### Worker Optimization

```python
# worker_optimization.py
import psutil
import os

def get_worker_recommendations():
    """Get resource recommendations based on system specs."""
    cpu_count = psutil.cpu_count()
    memory = psutil.virtual_memory()
    
    # Celery worker configuration
    worker_config = {
        # Concurrency = CPU cores (for CPU-bound tasks)
        # Concurrency = 2 * CPU cores (for I/O-bound tasks)
        'concurrency': min(cpu_count, 16),
        
        # Prefetch multiplier - how many tasks to prefetch
        'prefetch_multiplier': 1,
        
        # Maximum tasks per child before worker restart
        'max_tasks_per_child': 200,
        
        # Worker memory limit
        'max_memory_per_child': int(memory.total * 0.8 / cpu_count),
        
        # Task time limit (seconds)
        'task_time_limit': 3600,
        
        # Soft time limit (seconds) - raises SoftTimeLimitExceeded
        'task_soft_time_limit': 3000,
    }
    
    return worker_config

def monitor_worker_health():
    """Monitor worker health metrics."""
    import psutil
    
    metrics = {
        'cpu_percent': psutil.cpu_percent(interval=1),
        'memory_percent': psutil.virtual_memory().percent,
        'disk_usage': psutil.disk_usage('/').percent,
        'open_files': len(psutil.Process().open_files()),
        'connections': len(psutil.Process().connections()),
    }
    
    # Alert thresholds
    alerts = []
    if metrics['cpu_percent'] > 90:
        alerts.append(f"High CPU: {metrics['cpu_percent']}%")
    if metrics['memory_percent'] > 85:
        alerts.append(f"High Memory: {metrics['memory_percent']}%")
    if metrics['disk_usage'] > 90:
        alerts.append(f"High Disk: {metrics['disk_usage']}%")
    
    return {
        'metrics': metrics,
        'alerts': alerts,
        'healthy': len(alerts) == 0,
    }