使用Docker部署elasticsearch、logstash、kibana
指定版本:6.7.1 (建議使用同一的版本、屏蔽三個軟件間的不兼容性)
下載鏡像:
docker pull elasticsearch:6.7.1
docker pull logstash:6.7.1
docker pull kibana:6.7.1
修改vm.max_map_count
vim /etc/sysctl.conf
添加配置:vm.max_map_count=262144
執行命令,確保生效配置生效: sysctl -p
依據服務器配置而定
es集群
這里es集群用了3個節點,配置文件放在 /root/es/config/ 目錄下,
注意:es是不允許使用root用戶啟動的,/root/es/config/ 目錄最好改成 777權限,
es1.yml配置文件內容:
cluster.name: elasticsearch-cluster
node.name: es-node1
network.bind_host: 0.0.0.0
network.publish_host: 10.90.101.48
http.port: 9200
transport.tcp.port: 9300
http.cors.enabled: true
http.cors.allow-origin: "*"
node.master: true
node.data: true
discovery.zen.ping.unicast.hosts: ["10.90.101.48:9300","10.90.101.48:9301","10.90.101.48:9302"]
discovery.zen.minimum_master_nodes: 2
xpack.ml.enabled: false
xpack.monitoring.enabled: false
xpack.security.enabled: false
xpack.watcher.enabled: false
啟動當前配置文件的es命令:
docker run -e ES_JAVA_OPTS="-Xms512m -Xmx512m" -d -p 9200:9200 -p 9300:9300 -v /root/es/config/es1.yml:/usr/share/elasticsearch/config/elasticsearch.yml -v /root/es/data1:/usr/share/elasticsearch/data --name ES01 elasticsearch:6.7.1
es2.yml配置文件內容:
cluster.name: elasticsearch-cluster
node.name: es-node2
network.bind_host: 0.0.0.0
network.publish_host: 10.90.101.48
http.port: 9201
transport.tcp.port: 9301
http.cors.enabled: true
http.cors.allow-origin: "*"
node.master: true
node.data: true
discovery.zen.ping.unicast.hosts: ["10.90.101.48:9300","10.90.101.48:9301","10.90.101.48:9302"]
discovery.zen.minimum_master_nodes: 2
xpack.ml.enabled: false
xpack.monitoring.enabled: false
xpack.security.enabled: false
xpack.watcher.enabled: false
啟動當前配置文件的es命令:
docker run -e ES_JAVA_OPTS="-Xms512m -Xmx512m" -d -p 9201:9201 -p 9301:9301 -v /root/es/config/es2.yml:/usr/share/elasticsearch/config/elasticsearch.yml -v /root/es/data2:/usr/share/elasticsearch/data --name ES02 elasticsearch:6.7.1
es3.yml配置文件內容:
cluster.name: elasticsearch-cluster
node.name: es-node3
network.bind_host: 0.0.0.0
network.publish_host: 10.90.101.48
http.port: 9202
transport.tcp.port: 9302
http.cors.enabled: true
http.cors.allow-origin: "*"
node.master: true
node.data: true
discovery.zen.ping.unicast.hosts: ["10.90.101.48:9300","10.90.101.48:9301","10.90.101.48:9302"]
discovery.zen.minimum_master_nodes: 2
xpack.ml.enabled: false
xpack.monitoring.enabled: false
xpack.security.enabled: false
xpack.watcher.enabled: false
啟動當前配置文件的es命令:
docker run -e ES_JAVA_OPTS="-Xms512m -Xmx512m" -d -p 9202:9202 -p 9302:9302 -v /root/es/config/es3.yml:/usr/share/elasticsearch/config/elasticsearch.yml -v /root/es/data3:/usr/share/elasticsearch/data --name ES03 elasticsearch:6.7.1
1、-e JAVA_OPTS="-Xms512m -Xmx512m" 是配置當前es使用jvm的最大內存,內存配置過低會導致CPU非常高,如果服務器內存很大可配置2~4g
2、-p 9200:9200 -p 9300:9300 9200是es提供給外部的通訊端口,9300是es節點之間的通訊端口
3、 -v /root/es/config/es1.yml:/usr/share/elasticsearch/config/elasticsearch.yml 指定啟動的配置文件
4、-v /root/es/data1:/usr/share/elasticsearch/data 指定es的數據掛載到當前服務器的目錄
5、--name ES01 當前鏡像的名字
kibana
kibana.yml配置文件內容:
server.name: kibana
server.host: "0"
elasticsearch.url: http://10.90.101.48:9300
xpack.monitoring.ui.container.elasticsearch.enabled: false
xpack.security.enabled: false
xpack.ml.enabled: false
xpack.monitoring.enabled: false
啟動kibana
docker run --name kibana -v /root/kibana/config:/usr/share/kibana/config -p 5601:5601 -d kibana:6.7.1
logstash
把images中的配置文件拷貝出來:
1. 先運行一個logstash實例
2. docker cp 容器id:/usr/share/logstash/config /root/logstash/config
docker cp 容器id:/usr/share/logstash/pipeline /root/logstash/pipeline
pipeline/logstash.conf
input{
http{
host => "0.0.0.0"
port => 5050
additional_codecs => {"application/json"=>"json"}
codec => "plain"
threads => 4
ssl => false
}
}
output {
elasticsearch {
hosts => ["http://10.90.101.48:9200","http://10.90.101.51:9201","http://10.90.101.51:9202"]
index => "log_%{logtype}_%{+YYYY.MM.dd}"
}
}
設置日志輸入輸出方式
config/logstash.yml
http.host: "0.0.0.0"
xpack.monitoring.enabled: false
啟動logstash
docker run -d --name logstash -p 5050:5050 -v /root/logstash/config:/usr/share/logstash/config -v /root/logstash/pipeline:/usr/share/logstash/pipeline logstash:6.7.1
cerebro 一個管理es的工具
docker pull lmenezes/cerebro
啟動cerebro
docker run --name es-head -p 9000:9000 -d lmenezes/cerebro
瀏覽器中打開 ip:9000 鏈接 http://ip:9200 即可看到es 集群的狀態
