
    pub real_time_buffer: Arc<RwLock<MetricsBuffer>>,
    /// Collection statistics
    pub collection_stats: Arc<Mutex<CollectionStatistics>>,
}

/// Metric data stream
#[derive(Debug)]
pub struct MetricStream {
    /// Stream identifier
    pub stream_id: Uuid,
    /// Metric type being collected
    pub metric_type: MetricType,
    /// Current data points
    pub data_points: Arc<RwLock<VecDeque<MetricDataPoint>>>,
    /// Stream statistics
    pub stream_stats: Arc<Mutex<StreamStatistics>>,
    /// Quality indicators
    pub quality_indicators: Arc<RwLock<DataQualityIndicators>>,
}

/// Individual metric data point
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MetricDataPoint {
    /// Unique identifier for this data point
    pub data_point_id: Uuid,
    /// Metric type
    pub metric_type: MetricType,
    /// Timestamp of measurement
    pub timestamp: DateTime<Utc>,
    /// Primary metric value
    pub value: f64,
    /// Additional context values
    pub context_values: HashMap<String, f64>,
    /// Node identifier (if applicable)
    pub node_id: Option<NodeId>,
    /// Qubit identifier (if applicable)
    pub qubit_id: Option<u32>,
    /// Measurement quality indicators
    pub quality: DataQuality,
    /// Metadata about the measurement
    pub metadata: MetricMetadata,
}

/// Data quality indicators for measurements
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct DataQuality {
    /// Measurement accuracy (0.0 to 1.0)
    pub accuracy: f64,
    /// Measurement precision (0.0 to 1.0)
    pub precision: f64,
    /// Confidence level (0.0 to 1.0)
    pub confidence: f64,
    /// Data freshness (time since measurement)
    pub freshness: Duration,
    /// Calibration status
    pub calibration_status: CalibrationStatus,
}

/// Calibration status for measurements
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum CalibrationStatus {
    /// Recently calibrated (high confidence)
    RecentlyCalibrated,
    /// Calibrated within normal window
    NormallyCalibrated,
    /// Calibration aging (reduced confidence)
    CalibrationAging,
    /// Calibration expired (low confidence)
    CalibrationExpired,
    /// Calibration unknown
    Unknown,
}

/// Metadata about metric measurements
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MetricMetadata {
    /// Measurement method used
    pub measurement_method: String,
    /// Environmental conditions during measurement
    pub environmental_conditions: EnvironmentalConditions,
    /// Concurrent operations during measurement
    pub concurrent_operations: Vec<String>,
    /// Measurement context
    pub measurement_context: MeasurementContext,
}

/// Environmental conditions during measurement
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct EnvironmentalConditions {
    /// Temperature (Kelvin)
    pub temperature: Option<f64>,
    /// Pressure (Pascal)
    pub pressure: Option<f64>,
    /// Humidity (percentage)
    pub humidity: Option<f64>,
    /// Magnetic field strength (Tesla)
    pub magnetic_field: Option<f64>,
    /// Vibration levels
    pub vibration_levels: Option<f64>,
}

/// Measurement context information
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MeasurementContext {
    /// Experiment type being conducted
    pub experiment_type: Option<String>,
    /// User or application requesting measurement
    pub requester: Option<String>,
    /// Priority level of measurement
    pub priority: Priority,
    /// Associated circuit or algorithm
    pub associated_circuit: Option<Uuid>,
}

/// Quantum Network Analytics Engine
#[derive(Debug)]
pub struct QuantumNetworkAnalyticsEngine {
    /// Real-time analytics processor
    pub real_time_processor: Arc<RealTimeAnalyticsProcessor>,
    /// Pattern recognition system
    pub pattern_recognition: Arc<QuantumPatternRecognition>,
    /// Correlation analysis engine
    pub correlation_analyzer: Arc<QuantumCorrelationAnalyzer>,
    /// Trend analysis system
    pub trend_analyzer: Arc<QuantumTrendAnalyzer>,
    /// Performance modeling system
    pub performance_modeler: Arc<QuantumPerformanceModeler>,
    /// Optimization analytics
    pub optimization_analytics: Arc<QuantumOptimizationAnalytics>,
}

