企业级架构ELKF集群、日志收集方案

麦小轮
ELKF 云计算运维
2022-11-10
572
7

「ELK安装文件」https://www.aliyundrive.com/s/zvTBLm7pSXd 提取码: j60q

kafka登入阿里云网盘下载，格式无法分享。或者下载地址：http://kafka.apache.org/downloads

企业级架构ELKF集群

服务器

A：10.10.1.3

B：10.10.1.4

C：10.10.1.5

客户端

D：10.10.1.6

下面将用ABC代表服务器了

ABC修改计算机名称

A服务器：hostnamectl set-hostname node1

B服务器：hostnamectl set-hostname node2

C服务器：hostnamectl set-hostname node3

ADCD更新源并安装java

curl -o /etc/yum.repos.d/CentOS-Base.repo http://mirrors.aliyun.com/repo/Centos-7.repo curl -o /etc/yum.repos.d/epel.repo http://mirrors.aliyun.com/repo/epel-7.repo yum install lrzsz vim java-1.8.0-openjdk java-1.8.0-openjdk-devel-y java –version -y

ABC都切换到

cd /usr/local/src/

吧文件下面文件都拷贝到上面的这个目录

apache-zookeeper-3.6.0-bin.tar.gz elasticsearch-7.13.1-x86_64.rpm filebeat-7.13.1-x86_64.rpm kafka_2.12-2.5.0.tgz kibana-7.13.1-x86_64.rpm logstash-7.13.1-x86_64.rpm

ABC都要进行更新源，和安装java
curl -o /etc/yum.repos.d/CentOS-Base.repo http://mirrors.aliyun.com/repo/Centos-7.repo curl -o /etc/yum.repos.d/epel.repo http://mirrors.aliyun.com/repo/epel-7.repo yum install lrzsz vim java-1.8.0-openjdk java-1.8.0-openjdk-devel-y java –version -y

ABC安装ES集群服务，进行连接
cd /usr/local/src/ yum localinstall elasticsearch-7.13.1-x86_64.rpm -y

JVM的内存限制更改，根据实际环境调整，更具服务器内存修改，如果服务器8G，这里可以改为6G，给服务器预留1-2G即可
vi /etc/elasticsearch/jvm.options -Xms4g 改为 -Xmx2g

ES集群实战注意
集群交互是使用证书交互
搭建集群前需要先创建证书文件
ES集群交互CA证书创建 A服务器上
/usr/share/elasticsearch/bin/elasticsearch-certutil ca #一直回车

查看证书位置
ll -rht /usr/share/elasticsearch/elastic-stack-ca.p12

创建证书
/usr/share/elasticsearch/bin/elasticsearch-certutil cert --ca /usr/share/elasticsearch/elastic-stack-ca.p12 #一直回车

查看证书
ll -rht /usr/share/elasticsearch/elastic-certificates.p12 cp /usr/share/elasticsearch/elastic-certificates.p12 /etc/elasticsearch/elastic-certificates.p12

证书要求权限修改，不然集群搭建失败
chmod 600 /etc/elasticsearch/elastic-certificates.p12 chown elasticsearch:elasticsearch /etc/elasticsearch/elastic-certificates.p12

吧加密ca证书拷贝到BC服务器
scp /etc/elasticsearch/elastic-certificates.p12 10.10.1.4:/etc/elasticsearch/ scp /etc/elasticsearch/elastic-certificates.p12 10.10.1.5:/etc/elasticsearch/

ABC服务器对比MD5值是否一致

md5sum /etc/elasticsearch/elastic-certificates.p12

B服务器和C服务器都要执行
chmod 600 /etc/elasticsearch/elastic-certificates.p12 chown elasticsearch:elasticsearch /etc/elasticsearch/elastic-certificates.p12

ADC服务器都要进行修改
vi /etc/elasticsearch/elasticsearch.yml cluster.name: maixiaolun node.name: node1 #服务器A就改为nede1，服务器B改为node2，服务器C改为node3 node.master: true node.data: true path.data: /var/lib/elasticsearch path.logs: /var/log/elasticsearch network.host: 0.0.0.0 http.port: 9200 discovery.seed_hosts: ["10.10.1.3", "10.10.1.4", "10.10.1.5"] cluster.initial_master_nodes: ["10.10.1.3", "10.10.1.4", "10.10.1.5"] xpack.security.enabled: true xpack.monitoring.enabled: true xpack.security.transport.ssl.enabled: true xpack.security.transport.ssl.verification_mode: certificate xpack.security.transport.ssl.keystore.path: /etc/elasticsearch/elastic-certificates.p12 xpack.security.transport.ssl.truststore.path: /etc/elasticsearch/elastic-certificates.p12

ABC防火墙要放通端口
firewall-cmd --zone=public --add-port=9300/tcp --permanent firewall-cmd --zone=public --add-port=9300/udp --permanent firewall-cmd --zone=public --add-port=9200/tcp --permanent firewall-cmd --zone=public --add-port=9200/udp --permanent firewall-cmd --zone=public --add-port=5601/tcp --permanent firewall-cmd --zone=public --add-port=5601/udp --permanent firewall-cmd --zone=public --add-port=80/tcp --permanent firewall-cmd --zone=public --add-port=3000/tcp --permanent 重新载入 firewall-cmd --reload

