docker-compose部署ELK
本章基于
https://www.cnblogs.com/lirunzhou/p/10550675.html
在此基础上将ELK系统docker-compose.yml化。
其docker-compose 需要注意
1.不要把 docker 当做数据容器来使用,数据一定要用 volumes 放在容器外面
2.不要把 docker-compose 文件暴露给别人, 因为上面有你的服务器信息
3.多用 docker-compose 的命令去操作, 不要用 docker 手动命令&docker-compose 去同时操作
4.写一个脚本类的东西,自动备份docker 映射出来的数据。
5.不要把所有服务都放在一个 docker 容器里面
准备环境:
管理节点10.191.51.44
数据节点 10.191.51.45/46/47
具体文件:
es docker-compose.yml
version: '2' services: elasticsearch: container_name: ES environment : - ES_JAVA_OPTS=-Xms4G -Xmx4G image: 10.191.51.5/elk/elasticsearch:6.5.4 volumes: - ./config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml - ./data:/usr/share/elasticsearch/data ports: - "9200:9200" - "9300:9300"
管理节点 elasticsearch.yml
cluster.name: elasticsearch-cluster node.name: es-node1 network.bind_host: 0.0.0.0 network.publish_host: 10.191.51.44 http.port: 9200 transport.tcp.port: 9300 http.cors.enabled: true http.cors.allow-origin: "*" node.master: false node.data: false node.ingest: true discovery.zen.ping.unicast.hosts: ["10.191.51.44:9300","10.191.51.45:9300","10.191.51.46:9300","10.191.51.47:9300"] discovery.zen.minimum_master_nodes: 2
数据节点 elasticsearch.yml
cluster.name: elasticsearch-cluster node.name: es-node2 network.bind_host: 0.0.0.0 network.publish_host: 10.191.51.45 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: ["10.191.51.44:9300","10.191.51.45:9300","10.191.51.46:9300","10.191.51.47:9300"] discovery.zen.minimum_master_nodes: 2
kafka docker-compose.yml (其中environment需要配置)
version: '2' services: kafka: container_name: kafka0 environment: - KAFKA_BROKER_ID=0 - KAFKA_ZOOKEEPER_CONNECT=10.191.51.44:2181 - KAFKA_DEFAULT_REPLICATION_FACTOR=3 - KAFKA_LISTENERS=PLAINTEXT://0.0.0.0:9092 - KAFKA_ADVERTISED_HOST_NAME=kafka1 - KAFKA_ADVERTISED_LISTENERS=PLAINTEXT://10.191.51.45:9092 - KAFKA_delete_topic_enable=true image: 10.191.51.5/elk/wurstmeister/kafka:2.1.1 ports: - "9092:9092"
logstash docker-compose.yml
version: '2' services: logstash: container_name: logstash image: 10.191.51.5/elk/logstash:6.5.4 volumes: - ./config/:/usr/share/logstash/config/ - ./pipeline/:/usr/share/logstash/pipeline/ ports: - "5044:5044" - "9600:9600"
pipeline/logstash.conf
kafka{ bootstrap_servers => ["10.191.51.45:9092,10.191.51.46:9092,10.191.51.47:9092"] client_id => "logstash-garnet" group_id => "logstash-garnet" consumer_threads => 8 decorate_events => true topics => ["garnet_garnetAll_log"] type => "garnet_all_log" } } filter{ if[type]=="garnet_all_log"{ mutate{ gsub => ["message", "@timestamp", "sampling_time"] } json{ source=>"message" } grok{ match=>{ "message"=>[ "%{TIMESTAMP_ISO8601:log_time}\s+\[(?<thread_name>[a-zA-Z0-9\-\s]*)\]\s+%{LOGLEVEL:log_level}\s+\[(?<class_name>[a-zA-Z0-9.]*)\]\s+%{GREEDYDATA:msg_info}parameters=%{GREEDYDATA:msg_json_info}", "%{TIMESTAMP_ISO8601:log_time}\s+\[(?<thread_name>[a-zA-Z0-9\-\s]*)\]\s+%{LOGLEVEL:log_level}\s+\[(?<class_name>[a-zA-Z0-9.]*)\]\s+%{GREEDYDATA:msg_info}" ] } } if [msg_json_info]{ json{ source=>"msg_json_info" } } } } output { if[type] == "garnet_all_log"{ elasticsearch{ hosts => ["10.191.51.45:9200","10.191.51.46:9200","10.191.51.47:9200"] index => "garnet_all-%{+YYYY.MM.dd}" } } }
config/pipeline.yml
- pipeline.id: pipeline_1 pipeline.batch.size: 200 pipeline.batch.delay: 1 path.config: /usr/share/logstash/pipeline
config/logstash.yml
log.level: warn xpack.license.self_generated.type: basic xpack.monitoring.enabled: true xpack.monitoring.elasticsearch.url: "http://10.191.51.44:9200"
config/jvm.options 修改
-Xms4g
-Xmx4g