Performance Optimization

Juro v2.0.0 includes enterprise-grade performance optimization designed to handle large codebases efficiently with intelligent caching, parallel processing, and advanced memory management.

🚀 Performance Features

Intelligent Caching System

• Rule Pack Caching: 90%+ cache hit rate for repeated scans
• Scan Result Caching: Instant results for unchanged files
• Incremental Scanning: Only scan changed files for faster subsequent runs
• Smart Cache Invalidation: Automatic cache updates when rules change

Parallel Processing Architecture

• Worker Pool: Configurable 1-8 workers for optimal performance
• File Chunking: Process large files in manageable chunks
• Task Distribution: Intelligent work distribution across workers
• Load Balancing: Dynamic worker allocation based on system resources

Memory Management

• Chunked Processing: 10MB chunk size for large file processing
• Memory Streaming: Process files larger than 50MB efficiently
• Resource Cleanup: Automatic cleanup of temporary files and memory
• Memory Monitoring: Real-time memory usage tracking and optimization

📊 Performance Benchmarks

Scanning Speed

Project Size	Files	Scan Time	Memory Usage	Cache Hit Rate
Small	< 100	< 1 second	< 50MB	95%+
Medium	100-1000	< 10 seconds	< 200MB	90%+
Large	1000+	< 60 seconds	< 500MB	85%+
Enterprise	10,000+	< 5 minutes	< 1GB	80%+

Resource Optimization

• CPU Usage: Optimized for multi-core systems
• Memory Efficiency: 4x better than sequential processing
• Disk I/O: Minimized through intelligent caching
• Network: Reduced API calls through local caching

🏗️ Architecture Components

CacheManager

class CacheManager {
  // Rule pack caching
  async cacheRulePack(regulation: string, version: string, rules: Rule[]): Promise<void>
  
  // Scan result caching
  async cacheScanResult(filePath: string, hash: string, result: ScanResult): Promise<void>
  
  // Cache retrieval
  async getCachedResult(filePath: string, hash: string): Promise<ScanResult | null>
  
  // Cache invalidation
  async invalidateCache(pattern: string): Promise<void>
}

WorkerPool

class WorkerPool {
  // Worker management
  async createWorkers(count: number): Promise<void>
  async distributeTask(task: ScanTask): Promise<ScanResult>
  async scaleWorkers(targetCount: number): Promise<void>
  
  // Performance monitoring
  getWorkerStats(): WorkerStats[]
  getQueueLength(): number
  getAverageProcessingTime(): number
}

MemoryManager

class MemoryManager {
  // Memory optimization
  async processLargeFile(filePath: string, chunkSize: number): Promise<ScanResult>
  async cleanupMemory(): Promise<void>
  async monitorMemoryUsage(): Promise<MemoryStats>
  
  // Resource management
  async allocateMemory(size: number): Promise<Buffer>
  async deallocateMemory(buffer: Buffer): Promise<void>
}

⚡ Performance Configuration

Worker Pool Configuration

{
  "performance": {
    "workerPool": {
      "minWorkers": 1,
      "maxWorkers": 8,
      "defaultWorkers": 4,
      "autoScale": true
    }
  }
}

Caching Configuration

{
  "performance": {
    "caching": {
      "enabled": true,
      "ttl": 3600,
      "maxSize": "1GB",
      "strategy": "LRU"
    }
  }
}

Memory Configuration

{
  "performance": {
    "memory": {
      "chunkSize": "10MB",
      "maxFileSize": "50MB",
      "cleanupInterval": 300,
      "monitoringEnabled": true
    }
  }
}

🔧 Performance Tuning

For Small Projects (< 100 files)

# Optimize for speed
juro scan --path ./src --workers 1 --cache-enabled true

For Medium Projects (100-1000 files)

# Balanced performance
juro scan --path ./src --workers 4 --cache-enabled true --chunk-size 5MB

For Large Projects (1000+ files)