ABC服务器顺序启动ES服务

systemctl enable elasticsearch

systemctl restart elasticsearch

继续看第一台服务器日志

出现valid，表示成功了
接下来是查看3台集群中间的互动
yum -y install net-tools 安装 netstat netstat -anp |grep 10.0.0.20:9300 查看集群之间的交互

检查9300端口连接情况

确认集群中所有es的日志正常再设置密码maixiaolun..123

在主服务器(服务器A，想把那个当主服务器就在那个服务器上运行)上运行

ES设置密码/usr/share/elasticsearch/bin/elasticsearch-setup-passwords interactive

ES设置随机密码/usr/share/elasticsearch/bin/elasticsearch-setup-passwords auto

验证集群是否成功，标记为*的为master节点。网页访问或者curl访问

http://10.10.1.3:9200 账号：elastic 密码：刚刚设置的

http://10.10.1.3:9200/_cat/nodes?v //查看节点信息带*的就是主的

http://xxx:9200/_cat/indices?v

命令方式查看输入账号密码

curl -u elastic:maixiaolun..123 http://10.10.1.3:9200/_cat/nodes?v

B服务器安装Kibana (因为是前端，蹦了就蹦了，不要紧，所有不需要每个地方都搭建来)

B服务器安装

cd /usr/local/src/

yum localinstall kibana-7.13.1-x86_64.rpm -y

Kibana配置连接ES集群
vi /etc/kibana/kibana.yml server.port: 5601 server.host: "0.0.0.0" elasticsearch.hosts: ["http://10.10.1.3:9200", "http://10.10.1.4:9200", "http://10.10.1.5:9200"] elasticsearch.username: "elastic" elasticsearch.password: "maixiaolun..123" logging.dest: /tmp/kibana.log

B服务器Kibana的启动和访问
systemctl enable kibana systemctl restart kibana

Kibana监控开启
netstat -tulnp

http://10.10.1.3:5601
账号：elastic
密码：maixiaolun..123

BC服务器安装logstash日志分析（就是蹦了一台也不要紧，此做法为高可用做法，安装一台的话也是可以的）
cd /usr/local/src/ yum localinstall logstash-7.13.1-x86_64.rpm -y

内存配置jvm.options 1g,根据自己实际情况改

vi /etc/logstash/jvm.options

配置logstash配置文件
vi /etc/logstash/conf.d/logstash.conf #监听5044传来的日志 input { beats { host => '0.0.0.0' port => 5044 } } #这里是正则表达式，分析日志 filter { grok { match => { "message" => '%{IP:remote_addr} - (%{WORD:remote_user}|-) [% {HTTPDATE:time_local}] "%{WORD:method} %{NOTSPACE:request} HTTP/% {NUMBER}" %{NUMBER:status} %{NUMBER:body_bytes_sent} %{QS} % {QS:http_user_agent}' } remove_field => ["message"] } date { match => ["time_local", "dd/MMM/yyyy:HH:mm:ss Z"] target => "@timestamp" } } #发送给所有ES服务器 output { elasticsearch { hosts => ["http://10.10.1.3:9200", "http://10.10.1.4:9200", "http://10.10.1.5:9200"] user => "elastic" password => "maixiaolun..123" index => "mxlnginx-%{+YYYY.MM.dd}" } } #启动Logstash，配置重载： kill -1 pid systemctl restart logstash systemctl enable logstash #等待启动,查看日志 /var/log/logstash 日志生成的地方 tail -f logstash-plain.log

ZK集群部署
所有服务器都要进行安装
cd /usr/local/src/ tar -zxvf apache-zookeeper-3.6.0-bin.tar.gz mv apache-zookeeper-3.6.0-bin /usr/local/zookeeper mkdir -pv /usr/local/zookeeper/data cd /usr/local/zookeeper/conf cp zoo_sample.cfg zoo.cfg

zk集群至少需要三台机器
集群配置zoo.cfg
vi zoo.cfg

tickTime=2000 initLimit=10 syncLimit=5 dataDir=/usr/local/zookeeper/data clientPort=2181 autopurge.snapRetainCount=3 autopurge.purgeInterval=1 server.1=10.10.1.3:2888:3888 server.2=10.10.1.4:2888:3888 server.3=10.10.1.5:2888:3888

更改zk集群的id
vi /usr/local/zookeeper/data/myid
第一台就填写1
第二台就填写2
第三台就填写3

分别为1 2 3

systemctl管理
vi /usr/lib/systemd/system/zookeeper.service [Unit] Description=zookeeper After=network.target [Service] Type=forking ExecStart=/usr/local/zookeeper/bin/zkServer.sh start User=root [Install] WantedBy=multi-user.target

启动zk
systemctl enable zookeeper systemctl restart zookeeper

启动zk集群查看状态
cd /usr/local/zookeeper/bin/ ./zkServer.sh start ./zkServer.sh status

报错的话，检查防火墙。

正确显示为下

Kafka集群部署
下载地址：http://kafka.apache.org/downloads
安装
cd /usr/local/src/ tar -zxvf kafka_2.12-2.5.0.tgz -C /usr/local/