/// Real-time analytics processor
#[derive(Debug)]
pub struct RealTimeAnalyticsProcessor {
    /// Stream processing engine
    pub stream_processor: Arc<StreamProcessingEngine>,
    /// Real-time aggregators
    pub aggregators: Arc<RwLock<HashMap<MetricType, RealTimeAggregator>>>,
    /// Complex event processing
    pub cep_engine: Arc<ComplexEventProcessingEngine>,
    /// Real-time ML inference
    pub ml_inference: Arc<RealTimeMLInference>,
}

/// Quantum anomaly detection system
#[derive(Debug)]
pub struct QuantumAnomalyDetector {
    /// Anomaly detection models
    pub detection_models: Arc<RwLock<HashMap<MetricType, AnomalyDetectionModel>>>,
    /// Threshold-based detectors
    pub threshold_detectors: Arc<RwLock<HashMap<MetricType, ThresholdDetector>>>,
    /// ML-based anomaly detection
    pub ml_detectors: Arc<RwLock<HashMap<MetricType, MLAnomalyDetector>>>,
    /// Anomaly correlation analyzer
    pub correlation_analyzer: Arc<QuantumCorrelationAnalyzer>,
    /// Anomaly severity classifier
    pub severity_classifier: Arc<AnomalySeverityClassifier>,
}

/// Anomaly detection model
#[derive(Debug)]
pub struct AnomalyDetectionModel {
    /// Model identifier
    pub model_id: Uuid,
    /// Model type
    pub model_type: AnomalyModelType,
    /// Training data window
    pub training_window: Duration,
    /// Detection sensitivity
    pub sensitivity: f64,
    /// Model accuracy metrics
    pub accuracy_metrics: ModelAccuracyMetrics,
    /// Last training timestamp
    pub last_training: DateTime<Utc>,
}

/// Types of anomaly detection models
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum AnomalyModelType {
    /// Statistical anomaly detection
    Statistical {
        method: StatisticalMethod,
        confidence_level: f64,
    },
    /// Machine learning-based detection
    MachineLearning {
        algorithm: MLAlgorithm,
        feature_window: Duration,
    },
    /// Time series anomaly detection
    TimeSeries {
        model: TimeSeriesModel,
        seasonal_adjustment: bool,
    },
    /// Quantum-specific anomaly detection
    QuantumSpecific {
        quantum_model: QuantumAnomalyModel,
        context_awareness: bool,
    },
}

/// Statistical methods for anomaly detection
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum StatisticalMethod {
    ZScore,
    IQR,
    GESD,
    ModifiedZScore,
    RobustZScore,
}

/// ML algorithms for anomaly detection
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum MLAlgorithm {
    IsolationForest,
    OneClassSVM,
    LocalOutlierFactor,
    EllipticEnvelope,
    AutoEncoder,
    LSTM,
}

/// Time series models for anomaly detection
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum TimeSeriesModel {
    ARIMA,
    HoltWinters,
    Prophet,
    DeepAR,
    LSTM,
}

/// Quantum-specific anomaly models
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum QuantumAnomalyModel {
    /// Fidelity degradation detection
    FidelityDegradation,
    /// Coherence collapse detection
    CoherenceCollapse,
    /// Entanglement death detection
    EntanglementDeath,
    /// Quantum error burst detection
    ErrorBurst,
    /// Calibration drift detection
    CalibrationDrift,
}

/// Model accuracy metrics
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ModelAccuracyMetrics {
    /// True positive rate
    pub true_positive_rate: f64,
    /// False positive rate
    pub false_positive_rate: f64,
    /// Precision
    pub precision: f64,
    /// Recall
    pub recall: f64,
    /// F1 score
    pub f1_score: f64,
    /// Area under ROC curve
    pub auc_roc: f64,
}

/// Quantum Network Predictor for predictive analytics
#[derive(Debug)]
pub struct QuantumNetworkPredictor {
    /// Performance prediction models
    pub performance_predictors: Arc<RwLock<HashMap<MetricType, PerformancePredictionModel>>>,
    /// Failure prediction system
    pub failure_predictor: Arc<QuantumFailurePredictor>,
    /// Capacity planning predictor
    pub capacity_predictor: Arc<QuantumCapacityPredictor>,
    /// Load forecasting system
    pub load_forecaster: Arc<QuantumLoadForecaster>,
    /// Optimization opportunity predictor
    pub optimization_predictor: Arc<QuantumOptimizationOpportunityPredictor>,
}

