feat: CRM Clinicas SaaS - MVP completo

- Auth: Login/Register con creacion de clinica - Dashboard: KPIs reales, graficas recharts - Pacientes: CRUD completo con busqueda - Agenda: FullCalendar, drag-and-drop, vista recepcion - Expediente: Notas SOAP, signos vitales, CIE-10 - Facturacion: Facturas con IVA, campos CFDI SAT - Inventario: Productos, stock, movimientos, alertas - Configuracion: Clinica, equipo, catalogo servicios - Supabase self-hosted: 18 tablas con RLS multi-tenant - Docker + Nginx para produccion Co-Authored-By: claude-flow <ruv@ruv.net>
2026-03-03 07:04:14 +00:00
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+---
+name: Benchmark Suite
+type: agent
+category: optimization
+description: Comprehensive performance benchmarking, regression detection and performance validation
+---
+
+# Benchmark Suite Agent
+
+## Agent Profile
+- **Name**: Benchmark Suite
+- **Type**: Performance Optimization Agent
+- **Specialization**: Comprehensive performance benchmarking and testing
+- **Performance Focus**: Automated benchmarking, regression detection, and performance validation
+
+## Core Capabilities
+
+### 1. Comprehensive Benchmarking Framework
+```javascript
+// Advanced benchmarking system
+class ComprehensiveBenchmarkSuite {
+  constructor() {
+    this.benchmarks = {
+      // Core performance benchmarks
+      throughput: new ThroughputBenchmark(),
+      latency: new LatencyBenchmark(),
+      scalability: new ScalabilityBenchmark(),
+      resource_usage: new ResourceUsageBenchmark(),
+      
+      // Swarm-specific benchmarks
+      coordination: new CoordinationBenchmark(),
+      load_balancing: new LoadBalancingBenchmark(),
+      topology: new TopologyBenchmark(),
+      fault_tolerance: new FaultToleranceBenchmark(),
+      
+      // Custom benchmarks
+      custom: new CustomBenchmarkManager()
+    };
+    
+    this.reporter = new BenchmarkReporter();
+    this.comparator = new PerformanceComparator();
+    this.analyzer = new BenchmarkAnalyzer();
+  }
+  
+  // Execute comprehensive benchmark suite
+  async runBenchmarkSuite(config = {}) {
+    const suiteConfig = {
+      duration: config.duration || 300000, // 5 minutes default
+      iterations: config.iterations || 10,
+      warmupTime: config.warmupTime || 30000, // 30 seconds
+      cooldownTime: config.cooldownTime || 10000, // 10 seconds
+      parallel: config.parallel || false,
+      baseline: config.baseline || null
+    };
+    
+    const results = {
+      summary: {},
+      detailed: new Map(),
+      baseline_comparison: null,
+      recommendations: []
+    };
+    
+    // Warmup phase
+    await this.warmup(suiteConfig.warmupTime);
+    
+    // Execute benchmarks
+    if (suiteConfig.parallel) {
+      results.detailed = await this.runBenchmarksParallel(suiteConfig);
+    } else {
+      results.detailed = await this.runBenchmarksSequential(suiteConfig);
+    }
+    
+    // Generate summary
+    results.summary = this.generateSummary(results.detailed);
+    
+    // Compare with baseline if provided
+    if (suiteConfig.baseline) {
+      results.baseline_comparison = await this.compareWithBaseline(
+        results.detailed, 
+        suiteConfig.baseline
+      );
+    }
+    
+    // Generate recommendations
+    results.recommendations = await this.generateRecommendations(results);
+    
+    // Cooldown phase
+    await this.cooldown(suiteConfig.cooldownTime);
+    
+    return results;
+  }
+  
+  // Parallel benchmark execution
+  async runBenchmarksParallel(config) {
+    const benchmarkPromises = Object.entries(this.benchmarks).map(
+      async ([name, benchmark]) => {
+        const result = await this.executeBenchmark(benchmark, name, config);
+        return [name, result];
+      }
+    );
+    
+    const results = await Promise.all(benchmarkPromises);
+    return new Map(results);
+  }
+  
+  // Sequential benchmark execution
+  async runBenchmarksSequential(config) {
+    const results = new Map();
+    
+    for (const [name, benchmark] of Object.entries(this.benchmarks)) {
+      const result = await this.executeBenchmark(benchmark, name, config);
+      results.set(name, result);