Jvm内存修改/usr/local/kafka_2.12-2.5.0/bin/kafka-server-start.sh，根据实际情况修
改，每台服务器都要改

修改Kafka配置server.properties

cd /usr/local/kafka_2.12-2.5.0/config/

vi server.properties

broker.id=0 listeners=PLAINTEXT://xxx:9092 log.retention.hours=1 #根据实际情况修改日志保留时间 zookeeper.connect=xxx:2181,xxx:2181,xxx:2181 zookeeper.connection.timeout.ms=18000 改为 zookeeper.connection.timeout.ms=60000 拷贝到其他服务器上 scp server.properties 10.0.0.21:/usr/local/kafka_2.12-2.5.0/config/ 然后在新的服务器上 vi /usr/local/kafka_2.12-2.5.0/config/server.properties 改listeners=PLAINTEXT://xxx:9092 对应当前服务器的ip broker.id=0 改为broker.id=1

如果启动的时候报如下错误，是因为链接超时，吧60000改为 1200000也就是2分钟

Kafka使用systemctl管理
vi /usr/lib/systemd/system/kafka.service [Unit] Description=kafka After=network.target [Service] Type=simple ExecStart=/usr/local/kafka_2.12-2.5.0/bin/kafka-server-start.sh /usr/local/kafka_2.12-2.5.0/config/server.properties User=root [Install] WantedBy=multi-user.target

Kafka启动
systemctl enable kafka systemctl restart kafka

查看kafka日志
cd /usr/local/kafka_2.12-2.5.0/logs tail -f server.log

创建topic，创建成功说明kafka集群搭建成功
--replication-factor 3 代表3台服务器 cd /usr/local/kafka_2.12-2.5.0/bin/ ./kafka-topics.sh --create --zookeeper 10.10.1.4:2181 --replication-factor 3 --partitions 1 --topic maixiaolun #用这个测试

logstash获取kafka数据
vi /etc/logstash/conf.d/logstash.conf #获取kafka的日志 input { kafka { bootstrap_servers => "10.10.1.3:9092,10.10.1.4:9092,10.10.1.5:9092" topics => ["mxlkafka"] group_id => "mxlgroup" codec => "json" } } filter { mutate { remove_field => ["agent","ecs","log","input","[host][os]"] } } #正则表达式分析日志 filter { grok { match => { "message" => '%{IP:remote_addr} - (%{WORD:remote_user}|-) [% {HTTPDATE:time_local}] "%{WORD:method} %{NOTSPACE:request} HTTP/% {NUMBER}" %{NUMBER:status} %{NUMBER:body_bytes_sent} %{QS} % {QS:http_user_agent}' } remove_field => ["message"] } date { match => ["time_local", "dd/MMM/yyyy:HH:mm:ss Z"] target => "@timestamp" } } #吧分析过后的日志发送给ES output { elasticsearch { hosts => ["http://10.10.1.3:9200", "http://10.10.1.4:9200", "http://10.10.1.5:9200"] user => "elastic" password => "maixiaolun..123" index => "mxlnginx-%{+YYYY.MM.dd}" #这里代表日志的名字，不通服务器可以写不通的名字 } }
重载
ps auxfww | grep logstash kill -1 804

看日志

cd /var/log/logstash/

tail -f logstash-plain.log

测试环境是否正常

效果同ELFK，但架构做了优化

Kafka查看队列信息，验证新架构是否生效

cd /usr/local/kafka_2.12-2.5.0/bin/

./kafka-consumer-groups.sh --bootstrap-server 10.10.1.4:9092 --list

./kafka-consumer-groups.sh --bootstrap-server 10.10.1.4:9092 --group mxlgroup -describe

LOG-END-OFFSET不断增大，LAG不堆积说明架构生效

LOG-END-OFFSET 一直增加就代表kafka在消费
LAG 一直在堆积
Logstash扩展
配置保持一致，启动即可

客户端D进行安装nginx进行测试数据是否传入服务器集群
安装nginx做测试，如果有其他服务可以直接测试
yum install nginx -y systemctl start nginx

安装filebeat，用于发送日志到服务器
cd /usr/local/src/ yum localinstall filebeat-7.13.1-x86_64.rpm -y

配置filebeat进行监控nginx

vi /etc/filebeat/filebeat.yml
 filebeat.inputs:
 - type: log
   tail_files: true
   backoff: "1s"
   paths:
      - /var/log/nginx/access.log

 processors:
 - drop_fields:
    fields: ["agent","ecs","log","input"]

 output:
   kafka:
     hosts: ["10.10.1.3:9092", "10.10.1.4:9092", "10.10.1.5:9092"]
     topic: mxlkafka   #这里代表日志的名字，不通服务器可以写不通的名字

启动filebeat
systemctl start filebeat systemctl enable filebeat

登入B服务器网页
http://10.10.1.4:5601 账号：elastic 密码：maixiaolun..123

打开Stack Management