EFLFK - ELK log analysis system + kafka + filebeat architecture

Environmental preparation

node1 node	192.168.40.16	elasticsearch	2c/4G
node2 node	192.168.40.17	elasticsearch	2c/4G
Apache node	192.168.40.170	logstash/apache/kibana	2c/4G
filebeat node	192.168.40.20	filebeat	2c/4G

https://blog.csdn.net/m0_57554344/article/details/132059066?spm=1001.2014.3001.5501

Continuing from the previous elk deployment, we will add a filebeat node this time

experiment:

 Operate on the filebeat node

1．安装 Filebeat
#上传软件包 filebeat-6.2.4-linux-x86_64.tar.gz 到/opt目录
tar zxvf filebeat-6.2.4-linux-x86_64.tar.gz
mv filebeat-6.2.4-linux-x86_64/ /usr/local/filebeat

 

2．设置 filebeat 的主配置文件
cd /usr/local/filebeat

vim filebeat.yml
filebeat.prospectors:
- type: log         #指定 log 类型，从日志文件中读取消息
  enabled: true
  paths:
    - /var/log/messages       #指定监控的日志文件
    - /var/log/*.log
  fields:           #可以使用 fields 配置选项设置一些参数字段添加到 output 中
    service_name: filebeat
    log_type: log
    service_id: 192.168.40.20

--------------Elasticsearch output-------------------
(全部注释掉)

----------------Logstash output---------------------
output.logstash:
  hosts: ["192.168.40.170:5044"]      #指定 logstash 的 IP 和端口

#启动 filebeat
./filebeat -e -c filebeat.yml

 4. Create a new Logstash configuration file on the node where the Logstash component is located

cd /etc/logstash/conf.d

vim logstash.conf
input {
    beats {
        port => "5044"
    }
}
output {
    elasticsearch {
        hosts => ["192.168.40.16:9200"]
        index => "%{[fields][service_name]}-%{+YYYY.MM.dd}"
    }
    stdout {
        codec => rubydebug
    }
}

#启动 logstash
logstash -f logstash.conf

5．浏览器访问 http://192.168.40.170:5601 登录 Kibana，单击“Create Index Pattern”按钮添加索引“filebeat-*”，单击 “create” 按钮创建，单击 “Discover” 按钮可查看图表信息及日志信息。

 二、ELFK+zookeeper+kafka

1. Deploy the zookeeper cluster

// Prepare 3 servers for Zookeeper cluster
192.168.40.21     
192.168.40.22
192.168.40.23

1.安装前准备
//关闭防火墙
systemctl stop firewalld
systemctl disable firewalld
setenforce 0

//安装 JDK
yum install -y java-1.8.0-openjdk java-1.8.0-openjdk-devel
java -version



cd /opt
wget https://archive.apache.org/dist/zookeeper/zookeeper-3.5.7/apache-zookeeper-3.5.7-bin.tar.gz

2.安装 Zookeeper
cd /opt
tar -zxvf apache-zookeeper-3.5.7-bin.tar.gz
mv apache-zookeeper-3.5.7-bin /usr/local/zookeeper-3.5.7

//修改配置文件
cd /usr/local/zookeeper-3.5.7/conf/
cp zoo_sample.cfg zoo.cfg

vim zoo.cfg
tickTime=2000   #通信心跳时间，Zookeeper服务器与客户端心跳时间，单位毫秒
initLimit=10    #Leader和Follower初始连接时能容忍的最多心跳数（tickTime的数量），这里表示为10*2s
syncLimit=5     #Leader和Follower之间同步通信的超时时间，这里表示如果超过5*2s，Leader认为Follwer死掉，并从服务器列表中删除Follwer
dataDir=/usr/local/zookeeper-3.5.7/data      ●修改，指定保存Zookeeper中的数据的目录，目录需要单独创建
dataLogDir=/usr/local/zookeeper-3.5.7/logs   ●添加，指定存放日志的目录，目录需要单独创建
clientPort=2181   #客户端连接端口
#添加集群信息
server.1=192.168.40.21:3188:3288
server.2=192.168.40.22:3188:3288
server.3=192.168.40.23:3188:3288

 

 

 server.A=B:C:D
●A is a number, indicating which server number this is. In cluster mode, you need to create a file myid in the directory specified by dataDir in zoo.cfg. There is a data in this file that is the value of A. When Zookeeper starts, read this file, get the data in it and the configuration in zoo.cfg Compare the information to determine which server it is.
● B is the address of this server.
●C is the port through which the Follower of this server exchanges information with the Leader server in the cluster.
●D is in case the Leader server in the cluster hangs up, a port is needed to re-elect and elect a new Leader, and this port is the port used to communicate with each other during the election.

