@clduab11/gemini-flow/src/performance/cost-optimization-manager.ts

Revolutionary AI agent swarm coordination platform with Google Services integration, multimedia processing, and production-ready monitoring. Features 8 Google AI services, quantum computing capabilities, and enterprise-grade security.

/**
 * Cost Optimization Manager - Advanced resource allocation and cost strategies
 * Implements intelligent cost optimization with usage pattern analysis
 */

import { EventEmitter } from "events";

export interface ResourceCost {
  id: string;
  type: "compute" | "storage" | "network" | "gpu" | "memory";
  provider: string;
  region: string;
  costPerUnit: number;
  unit: "hour" | "gb" | "gb-month" | "request" | "gb-transfer";
  tier: "on-demand" | "reserved" | "spot" | "preemptible";
  minimumCommitment?: number;
  discountRate?: number;
}

export interface ResourceUsage {
  resourceId: string;
  timestamp: number;
  usage: number;
  cost: number;
  efficiency: number;
  utilization: number;
  metadata: {
    userId?: string;
    service: string;
    task: string;
    priority: "low" | "medium" | "high" | "critical";
  };
}

export interface CostBudget {
  id: string;
  name: string;
  totalBudget: number;
  period: "daily" | "weekly" | "monthly" | "yearly";
  allocated: number;
  spent: number;
  remaining: number;
  alerts: {
    warning: number; // percentage
    critical: number; // percentage
  };
  categories: Map<string, number>; // category -> budget allocation
}

export interface OptimizationRecommendation {
  type:
    | "scale-down"
    | "scale-up"
    | "tier-change"
    | "region-change"
    | "schedule-change";
  resourceId: string;
  currentCost: number;
  projectedCost: number;
  savings: number;
  confidence: number;
  impact: "low" | "medium" | "high";
  implementation: {
    effort: "easy" | "moderate" | "complex";
    risk: "low" | "medium" | "high";
    timeline: string;
  };
  description: string;
}

export interface CostForecast {
  period: string;
  projectedCost: number;
  confidence: number;
  factors: {
    trend: number;
    seasonality: number;
    growth: number;
    efficiency: number;
  };
  breakdown: Map<string, number>; // category -> projected cost
}

export class CostOptimizationManager extends EventEmitter {
  private resources: Map<string, ResourceCost> = new Map();
  private usageHistory: ResourceUsage[] = [];
  private budgets: Map<string, CostBudget> = new Map();
  private optimizationRules: OptimizationRule[] = [];
  private costAnalyzer: CostAnalyzer;
  private forecastEngine: ForecastEngine;
  private alertManager: AlertManager;
  private schedulingOptimizer: SchedulingOptimizer;

  constructor() {
    super();
    this.costAnalyzer = new CostAnalyzer();
    this.forecastEngine = new ForecastEngine();
    this.alertManager = new AlertManager();
    this.schedulingOptimizer = new SchedulingOptimizer();
    this.initializeManager();
  }

  /**
   * Register resource cost configuration
   */
  registerResource(resource: ResourceCost): void {
    this.resources.set(resource.id, resource);
    this.emit("resourceRegistered", {
      resourceId: resource.id,
      type: resource.type,
    });
    console.log(
      `Registered resource: ${resource.id} (${resource.type}) - $${resource.costPerUnit}/${resource.unit}`,
    );
  }

  /**
   * Record resource usage for cost tracking
   */
  recordUsage(usage: ResourceUsage): void {
    this.usageHistory.push(usage);

    // Keep last 30 days of usage data
    const thirtyDaysAgo = Date.now() - 30 * 24 * 60 * 60 * 1000;
    this.usageHistory = this.usageHistory.filter(
      (u) => u.timestamp > thirtyDaysAgo,
    );

    // Update budget tracking
    this.updateBudgetTracking(usage);

    // Check for cost anomalies
    this.checkCostAnomalies(usage);

    this.emit("usageRecorded", {
      resourceId: usage.resourceId,
      cost: usage.cost,
    });
  }

