Agent Performance Monitor

// Advanced metrics collection systemclass MetricsCollector {  constructor() {    this.collectors = new Map();    this.aggregators = new Map();    this.streams = new Map();    this.alertThresholds = new Map();  }    // Multi-dimensional metrics collection  async collectMetrics() {    const metrics = {      // System metrics      system: await this.collectSystemMetrics(),            // Agent-specific metrics      agents: await this.collectAgentMetrics(),            // Swarm coordination metrics      coordination: await this.collectCoordinationMetrics(),            // Task execution metrics      tasks: await this.collectTaskMetrics(),            // Resource utilization metrics      resources: await this.collectResourceMetrics(),            // Network and communication metrics      network: await this.collectNetworkMetrics()    };        // Real-time processing and analysis    await this.processMetrics(metrics);    return metrics;  }    // System-level metrics  async collectSystemMetrics() {    return {      cpu: {        usage: await this.getCPUUsage(),        loadAverage: await this.getLoadAverage(),        coreUtilization: await this.getCoreUtilization()      },      memory: {        usage: await this.getMemoryUsage(),        available: await this.getAvailableMemory(),        pressure: await this.getMemoryPressure()      },      io: {        diskUsage: await this.getDiskUsage(),        diskIO: await this.getDiskIOStats(),        networkIO: await this.getNetworkIOStats()      },      processes: {        count: await this.getProcessCount(),        threads: await this.getThreadCount(),        handles: await this.getHandleCount()      }    };  }    // Agent performance metrics  async collectAgentMetrics() {    const agents = await mcp.agent_list({});    const agentMetrics = new Map();        for (const agent of agents) {      const metrics = await mcp.agent_metrics({ agentId: agent.id });      agentMetrics.set(agent.id, {        ...metrics,        efficiency: this.calculateEfficiency(metrics),        responsiveness: this.calculateResponsiveness(metrics),        reliability: this.calculateReliability(metrics)      });    }        return agentMetrics;  }}

// Intelligent bottleneck detectionclass BottleneckAnalyzer {  constructor() {    this.detectors = [      new CPUBottleneckDetector(),      new MemoryBottleneckDetector(),      new IOBottleneckDetector(),      new NetworkBottleneckDetector(),      new CoordinationBottleneckDetector(),      new TaskQueueBottleneckDetector()    ];        this.patterns = new Map();    this.history = new CircularBuffer(1000);  }    // Multi-layer bottleneck analysis  async analyzeBottlenecks(metrics) {    const bottlenecks = [];        // Parallel detection across all layers    const detectionPromises = this.detectors.map(detector =>       detector.detect(metrics)    );        const results = await Promise.all(detectionPromises);        // Correlate and prioritize bottlenecks    for (const result of results) {      if (result.detected) {        bottlenecks.push({          type: result.type,          severity: result.severity,          component: result.component,          rootCause: result.rootCause,          impact: result.impact,          recommendations: result.recommendations,          timestamp: Date.now()        });      }    }        // Pattern recognition for recurring bottlenecks    await this.updatePatterns(bottlenecks);        return this.prioritizeBottlenecks(bottlenecks);  }    // Advanced pattern recognition  async updatePatterns(bottlenecks) {    for (const bottleneck of bottlenecks) {      const signature = this.createBottleneckSignature(bottleneck);            if (this.patterns.has(signature)) {        const pattern = this.patterns.get(signature);        pattern.frequency++;        pattern.lastOccurrence = Date.now();        pattern.averageInterval = this.calculateAverageInterval(pattern);      } else {        this.patterns.set(signature, {          signature,          frequency: 1,          firstOccurrence: Date.now(),          lastOccurrence: Date.now(),          averageInterval: 0,          predictedNext: null        });      }    }  }}

// Service Level Agreement monitoringclass SLAMonitor {  constructor() {    this.slaDefinitions = new Map();    this.violations = new Map();    this.alertChannels = new Set();    this.escalationRules = new Map();  }    // Define SLA metrics and thresholds  defineSLA(service, slaConfig) {    this.slaDefinitions.set(service, {      availability: slaConfig.availability || 99.9, // percentage      responseTime: slaConfig.responseTime || 1000, // milliseconds      throughput: slaConfig.throughput || 100, // requests per second      errorRate: slaConfig.errorRate || 0.1, // percentage      recoveryTime: slaConfig.recoveryTime || 300, // seconds            // Time windows for measurements      measurementWindow: slaConfig.measurementWindow || 300, // seconds      evaluationInterval: slaConfig.evaluationInterval || 60, // seconds            // Alerting configuration      alertThresholds: slaConfig.alertThresholds || {        warning: 0.8, // 80% of SLA threshold        critical: 0.9, // 90% of SLA threshold        breach: 1.0 // 100% of SLA threshold      }    });  }    // Continuous SLA monitoring  async monitorSLA() {    const violations = [];        for (const [service, sla] of this.slaDefinitions) {      const metrics = await this.getServiceMetrics(service);      const evaluation = this.evaluateSLA(service, sla, metrics);            if (evaluation.violated) {        violations.push(evaluation);        await this.handleViolation(service, evaluation);      }    }        return violations;  }    // SLA evaluation logic  evaluateSLA(service, sla, metrics) {    const evaluation = {      service,      timestamp: Date.now(),      violated: false,      violations: []    };        // Availability check    if (metrics.availability < sla.availability) {      evaluation.violations.push({        metric: 'availability',        expected: sla.availability,        actual: metrics.availability,        severity: this.calculateSeverity(metrics.availability, sla.availability, sla.alertThresholds)      });      evaluation.violated = true;    }        // Response time check    if (metrics.responseTime > sla.responseTime) {      evaluation.violations.push({        metric: 'responseTime',        expected: sla.responseTime,        actual: metrics.responseTime,        severity: this.calculateSeverity(metrics.responseTime, sla.responseTime, sla.alertThresholds)      });      evaluation.violated = true;    }        // Additional SLA checks...        return evaluation;  }}

