使用Python编写Prometheus监控的方法

Python  /  管理员 发布于 7年前   182

要使用python编写Prometheus监控，需要你先开启Prometheus集群。可以参考///article/148895.htm 安装。在python中实现服务器端。在Prometheus中配置请求网址，Prometheus会定期向该网址发起申请获取你想要返回的数据。

使用Python和Flask编写Prometheus监控

Installation

pip install flaskpip install prometheus_client

Metrics

Prometheus提供4种类型Metrics：Counter, Gauge, Summary和Histogram

Counter

Counter可以增长，并且在程序重启的时候会被重设为0，常被用于任务个数，总处理时间，错误个数等只增不减的指标。

import prometheus_clientfrom prometheus_client import Counterfrom prometheus_client.core import CollectorRegistryfrom flask import Response, Flaskapp = Flask(__name__)requests_total = Counter("request_count", "Total request cout of the host")@app.route("/metrics")def requests_count():  requests_total.inc()  # requests_total.inc(2)  return Response(prometheus_client.generate_latest(requests_total),          mimetype="text/plain")@app.route('/')def index():  requests_total.inc()  return "Hello World"if __name__ == "__main__":  app.run(host="0.0.0.0")

运行该脚本，访问youhost:5000/metrics

# HELP request_count Total request cout of the host# TYPE request_count counterrequest_count 3.0

Gauge

Gauge与Counter类似，唯一不同的是Gauge数值可以减少，常被用于温度、利用率等指标。

import randomimport prometheus_clientfrom prometheus_client import Gaugefrom flask import Response, Flaskapp = Flask(__name__)random_value = Gauge("random_value", "Random value of the request")@app.route("/metrics")def r_value():  random_value.set(random.randint(0, 10))  return Response(prometheus_client.generate_latest(random_value),          mimetype="text/plain")if __name__ == "__main__":  app.run(host="0.0.0.0")

运行该脚本，访问youhost:5000/metrics

# HELP random_value Random value of the request# TYPE random_value gaugerandom_value 3.0

Summary/Histogram

Summary/Histogram概念比较复杂，一般exporter很难用到，暂且不说。

LABELS

使用labels来区分metric的特征

from prometheus_client import Counterc = Counter('requests_total', 'HTTP requests total', ['method', 'clientip'])c.labels('get', '127.0.0.1').inc()c.labels('post', '192.168.0.1').inc(3)c.labels(method="get", clientip="192.168.0.1").inc()

使用Python和asyncio编写Prometheus监控

from prometheus_client import Counter, Gaugefrom prometheus_client.core import CollectorRegistryREGISTRY = CollectorRegistry(auto_describe=False)requests_total = Counter("request_count", "Total request cout of the host", registry=REGISTRY)random_value = Gauge("random_value", "Random value of the request", registry=REGISTRY)

import prometheus_clientfrom prometheus_client import Counter,Gaugefrom prometheus_client.core import CollectorRegistryfrom aiohttp import webimport aiohttpimport asyncioimport uvloopimport random,logging,time,datetimeasyncio.set_event_loop_policy(uvloop.EventLoopPolicy())routes = web.RouteTableDef()# metrics包含requests_total = Counter("request_count", "Total request cout of the host") # 数值只增random_value = Gauge("random_value", "Random value of the request") # 数值可大可小@routes.get('/metrics')async def metrics(request):  requests_total.inc()   # 计数器自增  # requests_total.inc(2)  data = prometheus_client.generate_latest(requests_total)  return web.Response(body = data,content_type="text/plain")  # 将计数器的值返回@routes.get("/metrics2")async def metrics2(request):  random_value.set(random.randint(0, 10))  # 设置值任意值，但是一定要为 整数或者浮点数  return web.Response(body = prometheus_client.generate_latest(random_value),content_type="text/plain")  # 将值返回@routes.get('/')async def hello(request):  return web.Response(text="Hello, world")# 使用labels来区分metric的特征c = Counter('requests_total', 'HTTP requests total', ['method', 'clientip']) # 添加lable的key，c.labels('get', '127.0.0.1').inc()    #为不同的label进行统计c.labels('post', '192.168.0.1').inc(3)   #为不同的label进行统计c.labels(method="get", clientip="192.168.0.1").inc()  #为不同的label进行统计g = Gauge('my_inprogress_requests', 'Description of gauge',['mylabelname'])g.labels(mylabelname='str').set(3.6)  #value自己定义,但是一定要为 整数或者浮点数if __name__ == '__main__':  logging.info('server start：%s'% datetime.datetime.now())  app = web.Application(client_max_size=int(2)*1024**2)  # 创建app，设置最大接收图片大小为2M  app.add_routes(routes)   # 添加路由映射  web.run_app(app,host='0.0.0.0',port=2222)  # 启动app  logging.info('server close：%s'% datetime.datetime.now())

总结

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