搭建ELK日志采集与分析系统

2024-08-22 06:52

本文主要是介绍搭建ELK日志采集与分析系统,希望对大家解决编程问题提供一定的参考价值,需要的开发者们随着小编来一起学习吧!

SpringCloud微服务实战——企业级开发框架

 💝💝💝欢迎来到我的博客,很高兴能够在这里和您见面!希望您在这里可以感受到一份轻松愉快的氛围,不仅可以获得有趣的内容和知识,也可以畅所欲言、分享您的想法和见解。

推荐:Linux运维老纪的首页,持续学习,不断总结,共同进步,活到老学到老
导航剑指大厂系列:全面总结 运维核心技术:系统基础、数据库、网路技术、系统安全、自动化运维、容器技术、监控工具、脚本编程、云服务等。
常用运维工具系列:常用的运维开发工具, zabbix、nagios、docker、k8s、puppet、ansible等
数据库系列:详细总结了常用数据库 mysql、Redis、MongoDB、oracle 技术点,以及工作中遇到的 mysql 问题等
懒人运维系列:总结好用的命令,解放双手不香吗?能用一个命令完成绝不用两个操作
数据结构与算法系列:总结数据结构和算法,不同类型针对性训练,提升编程思维,剑指大厂
非常期待和您一起在这个小小的网络世界里共同探索、学习和成长。💝💝💝 ✨✨ 欢迎订阅本专栏 ✨✨

搭建ELK日志采集与分析系统

一套好的日志分析系统可以详细记录系统的运行情况,方便我们定位分析系统性能瓶颈、查找定位系统问题。上一篇说明了日志的多种业务场景以及日志记录的实现方式,那么日志记录下来,相关人员就需要对日志数据进行处理与分析,基于E(ElasticSearch)L(Logstash)K(Kibana)组合的日志分析系统可以说是目前各家公司普遍的首选方案。

  • Elasticsearch: 分布式、RESTful 风格的搜索和数据分析引擎,可快速存储、搜索、分析海量的数据。在ELK中用于存储所有日志数据。
  • Logstash: 开源的数据采集引擎,具有实时管道传输功能。Logstash 能够将来自单独数据源的数据动态集中到一起,对这些数据加以标准化并传输到您所选的地方。在ELK中用于将采集到的日志数据进行处理、转换然后存储到Elasticsearch。
  • Kibana: 免费且开放的用户界面,能够让您对 Elasticsearch 数据进行可视化,并让您在 Elastic Stack 中进行导航。您可以进行各种操作,从跟踪查询负载,到理解请求如何流经您的整个应用,都能轻松完成。在ELK中用于通过界面展示存储在Elasticsearch中的日志数据。

作为微服务集群,必须要考虑当微服务访问量暴增时的高并发场景,此时系统的日志数据同样是爆发式增长,我们需要通过消息队列做流量削峰处理,Logstash官方提供Redis、Kafka、RabbitMQ等输入插件。Redis虽然可以用作消息队列,但其各项功能显示不如单一实现的消息队列,所以通常情况下并不使用它的消息队列功能;Kafka的性能要优于RabbitMQ,通常在日志采集,数据采集时使用较多,所以这里我们采用Kafka实现消息队列功能。

ELK日志分析系统中,数据传输、数据保存、数据展示、流量削峰功能都有了,还少一个组件,就是日志数据的采集,虽然log4j2可以将日志数据发送到Kafka,甚至可以将日志直接输入到Logstash,但是基于系统设计解耦的考虑,业务系统运行不会影响到日志分析系统,同时日志分析系统也不会影响到业务系统,所以,业务只需将日志记录下来,然后由日志分析系统去采集分析即可,Filebeat是ELK日志系统中常用的日志采集器,它是 Elastic Stack 的一部分,因此能够与 Logstash、Elasticsearch 和 Kibana 无缝协作。

  • Kafka: 高吞吐量的分布式发布订阅消息队列,主要应用于大数据的实时处理。
  • Filebeat: 轻量型日志采集器。在 Kubernetes、Docker 或云端部署中部署 Filebeat,即可获得所有的日志流:信息十分完整,包括日志流的 pod、容器、节点、VM、主机以及自动关联时用到的其他元数据。此外,Beats Autodiscover 功能可检测到新容器,并使用恰当的 Filebeat 模块对这些容器进行自适应监测。

软件下载:

因经常遇到在内网搭建环境的问题,所以这里习惯使用下载软件包的方式进行安装,虽没有使用Yum、Docker等安装方便,但是可以对软件目录、配置信息等有更深的了解,在后续采用Yum、Docker等方式安装时,也能清楚安装了哪些东西,安装配置的文件是怎样的,即使出现问题,也可以快速的定位解决。

