zabbix配合腳本監控Kafka

簡介：

Kafka是一種高吞吐量的分佈式發佈訂閱消息系統，它能夠處理消費者規模的網站中的全部動做流數據。Kafka以下特性，受到諸多公司的青睞。

一、高吞吐量：即便是很是普通的硬件Kafka也能夠支持每秒數百萬的消息(核心目標之一)。

二、支持經過Kafka服務器和消費機集羣來分區消息

…………

場景：

Kafka的做用我就不在這BB了，你們能夠瞅瞅http://blog.jobbole.com/75328/，總結的很是好。

Kafka監控的幾個指標

一、lag：多少消息沒有消費

二、logsize：Kafka存的消息總數

三、offset：已經消費的消息

lag = logsize - offset， 主要監控lag是否正常

腳本：

• spoorer.py文件，獲取Kafka中的監控指標內容，並將監控結果寫到spooer.log文件中

crontab設置每分鐘執行spoorer.py

# -*- coding:utf-8 -*-

import os, sys, time, json, yaml
from kazoo.client import KazooClient
from kazoo.exceptions import NoNodeError
from kafka import (KafkaClient, KafkaConsumer)

class spoorerClient(object):

    def __init__(self, zookeeper_hosts, kafka_hosts, zookeeper_url='/', timeout=3, log_dir='/tmp/spoorer'):
        self.zookeeper_hosts = zookeeper_hosts
        self.kafka_hosts = kafka_hosts
        self.timeout = timeout
        self.log_dir = log_dir
        self.log_file = log_dir + '/' + 'spoorer.log'
        self.kafka_logsize = {}
        self.result = []
    self.log_day_file = log_dir + '/' + 'spoorer_day.log.' + str(time.strftime("%Y-%m-%d", time.localtime()))
        self.log_keep_day = 1

        try:
            f = file(os.path.dirname(os.path.abspath(__file__)) + '/' + 'spoorer.yaml')
            self.white_topic_group = yaml.load(f)
        except IOError as e:
            print 'Error, spoorer.yaml is not found'
            sys.exit(1)
        else:
            f.close()
            if self.white_topic_group is None:
                self.white_topic_group = {}

        if not os.path.exists(self.log_dir):     os.mkdir(self.log_dir)

    for logfile in [x for x in os.listdir(self.log_dir) if x.split('.')[-1] != 'log' and x.split('.')[-1] != 'swp']:
        if int(time.mktime(time.strptime(logfile.split('.')[-1], '%Y-%m-%d'))) < int(time.time()) - self.log_keep_day * 86400:
            os.remove(self.log_dir + '/' + logfile)

    if zookeeper_url == '/':
        self.zookeeper_url = zookeeper_url
    else:
        self.zookeeper_url = zookeeper_url + '/'

def spoorer(self):
    try:
        kafka_client = KafkaClient(self.kafka_hosts, timeout=self.timeout)
    except Exception as e:
        print "Error, cannot connect kafka broker."
        sys.exit(1)
    else:
        kafka_topics = kafka_client.topics
    finally:
        kafka_client.close()

    try:
        zookeeper_client = KazooClient(hosts=self.zookeeper_hosts, read_only=True, timeout=self.timeout)
        zookeeper_client.start()
    except Exception as e:
        print "Error, cannot connect zookeeper server."
        sys.exit(1)

    try:
        groups = map(str,zookeeper_client.get_children(self.zookeeper_url + 'consumers'))
    except NoNodeError as e:
        print "Error, invalid zookeeper url."
        zookeeper_client.stop()
        sys.exit(2)
    else:
        for group in groups:
            if 'offsets' not in zookeeper_client.get_children(self.zookeeper_url + 'consumers/%s' % group): continue
            topic_path = 'consumers/%s/offsets' % (group)
            topics = map(str,zookeeper_client.get_children(self.zookeeper_url + topic_path))
            if len(topics) == 0: continue
        
            for topic in topics:
                if topic not in self.white_topic_group.keys():
                    continue 
                elif group not in self.white_topic_group[topic].replace(' ','').split(','):
                    continue
                partition_path = 'consumers/%s/offsets/%s' % (group,topic)
                partitions = map(int,zookeeper_client.get_children(self.zookeeper_url + partition_path))
        
                for partition in partitions:
                    base_path = 'consumers/%s/%s/%s/%s' % (group, '%s', topic, partition)
                    owner_path, offset_path = base_path % 'owners', base_path % 'offsets'
                    offset = zookeeper_client.get(self.zookeeper_url + offset_path)[0]
    
