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要使用python编写prometheus监控，需要你先开启prometheus集群。可以参考 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 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。
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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())
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