使用Python编写Prometheus监控的方法_Python

要使用python编写Prometheus 监控，需要你先开启Prometheus集群。可以参考http://www.zzvips.com/article/145477.html 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

1 2	`pip install flask` `pip 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_client

									from prometheus_client import Counter

									from prometheus_client.core import CollectorRegistry

									from flask import Response, Flask

									app = 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 counter

									request_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 random

									import prometheus_client

									from prometheus_client import Gauge

									from flask import Response, Flask

									app = 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 gauge

									random_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 Counter

									c = 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, Gauge

									from prometheus_client.core import CollectorRegistry

									REGISTRY = 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_client

									from prometheus_client import Counter,Gauge

									from prometheus_client.core import CollectorRegistry

									from aiohttp import web

									import aiohttp

									import asyncio

									import uvloop

									import random,logging,time,datetime

									asyncio.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())