如何构建基于容器的本机监控系统

Docker 目前非常火爆，如何把Docker使用起来，并且和日常工作结合起来，是需要考虑的一个问题。本文意图将一个测试的具体步骤展示给大家，可以在一台内存较 大的台式机上进行（建议16GB内存），另外本文的参考意义更加在于尝试和使用，对于实际场景的意义则需要方家讨论。

测试拓扑图如下所示：

各个功能Docker模块功能如下：

• Flume：负责搜集日志信息（本文中启动了三个flume容器）

o 第一个负责从本机搜集/var/log/messages日志，直接发送到elasticsearch中

o 第二个负责从本机搜集/var/log/messages日志，发送到kafka中间件，读取日志序列，发送到elasticsearch

o 第三个负责从kafka读取日志序列，发送到elasticsearch。

o 还有一个没有实现的可能性，从kafka读取日志序列，写入HDFS，以便后续进行hadoop分析

• docker ps的输出则是真正运行在CentOS7中的容器集合，共同完成以上任务。

Config docker hub repository accelerator to Daocloud

http://dashboard.daocloud.io/mirror

For CentOS:

• sudo sed -i 's|other_args=|other_args=--registry-mirror= http://4c5cf935.m.daocloud.io |g' /etc/sysconfig/docker

• sudo sed -i "s|OPTIONS='|OPTIONS='--registry-mirror= http://4c5cf935.m.daocloud.io |g" /etc/sysconfig/docker

• sudo service docker restart

Install docker

• https://docs.docker.com/installation/centos

• yum –y update <make sure kernel >= 3.10.0-229.el7.x86_64>

• crul –sSL https://get.docker/com/ | sh

o this script adds the ‘docker.repo’ repository and installs Docker

• yum –y install docker-selinux

• systemctl start docker.service

Install docker-compose

• https://docs.docker.com/compose/install

• curl -L https://github.com/docker/comp ... ose-X 28X-uname -m> /usr/local/bin/docker-compose

• chmod +x /usr/local/bin/docker-compose

docker-compose kafka

• https://github.com/wurstmeister/kafka-docker

• under the kafka-docker-master directory:

o modify the KAFKA_ADVERTISED_HOST_NAME in docker-compose.yml to match your docker host IP (Note: Do not use localhost or 127.0.0.1 as the host ip if you want to run multiple brokers.)

o start a cluster : #docker-compute up –d

o Add user broker: docker-compose scale kafka=2<-(no less than replication factor below)

o Destroy a cluster: docker-compose stop

o Monitor the logs: docker-compose logs

o To see the containers IP and ports:

• Systemctl status docker.service

o ./start-kafka-shell <docker_host_ip> <zk_host:zk_port>

o <container1># $KAFKA_HOME/bin/kafka-topics.sh –create –topic topic –partitions 4 –zookeeper $ZK –replication-factor 2←(must equal to kafka broker’s #)

o <container1># $KAFKA_HOME/bin/kafka-topics.sh –list –zookeeper $ZK

o <container1># $KAFKA_HOME/bin/kafka-topics.sh –describe –topic topic –zookeeper $ZK

o <container1># $KAFKA_HOME/bin/kafka-console-producer.sh –topic=topic –broker-list=broker-list.sh

o ./start-kafka-shell <docker_host_ip> <zk_host:zk_port>

o <container2># $KAFKA_HOME/bin/kafka-console-consumer.sh –topic=topic –zookeeper=$ZK –from-beginning

o troubleshooting: http://wurstmeister.github.io/kafka-docker/

配置elasticsearch

• docker pull elasticsearch:latest

• mkdir /mnt/isilon

• mount isilon.mini:/ifs/hdfs /mnt/isilon

• docker run –d –p 9200:9200 –p 9300:9300 –v /mnt/isilon/elasticsearch:/data –v /mnt/isilon/elasticsearch/conf/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml elasticsearch

o <会将以上目录和文件挂载到container内部；>

o 起作用的配置文件在:/usr/share/elasticsearch/config目录下

o 一台物理机，只能启动一个elasticsearch容器

• systemctl status docker.service <to get the elasticsearch IP>

• http://<elasticsearch_i p>:9200 or http://<host_I P>:9200

• docker exec –it <elasticsearch_container_ID> /bin/bash

o cd /usr/share/elasticsearch/plugins

o /usr/share/elasticsearch/bin/plugin –install mobz/elasticsearch-head

o /usr/share/elasticsearch/bin/plugin –install lukas-vlcek/bigdesk

o http://<host_I P>:9200/_plugin/bigdesk

o http://<host_I P>:9200/_plugin/head

• docker exec –it <es_container_ID> /bin/bash

• cp –r /usr/share/elasticsearch/lib/* /data/lib

o used for later flume library to access elasticsearch

配置kibana

• docker pull kibana

• docker run - -link <elasticsearch_container_name> -d kibana

o 默认方式，5601端口只在container内部可用

• docker run - -link <elasticsearch_container_name> -d kibana - -plugins /somewhere/else

