性能优化与监控

本文介绍 OpenClaw 的性能优化和监控配置。

性能配置

缓存策略

{
  "cache": {
    "enabled": true,
    "provider": "redis",
    "ttl": {
      "default": 3600,
      "user_profile": 86400,
      "channel_state": 300
    }
  }
}

内存管理

{
  "performance": {
    "memory": {
      "max_heap_size": "2GB",
      "gc_interval": 60000,
      "monitor_threshold": 0.8
    }
  }
}

并发配置

{
  "performance": {
    "concurrency": {
      "max_concurrent_requests": 50,
      "max_queue_size": 100,
      "timeout": 30000
    }
  }
}

资源优化

模型优化

{
  "models": {
    "default": "claude-3-5-sonnet",
    "optimization": {
      "streaming": true,
      "cache_prompt": true,
      "max_tokens": 4096
    }
  }
}

工具优化

{
  "tools": {
    "browser": {
      "pool_size": 3,
      "idle_timeout": 300000,
      "max_pages": 10
    },
    "exec": {
      "timeout": 180000,
      "max_output": 1048576
    }
  }
}

监控配置

指标收集

{
  "monitoring": {
    "enabled": true,
    "provider": "prometheus",
    "port": 9090,
    "metrics": [
      "requests_total",
      "requests_duration",
      "errors_total",
      "active_sessions",
      "memory_usage",
      "cpu_usage"
    ]
  }
}

Prometheus 配置

scrape_configs:
  - job_name: 'openclaw'
    static_configs:
      - targets: ['openclaw:9090']

Grafana 仪表板

{
  "dashboard": {
    "panels": [
      {
        "title": "请求速率",
        "metrics": "rate(requests_total[5m])"
      },
      {
        "title": "响应时间",
        "metrics": "histogram_quantile(0.95, requests_duration)"
      },
      {
        "title": "活跃会话",
        "metrics": "active_sessions"
      }
    ]
  }
}

日志管理

日志级别

{
  "logging": {
    "level": "info",
    "levels": {
      "default": "info",
      "openclaw": "debug",
      "channel": "warn"
    }
  }
}

日志输出

{
  "logging": {
    "outputs": [
      {
        "type": "file",
        "path": "/var/log/openclaw/app.log",
        "rotation": {
          "max_size": "100MB",
          "max_files": 10
        }
      },
      {
        "type": "stdout",
        "format": "json"
      }
    ]
  }
}

性能调优

连接池

{
  "database": {
    "pool": {
      "min": 5,
      "max": 20,
      "idle_timeout": 30000
    }
  }
}

WebSocket 优化

{
  "websocket": {
    "max_connections": 1000,
    "heartbeat_interval": 30000,
    "message_queue_size": 100
  }
}

告警配置

告警规则

{
  "alerts": {
    "rules": [
      {
        "name": "high_memory",
        "condition": "memory_usage > 0.9",
        "severity": "critical",
        "action": "notify"
      },
      {
        "name": "high_error_rate",
        "condition": "errors_total / requests_total > 0.05",
        "severity": "warning",
        "action": "notify"
      },
      {
        "name": "slow_response",
        "condition": "p95_duration > 5000",
        "severity": "warning",
        "action": "notify"
      }
    ]
  }
}

通知渠道

{
  "alerts": {
    "channels": {
      "email": {
        "enabled": true,
        "recipients": ["admin@example.com"]
      },
      "slack": {
        "enabled": true,
        "webhook": "${SLACK_WEBHOOK}"
      }
    }
  }
}

性能测试

负载测试

# 使用 wrk 进行负载测试
wrk -t4 -c100 -d30s http://localhost:18789/health

压力测试脚本

import asyncio
import aiohttp

async def load_test():
    async with aiohttp.ClientSession() as session:
        tasks = []
        for _ in range(100):
            task = session.get('http://localhost:18789/api/chat')
            tasks.append(task)
        
        responses = await asyncio.gather(*tasks)
        print(f"完成 {len(responses)} 个请求")

asyncio.run(load_test())

下一步

• Docker 部署
• 安全配置
• 故障排除