/// Performance prediction model
#[derive(Debug)]
pub struct PerformancePredictionModel {
    /// Model identifier
    pub model_id: Uuid,
    /// Prediction horizon
    pub prediction_horizon: Duration,
    /// Model type
    pub model_type: PredictionModelType,
    /// Feature extractors
    pub feature_extractors: Vec<FeatureExtractor>,
    /// Prediction accuracy
    pub prediction_accuracy: f64,
    /// Model confidence intervals
    pub confidence_intervals: ConfidenceIntervals,
}

/// Types of prediction models
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum PredictionModelType {
    /// Linear regression models
    Linear { regularization: RegularizationType },
    /// Time series forecasting
    TimeSeries {
        model: TimeSeriesModel,
        seasonal_components: bool,
    },
    /// Neural network models
    NeuralNetwork {
        architecture: NeuralNetworkArchitecture,
        optimization: OptimizationMethod,
    },
    /// Ensemble models
    Ensemble {
        base_models: Vec<String>,
        combination_method: EnsembleCombinationMethod,
    },
    /// Quantum machine learning models
    QuantumML {
        ansatz: QuantumAnsatz,
        parameter_optimization: ParameterOptimization,
    },
}

/// Regularization types for linear models
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum RegularizationType {
    None,
    L1,
    L2,
    ElasticNet { l1_ratio: f64 },
}

/// Neural network architectures
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct NeuralNetworkArchitecture {
    /// Layer specifications
    pub layers: Vec<LayerSpec>,
    /// Activation functions
    pub activations: Vec<ActivationFunction>,
    /// Dropout rates
    pub dropout_rates: Vec<f64>,
}

/// Layer specification for neural networks
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct LayerSpec {
    /// Layer type
    pub layer_type: LayerType,
    /// Number of units
    pub units: u32,
    /// Additional parameters
    pub parameters: HashMap<String, f64>,
}

/// Neural network layer types
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum LayerType {
    Dense,
    LSTM,
    GRU,
    Conv1D,
    Attention,
}

/// Activation functions
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum ActivationFunction {
    ReLU,
    Sigmoid,
    Tanh,
    Swish,
    GELU,
}

/// Optimization methods for neural networks
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum OptimizationMethod {
    SGD {
        learning_rate: f64,
        momentum: f64,
    },
    Adam {
        learning_rate: f64,
        beta1: f64,
        beta2: f64,
    },
    AdamW {
        learning_rate: f64,
        weight_decay: f64,
    },
    RMSprop {
        learning_rate: f64,
        decay: f64,
    },
}

/// Ensemble combination methods
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum EnsembleCombinationMethod {
    Averaging,
    Voting,
    Stacking,
    Blending,
    BayesianModelAveraging,
}

/// Quantum ansatz for quantum ML
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum QuantumAnsatz {
    VariationalQuantumEigensolver,
    QuantumApproximateOptimizationAlgorithm,
    HardwareEfficientAnsatz,
    EquivariantAnsatz,
}

/// Parameter optimization for quantum ML
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum ParameterOptimization {
    GradientDescent,
    COBYLA,
    SPSA,
    NelderMead,
    QuantumNaturalGradient,
}

/// Confidence intervals for predictions
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ConfidenceIntervals {
    /// Lower bound confidence levels (confidence_level, lower_bound)
    pub lower_bounds: Vec<(f64, f64)>,
    /// Upper bound confidence levels (confidence_level, upper_bound)
    pub upper_bounds: Vec<(f64, f64)>,
    /// Prediction uncertainty
    pub uncertainty_estimate: f64,
}

/// Feature extractor for ML models
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct FeatureExtractor {
    /// Extractor name
    pub name: String,
    /// Feature types extracted
    pub feature_types: Vec<FeatureType>,
    /// Extraction window
    pub extraction_window: Duration,
    /// Feature importance weights
    pub importance_weights: HashMap<String, f64>,
}

/// Types of features for ML models
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum FeatureType {
    /// Raw metric values
    RawMetric,
    /// Statistical features (mean, std, etc.)
    Statistical,
    /// Temporal features (trends, seasonality)
    Temporal,
    /// Frequency domain features (FFT, spectral)
    FrequencyDomain,
    /// Quantum-specific features
    QuantumSpecific,
    /// Cross-correlation features
    CrossCorrelation,
}