Elastic Stack全家桶下载主页: https://www.elastic.co/cn/downloads/

我们选择如下版本:

  • Elasticsearch8.0.0,下载地址:https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-8.0.0-linux-x86_64.tar.gz
  • Logstash8.0.0,下载地址:https://artifacts.elastic.co/downloads/logstash/logstash-8.0.0-linux-x86_64.tar.gz
  • Kibana8.0.0,下载地址:https://artifacts.elastic.co/downloads/kibana/kibana-8.0.0-linux-x86_64.tar.gz
  • Filebeat8.0.0,下载地址:https://artifacts.elastic.co/downloads/beats/filebeat/filebeat-8.0.0-linux-x86_64.tar.gz

Kafka下载:

  • Kafka3.1.0,下载地址:https://dlcdn.apache.org/kafka/3.1.0/kafka_2.13-3.1.0.tgz

安装配置:

安装前先准备好三台CentOS7服务器用于集群安装,这是IP地址为:172.16.20.220、172.16.20.221、172.16.20.222,然后将上面下载的软件包上传至三台服务器的/usr/local目录。因服务器资源有限,这里所有的软件都安装在这三台集群服务器上,在实际生产环境中,请根据业务需求设计规划进行安装。

在集群搭建时,如果能够编写shell安装脚本就会很方便,如果不能编写,就需要在每台服务器上执行安装命令,多数ssh客户端提供了多会话同时输入的功能,这里一些通用安装命令可以选择启用该功能。

一、安装Elasticsearch集群

1、Elasticsearch是使用Java语言开发的,所以需要在环境上安装jdk并配置环境变量。

  • 下载jdk软件包安装,https://www.oracle.com/java/technologies/downloads/#java8

新建/usr/local/java目录

mkdir /usr/local/java

将下载的jdk软件包jdk-8u64-linux-x64.tar.gz上传到/usr/local/java目录,然后解压

tar -zxvf jdk-8u77-linux-x64.tar.gz

配置环境变量/etc/profile

vi /etc/profile

在底部添加以下内容

JAVA_HOME=/usr/local/java/jdk1.8.0_64
PATH=$JAVA_HOME/bin:$PATH
CLASSPATH=$JAVA_HOME/jre/lib/ext:$JAVA_HOME/lib/tools.jar
export PATH JAVA_HOME CLASSPATH

使环境变量生效

source /etc/profile
  • 另外一种十分快捷的方式,如果不是内网环境,可以直接使用命令行安装,这里安装的是免费版本的openjdk
yum install java-1.8.0-openjdk* -y

