这篇文章主要介绍了Docker如何构建ELK Docker集群日志收集系统的相关知识，内容详细易懂，操作简单快捷，具有一定借鉴价值，相信大家阅读完这篇Docker如何构建ELK Docker集群日志收集系统文章都会有所收获，下面我们一起来看看吧。
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elk简介
elk由elasticsearch、logstash和kiabana三个开源工具组成
elasticsearch是个开源分布式搜索引擎，它的特点有：分布式，零配置，自动发现，索引自动分片，索引副本机制，restful风格接口，多数据源，自动搜索负载等。
logstash是一个完全开源的工具，他可以对你的日志进行收集、过滤，并将其存储供以后使用
kibana 也是一个开源和免费的工具，它kibana可以为 logstash 和 elasticsearch 提供的日志分析友好的 web 界面，可以帮助您汇总、分析和搜索重要数据日志。
使用docker搭建elk平台
首先我们编辑一下 logstash的配置文件 logstash.conf
重庆分公司
重庆分公司
input {
udp {
port => 5000
type => json
}
}
filter {
json {
source => "message"
}
}
output {
elasticsearch {
hosts => "elasticsearch:9200" #将logstash的输出到 elasticsearch 这里改成你们自己的host
}
}然后我们还需要需要一下kibana 的启动方式
编写启动脚本 等待elasticserach 运行成功后启动
#!/usr/bin/env bash # wait for the elasticsearch container to be ready before starting kibana. echo "stalling for elasticsearch" while true; do nc -q 1 elasticsearch 9200 2>/dev/null && break done echo "starting kibana" exec kibana
修改dockerfile 生成自定义的kibana镜像
from kibana:latest run apt-get update && apt-get install -y netcat copy entrypoint.sh /tmp/entrypoint.sh run chmod +x /tmp/entrypoint.sh run kibana plugin --install elastic/sense cmd ["/tmp/entrypoint.sh"]
同时也可以修改一下kibana 的配置文件 选择需要的插件
# kibana is served by a back end server. this controls which port to use. port: 5601 # the host to bind the server to. host: "0.0.0.0" # the elasticsearch instance to use for all your queries. elasticsearch_url: "http://elasticsearch:9200" # preserve_elasticsearch_host true will send the hostname specified in `elasticsearch`. if you set it to false, # then the host you use to connect to *this* kibana instance will be sent. elasticsearch_preserve_host: true # kibana uses an index in elasticsearch to store saved searches, visualizations # and dashboards. it will create a new index if it doesn't already exist. kibana_index: ".kibana" # if your elasticsearch is protected with basic auth, this is the user credentials # used by the kibana server to perform maintence on the kibana_index at statup. your kibana # users will still need to authenticate with elasticsearch (which is proxied thorugh # the kibana server) # kibana_elasticsearch_username: user # kibana_elasticsearch_password: pass # if your elasticsearch requires client certificate and key # kibana_elasticsearch_client_crt: /path/to/your/client.crt # kibana_elasticsearch_client_key: /path/to/your/client.key # if you need to provide a ca certificate for your elasticsarech instance, put # the path of the pem file here. # ca: /path/to/your/ca.pem # the default application to load. default_app_id: "discover" # time in milliseconds to wait for elasticsearch to respond to pings, defaults to # request_timeout setting # ping_timeout: 1500 # time in milliseconds to wait for responses from the back end or elasticsearch. # this must be > 0 request_timeout: 300000 # time in milliseconds for elasticsearch to wait for responses from shards. # set to 0 to disable. shard_timeout: 0 # time in milliseconds to wait for elasticsearch at kibana startup before retrying # startup_timeout: 5000 # set to false to have a complete disregard for the validity of the ssl # certificate. verify_ssl: true # ssl for outgoing requests from the kibana server (pem formatted) # ssl_key_file: /path/to/your/server.key # ssl_cert_file: /path/to/your/server.crt # set the path to where you would like the process id file to be created. # pid_file: /var/run/kibana.pid # if you would like to send the log output to a file you can set the path below. # this will also turn off the stdout log output. log_file: ./kibana.log # plugins that are included in the build, and no longer found in the plugins/ folder bundled_plugin_ids: - plugins/dashboard/index - plugins/discover/index - plugins/doc/index - plugins/kibana/index - plugins/markdown_vis/index - plugins/metric_vis/index - plugins/settings/index - plugins/table_vis/index - plugins/vis_types/index - plugins/visualize/index
好了下面我们编写一下 docker-compose.yml 方便构建
端口之类的可以根据自己的需求修改 配置文件的路径根据你的目录修改一下 整体系统配置要求较高 请选择配置好点的机器
elasticsearch: image: elasticsearch:latest command: elasticsearch -des.network.host=0.0.0.0 ports: - "9200:9200" - "9300:9300" logstash: image: logstash:latest command: logstash -f /etc/logstash/conf.d/logstash.conf volumes: - ./logstash/config:/etc/logstash/conf.d ports: - "5001:5000/udp" links: - elasticsearch kibana: build: kibana/ volumes: - ./kibana/config/:/opt/kibana/config/ ports: - "5601:5601" links: - elasticsearch
#好了命令 就可以直接启动elk了 docker-compose up -d
访问之前的设置的kibanna的5601端口就可以看到是否启动成功了
使用logspout收集docker日志
下一步我们要使用logspout对docker日志进行收集 我们根据我们的需求修改一下logspout镜像
编写配置文件 modules.go
package main import ( _ "github.com/looplab/logspout-logstash" _ "github.com/gliderlabs/logspout/transports/udp" )
编写dockerfile
from gliderlabs/logspout:latest copy ./modules.go /src/modules.go
重新构建镜像后 在各个节点运行即可
docker run -d --name="logspout" --volume=/var/run/docker.sock:/var/run/docker.sock \ jayqqaa12/logspout logstash://你的logstash地址
现在打开kibana 就可以看到收集到的 docker日志了
注意docker容器应该选择以console输出 这样才能采集到
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