/// Alert system for quantum networks
pub struct QuantumNetworkAlertSystem {
    /// Alert rules engine
    pub rules_engine: Arc<AlertRulesEngine>,
    /// Notification dispatcher
    pub notification_dispatcher: Arc<NotificationDispatcher>,
    /// Alert severity classifier
    pub severity_classifier: Arc<AlertSeverityClassifier>,
    /// Alert correlation engine
    pub correlation_engine: Arc<AlertCorrelationEngine>,
    /// Escalation manager
    pub escalation_manager: Arc<AlertEscalationManager>,
}

impl std::fmt::Debug for QuantumNetworkAlertSystem {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        f.debug_struct("QuantumNetworkAlertSystem")
            .field("rules_engine", &self.rules_engine)
            .field("notification_dispatcher", &"<NotificationDispatcher>")
            .field("severity_classifier", &self.severity_classifier)
            .field("correlation_engine", &self.correlation_engine)
            .field("escalation_manager", &self.escalation_manager)
            .finish()
    }
}

/// Alert rules engine
#[derive(Debug)]
pub struct AlertRulesEngine {
    /// Active alert rules
    pub active_rules: Arc<RwLock<HashMap<Uuid, AlertRule>>>,
    /// Rule evaluation engine
    pub evaluation_engine: Arc<RuleEvaluationEngine>,
    /// Custom rule compiler
    pub rule_compiler: Arc<CustomRuleCompiler>,
    /// Rule performance tracker
    pub performance_tracker: Arc<RulePerformanceTracker>,
}

impl Default for AlertRulesEngine {
    fn default() -> Self {
        Self::new()
    }
}

impl AlertRulesEngine {
    pub fn new() -> Self {
        Self {
            active_rules: Arc::new(RwLock::new(HashMap::new())),
            evaluation_engine: Arc::new(RuleEvaluationEngine::new()),
            rule_compiler: Arc::new(CustomRuleCompiler::new()),
            performance_tracker: Arc::new(RulePerformanceTracker::new()),
        }
    }
}

/// Alert rule definition
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AlertRule {
    /// Rule identifier
    pub rule_id: Uuid,
    /// Rule name
    pub rule_name: String,
    /// Rule description
    pub description: String,
    /// Rule condition
    pub condition: RuleCondition,
    /// Alert severity
    pub severity: AlertSeverity,
    /// Notification settings
    pub notification_settings: NotificationSettings,
    /// Rule metadata
    pub metadata: RuleMetadata,
}

/// Rule condition specification
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum RuleCondition {
    /// Simple threshold condition
    Threshold {
        metric_type: MetricType,
        operator: ComparisonOperator,
        threshold_value: f64,
        duration: Duration,
    },
    /// Complex condition with multiple metrics
    Complex {
        expression: String,
        metrics: Vec<MetricType>,
        evaluation_window: Duration,
    },
    /// Anomaly-based condition
    Anomaly {
        metric_type: MetricType,
        anomaly_model: AnomalyModelType,
        sensitivity: f64,
    },
    /// Trend-based condition
    Trend {
        metric_type: MetricType,
        trend_direction: TrendDirection,
        trend_strength: f64,
        evaluation_period: Duration,
    },
    /// Quantum-specific condition
    QuantumSpecific {
        quantum_condition: QuantumCondition,
        parameters: HashMap<String, f64>,
    },
}

/// Comparison operators for rule conditions
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum ComparisonOperator {
    GreaterThan,
    LessThan,
    GreaterThanOrEqual,
    LessThanOrEqual,
    Equal,
    NotEqual,
    Between { lower: f64, upper: f64 },
    Outside { lower: f64, upper: f64 },
}

/// Trend directions for trend-based alerts
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum TrendDirection {
    Increasing,
    Decreasing,
    Stable,
    Oscillating,
    Chaotic,
}

/// Quantum-specific alert conditions
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum QuantumCondition {
    /// Fidelity below threshold
    FidelityDegradation,
    /// Coherence time decreasing rapidly
    CoherenceDecay,
    /// Entanglement quality degrading
    EntanglementDegradation,
    /// Error rates increasing
    ErrorRateIncrease,
    /// Calibration drift detected
    CalibrationDrift,
    /// Quantum volume decreasing
    QuantumVolumeDecrease,
}

/// Alert severity levels
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq, PartialOrd, Ord, Hash)]
pub enum AlertSeverity {
    Info = 0,
    Warning = 1,
    Minor = 2,
    Major = 3,
    Critical = 4,
    Emergency = 5,
}