2、安装配置Elasticsearch

  • 进入/usr/local目录,解压Elasticsearch安装包,请确保执行命令前已将环境准备时的Elasticsearch安装包上传至该目录。
tar -zxvf elasticsearch-8.0.0-linux-x86_64.tar.gz
  • 重命名文件夹
mv elasticsearch-8.0.0 elasticsearch
  • elasticsearch不能使用root用户运行,这里创建运行elasticsearch的用户组和用户
# 创建用户组
groupadd elasticsearch
# 创建用户并添加至用户组
useradd elasticsearch -g elasticsearch
# 更改elasticsearch密码,设置一个自己需要的密码,这里设置为和用户名一样:El12345678
passwd elasticsearch
  • 新建elasticsearch数据和日志存放目录,并给elasticsearch用户赋权限
mkdir -p /data/elasticsearch/data
mkdir -p /data/elasticsearch/log
chown -R elasticsearch:elasticsearch /data/elasticsearch/*
chown -R elasticsearch:elasticsearch /usr/local/elasticsearch/*
  • elasticsearch默认启用了x-pack,集群通信需要进行安全认证,所以这里需要用到SSL证书。注意:这里生成证书的命令只在一台服务器上执行,执行之后copy到另外两台服务器的相同目录下。
# 提示输入密码时,直接回车
./elasticsearch-certutil ca -out /usr/local/elasticsearch/config/elastic-stack-ca.p12# 提示输入密码时,直接回车
./elasticsearch-certutil cert --ca /usr/local/elasticsearch/config/elastic-stack-ca.p12 -out /usr/local/elasticsearch/config/elastic-certificates.p12 -pass ""
# 如果使用root用户生成的证书,记得给elasticsearch用户赋权限
chown -R elasticsearch:elasticsearch /usr/local/elasticsearch/config/elastic-certificates.p12
  • 设置密码,这里在出现输入密码时,所有的都是输入的123456
./elasticsearch-setup-passwords interactiveEnter password for [elastic]: 
Reenter password for [elastic]: 
Enter password for [apm_system]: 
Reenter password for [apm_system]: 
Enter password for [kibana_system]: 
Reenter password for [kibana_system]: 
Enter password for [logstash_system]: 
Reenter password for [logstash_system]: 
Enter password for [beats_system]: 
Reenter password for [beats_system]: 
Enter password for [remote_monitoring_user]: 
Reenter password for [remote_monitoring_user]: 
Changed password for user [apm_system]
Changed password for user [kibana_system]
Changed password for user [kibana]
Changed password for user [logstash_system]
Changed password for user [beats_system]
Changed password for user [remote_monitoring_user]
Changed password for user [elastic]
  • 修改elasticsearch配置文件
vi /usr/local/elasticsearch/config/elasticsearch.yml
# 修改配置
# 集群名称
cluster.name: log-elasticsearch
# 节点名称
node.name: node-1
# 数据存放路径
path.data: /data/elasticsearch/data# 日志存放路径
path.logs: /data/elasticsearch/log
# 当前节点IP
network.host: 192.168.60.201# 对外端口
http.port: 9200
# 集群ip
discovery.seed_hosts: ["172.16.20.220", "172.16.20.221", "172.16.20.222"]
# 初始主节点
cluster.initial_master_nodes: ["node-1", "node-2", "node-3"]
# 新增配置
# 集群端口
transport.tcp.port: 9300
transport.tcp.compress: truehttp.cors.enabled: true
http.cors.allow-origin: "*" 
http.cors.allow-methods: OPTIONS, HEAD, GET, POST, PUT, DELETE
http.cors.allow-headers: "X-Requested-With, Content-Type, Content-Length, X-User"xpack.security.enabled: true
xpack.security.transport.ssl.enabled: true
xpack.security.transport.ssl.verification_mode: certificate
xpack.security.transport.ssl.keystore.path: elastic-certificates.p12
xpack.security.transport.ssl.truststore.path: elastic-certificates.p12
  • 配置Elasticsearch的JVM参数
vi /usr/local/elasticsearch/config/jvm.options
-Xms1g
-Xmx1g
  • 修改Linux默认资源限制数
vi /etc/security/limits.conf
# 在最后加入,修改完成后,重启系统生效。
*                soft    nofile          131072
*                hard   nofile          131072
vi /etc/sysctl.conf
# 将值vm.max_map_count值修改为655360
vm.max_map_count=655360
# 使配置生效
sysctl -p
  • 切换用户启动服务
su elasticsearch
cd /usr/local/elasticsearch/bin
# 控制台启动命令,可以看到具体报错信息
./elasticsearch
  • 访问我们的服务器地址和端口,可以看到,服务已启动: http://172.16.20.220:9200/ http://172.16.20.221:9200/ http://172.16.20.222:9200/

elasticsearch服务已启动

  • 正常运行没有问题后,Ctrl+c关闭服务,然后使用后台启动命令
./elasticsearch -d

备注:后续可通过此命令停止elasticsearch运行

# 查看进程id
ps -ef | grep elastic
# 关闭进程
kill -9 1376(进程id)

3、安装ElasticSearch界面管理插件elasticsearch-head,只需要在一台服务器上安装即可,这里我们安装到172.16.20.220服务器上

  • 配置nodejs环境 下载地址: (https://nodejs.org/dist/v16.14.0/node-v16.14.0-linux-x64.tar.xz)[https://nodejs.org/dist/v16.14.0/node-v16.14.0-linux-x64.tar.xz],将node-v16.14.0-linux-x64.tar.xz上传到服务器172.16.20.220的/usr/local目录
# 解压
tar -xvJf node-v16.14.0-linux-x64.tar.xz
# 重命名
mv node-v16.14.0-linux-x64 nodejs
# 配置环境变量
vi /etc/profile
# 新增以下内容
export NODE_HOME=/usr/local/nodejs
PATH=$JAVA_HOME/bin:$NODE_HOME/bin:/usr/local/mysql/bin:/usr/local/subversion/bin:$PATH
export PATH JAVA_HOME NODE_HOME JENKINS_HOME CLASSPATH
# 使配置生效
source /etc/profile
# 测试是否配置成功
node -v
  • 配置elasticsearch-head 项目开源地址:https://github.com/mobz/elasticsearch-head zip包下载地址:https://github.com/mobz/elasticsearch-head/archive/master.zip 下载后上传至172.16.20.220的/usr/local目录,然后进行解压安装
# 解压
unzip elasticsearch-head-master.zip
# 重命名
mv elasticsearch-head-master elasticsearch-head
# 进入到elasticsearch-head目录
cd elasticsearch-head
#切换软件源,可以提升安装速度
npm config set registry https://registry.npm.taobao.org
# 执行安装命令
npm install -g npm@8.5.1
npm install phantomjs-prebuilt@2.1.16 --ignore-scripts
npm install
# 启动命令
npm run start
  • 浏览器访问http://172.16.20.220:9100/?auth_user=elastic&auth_password=123456 ,需要加上我们上面设置的用户名密码,就可以看到我们的Elasticsearch集群状态了。

elasticsearch集群状态

二、安装Kafka集群

  • 环境准备:
    新建kafka的日志目录和zookeeper数据目录,因为这两项默认放在tmp目录,而tmp目录中内容会随重启而丢失,所以我们自定义以下目录:
mkdir /data/zookeepermkdir /data/zookeeper/datamkdir /data/zookeeper/logsmkdir /data/kafkamkdir /data/kafka/datamkdir /data/kafka/logs
  • zookeeper.properties配置
vi /usr/local/kafka/config/zookeeper.properties

