自定义数据采集export到prometheus使用 Flask实现

背景描述

如图 想要取到 url get请求的值，使用prometheus blackbox 无法获取，所以考虑使用flask自定义exporter 获取

• install 库

  pip install prometheus_client  flask
  

from atexit import register
import mimetypes
import requests
from prometheus_client.core import CollectorRegistry
from prometheus_client import Gauge, Counter, Info, Enum, generate_latest, start_http_server

from flask import Response, Flask



meeting_useroom_url = 'http://10.31.140.24:9000/meeting_use_count/2'
json_meeting_count = requests.get(meeting_useroom_url)
dic_meeting_count = json_meeting_count.json()

meeting_totalroom_url = 'http://10.31.140.24:9000/meeting_rooms'
json_totalroom_count = requests.get(meeting_totalroom_url)
dic_totalroom_count = json_totalroom_count.json()


meeting_totalpersion_url = 'http://10.31.140.24:9000/meeting_persions'
json_totalpersion_count = requests.get(meeting_totalpersion_url)
dic_totalpersion_count = json_totalpersion_count.json()


# 获取源数据，数据源可以是任意接口、数据库、文件等
def get_qcloud_data():
    data = {
        'meeting_count': int(dic_meeting_count),
        'room_count': int(dic_totalroom_count),
        'persion_count': int(dic_totalpersion_count),
        'cbs': 2,
        'clb': 3
    }
    return data



# 设置metrics
# Prometheus提供4种类型Metrics：Counter, Gauge, Summary和Histogram
# Counter 累加器，只有inc方法,定义方法指标名，描述，默认增长值是1
# Gauge 可任意设置，比如cpu、内存、磁盘等指标，定义方法，指标名，描述，标签
# Histogram 分桶统计，对每个桶的数据进行统计
# Summary 分位统计，对每个值进行统计

registry = CollectorRegistry(auto_describe=False)
product_meeting_count = Gauge('product_meeting_count', 'product_usage_meeting_count', ['product'], registry=registry)
product_room_count = Gauge('product_room_count', 'product_usage_room_count', ['product'], registry=registry)
product_persion_count = Gauge('product_persion_count', 'product_usage_persion_count', ['product'], registry=registry)
product_cbs = Gauge('product_cbs', 'product_usage_cbs', ['product'], registry=registry)
product_clb = Gauge('product_clb', 'product_usage_clb', ['product'], registry=registry)

app = Flask(__name__)


@app.route("/metrics")
def main():
    data = get_qcloud_data()
    for key, value in data.items():
        if key == 'meeting_count':
            product_meeting_count.labels(product=key).set(value)
        elif key == 'room_count':
            product_room_count.labels(product=key).set(value)
        elif key == 'persion_count':
            product_persion_count.labels(product=key).set(value)
        elif key == 'cbs':
            product_cbs.labels(product=key).set(value)
        elif key == 'clb':
            product_clb.labels(product=key).set(value)
    return Response(generate_latest(registry), mimetype="text/plain")


@app.route('/')
def index():
    print(dic_meeting_count, dic_totalpersion_count, dic_totalroom_count)
    return "welecome to qcloud export"


if __name__ == "__main__":
    app.run(host="0.0.0.0", port=9117)

优化获取udp接口

import os

from flask import Flask, Response, redirect
from prometheus_client import generate_latest, CollectorRegistry, Gauge

app = Flask(__name__)
registry = CollectorRegistry(auto_describe=False)
gauge = Gauge('process_sum', 'an example showed how to use gauge', ['pid'], registry=registry)


@app.route('/metrics')
def hello():
    command = os.popen("netstat -unlp |awk -F: '{print $4}'|grep 6984 |wc -l")
    command = command.read()
    print(command)
    gauge.labels('pid').set(float(command))

    return Response(generate_latest(registry), mimetype='text/plain')


@app.route('/')
def index():
    return redirect("/metrics")


if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)