/// Notification settings for alerts
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct NotificationSettings {
    /// Notification channels
    pub channels: Vec<NotificationChannel>,
    /// Notification frequency limits
    pub frequency_limits: FrequencyLimits,
    /// Escalation settings
    pub escalation_settings: EscalationSettings,
    /// Custom message templates
    pub message_templates: HashMap<String, String>,
}

/// Notification channels
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum NotificationChannel {
    /// Email notifications
    Email {
        recipients: Vec<String>,
        subject_template: String,
    },
    /// SMS notifications
    SMS {
        phone_numbers: Vec<String>,
        message_template: String,
    },
    /// Slack notifications
    Slack {
        webhook_url: String,
        channel: String,
    },
    /// Discord notifications
    Discord {
        webhook_url: String,
        channel: String,
    },
    /// Custom webhook
    Webhook {
        url: String,
        headers: HashMap<String, String>,
        payload_template: String,
    },
    /// Dashboard notifications
    Dashboard {
        dashboard_id: String,
        notification_type: DashboardNotificationType,
    },
}

/// Dashboard notification types
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum DashboardNotificationType {
    PopupAlert,
    StatusBarUpdate,
    BannerNotification,
    SidebarAlert,
}

/// Frequency limits for notifications
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct FrequencyLimits {
    /// Maximum notifications per time window
    pub max_notifications_per_window: u32,
    /// Time window for frequency limiting
    pub time_window: Duration,
    /// Cooldown period after max reached
    pub cooldown_period: Duration,
    /// Burst allowance for critical alerts
    pub burst_allowance: u32,
}

/// Escalation settings for alerts
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct EscalationSettings {
    /// Escalation enabled
    pub enabled: bool,
    /// Escalation levels
    pub escalation_levels: Vec<EscalationLevel>,
    /// Automatic escalation rules
    pub auto_escalation_rules: Vec<AutoEscalationRule>,
}

/// Escalation level definition
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct EscalationLevel {
    /// Level number
    pub level: u32,
    /// Delay before escalating to this level
    pub escalation_delay: Duration,
    /// Additional notification channels for this level
    pub additional_channels: Vec<NotificationChannel>,
    /// Required acknowledgment for this level
    pub requires_acknowledgment: bool,
}

/// Automatic escalation rule
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AutoEscalationRule {
    /// Rule condition
    pub condition: EscalationCondition,
    /// Target escalation level
    pub target_level: u32,
    /// Escalation reason
    pub reason: String,
}

/// Conditions for automatic escalation
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum EscalationCondition {
    /// No acknowledgment within time limit
    NoAcknowledgment { timeout: Duration },
    /// Alert persists for duration
    AlertPersistence { duration: Duration },
    /// Related alerts triggered
    RelatedAlerts { count: u32, time_window: Duration },
    /// Severity threshold reached
    SeverityThreshold { severity: AlertSeverity },
}

/// Rule metadata
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct RuleMetadata {
    /// Rule creation timestamp
    pub created_at: DateTime<Utc>,
    /// Rule creator
    pub created_by: String,
    /// Last modification timestamp
    pub last_modified: DateTime<Utc>,
    /// Rule version
    pub version: u32,
    /// Rule tags
    pub tags: Vec<String>,
    /// Rule category
    pub category: RuleCategory,
}

/// Rule categories
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum RuleCategory {
    Performance,
    Security,
    Availability,
    QuantumSpecific,
    Hardware,
    Network,
    Application,
    Custom,
}

/// Collection scheduler for specific metric types
#[derive(Debug)]
pub struct MetricCollectionScheduler {
    pub metric_type: MetricType,
    pub collection_interval: Duration,
    pub priority: Priority,
    pub enabled: bool,
}

/// Metrics aggregation engine
#[derive(Debug)]
pub struct MetricsAggregationEngine {
    pub aggregation_window: Duration,
    pub aggregation_functions: Vec<String>,
    pub buffer_size: usize,
}

/// Buffer for real-time metrics
#[derive(Debug)]
pub struct MetricsBuffer {
    pub buffer_size: usize,
    pub data_points: VecDeque<MetricDataPoint>,
    pub overflow_policy: String,
}