// Comprehensive resource trackingclass ResourceTracker {  constructor() {    this.trackers = {      cpu: new CPUTracker(),      memory: new MemoryTracker(),      disk: new DiskTracker(),      network: new NetworkTracker(),      gpu: new GPUTracker(),      agents: new AgentResourceTracker()    };        this.forecaster = new ResourceForecaster();    this.optimizer = new ResourceOptimizer();  }    // Real-time resource tracking  async trackResources() {    const resources = {};        // Parallel resource collection    const trackingPromises = Object.entries(this.trackers).map(      async ([type, tracker]) => [type, await tracker.collect()]    );        const results = await Promise.all(trackingPromises);        for (const [type, data] of results) {      resources[type] = {        ...data,        utilization: this.calculateUtilization(data),        efficiency: this.calculateEfficiency(data),        trend: this.calculateTrend(type, data),        forecast: await this.forecaster.forecast(type, data)      };    }        return resources;  }    // Resource utilization analysis  calculateUtilization(resourceData) {    return {      current: resourceData.used / resourceData.total,      peak: resourceData.peak / resourceData.total,      average: resourceData.average / resourceData.total,      percentiles: {        p50: resourceData.p50 / resourceData.total,        p90: resourceData.p90 / resourceData.total,        p95: resourceData.p95 / resourceData.total,        p99: resourceData.p99 / resourceData.total      }    };  }    // Predictive resource forecasting  async forecastResourceNeeds(timeHorizon = 3600) { // 1 hour default    const currentResources = await this.trackResources();    const forecasts = {};        for (const [type, data] of Object.entries(currentResources)) {      forecasts[type] = await this.forecaster.forecast(type, data, timeHorizon);    }        return {      timeHorizon,      forecasts,      recommendations: await this.optimizer.generateRecommendations(forecasts),      confidence: this.calculateForecastConfidence(forecasts)    };  }}

// Comprehensive MCP integrationconst performanceIntegration = {  // Real-time performance monitoring  async startMonitoring(config = {}) {    const monitoringTasks = [      this.monitorSwarmHealth(),      this.monitorAgentPerformance(),      this.monitorResourceUtilization(),      this.monitorBottlenecks(),      this.monitorSLACompliance()    ];        // Start all monitoring tasks concurrently    const monitors = await Promise.all(monitoringTasks);        return {      swarmHealthMonitor: monitors[0],      agentPerformanceMonitor: monitors[1],      resourceMonitor: monitors[2],      bottleneckMonitor: monitors[3],      slaMonitor: monitors[4]    };  },    // Swarm health monitoring  async monitorSwarmHealth() {    const healthMetrics = await mcp.health_check({      components: ['swarm', 'coordination', 'communication']    });        return {      status: healthMetrics.overall,      components: healthMetrics.components,      issues: healthMetrics.issues,      recommendations: healthMetrics.recommendations    };  },    // Agent performance monitoring  async monitorAgentPerformance() {    const agents = await mcp.agent_list({});    const performanceData = new Map();        for (const agent of agents) {      const metrics = await mcp.agent_metrics({ agentId: agent.id });      const performance = await mcp.performance_report({        format: 'detailed',        timeframe: '24h'      });            performanceData.set(agent.id, {        ...metrics,        performance,        efficiency: this.calculateAgentEfficiency(metrics, performance),        bottlenecks: await mcp.bottleneck_analyze({ component: agent.id })      });    }        return performanceData;  },    // Bottleneck monitoring and analysis  async monitorBottlenecks() {    const bottlenecks = await mcp.bottleneck_analyze({});        // Enhanced bottleneck analysis    const analysis = {      detected: bottlenecks.length > 0,      count: bottlenecks.length,      severity: this.calculateOverallSeverity(bottlenecks),      categories: this.categorizeBottlenecks(bottlenecks),      trends: await this.analyzeBottleneckTrends(bottlenecks),      predictions: await this.predictBottlenecks(bottlenecks)    };        return analysis;  }};

