使用Python编写Prometheus监控的方法
要使用python编写Prometheus监控，需要你先开启Prometheus集群。可以参考//www.nhooo.com/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
pipinstallflask pipinstallprometheus_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。
importprometheus_client
fromprometheus_clientimportCounter
fromprometheus_client.coreimportCollectorRegistry
fromflaskimportResponse,Flask
app=Flask(__name__)
requests_total=Counter("request_count","Totalrequestcoutofthehost")
@app.route("/metrics")
defrequests_count():
requests_total.inc()
#requests_total.inc(2)
returnResponse(prometheus_client.generate_latest(requests_total),
mimetype="text/plain")
@app.route('/')
defindex():
requests_total.inc()
return"HelloWorld"
if__name__=="__main__":
app.run(host="0.0.0.0")
运行该脚本，访问youhost:5000/metrics
#HELPrequest_countTotalrequestcoutofthehost #TYPErequest_countcounter request_count3.0
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。
importrandom
importprometheus_client
fromprometheus_clientimportGauge
fromflaskimportResponse,Flask
app=Flask(__name__)
random_value=Gauge("random_value","Randomvalueoftherequest")
@app.route("/metrics")
defr_value():
random_value.set(random.randint(0,10))
returnResponse(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
#HELPrandom_valueRandomvalueoftherequest #TYPErandom_valuegauge random_value3.0
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
fromprometheus_clientimportCounter
c=Counter('requests_total','HTTPrequeststotal',['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
fromprometheus_clientimportCounter,Gauge
fromprometheus_client.coreimportCollectorRegistry
REGISTRY=CollectorRegistry(auto_describe=False)
requests_total=Counter("request_count","Totalrequestcoutofthehost",registry=REGISTRY)
random_value=Gauge("random_value","Randomvalueoftherequest",registry=REGISTRY)
importprometheus_client
fromprometheus_clientimportCounter,Gauge
fromprometheus_client.coreimportCollectorRegistry
fromaiohttpimportweb
importaiohttp
importasyncio
importuvloop
importrandom,logging,time,datetime
asyncio.set_event_loop_policy(uvloop.EventLoopPolicy())
routes=web.RouteTableDef()
#metrics包含
requests_total=Counter("request_count","Totalrequestcoutofthehost")#数值只增
random_value=Gauge("random_value","Randomvalueoftherequest")#数值可大可小
@routes.get('/metrics')
asyncdefmetrics(request):
requests_total.inc()#计数器自增
#requests_total.inc(2)
data=prometheus_client.generate_latest(requests_total)
returnweb.Response(body=data,content_type="text/plain")#将计数器的值返回
@routes.get("/metrics2")
asyncdefmetrics2(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
returnweb.Response(body=prometheus_client.generate_latest(random_value),content_type="text/plain")#将值返回
@routes.get('/')
asyncdefhello(request):
returnweb.Response(text="Hello,world")
#使用labels来区分metric的特征
c=Counter('requests_total','HTTPrequeststotal',['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','Descriptionofgauge',['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('serverstart：%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('serverclose：%s'%datetime.datetime.now())
总结
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