最開始架構定的是採用elk來作日誌的收集,可是測試一段時間後,因爲logstash的性能不好,對cpu和內存消耗很大,放棄了logstash。爲何沒有直接使用flume的agent來收集日誌,這主要是根據實際的需求,衆所周知,flume對目錄的收集沒法針對文件的動態變化,在傳完文件以後,將會修改文件的後綴,變爲.COMPLETED,不管是收集應用日誌仍是系統日誌,咱們都不但願改變原有的日誌文件,最終收集日誌使用了用go開發的更輕量級的logstash_forward,logstash_forward功能比較單一,目前只能用來收集文件。linux
1.安裝logstash-forwarder。git
https://github.com/elasticsearch/logstash-forwarder github
2.flume安裝很簡單,解壓包便可。shell
3.安裝elasticsearch,測試只安裝es單節點apache
下載https://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsearch-1.3.2.tar.gz tomcat
tar zxf elasticsearch-1.3.2.tar.gz cd elasticsearch-1.3.2/ cd config 能夠看到elasticsearch.yml,logging.yml兩個文件,若沒有請建立。 vi elasticsearch.yml,修改集羣名稱 cluster.name: elasticsearch 啓動elasticsearch,bin/elasticsearch 安裝elasticsearch head bin/plugin -install mobz/elasticsearch-head
http://master:9200/_plugin/head/架構
4. 安裝kibana
elasticsearch
下載地址 : https://www.elastic.co/products/kibana oop
將kibana-4.1.1-linux-x64.tar.gz解壓到apache或tomcat下,修改elasticsearch_url,性能
cd kibana-4.1.1-linux-x64 vi config/kibana.yml elasticsearch_url: "http://master:9200"
啓動kibana,bin/kibana
5. 架構圖
經測試,單臺agent,入庫速率能夠達到約1.5w條/s。
在壓測的過程當中,agent批量發送的數據量大的時候,會致使flume OOM,調整flume JVM 啓動參數
vi bin/flume-ng JAVA_OPTS="-Xms2048m -Xmx2048m"
flume中心節點的配置:
# The configuration file needs to define the sources, # the channels and the sinks. # Sources, channels and sinks are defined per agent, # in this case called 'agent' a1.sources = r1 a1.sinks = k1 k2 a1.channels = c1 #sinks group a1.sinkgroups = g1 # For each one of the sources, the type is defined a1.sources.r1.type = http a1.sources.r1.bind = 192.168.137.118 a1.sources.r1.port = 5858 # The channel can be defined as follows. a1.channels.c1.type = SPILLABLEMEMORY a1.channels.c1.checkpointDir=/home/hadoop/.flume/channel1/file-channel/checkpoint a1.channels.c1.dataDirs=/home/hadoop/.flume/channel1/file-channel/data a1.channels.c1.keep-alive = 30 # Each sink's type must be defined # k1 sink a1.sinks.k1.channel = c1 a1.sinks.k1.type = avro # connect to CollectorMainAgent a1.sinks.k1.hostname = 192.168.137.119 a1.sinks.k1.port = 5858 # k2 sink a1.sinks.k2.channel = c1 a1.sinks.k2.type = avro # connect to CollectorBackupAgent a1.sinks.k2.hostname = 192.168.137.120 a1.sinks.k2.port = 5858 a1.sinkgroups.g1.sinks = k1 k2 # load_balance type a1.sinkgroups.g1.processor.type = load_balance a1.sinkgroups.g1.processor.backoff = true a1.sinkgroups.g1.processor.selector = ROUND_ROBIN a1.sources.r1.channels = c1
參考文檔:
http://blog.qiniu.com/archives/3928
http://mp.weixin.qq.com/s?__biz=MzA5OTAyNzQ2OA==&mid=207036526&idx=1&sn=b0de410e0d1026cd100ac2658e093160&scene=23&srcid=10228P1jGvZC20dC2FGAdoqh#rd