/// Statistics for metric streams
#[derive(Debug)]
pub struct StreamStatistics {
    pub total_points: u64,
    pub average_rate: f64,
    pub error_count: u64,
    pub last_update: DateTime<Utc>,
}

/// Data quality indicators
#[derive(Debug)]
pub struct DataQualityIndicators {
    pub completeness: f64,
    pub accuracy: f64,
    pub consistency: f64,
    pub timeliness: f64,
}

/// Collection statistics
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CollectionStatistics {
    pub total_data_points: u64,
    pub collection_rate: f64,
    pub error_rate: f64,
    pub last_collection: DateTime<Utc>,
}

/// Real-time ML inference engine
#[derive(Debug)]
pub struct RealTimeMLInference {
    pub model_path: String,
}

/// Optimization recommendation
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct OptimizationRecommendation {
    pub recommendation_id: Uuid,
    pub recommendation_type: String,
    pub description: String,
    pub confidence: f64,
    pub estimated_improvement: f64,
}

#[derive(Debug)]
pub struct ThresholdDetector {
    pub lower_threshold: f64,
    pub upper_threshold: f64,
    pub sensitivity: f64,
}

impl ThresholdDetector {
    pub const fn new(lower: f64, upper: f64, sensitivity: f64) -> Self {
        Self {
            lower_threshold: lower,
            upper_threshold: upper,
            sensitivity,
        }
    }
}

/// Machine learning-based anomaly detector
#[derive(Debug, Clone)]
pub struct MLAnomalyDetector {
    pub model_type: String,
    pub sensitivity: f64,
    pub training_data_size: usize,
}

impl MLAnomalyDetector {
    pub const fn new(model_type: String, sensitivity: f64) -> Self {
        Self {
            model_type,
            sensitivity,
            training_data_size: 0,
        }
    }
}

/// Anomaly severity classifier
#[derive(Debug, Clone)]
pub struct AnomalySeverityClassifier {
    pub thresholds: HashMap<String, f64>,
    pub weights: HashMap<String, f64>,
}

impl Default for AnomalySeverityClassifier {
    fn default() -> Self {
        Self::new()
    }
}

impl AnomalySeverityClassifier {
    pub fn new() -> Self {
        Self {
            thresholds: HashMap::new(),
            weights: HashMap::new(),
        }
    }
}

/// Quantum failure predictor
#[derive(Debug, Clone)]
pub struct QuantumFailurePredictor {
    pub model_accuracy: f64,
    pub prediction_window: Duration,
}

impl Default for QuantumFailurePredictor {
    fn default() -> Self {
        Self::new()
    }
}

impl QuantumFailurePredictor {
    pub const fn new() -> Self {
        Self {
            model_accuracy: 0.9,
            prediction_window: Duration::from_secs(300),
        }
    }
}

/// Quantum capacity predictor
#[derive(Debug, Clone)]
pub struct QuantumCapacityPredictor {
    pub prediction_horizon: Duration,
    pub confidence_interval: f64,
}

impl Default for QuantumCapacityPredictor {
    fn default() -> Self {
        Self::new()
    }
}

impl QuantumCapacityPredictor {
    pub const fn new() -> Self {
        Self {
            prediction_horizon: Duration::from_secs(600),
            confidence_interval: 0.95,
        }
    }
}

/// Quantum load forecaster
#[derive(Debug, Clone)]
pub struct QuantumLoadForecaster {
    pub forecast_window: Duration,
    pub update_frequency: Duration,
}

impl Default for QuantumLoadForecaster {
    fn default() -> Self {
        Self::new()
    }
}

impl QuantumLoadForecaster {
    pub const fn new() -> Self {
        Self {
            forecast_window: Duration::from_secs(1800),
            update_frequency: Duration::from_secs(60),
        }
    }
}

/// Quantum optimization opportunity predictor
#[derive(Debug, Clone)]
pub struct QuantumOptimizationOpportunityPredictor {
    pub opportunity_types: Vec<String>,
    pub detection_threshold: f64,
}

impl Default for QuantumOptimizationOpportunityPredictor {
    fn default() -> Self {
        Self::new()
    }
}

impl QuantumOptimizationOpportunityPredictor {
    pub fn new() -> Self {
        Self {
            opportunity_types: vec![
                "load_balancing".to_string(),
                "resource_allocation".to_string(),
            ],
            detection_threshold: 0.8,
        }
    }
}