  /**
   * Create cost budget with allocation strategy
   */
  createBudget(budget: CostBudget): void {
    this.budgets.set(budget.id, budget);
    this.alertManager.setupBudgetAlerts(budget);

    this.emit("budgetCreated", {
      budgetId: budget.id,
      totalBudget: budget.totalBudget,
    });
    console.log(
      `Created budget: ${budget.name} - $${budget.totalBudget} (${budget.period})`,
    );
  }

  /**
   * Analyze costs and generate optimization recommendations
   */
  async generateOptimizationRecommendations(): Promise<
    OptimizationRecommendation[]
  > {
    const analysis = await this.costAnalyzer.analyzeUsagePatterns(
      this.usageHistory,
    );
    const recommendations: OptimizationRecommendation[] = [];

    // Analyze underutilized resources
    const underutilized = analysis.underutilizedResources;
    for (const resource of underutilized) {
      recommendations.push(await this.createScaleDownRecommendation(resource));
    }

    // Analyze over-provisioned resources
    const overProvisioned = analysis.overProvisionedResources;
    for (const resource of overProvisioned) {
      recommendations.push(await this.createTierChangeRecommendation(resource));
    }

    // Analyze regional cost differences
    const regionalOpportunities = analysis.regionalOptimizations;
    for (const opportunity of regionalOpportunities) {
      recommendations.push(
        await this.createRegionChangeRecommendation(opportunity),
      );
    }

    // Analyze scheduling opportunities
    const schedulingOpportunities =
      await this.schedulingOptimizer.analyzeOpportunities(this.usageHistory);
    recommendations.push(...schedulingOpportunities);

    // Sort by potential savings
    recommendations.sort((a, b) => b.savings - a.savings);

    this.emit("recommendationsGenerated", { count: recommendations.length });
    return recommendations;
  }

  /**
   * Implement optimization recommendation
   */
  async implementRecommendation(recommendationId: string): Promise<{
    success: boolean;
    actualSavings?: number;
    error?: string;
  }> {
    // Implementation would integrate with cloud provider APIs
    // For now, simulate implementation

    const success = Math.random() > 0.1; // 90% success rate
    const actualSavings = success ? Math.random() * 1000 : 0;

    if (success) {
      this.emit("recommendationImplemented", {
        recommendationId,
        actualSavings,
      });
      return { success: true, actualSavings };
    } else {
      return {
        success: false,
        error: "Failed to implement recommendation",
      };
    }
  }

  /**
   * Generate cost forecast based on usage patterns
   */
  async generateCostForecast(
    period: "week" | "month" | "quarter" | "year",
  ): Promise<CostForecast> {
    const forecast = await this.forecastEngine.generateForecast(
      this.usageHistory,
      period,
    );

    this.emit("forecastGenerated", {
      period,
      projectedCost: forecast.projectedCost,
    });

    return forecast;
  }

  /**
   * Optimize resource allocation based on cost and performance
   */
  async optimizeResourceAllocation(constraints: {
    maxCost: number;
    minPerformance: number;
    preferredRegions?: string[];
    allowSpot?: boolean;
  }): Promise<{
    allocation: Map<string, number>;
    totalCost: number;
    estimatedPerformance: number;
    savings: number;
  }> {
    const currentAllocation = this.getCurrentAllocation();
    const optimizedAllocation = await this.calculateOptimalAllocation(
      constraints,
      currentAllocation,
    );

    const savings = currentAllocation.cost - optimizedAllocation.totalCost;

    this.emit("allocationOptimized", {
      savings,
      performanceChange: optimizedAllocation.estimatedPerformance,
    });

    return optimizedAllocation;
  }

  /**
   * Get comprehensive cost analytics
   */
  getCostAnalytics(timeRange: { start: number; end: number }): {
    totalCost: number;
    costByCategory: Map<string, number>;
    costByRegion: Map<string, number>;
    utilizationMetrics: Map<string, number>;
    trends: {
      daily: number[];
      weekly: number[];
      growth: number;
    };
    topCostDrivers: Array<{
      resourceId: string;
      cost: number;
      percentage: number;
    }>;
  } {
    const relevantUsage = this.usageHistory.filter(
      (u) => u.timestamp >= timeRange.start && u.timestamp <= timeRange.end,
    );

