Python自动化运维系统性能监控代码

Python在自动化运维中常用于性能监控，因为它提供了丰富的库和易于编程的特性。要编写一个基本的性能监控代码，通常会用到像`psutil`、`celery`（用于分布式任务）、`requests`（处理HTTP请求）和`logging`（日志记录）等库。以下是一个简化的示例，展示了如何使用这些工具来监控CPU、内存、网络和HTTP服务的性能：

import psutil
import requests
from celery import Celery
import logging

# 初始化日志
logging.basicConfig(filename='app.log', level=logging.INFO)

# 创建Celery实例
app = Celery('tasks', broker='pyamqp://guest@localhost//')

@app.task
def monitor_service(url):
    try:
        response = requests.get(url, timeout=5)
        response.raise_for_status()
        logging.info(f"Service status: {response.status_code}")
    except requests.exceptions.RequestException as e:
        logging.error(f"Performance issue: {e}")

# 监控函数
def monitor_system():
    cpu_percent = psutil.cpu_percent(interval=1)
    memory_info = psutil.virtual_memory()
    mem_percent = memory_info.percent
    network_info = psutil.net_io_counters()
    
    logging.info(f"CPU usage: {cpu_percent}%")
    logging.info(f"Memory usage: {mem_percent}%")
    logging.info(f"Network traffic: {network_info.bytes_sent / (1024 * 1024)} MB sent")

    # 每隔一定时间监控一次服务
    app.send_task('monitor_service', args=['http://your-service.com'])

if __name__ == "__main__":
    monitor_system()