@ahmedhegazee/nestjs-telescope/dist/telescope/dashboard/controllers/ml-analytics.controller.d.ts

Advanced observability and monitoring solution for NestJS applications with ML-powered analytics, enterprise features, and production-ready scaling

/// <reference types="node" />
import { Observable } from 'rxjs';
import { MLAnalyticsService, AnomalyDetection, RegressionAnalysis, QueryOptimizationSuggestion, PredictiveInsight, MLAlert } from '../../core/services/ml-analytics.service';
import { AutomatedAlertingService, AlertChannel, AlertRule, AlertHistory, AlertMetrics } from '../../core/services/automated-alerting.service';
export declare class AnomalyQueryDto {
    component?: string;
    severity?: 'low' | 'medium' | 'high' | 'critical';
    type?: 'performance' | 'error' | 'traffic' | 'resource' | 'query';
    limit?: number;
    from?: Date;
    to?: Date;
}
export declare class AlertChannelDto {
    name: string;
    type: 'email' | 'slack' | 'teams' | 'webhook' | 'sms' | 'pagerduty';
    enabled?: boolean;
    config: {
        url?: string;
        token?: string;
        email?: string;
        phone?: string;
        [key: string]: any;
    };
    severityFilter?: ('info' | 'warning' | 'error' | 'critical')[];
    componentFilter?: string[];
    rateLimit?: {
        maxAlerts: number;
        timeWindow: number;
    };
}
export declare class AlertRuleDto {
    name: string;
    description: string;
    enabled?: boolean;
    priority?: number;
    conditions: Array<{
        metric: string;
        operator: '>' | '<' | '==' | '!=' | '>=' | '<=';
        threshold: number;
        duration?: number;
        component?: string;
    }>;
    actions: {
        channelIds: string[];
        escalation?: {
            delayMinutes: number;
            channels: string[];
        };
        autoRemediation?: {
            enabled: boolean;
            actions: Array<{
                type: 'restart' | 'scale' | 'rollback' | 'cache_clear';
                config: any;
            }>;
        };
    };
    schedule?: {
        timezone: string;
        activeHours: {
            start: string;
            end: string;
        };
        activeDays: number[];
    };
}
export declare class MLInsightSummary {
    timestamp: Date;
    anomaliesCount: number;
    regressionsCount: number;
    optimizationsCount: number;
    predictionsCount: number;
    alertsCount: number;
    healthScore: number;
    riskLevel: 'low' | 'medium' | 'high' | 'critical';
    topConcerns: Array<{
        type: string;
        component: string;
        severity: string;
        description: string;
    }>;
}
export declare class Week8MLAnalyticsController {
    private readonly mlAnalyticsService;
    private readonly alertingService;
    constructor(mlAnalyticsService: MLAnalyticsService, alertingService: AutomatedAlertingService);
    getMLOverview(): Promise<MLInsightSummary>;
    getAnomalies(query: AnomalyQueryDto): AnomalyDetection[];
    getAnomaliesStream(): Observable<AnomalyDetection[]>;
    dismissAnomaly(anomalyId: string): boolean;
    getRegressions(component?: string, trend?: 'improving' | 'degrading' | 'stable', limit?: number): RegressionAnalysis[];
    getRegressionsStream(): Observable<RegressionAnalysis[]>;
    getOptimizations(table?: string, type?: 'index' | 'rewrite' | 'cache' | 'partition' | 'normalize', effort?: 'low' | 'medium' | 'high', limit?: number): QueryOptimizationSuggestion[];
    getOptimizationsStream(): Observable<QueryOptimizationSuggestion[]>;
    getPredictions(component?: string, predictionType?: 'load' | 'failure' | 'performance' | 'resource', timeHorizon?: '1h' | '6h' | '24h' | '7d' | '30d', riskLevel?: 'low' | 'medium' | 'high' | 'critical', limit?: number): PredictiveInsight[];
    getPredictionsStream(): Observable<PredictiveInsight[]>;
    getMLMetrics(): {
        anomaliesDetected: number;
        regressionsAnalyzed: number;
        optimizationSuggestions: number;
        predictiveInsights: number;
        activeAlerts: number;
        dataHistorySize: number;
    };
    getMLAlerts(severity?: 'info' | 'warning' | 'error' | 'critical', type?: 'anomaly' | 'regression' | 'prediction' | 'optimization', limit?: number): MLAlert[];
    getMLAlertsStream(): Observable<MLAlert[]>;
    acknowledgeMLAlert(alertId: string): {
        success: boolean;
        alertId: string;
        acknowledgedAt: Date;
    };
    getAlertChannels(): AlertChannel[];
    createAlertChannel(channelDto: AlertChannelDto): {
        success: boolean;
        channel: AlertChannel;
    };
    deleteAlertChannel(channelId: string): void;
    testAlertChannel(channelId: string): Promise<{
        success: boolean;
        message: any;
    }>;
    getAlertRules(): AlertRule[];
    createAlertRule(ruleDto: AlertRuleDto): {
        success: boolean;
        rule: AlertRule;
    };
    deleteAlertRule(ruleId: string): void;
    getAlertHistory(limit?: number): AlertHistory[];
    getAlertHistoryStream(): Observable<AlertHistory>;
    getAlertMetrics(): AlertMetrics;
    acknowledgeHistoryAlert(alertId: string): {
        success: boolean;
        alertId: string;
        acknowledgedAt: Date;
    };
    getDashboardSummary(): Promise<{
        timestamp: Date;
        overview: MLInsightSummary;
        alerting: AlertMetrics;
        mlEngine: {
            anomaliesDetected: number;
            regressionsAnalyzed: number;
            optimizationSuggestions: number;
            predictiveInsights: number;
            activeAlerts: number;
            dataHistorySize: number;
        };
        system: {
            uptime: number;
            memoryUsage: NodeJS.MemoryUsage;
            version: string;
        };
    }>;
    getLiveFeed(): Observable<any>;
}