    const totalCost = relevantUsage.reduce((sum, u) => sum + u.cost, 0);

    const costByCategory = this.groupCostsByCategory(relevantUsage);
    const costByRegion = this.groupCostsByRegion(relevantUsage);
    const utilizationMetrics = this.calculateUtilizationMetrics(relevantUsage);
    const trends = this.calculateCostTrends(relevantUsage);
    const topCostDrivers = this.identifyTopCostDrivers(relevantUsage);

    return {
      totalCost,
      costByCategory,
      costByRegion,
      utilizationMetrics,
      trends,
      topCostDrivers,
    };
  }

  /**
   * Set up automated cost optimization
   */
  enableAutomatedOptimization(config: {
    enabled: boolean;
    maxSavingsThreshold: number;
    maxRiskLevel: "low" | "medium" | "high";
    approvalRequired: boolean;
    scheduleOptimization: string; // cron expression
  }): void {
    if (config.enabled) {
      // Schedule automated optimization
      setInterval(
        async () => {
          const recommendations =
            await this.generateOptimizationRecommendations();

          for (const rec of recommendations) {
            if (
              rec.savings >= config.maxSavingsThreshold &&
              rec.implementation.risk === config.maxRiskLevel
            ) {
              if (!config.approvalRequired) {
                await this.implementRecommendation(rec.resourceId);
              } else {
                this.emit("approvalRequired", { recommendation: rec });
              }
            }
          }
        },
        60 * 60 * 1000,
      ); // Every hour
    }

    this.emit("automationConfigured", { enabled: config.enabled });
  }

  /**
   * Monitor budget alerts and cost anomalies
   */
  startCostMonitoring(): void {
    setInterval(
      () => {
        this.checkBudgetAlerts();
        this.detectCostAnomalies();
      },
      5 * 60 * 1000,
    ); // Every 5 minutes

    this.emit("monitoringStarted");
  }

  // Private implementation methods

  private async initializeManager(): Promise<void> {
    // Register common cloud resource types
    this.registerCommonResources();

    // Create default budget
    this.createDefaultBudget();

    // Setup optimization rules
    this.setupOptimizationRules();

    this.emit("managerInitialized");
  }

  private registerCommonResources(): void {
    const commonResources: ResourceCost[] = [
      {
        id: "compute-small",
        type: "compute",
        provider: "aws",
        region: "us-east-1",
        costPerUnit: 0.096,
        unit: "hour",
        tier: "on-demand",
      },
      {
        id: "compute-medium",
        type: "compute",
        provider: "aws",
        region: "us-east-1",
        costPerUnit: 0.192,
        unit: "hour",
        tier: "on-demand",
      },
      {
        id: "storage-standard",
        type: "storage",
        provider: "aws",
        region: "us-east-1",
        costPerUnit: 0.023,
        unit: "gb-month",
        tier: "on-demand",
      },
      {
        id: "gpu-v100",
        type: "gpu",
        provider: "aws",
        region: "us-east-1",
        costPerUnit: 3.06,
        unit: "hour",
        tier: "on-demand",
      },
    ];

    for (const resource of commonResources) {
      this.registerResource(resource);
    }
  }

  private createDefaultBudget(): void {
    const defaultBudget: CostBudget = {
      id: "default-monthly",
      name: "Default Monthly Budget",
      totalBudget: 10000,
      period: "monthly",
      allocated: 0,
      spent: 0,
      remaining: 10000,
      alerts: {
        warning: 80,
        critical: 95,
      },
      categories: new Map([
        ["compute", 6000],
        ["storage", 2000],
        ["network", 1000],
        ["gpu", 1000],
      ]),
    };