// Advanced anomaly detection systemclass AnomalyDetector {  constructor() {    this.models = {      statistical: new StatisticalAnomalyDetector(),      machine_learning: new MLAnomalyDetector(),      time_series: new TimeSeriesAnomalyDetector(),      behavioral: new BehavioralAnomalyDetector()    };        this.ensemble = new EnsembleDetector(this.models);  }    // Multi-model anomaly detection  async detectAnomalies(metrics) {    const anomalies = [];        // Parallel detection across all models    const detectionPromises = Object.entries(this.models).map(      async ([modelType, model]) => {        const detected = await model.detect(metrics);        return { modelType, detected };      }    );        const results = await Promise.all(detectionPromises);        // Ensemble voting for final decision    const ensembleResult = await this.ensemble.vote(results);        return {      anomalies: ensembleResult.anomalies,      confidence: ensembleResult.confidence,      consensus: ensembleResult.consensus,      individualResults: results    };  }    // Statistical anomaly detection  detectStatisticalAnomalies(data) {    const mean = this.calculateMean(data);    const stdDev = this.calculateStandardDeviation(data, mean);    const threshold = 3 * stdDev; // 3-sigma rule        return data.filter(point => Math.abs(point - mean) > threshold)               .map(point => ({                 value: point,                 type: 'statistical',                 deviation: Math.abs(point - mean) / stdDev,                 probability: this.calculateProbability(point, mean, stdDev)               }));  }    // Time series anomaly detection  async detectTimeSeriesAnomalies(timeSeries) {    // LSTM-based anomaly detection    const model = await this.loadTimeSeriesModel();    const predictions = await model.predict(timeSeries);        const anomalies = [];    for (let i = 0; i < timeSeries.length; i++) {      const error = Math.abs(timeSeries[i] - predictions[i]);      const threshold = this.calculateDynamicThreshold(timeSeries, i);            if (error > threshold) {        anomalies.push({          timestamp: i,          actual: timeSeries[i],          predicted: predictions[i],          error: error,          type: 'time_series'        });      }    }        return anomalies;  }}

// Dashboard data providerclass DashboardProvider {  constructor() {    this.updateInterval = 1000; // 1 second updates    this.subscribers = new Set();    this.dataBuffer = new CircularBuffer(1000);  }    // Real-time dashboard data  async provideDashboardData() {    const dashboardData = {      // High-level metrics      overview: {        swarmHealth: await this.getSwarmHealthScore(),        activeAgents: await this.getActiveAgentCount(),        totalTasks: await this.getTotalTaskCount(),        averageResponseTime: await this.getAverageResponseTime()      },            // Performance metrics      performance: {        throughput: await this.getCurrentThroughput(),        latency: await this.getCurrentLatency(),        errorRate: await this.getCurrentErrorRate(),        utilization: await this.getResourceUtilization()      },            // Real-time charts data      timeSeries: {        cpu: this.getCPUTimeSeries(),        memory: this.getMemoryTimeSeries(),        network: this.getNetworkTimeSeries(),        tasks: this.getTaskTimeSeries()      },            // Alerts and notifications      alerts: await this.getActiveAlerts(),      notifications: await this.getRecentNotifications(),            // Agent status      agents: await this.getAgentStatusSummary(),            timestamp: Date.now()    };        // Broadcast to subscribers    this.broadcast(dashboardData);        return dashboardData;  }    // WebSocket subscription management  subscribe(callback) {    this.subscribers.add(callback);    return () => this.subscribers.delete(callback);  }    broadcast(data) {    this.subscribers.forEach(callback => {      try {        callback(data);      } catch (error) {        console.error('Dashboard subscriber error:', error);      }    });  }}

// Performance analytics engineconst analytics = {  // Key Performance Indicators  calculateKPIs(metrics) {    return {      // Availability metrics      uptime: this.calculateUptime(metrics),      availability: this.calculateAvailability(metrics),            // Performance metrics      responseTime: {        average: this.calculateAverage(metrics.responseTimes),        p50: this.calculatePercentile(metrics.responseTimes, 50),        p90: this.calculatePercentile(metrics.responseTimes, 90),        p95: this.calculatePercentile(metrics.responseTimes, 95),        p99: this.calculatePercentile(metrics.responseTimes, 99)      },            // Throughput metrics      throughput: this.calculateThroughput(metrics),            // Error metrics      errorRate: this.calculateErrorRate(metrics),            // Resource efficiency      resourceEfficiency: this.calculateResourceEfficiency(metrics),            // Cost metrics      costEfficiency: this.calculateCostEfficiency(metrics)    };  },    // Trend analysis  analyzeTrends(historicalData, timeWindow = '7d') {    return {      performance: this.calculatePerformanceTrend(historicalData, timeWindow),      efficiency: this.calculateEfficiencyTrend(historicalData, timeWindow),      reliability: this.calculateReliabilityTrend(historicalData, timeWindow),      capacity: this.calculateCapacityTrend(historicalData, timeWindow)    };  }};