o 可以传递某些参数

• docker run - -name kibana - -link <elasticsearch_container_name> -p 5601:5601 –d kibana

o 对外输出5601端口，可以通过主机IP访问，但是有可能对elasticsearch提供服务的主机名localhost解析不了，造成问题。建议用下一种方式

• docker run - -name kibana –e http://<host_I P>:9200 -p 5601:5601 –d kibana

o netstat –tupln | grep 5601

o docker logs <kibana_container_ID>

o http://<host_I P>:5601

配置flume-----监控文件日志输出到elasticsearch

• docker pull probablyfine/flume <最新flume-ng为1.6.0版本>

• cat /mnt/isilon/config/flume_log2es.conf

o refer to 《配置ELK》文章中，配置flume-ng一节，第12A步配置

• docker run -e FLUME_AGENT_NAME=log2es -v /mnt/isilon:/data –v /var/log/messages:/var/log/messages -e FLUME_CONF_FILE=/data/config/flume_log2es.conf -d probablyfine/flume

o 为调试起见将host机器/var/log/messages挂入flume容器中

o flume_log2es.conf中监控/var/log/messages的变化，可以修改为容器内任何感兴趣的日志

• docker exec –it <flume_container_ID> /bin/bash

o cp –r /data/elasticsearch/lib/* /opt/flume/lib

• copy previous elasticsearch lib files to flume lib

• docker logs <flume_container_ID>

o docker stop <flume_container_ID>

o docker start <flume_container_ID> 即可，再用logs命令看状态

配置flume-----监控日志文件输出到kafka

• docker pull probablyfine/flume

• yum –y install maven

o to create flume-ng-kafka library

• https://github.com/jinoos/flume-ng-extends , download the zip file

• unzip flume-ng-extends-source-master.zip

• cd flume-ng-extends-source-master

• mvn clean packages

• mkdir –p /mnt/isilon/kafka/lib

• cp target/flume-ng-extends-source-0.8.0.jar /mnt/isilon/kafka/lib

• cat /mnt/isilon/config/flume_kafka_producer.conf

o refer to 《配置ELK》文章中，配置flume-ng一节，第12B步配置

• docker run -e FLUME_AGENT_NAME=kfk_pro -v /mnt/isilon:/data -v /var/log/messages:/var/log/messages -e FLUME_CONF_FILE=/data/config/flume_kafka_producer.conf -d probablyfine/flume

• docker exec –it <kfk_pro_container_ID> /bin/bash

o cp –r /data/elasticsearch/lib/* /opt/flume/lib

o cp –r /data/kafka/lib/* /opt/flume/lib

• docker stop <kfk_pro_container_ID>

• docker start <kfk_pro_container_ID>

o docker logs <kfk_pro_container_ID>

o refer to “docker-compose kafka” about topic list and consumer command

• cat /mnt/isilon/config/flume_kafka_consumer.conf

o refer to 《配置ELK》文章中，配置flume-ng一节，第12C步配置

• docker run -e FLUME_AGENT_NAME=kfk_con -v /mnt/isilon:/data -e FLUME_CONF_FILE=/data/config/flume_kafka_consumer.conf -d probablyfine/flume

• docker exec –it <kfk_con_container_ID> /bin/bash

o cp –r /data/elasticsearch/lib/* /opt/flume/lib

o cp –r /data/kafka/lib/* /opt/flume/lib

• docker stop <kfk_con_container_ID>

• docker start <kfk_con_container_ID>

o docker logs <kfk_con_container_ID>

o refer to “docker-compose kafka” about topic list and consumer command

配置kibana

Bigdesk插件输出情况

logstash日志为12A配置的flume生成。

es-index日志为12B/C配置的flume生成（via kafka）

通过kibana接收到的基于时序的日志信息。

整个系统状况

加粗文字

停止所有docker：

• docker ps | grep ^[0-9] | awk ‘{print $1}’ | xargs –t –I docker stop {}

启动所有docker：

• docker ps -a| grep ^[0-9] | awk ‘{print $1}’ | xargs –t –I docker stop {}