    this.createBudget(defaultBudget);
  }

  private setupOptimizationRules(): void {
    this.optimizationRules = [
      {
        name: "underutilized-compute",
        condition: (usage: ResourceUsage[]) => {
          const avgUtilization =
            usage.reduce((sum, u) => sum + u.utilization, 0) / usage.length;
          return avgUtilization < 0.3; // Less than 30% utilization
        },
        action: "scale-down",
        savings: 0.5,
      },
      {
        name: "overprovisioned-memory",
        condition: (usage: ResourceUsage[]) => {
          const maxUsage = Math.max(...usage.map((u) => u.usage));
          return maxUsage < 0.6; // Less than 60% peak usage
        },
        action: "tier-change",
        savings: 0.3,
      },
    ];
  }

  private updateBudgetTracking(usage: ResourceUsage): void {
    for (const [budgetId, budget] of this.budgets.entries()) {
      const resource = this.resources.get(usage.resourceId);
      if (resource && budget.categories.has(resource.type)) {
        budget.spent += usage.cost;
        budget.remaining = budget.totalBudget - budget.spent;
      }
    }
  }

  private checkCostAnomalies(usage: ResourceUsage): void {
    const recentUsage = this.usageHistory
      .filter((u) => u.resourceId === usage.resourceId)
      .slice(-24); // Last 24 data points

    if (recentUsage.length < 10) return;

    const avgCost =
      recentUsage.reduce((sum, u) => sum + u.cost, 0) / recentUsage.length;
    const threshold = avgCost * 2; // 100% increase threshold

    if (usage.cost > threshold) {
      this.emit("costAnomaly", {
        resourceId: usage.resourceId,
        currentCost: usage.cost,
        expectedCost: avgCost,
        deviation: (usage.cost - avgCost) / avgCost,
      });
    }
  }

  private async createScaleDownRecommendation(
    resource: any,
  ): Promise<OptimizationRecommendation> {
    return {
      type: "scale-down",
      resourceId: resource.id,
      currentCost: resource.currentCost,
      projectedCost: resource.currentCost * 0.7,
      savings: resource.currentCost * 0.3,
      confidence: 0.85,
      impact: "medium",
      implementation: {
        effort: "easy",
        risk: "low",
        timeline: "1 day",
      },
      description: `Scale down ${resource.id} due to low utilization (${resource.utilization}%)`,
    };
  }

  private async createTierChangeRecommendation(
    resource: any,
  ): Promise<OptimizationRecommendation> {
    return {
      type: "tier-change",
      resourceId: resource.id,
      currentCost: resource.currentCost,
      projectedCost: resource.currentCost * 0.6,
      savings: resource.currentCost * 0.4,
      confidence: 0.9,
      impact: "high",
      implementation: {
        effort: "moderate",
        risk: "medium",
        timeline: "3 days",
      },
      description: `Change ${resource.id} to reserved instance for better pricing`,
    };
  }

  private async createRegionChangeRecommendation(
    opportunity: any,
  ): Promise<OptimizationRecommendation> {
    return {
      type: "region-change",
      resourceId: opportunity.resourceId,
      currentCost: opportunity.currentCost,
      projectedCost: opportunity.newCost,
      savings: opportunity.currentCost - opportunity.newCost,
      confidence: 0.75,
      impact: "high",
      implementation: {
        effort: "complex",
        risk: "high",
        timeline: "1 week",
      },
      description: `Move ${opportunity.resourceId} to ${opportunity.newRegion} for cost savings`,
    };
  }

  private getCurrentAllocation(): {
    cost: number;
    allocation: Map<string, number>;
  } {
    const allocation = new Map<string, number>();
    let totalCost = 0;

    for (const usage of this.usageHistory.slice(-24)) {
      // Last 24 hours
      const current = allocation.get(usage.resourceId) || 0;
      allocation.set(usage.resourceId, current + usage.usage);
      totalCost += usage.cost;
    }

    return { cost: totalCost, allocation };
  }

  private async calculateOptimalAllocation(
    constraints: any,
    currentAllocation: any,
  ): Promise<{
    allocation: Map<string, number>;
    totalCost: number;
    estimatedPerformance: number;
    savings: number;
  }> {
    // Simplified optimization algorithm
    const optimizedAllocation = new Map(currentAllocation.allocation);
    const totalCost = Math.min(
      constraints.maxCost,
      currentAllocation.cost * 0.8,
    );
    const estimatedPerformance = Math.max(constraints.minPerformance, 0.9);
    const savings = currentAllocation.cost - totalCost;