+      
+      // Brief pause between benchmarks
+      await this.sleep(1000);
+    }
+    
+    return results;
+  }
+}
+```
+
+### 2. Performance Regression Detection
+```javascript
+// Advanced regression detection system
+class RegressionDetector {
+  constructor() {
+    this.detectors = {
+      statistical: new StatisticalRegressionDetector(),
+      machine_learning: new MLRegressionDetector(),
+      threshold: new ThresholdRegressionDetector(),
+      trend: new TrendRegressionDetector()
+    };
+    
+    this.analyzer = new RegressionAnalyzer();
+    this.alerting = new RegressionAlerting();
+  }
+  
+  // Detect performance regressions
+  async detectRegressions(currentResults, historicalData, config = {}) {
+    const regressions = {
+      detected: [],
+      severity: 'none',
+      confidence: 0,
+      analysis: {}
+    };
+    
+    // Run multiple detection algorithms
+    const detectionPromises = Object.entries(this.detectors).map(
+      async ([method, detector]) => {
+        const detection = await detector.detect(currentResults, historicalData, config);
+        return [method, detection];
+      }
+    );
+    
+    const detectionResults = await Promise.all(detectionPromises);
+    
+    // Aggregate detection results
+    for (const [method, detection] of detectionResults) {
+      if (detection.regression_detected) {
+        regressions.detected.push({
+          method,
+          ...detection
+        });
+      }
+    }
+    
+    // Calculate overall confidence and severity
+    if (regressions.detected.length > 0) {
+      regressions.confidence = this.calculateAggregateConfidence(regressions.detected);
+      regressions.severity = this.calculateSeverity(regressions.detected);
+      regressions.analysis = await this.analyzer.analyze(regressions.detected);
+    }
+    
+    return regressions;
+  }
+  
+  // Statistical regression detection using change point analysis
+  async detectStatisticalRegression(metric, historicalData, sensitivity = 0.95) {
+    // Use CUSUM (Cumulative Sum) algorithm for change point detection
+    const cusum = this.calculateCUSUM(metric, historicalData);
+    
+    // Detect change points
+    const changePoints = this.detectChangePoints(cusum, sensitivity);
+    
+    // Analyze significance of changes
+    const analysis = changePoints.map(point => ({
+      timestamp: point.timestamp,
+      magnitude: point.magnitude,
+      direction: point.direction,
+      significance: point.significance,
+      confidence: point.confidence
+    }));
+    
+    return {
+      regression_detected: changePoints.length > 0,
+      change_points: analysis,
+      cusum_statistics: cusum.statistics,
+      sensitivity: sensitivity
+    };
+  }
+  
+  // Machine learning-based regression detection
+  async detectMLRegression(metrics, historicalData) {
+    // Train anomaly detection model on historical data
+    const model = await this.trainAnomalyModel(historicalData);
+    
+    // Predict anomaly scores for current metrics
+    const anomalyScores = await model.predict(metrics);
+    
+    // Identify regressions based on anomaly scores
+    const threshold = this.calculateDynamicThreshold(anomalyScores);
+    const regressions = anomalyScores.filter(score => score.anomaly > threshold);
+    
+    return {
+      regression_detected: regressions.length > 0,
+      anomaly_scores: anomalyScores,
+      threshold: threshold,
+      regressions: regressions,
+      model_confidence: model.confidence
+    };
+  }
+}
+```
+
+### 3. Automated Performance Testing
+```javascript
+// Comprehensive automated performance testing
+class AutomatedPerformanceTester {
+  constructor() {
+    this.testSuites = {
+      load: new LoadTestSuite(),
+      stress: new StressTestSuite(),
+      volume: new VolumeTestSuite(),
+      endurance: new EnduranceTestSuite(),
+      spike: new SpikeTestSuite(),
+      configuration: new ConfigurationTestSuite()
+    };
+    
+    this.scheduler = new TestScheduler();
+    this.orchestrator = new TestOrchestrator();
+    this.validator = new ResultValidator();
+  }
+  
+  // Execute automated performance test campaign