                    try:
                        owner = zookeeper_client.get(self.zookeeper_url + owner_path)[0]
                    except NoNodeError as e:
                        owner = 'null'

                    metric = {'datetime':time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()), 'topic':topic, 'group':group, 'partition':int(partition), 'logsize':None, 'offset':int(offset), 'lag':None, 'owner':owner}
                    self.result.append(metric)
    finally:
        zookeeper_client.stop()

    try:
        kafka_consumer = KafkaConsumer(bootstrap_servers=self.kafka_hosts)
    except Exception as e:
        print "Error, cannot connect kafka broker."
        sys.exit(1)
    else:
        for kafka_topic in kafka_topics:
            self.kafka_logsize[kafka_topic] = {}
            partitions = kafka_client.get_partition_ids_for_topic(kafka_topic)

            for partition in partitions:
                offset = kafka_consumer.get_partition_offsets(kafka_topic, partition, -1, 1)[0]
                self.kafka_logsize[kafka_topic][partition] = offset

        with open(self.log_file,'w') as f1, open(self.log_day_file,'a') as f2:

            for metric in self.result:
                logsize = self.kafka_logsize[metric['topic']][metric['partition']]
                metric['logsize'] = int(logsize)
                metric['lag'] = int(logsize) - int(metric['offset'])
                
                f1.write(json.dumps(metric,sort_keys=True) + '\n')
                f1.flush()
                f2.write(json.dumps(metric,sort_keys=True) + '\n')
                f2.flush()
    finally:
        kafka_consumer.close()

    return ''

if __name__ == '__main__':
    check = spoorerClient(zookeeper_hosts=‘zookeeperIP地址：端口', zookeeper_url=‘znode節點', kafka_hosts=‘kafkaIP：PORT', log_dir='/tmp/log/spoorer', timeout=3)
    print check.spoorer()

• spoorer.py讀取同一目錄的spoorer.yaml配置文件

格式：

kafka_topic_name:
    group_name1,
    group_name2,
(group名字縮進4個空格，嚴格按照yaml格式)

• spoorer.log數據格式

{"datetime": "2016-03-18 11:36:02", "group": "group_name1", "lag": 73, "logsize": 28419259, "offset": 28419186, "owner": "消費partition線程", "partition": 3, "topic": "kafka_topic_name"}

monitor_kafka.sh腳本檢索spoorer.log文件，並配合zabbix監控

#!/bin/bash

    topic=$1
group=$2
#$3可取值lag、logsize、offset
class=$3

case $3 in
lag)
echo "`cat /tmp/log/spoorer/spoorer.log | grep -w \\"${topic}\\" | grep -w \\"${group}\\" |awk -F'[ ,]' '{sum+=$9}'END'{print sum}'`"
;;
logsize)
echo "`cat /tmp/log/spoorer/spoorer.log | grep -w \\"${topic}\\" | grep -w \\"${group}\\" |awk -F'[ ,]' '{sum+=$12}'END'{print sum}'`"
;;
offset)
echo "`cat /tmp/log/spoorer/spoorer.log | grep -w \\"${topic}\\" | grep -w \\"${group}\\" |awk -F'[ ,]' '{sum+=$15}'END'{print sum}'`"
;;
*)
echo "Error input:"
;;
esac
exit 0

zabbix_agentd.conf擴展配置

UserParameter=kafka.lag[*],/usr/local/zabbix-2.4.5/script/monitor_kafka.sh $1 $2 lag
UserParameter=kafka.offset[*],/usr/local/zabbix-2.4.5/script/monitor_kafka.sh $1 $2 offset
UserParameter=kafka.logsize[*],/usr/local/zabbix-2.4.5/script/monitor_kafka.sh $1 $2 logsize

zabbix設置Key

kafka.lag[kafka_topic_name,group_name1]
kafka.logsize[kafka_topic_name,group_name1]
kafka.offset[kafka_topic_name,group_name1]

• 出現問題第一時間發送報警消息。

報警的Trigger觸發規則也是對lag的值作報警，具體閥值設置爲多少，仍是看你們各自業務需求了。

接收告警消息能夠選擇郵件和短信、網上教程也比較多，教程帖子：
http://www.iyunv.com/thread-22904-1-1.html 10 http://www.iyunv.com/thread-40998-1-1.html 12

若是以爲本身搞這些比較麻煩的話，也能夠試試 OneAlert 一鍵集成zabbix，短信、電話、微信、APP啥都能搞定，還免費，用着不錯。
http://www.onealert.com/activity/zabbix.html 37