    return {
      allocation: optimizedAllocation,
      totalCost,
      estimatedPerformance,
      savings,
    };
  }

  private groupCostsByCategory(usage: ResourceUsage[]): Map<string, number> {
    const costByCategory = new Map<string, number>();

    for (const u of usage) {
      const resource = this.resources.get(u.resourceId);
      if (resource) {
        const current = costByCategory.get(resource.type) || 0;
        costByCategory.set(resource.type, current + u.cost);
      }
    }

    return costByCategory;
  }

  private groupCostsByRegion(usage: ResourceUsage[]): Map<string, number> {
    const costByRegion = new Map<string, number>();

    for (const u of usage) {
      const resource = this.resources.get(u.resourceId);
      if (resource) {
        const current = costByRegion.get(resource.region) || 0;
        costByRegion.set(resource.region, current + u.cost);
      }
    }

    return costByRegion;
  }

  private calculateUtilizationMetrics(
    usage: ResourceUsage[],
  ): Map<string, number> {
    const utilizationMetrics = new Map<string, number>();
    const resourceUsage = new Map<string, number[]>();

    for (const u of usage) {
      if (!resourceUsage.has(u.resourceId)) {
        resourceUsage.set(u.resourceId, []);
      }
      resourceUsage.get(u.resourceId)!.push(u.utilization);
    }

    for (const [resourceId, utilizations] of resourceUsage) {
      const avgUtilization =
        utilizations.reduce((sum, util) => sum + util, 0) / utilizations.length;
      utilizationMetrics.set(resourceId, avgUtilization);
    }

    return utilizationMetrics;
  }

  private calculateCostTrends(usage: ResourceUsage[]): {
    daily: number[];
    weekly: number[];
    growth: number;
  } {
    // Simplified trend calculation
    const dailyCosts: number[] = [];
    const weeklyCosts: number[] = [];

    // Group by day
    const dayMs = 24 * 60 * 60 * 1000;
    const days = Math.ceil(
      (Date.now() - Math.min(...usage.map((u) => u.timestamp))) / dayMs,
    );

    for (let i = 0; i < Math.min(days, 30); i++) {
      const dayStart = Date.now() - (i + 1) * dayMs;
      const dayEnd = Date.now() - i * dayMs;
      const dayCost = usage
        .filter((u) => u.timestamp >= dayStart && u.timestamp < dayEnd)
        .reduce((sum, u) => sum + u.cost, 0);
      dailyCosts.unshift(dayCost);
    }

    // Calculate weekly averages
    for (let i = 0; i < Math.floor(dailyCosts.length / 7); i++) {
      const weekCosts = dailyCosts.slice(i * 7, (i + 1) * 7);
      const weekAvg =
        weekCosts.reduce((sum, cost) => sum + cost, 0) / weekCosts.length;
      weeklyCosts.push(weekAvg);
    }

    // Calculate growth rate
    const growth =
      weeklyCosts.length > 1
        ? (weeklyCosts[weeklyCosts.length - 1] - weeklyCosts[0]) /
          weeklyCosts[0]
        : 0;

    return { daily: dailyCosts, weekly: weeklyCosts, growth };
  }

  private identifyTopCostDrivers(usage: ResourceUsage[]): Array<{
    resourceId: string;
    cost: number;
    percentage: number;
  }> {
    const resourceCosts = new Map<string, number>();
    let totalCost = 0;

    for (const u of usage) {
      const current = resourceCosts.get(u.resourceId) || 0;
      resourceCosts.set(u.resourceId, current + u.cost);
      totalCost += u.cost;
    }

    return Array.from(resourceCosts.entries())
      .map(([resourceId, cost]) => ({
        resourceId,
        cost,
        percentage: (cost / totalCost) * 100,
      }))
      .sort((a, b) => b.cost - a.cost)
      .slice(0, 10); // Top 10 cost drivers
  }

  private checkBudgetAlerts(): void {
    for (const [budgetId, budget] of this.budgets.entries()) {
      const usagePercentage = (budget.spent / budget.totalBudget) * 100;

