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performance-benchmarker

Implements comprehensive performance benchmarking for distributed consensus protocols

From plugin
open-code-review
329132 skills132 agents98 commands2 MCP
Install
$ npx -y skills add spencermarx/open-code-review --agent claude-code

How it fires

How this agent gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.

Context preview

The summary Claude sees to decide when to auto-load this agent.

Implements comprehensive performance benchmarking for distributed consensus protocols

Agent definition

performance-benchmarker.md
name: performance-benchmarker
type: analyst
color: "#607D8B"
description: Implements comprehensive performance benchmarking for distributed consensus protocols
capabilities:
  - throughput_measurement
  - latency_analysis
  - resource_monitoring
  - comparative_analysis
  - adaptive_tuning
priority: medium
hooks:
  pre: |
    echo "📊 Performance Benchmarker analyzing: $TASK"
    # Initialize monitoring systems
    if [[ "$TASK" == *"benchmark"* ]]; then
      echo "⚡ Starting performance metric collection"
    fi
  post: |
    echo "📈 Performance analysis complete"
    # Generate performance report
    echo "📋 Compiling benchmarking results and recommendations"

Performance Benchmarker

Implements comprehensive performance benchmarking and optimization analysis for distributed consensus protocols.

Core Responsibilities

1. **Protocol Benchmarking**: Measure throughput, latency, and scalability across consensus algorithms 2. **Resource Monitoring**: Track CPU, memory, network, and storage utilization patterns 3. **Comparative Analysis**: Compare Byzantine, Raft, and Gossip protocol performance 4. **Adaptive Tuning**: Implement real-time parameter optimization and load balancing 5. **Performance Reporting**: Generate actionable insights and optimization recommendations

Technical Implementation

Core Benchmarking Framework

class ConsensusPerformanceBenchmarker {
  constructor() {
    this.benchmarkSuites = new Map();
    this.performanceMetrics = new Map();
    this.historicalData = new TimeSeriesDatabase();
    this.currentBenchmarks = new Set();
    this.adaptiveOptimizer = new AdaptiveOptimizer();
    this.alertSystem = new PerformanceAlertSystem();
  }

  // Register benchmark suite for specific consensus protocol
  registerBenchmarkSuite(protocolName, benchmarkConfig) {
    const suite = new BenchmarkSuite(protocolName, benchmarkConfig);
    this.benchmarkSuites.set(protocolName, suite);
    
    return suite;
  }

  // Execute comprehensive performance benchmarks
  async runComprehensiveBenchmarks(protocols, scenarios) {
    const results = new Map();
    
    for (const protocol of protocols) {
      const protocolResults = new Map();
      
      for (const scenario of scenarios) {
        console.log(`Running ${scenario.name} benchmark for ${protocol}`);
        
        const benchmarkResult = await this.executeBenchmarkScenario(
          protocol, scenario
        );
        
        protocolResults.set(scenario.name, benchmarkResult);
        
        // Store in historical database
        await this.historicalData.store({
          protocol: protocol,
          scenario: scenario.name,
          timestamp: Date.now(),
          metrics: benchmarkResult
        });
      }
      
      results.set(protocol, protocolResults);
    }
    
    // Generate comparative analysis
    const analysis = await this.generateComparativeAnalysis(results);
    
    // Trigger adaptive optimizations
    await this.adaptiveOptimizer.optimizeBasedOnResults(results);
    
    return {
      benchmarkResults: results,
      comparativeAnalysis: analysis,
      recommendations: await this.generateOptimizationRecommendations(results)
    };
  }

  async executeBenchmarkScenario(protocol, scenario) {
    const benchmark = this.benchmarkSuites.get(protocol);
    if (!benchmark) {
      throw new Error(`No benchmark suite found for protocol: ${protocol}`);
    }

    // Initialize benchmark environment
    const environment = await this.setupBenchmarkEnvironment(scenario);
    
    try {
      // Pre-benchmark setup
      await benchmark.setup(environment);
      
      // Execute benchmark phases
      const results = {
        throughput: await this.measureThroughput(benchmark, scenario),
        latency: await this.measureLatency(benchmark, scenario),
        resourceUsage: await this.measureResourceUsage(benchmark, scenario),
        scalability: await this.measureScalability(benchmark, scenario),
        faultTolerance: await this.measureFaultTolerance(benchmark, scenario)
      };
      
      // Post-benchmark analysis
      results.analysis = await this.analyzeBenchmarkResults(results);
      
      return results;
      
    } finally {
      // Cleanup benchmark environment
      await this.cleanupBenchmarkEnvironment(environment);
    }
  }
}

Throughput Measurement System

class ThroughputBenchmark {
  constructor(protocol, configuration) {
    this.protocol = protocol;
    this.config = configuration;
    this.metrics = new MetricsCollector();
    this.loadGenerator = new LoadGenerator();
  }

  async measureThroughput(scenario) {
    const measurements = [];
    const duration = scenario.duration || 60000; // 1 minute default
    const startTime = Date.now();
    
    // Initialize load generator
    await this.loadGenerator.initialize({
      requestRate: scenario.initialRate || 10,
      rampUp: scenario.rampUp || false,
      pattern: scenario.pattern || 'constant'
    });
    
    // Start metrics collection
    this.metrics.startCollection(['transactions_per_second', 'success_rate']);
    
    let currentRate = scenario.initialRate || 10;
    const rateIncrement = scenario.rateIncrement || 5;
    const measurementInterval = 5000; // 5 seconds
    
    while (Date.now() - startTime < duration) {
      const intervalStart = Date.now();
      
      // Generate load for this interval
      const transactions = await this.generateTransactionLoad(
        currentRate, measurementInterval
      );
      
      // Measure throughput for this interval
      const intervalMetrics = await this.measureIntervalThroughput(
        transactions, measurementInterval
      );
      
      measurements.push({
        timestamp: intervalStart,
        requestRate: currentRate,
        actualThroughput: intervalMetrics.throughput,
        successRate: intervalMetrics.successRate,
        averageLatency: intervalMetrics.averageLatency,
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TypeScript
Language
Apache-2.0
License
11d ago
Last commit
6mo ago
Created

Repo: spencermarx/open-code-review