//拷贝配置好的 Zookeeper 配置文件到其他机器上
scp /usr/local/zookeeper-3.5.7/conf/zoo.cfg 192.168.40.22:/usr/local/zookeeper-3.5.7/conf/
scp /usr/local/zookeeper-3.5.7/conf/zoo.cfg 192.168.40.23:/usr/local/zookeeper-3.5.7/conf/

//在每个节点上创建数据目录和日志目录
mkdir /usr/local/zookeeper-3.5.7/data
mkdir /usr/local/zookeeper-3.5.7/logs

//在每个节点的dataDir指定的目录下创建一个 myid 的文件
echo 1 > /usr/local/zookeeper-3.5.7/data/myid
echo 2 > /usr/local/zookeeper-3.5.7/data/myid
echo 3 > /usr/local/zookeeper-3.5.7/data/myid

//配置 Zookeeper 启动脚本
vim /etc/init.d/zookeeper
#!/bin/bash
#chkconfig:2345 20 90
#description:Zookeeper Service Control Script
ZK_HOME='/usr/local/zookeeper-3.5.7'
case $1 in
start)
	echo "---------- zookeeper 启动 ------------"
	$ZK_HOME/bin/zkServer.sh start
;;
stop)
	echo "---------- zookeeper 停止 ------------"
	$ZK_HOME/bin/zkServer.sh stop
;;
restart)
	echo "---------- zookeeper 重启 ------------"
	$ZK_HOME/bin/zkServer.sh restart
;;
status)
	echo "---------- zookeeper 状态 ------------"
	$ZK_HOME/bin/zkServer.sh status
;;
*)
    echo "Usage: $0 {start|stop|restart|status}"
esac

//	设置开机自启
chmod +x /etc/init.d/zookeeper
chkconfig --add zookeeper

 

//分别启动 Zookeeper
service zookeeper start

//查看当前状态
service zookeeper status

 Three deployment kafka cluster

1. Download the installation package

2. Install Kafka

cd /opt/
tar zxvf kafka_2.13-2.7.1.tgz
mv kafka_2.13-2.7.1 /usr/local/kafka

//修改配置文件
cd /usr/local/kafka/config/
cp server.properties{,.bak}

vim server.properties
broker.id=0    ●21行，broker的全局唯一编号，每个broker不能重复，因此要在其他机器上配置 broker.id=1、broker.id=2
listeners=PLAINTEXT://192.168.10.17:9092    ●31行，指定监听的IP和端口，如果修改每个broker的IP需区分开来，也可保持默认配置不用修改
num.network.threads=3    #42行，broker 处理网络请求的线程数量，一般情况下不需要去修改
num.io.threads=8         #45行，用来处理磁盘IO的线程数量，数值应该大于硬盘数
socket.send.buffer.bytes=102400       #48行，发送套接字的缓冲区大小
socket.receive.buffer.bytes=102400    #51行，接收套接字的缓冲区大小
socket.request.max.bytes=104857600    #54行，请求套接字的缓冲区大小
log.dirs=/usr/local/kafka/logs        #60行，kafka运行日志存放的路径，也是数据存放的路径
num.partitions=1    #65行，topic在当前broker上的默认分区个数，会被topic创建时的指定参数覆盖
num.recovery.threads.per.data.dir=1    #69行，用来恢复和清理data下数据的线程数量
log.retention.hours=168    #103行，segment文件（数据文件）保留的最长时间，单位为小时，默认为7天，超时将被删除
log.segment.bytes=1073741824    #110行，一个segment文件最大的大小，默认为 1G，超出将新建一个新的segment文件
zookeeper.connect=192.168.40.21:2181,192.168.40.22:2181,192.168.40.23:2181    ●123行，配置连接Zookeeper集群地址

//修改环境变量
vim /etc/profile
export KAFKA_HOME=/usr/local/kafka
export PATH=$PATH:$KAFKA_HOME/bin


source /etc/profile

//配置 Zookeeper 启动脚本
vim /etc/init.d/kafka
#!/bin/bash
#chkconfig:2345 22 88
#description:Kafka Service Control Script
KAFKA_HOME='/usr/local/kafka'
case $1 in
start)
	echo "---------- Kafka 启动 ------------"
	${KAFKA_HOME}/bin/kafka-server-start.sh -daemon ${KAFKA_HOME}/config/server.properties
;;
stop)
	echo "---------- Kafka 停止 ------------"
	${KAFKA_HOME}/bin/kafka-server-stop.sh
;;
restart)
	$0 stop
	$0 start
;;
status)
	echo "---------- Kafka 状态 ------------"
	count=$(ps -ef | grep kafka | egrep -cv "grep|$$")
	if [ "$count" -eq 0 ];then
        echo "kafka is not running"
    else
        echo "kafka is running"
    fi
;;
*)
    echo "Usage: $0 {start|stop|restart|status}"
esac

//设置开机自启
chmod +x /etc/init.d/kafka
chkconfig --add kafka

//分别启动 Kafka
service kafka start

 

Four Deploy Filebeat+Kafka+ELK

 1. Modify the filebeat configuration file filebeat.yml to collect logs and forward (production) to kafka

cd /usr/local/filebeat

vim filebeat.yml
filebeat.prospectors:
- type: log
  enabled: true
  paths:
    - /var/log/httpd/access_log
  tags: ["nginx_access"]
  
- type: log
  enabled: true
  paths:
    - /var/log/httpd/error_log
  tags: ["nginx_error"]
  
......
#添加输出到 Kafka 的配置
output.kafka:
  enabled: true
  hosts: ["192.168.40.21:9092","192.168.40.22:9092","192.168.40.23:9092"]    #指定 Kafka 集群配置
  topic: "httpd"    #指定 Kafka 的 topic
  
#启动 filebeat
./filebeat -e -c filebeat.yml

 2. Modify the logstash configuration to consume logs from kafka and output them to the front end of kibana for display

 Open logstash, visit the web test page at this time, you can collect and analyze logs in kibana