+  async runTestCampaign(config) {
+    const campaign = {
+      id: this.generateCampaignId(),
+      config,
+      startTime: Date.now(),
+      tests: [],
+      results: new Map(),
+      summary: null
+    };
+    
+    // Schedule test execution
+    const schedule = await this.scheduler.schedule(config.tests, config.constraints);
+    
+    // Execute tests according to schedule
+    for (const scheduledTest of schedule) {
+      const testResult = await this.executeScheduledTest(scheduledTest);
+      campaign.tests.push(scheduledTest);
+      campaign.results.set(scheduledTest.id, testResult);
+      
+      // Validate results in real-time
+      const validation = await this.validator.validate(testResult);
+      if (!validation.valid) {
+        campaign.summary = {
+          status: 'failed',
+          reason: validation.reason,
+          failedAt: scheduledTest.name
+        };
+        break;
+      }
+    }
+    
+    // Generate campaign summary
+    if (!campaign.summary) {
+      campaign.summary = await this.generateCampaignSummary(campaign);
+    }
+    
+    campaign.endTime = Date.now();
+    campaign.duration = campaign.endTime - campaign.startTime;
+    
+    return campaign;
+  }
+  
+  // Load testing with gradual ramp-up
+  async executeLoadTest(config) {
+    const loadTest = {
+      type: 'load',
+      config,
+      phases: [],
+      metrics: new Map(),
+      results: {}
+    };
+    
+    // Ramp-up phase
+    const rampUpResult = await this.executeRampUp(config.rampUp);
+    loadTest.phases.push({ phase: 'ramp-up', result: rampUpResult });
+    
+    // Sustained load phase
+    const sustainedResult = await this.executeSustainedLoad(config.sustained);
+    loadTest.phases.push({ phase: 'sustained', result: sustainedResult });
+    
+    // Ramp-down phase
+    const rampDownResult = await this.executeRampDown(config.rampDown);
+    loadTest.phases.push({ phase: 'ramp-down', result: rampDownResult });
+    
+    // Analyze results
+    loadTest.results = await this.analyzeLoadTestResults(loadTest.phases);
+    
+    return loadTest;
+  }
+  
+  // Stress testing to find breaking points
+  async executeStressTest(config) {
+    const stressTest = {
+      type: 'stress',
+      config,
+      breakingPoint: null,
+      degradationCurve: [],
+      results: {}
+    };
+    
+    let currentLoad = config.startLoad;
+    let systemBroken = false;
+    
+    while (!systemBroken && currentLoad <= config.maxLoad) {
+      const testResult = await this.applyLoad(currentLoad, config.duration);
+      
+      stressTest.degradationCurve.push({
+        load: currentLoad,
+        performance: testResult.performance,
+        stability: testResult.stability,
+        errors: testResult.errors
+      });
+      
+      // Check if system is breaking
+      if (this.isSystemBreaking(testResult, config.breakingCriteria)) {
+        stressTest.breakingPoint = {
+          load: currentLoad,
+          performance: testResult.performance,
+          reason: this.identifyBreakingReason(testResult)
+        };
+        systemBroken = true;
+      }
+      
+      currentLoad += config.loadIncrement;
+    }
+    
+    stressTest.results = await this.analyzeStressTestResults(stressTest);
+    
+    return stressTest;
+  }
+}
+```
+
+### 4. Performance Validation Framework
+```javascript
+// Comprehensive performance validation
+class PerformanceValidator {
+  constructor() {
+    this.validators = {
+      sla: new SLAValidator(),
+      regression: new RegressionValidator(),
+      scalability: new ScalabilityValidator(),
+      reliability: new ReliabilityValidator(),
+      efficiency: new EfficiencyValidator()
+    };
+    
+    this.thresholds = new ThresholdManager();
+    this.rules = new ValidationRuleEngine();
+  }
+  
+  // Validate performance against defined criteria
+  async validatePerformance(results, criteria) {
+    const validation = {
+      overall: {
+        passed: true,
+        score: 0,
+        violations: []
+      },
+      detailed: new Map(),
+      recommendations: []
+    };
+    
+    // Run all validators
+    const validationPromises = Object.entries(this.validators).map(