/// Alert severity classifier
#[derive(Debug, Clone)]
pub struct AlertSeverityClassifier {
    pub classification_rules: HashMap<String, AlertSeverity>,
    pub confidence_threshold: f64,
}

impl Default for AlertSeverityClassifier {
    fn default() -> Self {
        Self::new()
    }
}

impl AlertSeverityClassifier {
    pub fn new() -> Self {
        Self {
            classification_rules: HashMap::new(),
            confidence_threshold: 0.8,
        }
    }
}

/// Alert correlation engine
#[derive(Debug, Clone)]
pub struct AlertCorrelationEngine {
    pub correlation_window: Duration,
    pub correlation_threshold: f64,
}

impl Default for AlertCorrelationEngine {
    fn default() -> Self {
        Self::new()
    }
}

impl AlertCorrelationEngine {
    pub const fn new() -> Self {
        Self {
            correlation_window: Duration::from_secs(300),
            correlation_threshold: 0.7,
        }
    }
}

/// Alert escalation manager
#[derive(Debug, Clone)]
pub struct AlertEscalationManager {
    pub escalation_levels: Vec<String>,
    pub escalation_timeouts: Vec<Duration>,
}

impl Default for AlertEscalationManager {
    fn default() -> Self {
        Self::new()
    }
}

impl AlertEscalationManager {
    pub fn new() -> Self {
        Self {
            escalation_levels: vec![
                "tier1".to_string(),
                "tier2".to_string(),
                "tier3".to_string(),
            ],
            escalation_timeouts: vec![
                Duration::from_secs(300),
                Duration::from_secs(900),
                Duration::from_secs(1800),
            ],
        }
    }
}

/// Rule evaluation engine
#[derive(Debug, Clone)]
pub struct RuleEvaluationEngine {
    pub evaluation_frequency: Duration,
    pub rule_cache_size: usize,
}

impl Default for RuleEvaluationEngine {
    fn default() -> Self {
        Self::new()
    }
}

impl RuleEvaluationEngine {
    pub const fn new() -> Self {
        Self {
            evaluation_frequency: Duration::from_secs(30),
            rule_cache_size: 1000,
        }
    }
}

/// Custom rule compiler
#[derive(Debug, Clone)]
pub struct CustomRuleCompiler {
    pub supported_languages: Vec<String>,
    pub compilation_timeout: Duration,
}

impl Default for CustomRuleCompiler {
    fn default() -> Self {
        Self::new()
    }
}

impl CustomRuleCompiler {
    pub fn new() -> Self {
        Self {
            supported_languages: vec!["lua".to_string(), "python".to_string()],
            compilation_timeout: Duration::from_secs(30),
        }
    }
}

/// Rule performance tracker
#[derive(Debug, Clone)]
pub struct RulePerformanceTracker {
    pub metrics_window: Duration,
    pub performance_threshold: f64,
}

impl Default for RulePerformanceTracker {
    fn default() -> Self {
        Self::new()
    }
}

impl RulePerformanceTracker {
    pub const fn new() -> Self {
        Self {
            metrics_window: Duration::from_secs(600),
            performance_threshold: 0.95,
        }
    }
}

/// Quantum pattern recognition engine
#[derive(Debug)]
pub struct QuantumPatternRecognition {
    pub pattern_algorithms: Vec<String>,
}

/// Quantum correlation analyzer
#[derive(Debug)]
pub struct QuantumCorrelationAnalyzer {
    pub correlation_threshold: f64,
}

/// Quantum trend analyzer
#[derive(Debug)]
pub struct QuantumTrendAnalyzer {
    pub trend_algorithms: Vec<String>,
}

/// Quantum performance modeler
#[derive(Debug)]
pub struct QuantumPerformanceModeler {
    pub modeling_algorithms: Vec<String>,
}

/// Quantum optimization analytics
#[derive(Debug)]
pub struct QuantumOptimizationAnalytics {
    pub analytics_algorithms: Vec<String>,
}

/// Stream processing engine
#[derive(Debug)]
pub struct StreamProcessingEngine {
    pub processing_threads: usize,
}

/// Real-time aggregator
#[derive(Debug)]
pub struct RealTimeAggregator {
    pub aggregation_window: Duration,
}

/// Complex event processing engine
#[derive(Debug)]
pub struct ComplexEventProcessingEngine {
    pub event_rules: Vec<String>,
}