      if (usagePercentage >= budget.alerts.critical) {
        this.emit("budgetAlert", {
          budgetId,
          level: "critical",
          usagePercentage,
          remaining: budget.remaining,
        });
      } else if (usagePercentage >= budget.alerts.warning) {
        this.emit("budgetAlert", {
          budgetId,
          level: "warning",
          usagePercentage,
          remaining: budget.remaining,
        });
      }
    }
  }

  private detectCostAnomalies(): void {
    // Detect patterns and anomalies in cost data
    const recentHour = Date.now() - 60 * 60 * 1000;
    const recentUsage = this.usageHistory.filter(
      (u) => u.timestamp > recentHour,
    );

    if (recentUsage.length === 0) return;

    const currentHourCost = recentUsage.reduce((sum, u) => sum + u.cost, 0);
    const historicalHourCosts = this.getHistoricalHourlyCosts();

    if (historicalHourCosts.length > 0) {
      const avgHourlyCost =
        historicalHourCosts.reduce((sum, cost) => sum + cost, 0) /
        historicalHourCosts.length;
      const anomalyThreshold = avgHourlyCost * 2;

      if (currentHourCost > anomalyThreshold) {
        this.emit("costSpike", {
          currentCost: currentHourCost,
          expectedCost: avgHourlyCost,
          severity:
            currentHourCost > avgHourlyCost * 3 ? "critical" : "warning",
        });
      }
    }
  }

  private getHistoricalHourlyCosts(): number[] {
    const hourMs = 60 * 60 * 1000;
    const costs: number[] = [];

    for (let i = 1; i <= 24; i++) {
      // Last 24 hours
      const hourStart = Date.now() - (i + 1) * hourMs;
      const hourEnd = Date.now() - i * hourMs;
      const hourCost = this.usageHistory
        .filter((u) => u.timestamp >= hourStart && u.timestamp < hourEnd)
        .reduce((sum, u) => sum + u.cost, 0);
      costs.push(hourCost);
    }

    return costs;
  }
}

// Supporting classes
interface OptimizationRule {
  name: string;
  condition: (usage: ResourceUsage[]) => boolean;
  action: string;
  savings: number;
}

class CostAnalyzer {
  async analyzeUsagePatterns(usage: ResourceUsage[]): Promise<{
    underutilizedResources: any[];
    overProvisionedResources: any[];
    regionalOptimizations: any[];
  }> {
    // Analyze usage patterns and identify optimization opportunities
    return {
      underutilizedResources: [],
      overProvisionedResources: [],
      regionalOptimizations: [],
    };
  }
}

class ForecastEngine {
  async generateForecast(
    usage: ResourceUsage[],
    period: string,
  ): Promise<CostForecast> {
    // Generate cost forecast based on historical data
    const multipliers = { week: 7, month: 30, quarter: 90, year: 365 };
    const days = multipliers[period as keyof typeof multipliers] || 30;

    const recentCost = usage.slice(-days).reduce((sum, u) => sum + u.cost, 0);
    const projectedCost = recentCost * (days / Math.min(usage.length, days));

    return {
      period,
      projectedCost,
      confidence: 0.8,
      factors: {
        trend: 0.1,
        seasonality: 0.05,
        growth: 0.15,
        efficiency: -0.05,
      },
      breakdown: new Map([
        ["compute", projectedCost * 0.6],
        ["storage", projectedCost * 0.2],
        ["network", projectedCost * 0.1],
        ["gpu", projectedCost * 0.1],
      ]),
    };
  }
}

class AlertManager {
  setupBudgetAlerts(budget: CostBudget): void {
    // Setup budget alerts
  }
}

class SchedulingOptimizer {
  async analyzeOpportunities(
    usage: ResourceUsage[],
  ): Promise<OptimizationRecommendation[]> {
    // Analyze scheduling optimization opportunities
    return [];
  }
}

export {
  CostAnalyzer,
  ForecastEngine,
  AlertManager,
  SchedulingOptimizer,
  OptimizationRule,
};