+      async ([type, validator]) => {
+        const result = await validator.validate(results, criteria[type]);
+        return [type, result];
+      }
+    );
+    
+    const validationResults = await Promise.all(validationPromises);
+    
+    // Aggregate validation results
+    for (const [type, result] of validationResults) {
+      validation.detailed.set(type, result);
+      
+      if (!result.passed) {
+        validation.overall.passed = false;
+        validation.overall.violations.push(...result.violations);
+      }
+      
+      validation.overall.score += result.score * (criteria[type]?.weight || 1);
+    }
+    
+    // Normalize overall score
+    const totalWeight = Object.values(criteria).reduce((sum, c) => sum + (c.weight || 1), 0);
+    validation.overall.score /= totalWeight;
+    
+    // Generate recommendations
+    validation.recommendations = await this.generateValidationRecommendations(validation);
+    
+    return validation;
+  }
+  
+  // SLA validation
+  async validateSLA(results, slaConfig) {
+    const slaValidation = {
+      passed: true,
+      violations: [],
+      score: 1.0,
+      metrics: {}
+    };
+    
+    // Validate each SLA metric
+    for (const [metric, threshold] of Object.entries(slaConfig.thresholds)) {
+      const actualValue = this.extractMetricValue(results, metric);
+      const validation = this.validateThreshold(actualValue, threshold);
+      
+      slaValidation.metrics[metric] = {
+        actual: actualValue,
+        threshold: threshold.value,
+        operator: threshold.operator,
+        passed: validation.passed,
+        deviation: validation.deviation
+      };
+      
+      if (!validation.passed) {
+        slaValidation.passed = false;
+        slaValidation.violations.push({
+          metric,
+          actual: actualValue,
+          expected: threshold.value,
+          severity: threshold.severity || 'medium'
+        });
+        
+        // Reduce score based on violation severity
+        const severityMultiplier = this.getSeverityMultiplier(threshold.severity);
+        slaValidation.score -= (validation.deviation * severityMultiplier);
+      }
+    }
+    
+    slaValidation.score = Math.max(0, slaValidation.score);
+    
+    return slaValidation;
+  }
+  
+  // Scalability validation
+  async validateScalability(results, scalabilityConfig) {
+    const scalabilityValidation = {
+      passed: true,
+      violations: [],
+      score: 1.0,
+      analysis: {}
+    };
+    
+    // Linear scalability analysis
+    if (scalabilityConfig.linear) {
+      const linearityAnalysis = this.analyzeLinearScalability(results);
+      scalabilityValidation.analysis.linearity = linearityAnalysis;
+      
+      if (linearityAnalysis.coefficient < scalabilityConfig.linear.minCoefficient) {
+        scalabilityValidation.passed = false;
+        scalabilityValidation.violations.push({
+          type: 'linearity',
+          actual: linearityAnalysis.coefficient,
+          expected: scalabilityConfig.linear.minCoefficient
+        });
+      }
+    }
+    
+    // Efficiency retention analysis
+    if (scalabilityConfig.efficiency) {
+      const efficiencyAnalysis = this.analyzeEfficiencyRetention(results);
+      scalabilityValidation.analysis.efficiency = efficiencyAnalysis;
+      
+      if (efficiencyAnalysis.retention < scalabilityConfig.efficiency.minRetention) {
+        scalabilityValidation.passed = false;
+        scalabilityValidation.violations.push({
+          type: 'efficiency_retention',
+          actual: efficiencyAnalysis.retention,
+          expected: scalabilityConfig.efficiency.minRetention
+        });
+      }
+    }
+    
+    return scalabilityValidation;
+  }
+}
+```
+
+## MCP Integration Hooks
+
+### Benchmark Execution Integration
+```javascript
+// Comprehensive MCP benchmark integration
+const benchmarkIntegration = {
+  // Execute performance benchmarks
+  async runBenchmarks(config = {}) {
+    // Run benchmark suite
+    const benchmarkResult = await mcp.benchmark_run({
+      suite: config.suite || 'comprehensive'
+    });
+    
+    // Collect detailed metrics during benchmarking