# Optimize for throughput
juro scan --path ./src --workers 8 --cache-enabled true --chunk-size 10MB --incremental

For Enterprise Projects (10,000+ files)

# Maximum performance
juro scan --path ./src --workers 8 --cache-enabled true --chunk-size 20MB --incremental --parallel

📈 Performance Monitoring

Real-Time Metrics

# Enable performance monitoring
juro scan --path ./src --monitor-performance --output-format json

Performance Report

{
  "performance": {
    "scanDuration": 1250,
    "filesProcessed": 150,
    "cacheHits": 135,
    "cacheMisses": 15,
    "cacheHitRate": 0.9,
    "memoryUsage": {
      "peak": "245MB",
      "average": "180MB",
      "final": "120MB"
    },
    "workerStats": {
      "activeWorkers": 4,
      "averageTaskTime": 125,
      "queueLength": 0
    }
  }
}

🎯 Performance Best Practices

1. Enable Caching

# Always enable caching for better performance
juro scan --path ./src --cache-enabled true

2. Use Incremental Scanning

# Only scan changed files
juro scan --path ./src --incremental

3. Optimize Worker Count

# Match worker count to CPU cores
juro scan --path ./src --workers $(nproc)

4. Configure Memory Limits

# Set appropriate memory limits
juro scan --path ./src --max-memory 1GB --chunk-size 10MB

5. Use Appropriate File Patterns

# Exclude unnecessary files
juro scan --path ./src --exclude "**/node_modules/**" --exclude "**/dist/**"

🔍 Performance Troubleshooting

Slow Scanning

1. Check Cache Status: Ensure caching is enabled
2. Verify Worker Count: Use appropriate number of workers
3. Review File Patterns: Exclude unnecessary files
4. Monitor Memory Usage: Check for memory leaks

High Memory Usage

1. Reduce Chunk Size: Use smaller chunks for large files
2. Enable Cleanup: Ensure automatic cleanup is enabled
3. Check File Sizes: Exclude very large files if not needed
4. Monitor Workers: Reduce worker count if needed

Cache Issues

1. Clear Cache: juro cache clear
2. Check Cache Size: Monitor cache disk usage
3. Verify TTL: Check cache time-to-live settings
4. Update Rules: Clear cache when rules change

📊 Performance Comparison

Before Optimization (v1.0.0)

• Small Projects: 5-10 seconds
• Medium Projects: 30-60 seconds
• Large Projects: 5-10 minutes
• Memory Usage: High and inconsistent
• Cache Hit Rate: 0% (no caching)

After Optimization (v2.0.0)

• Small Projects: < 1 second (5-10x faster)
• Medium Projects: < 10 seconds (3-6x faster)
• Large Projects: < 60 seconds (5-10x faster)
• Memory Usage: Optimized and predictable
• Cache Hit Rate: 90%+ (massive improvement)

🚀 Advanced Performance Features

Adaptive Scaling

• Auto-Scaling: Automatically adjust worker count based on load
• Load Balancing: Distribute tasks evenly across workers
• Resource Monitoring: Real-time monitoring of system resources
• Dynamic Optimization: Adjust settings based on performance metrics

Intelligent Caching

• Predictive Caching: Pre-cache likely-to-be-scanned files
• Smart Invalidation: Only invalidate affected cache entries
• Compression: Compress cached data to save disk space
• Distributed Caching: Share cache across multiple instances

Memory Optimization

• Garbage Collection: Proactive memory cleanup
• Memory Pooling: Reuse memory allocations
• Streaming Processing: Process files without loading entirely into memory
• Memory Profiling: Detailed memory usage analysis

📚 Performance Resources

Configuration Guides

• Worker Pool Configuration
• Caching Configuration
• Memory Management

Monitoring Tools

• Performance Dashboard
• Metrics Collection
• Alerting Setup

Troubleshooting

• Common Issues
• Debug Mode
• Performance Profiling

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Ready to optimize your compliance scanning performance? Get started with Juro's performance features and experience enterprise-grade scanning speed!