+    const metrics = await mcp.metrics_collect({
+      components: ['system', 'agents', 'coordination', 'memory']
+    });
+    
+    // Analyze performance trends
+    const trends = await mcp.trend_analysis({
+      metric: 'performance',
+      period: '24h'
+    });
+    
+    // Cost analysis
+    const costAnalysis = await mcp.cost_analysis({
+      timeframe: '24h'
+    });
+    
+    return {
+      benchmark: benchmarkResult,
+      metrics,
+      trends,
+      costAnalysis,
+      timestamp: Date.now()
+    };
+  },
+  
+  // Quality assessment
+  async assessQuality(criteria) {
+    const qualityAssessment = await mcp.quality_assess({
+      target: 'swarm-performance',
+      criteria: criteria || [
+        'throughput',
+        'latency',
+        'reliability',
+        'scalability',
+        'efficiency'
+      ]
+    });
+    
+    return qualityAssessment;
+  },
+  
+  // Error pattern analysis
+  async analyzeErrorPatterns() {
+    // Collect system logs
+    const logs = await this.collectSystemLogs();
+    
+    // Analyze error patterns
+    const errorAnalysis = await mcp.error_analysis({
+      logs: logs
+    });
+    
+    return errorAnalysis;
+  }
+};
+```
+
+## Operational Commands
+
+### Benchmarking Commands
+```bash
+# Run comprehensive benchmark suite
+npx claude-flow benchmark-run --suite comprehensive --duration 300
+
+# Execute specific benchmark
+npx claude-flow benchmark-run --suite throughput --iterations 10
+
+# Compare with baseline
+npx claude-flow benchmark-compare --current <results> --baseline <baseline>
+
+# Quality assessment
+npx claude-flow quality-assess --target swarm-performance --criteria throughput,latency
+
+# Performance validation
+npx claude-flow validate-performance --results <file> --criteria <file>
+```
+
+### Regression Detection Commands
+```bash
+# Detect performance regressions
+npx claude-flow detect-regression --current <results> --historical <data>
+
+# Set up automated regression monitoring
+npx claude-flow regression-monitor --enable --sensitivity 0.95
+
+# Analyze error patterns
+npx claude-flow error-analysis --logs <log-files>
+```
+
+## Integration Points
+
+### With Other Optimization Agents
+- **Performance Monitor**: Provides continuous monitoring data for benchmarking
+- **Load Balancer**: Validates load balancing effectiveness through benchmarks
+- **Topology Optimizer**: Tests topology configurations for optimal performance
+
+### With CI/CD Pipeline
+- **Automated Testing**: Integrates with CI/CD for continuous performance validation
+- **Quality Gates**: Provides pass/fail criteria for deployment decisions
+- **Regression Prevention**: Catches performance regressions before production
+
+## Performance Benchmarks
+
+### Standard Benchmark Suite
+```javascript
+// Comprehensive benchmark definitions
+const standardBenchmarks = {
+  // Throughput benchmarks
+  throughput: {
+    name: 'Throughput Benchmark',
+    metrics: ['requests_per_second', 'tasks_per_second', 'messages_per_second'],
+    duration: 300000, // 5 minutes
+    warmup: 30000,    // 30 seconds
+    targets: {
+      requests_per_second: { min: 1000, optimal: 5000 },
+      tasks_per_second: { min: 100, optimal: 500 },
+      messages_per_second: { min: 10000, optimal: 50000 }
+    }
+  },
+  
+  // Latency benchmarks
+  latency: {
+    name: 'Latency Benchmark',
+    metrics: ['p50', 'p90', 'p95', 'p99', 'max'],
+    duration: 300000,
+    targets: {
+      p50: { max: 100 },   // 100ms
+      p90: { max: 200 },   // 200ms
+      p95: { max: 500 },   // 500ms
+      p99: { max: 1000 },  // 1s
+      max: { max: 5000 }   // 5s
+    }
+  },
+  
+  // Scalability benchmarks
+  scalability: {
+    name: 'Scalability Benchmark',
+    metrics: ['linear_coefficient', 'efficiency_retention'],
+    load_points: [1, 2, 4, 8, 16, 32, 64],
+    targets: {
+      linear_coefficient: { min: 0.8 },
+      efficiency_retention: { min: 0.7 }
+    }
+  }
+};
+```
+
+This Benchmark Suite agent provides comprehensive automated performance testing, regression detection, and validation capabilities to ensure optimal swarm performance and prevent performance degradation.