修改如下:

# 修改为自定义的zookeeper数据目录
dataDir=/data/zookeeper/data# 修改为自定义的zookeeper日志目录
dataLogDir=/data/zookeeper/logs# 端口
clientPort=2181# 注释掉
#maxClientCnxns=0# 设置连接参数,添加如下配置
# 为zk的基本时间单元,毫秒
tickTime=2000
# Leader-Follower初始通信时限 tickTime*10
initLimit=10
# Leader-Follower同步通信时限 tickTime*5
syncLimit=5# 设置broker Id的服务地址,本机ip一定要用0.0.0.0代替
server.1=0.0.0.0:2888:3888
server.2=172.16.20.221:2888:3888
server.3=172.16.20.222:2888:3888
  • 在各台服务器的zookeeper数据目录/data/zookeeper/data添加myid文件,写入服务broker.id属性值
    在data文件夹中新建myid文件,myid文件的内容为1(一句话创建:echo 1 > myid)
cd /data/zookeeper/datavi myid#添加内容:1 其他两台主机分别配置 2和3
1
  • kafka配置,进入config目录下,修改server.properties文件
vi /usr/local/kafka/config/server.properties
# 每台服务器的broker.id都不能相同
broker.id=1
# 是否可以删除topic
delete.topic.enable=true
# topic 在当前broker上的分片个数,与broker保持一致
num.partitions=3
# 每个主机地址不一样:
listeners=PLAINTEXT://172.16.20.220:9092
advertised.listeners=PLAINTEXT://172.16.20.220:9092
# 具体一些参数
log.dirs=/data/kafka/kafka-logs
# 设置zookeeper集群地址与端口如下:
zookeeper.connect=172.16.20.220:2181,172.16.20.221:2181,172.16.20.222:2181
  • Kafka启动
    kafka启动时先启动zookeeper,再启动kafka;关闭时相反,先关闭kafka,再关闭zookeeper。 1、zookeeper启动命令
./zookeeper-server-start.sh ../config/zookeeper.properties &

后台运行启动命令:

nohup ./zookeeper-server-start.sh ../config/zookeeper.properties >/data/zookeeper/logs/zookeeper.log 2>1 &

或者

./zookeeper-server-start.sh -daemon ../config/zookeeper.properties &

查看集群状态:

./zookeeper-server-start.sh status ../config/zookeeper.properties

2、kafka启动命令

./kafka-server-start.sh ../config/server.properties &

后台运行启动命令:

nohup bin/kafka-server-start.sh ../config/server.properties >/data/kafka/logs/kafka.log 2>1 &

或者

./kafka-server-start.sh -daemon ../config/server.properties &

3、创建topic,最新版本已经不需要使用zookeeper参数创建。

./kafka-topics.sh --create --replication-factor 2 --partitions 1 --topic test --bootstrap-server 172.16.20.220:9092

参数解释: 复制两份   --replication-factor 2 创建1个分区   --partitions 1 topic 名称   --topic test

4、查看已经存在的topic(三台设备都执行时可以看到)

./kafka-topics.sh --list --bootstrap-server 172.16.20.220:9092

5、启动生产者:

./kafka-console-producer.sh --broker-list 172.16.20.220:9092 --topic test

6、启动消费者:

./kafka-console-consumer.sh --bootstrap-server 172.16.20.221:9092 --topic test
./kafka-console-consumer.sh --bootstrap-server 172.16.20.222:9092 --topic test

添加参数 --from-beginning 从开始位置消费,不是从最新消息

./kafka-console-consumer.sh --bootstrap-server 172.16.20.221 --topic test --from-beginning

7、测试:在生产者输入test,可以在消费者的两台服务器上看到同样的字符test,说明Kafka服务器集群已搭建成功。

三、安装配置Logstash

Logstash没有提供集群安装方式,相互之间并没有交互,但是我们可以配置同属一个Kafka消费者组,来实现统一消息只消费一次的功能。 - 解压安装包

tar -zxvf logstash-8.0.0-linux-x86_64.tar.gz
mv logstash-8.0.0 logstash
  • 配置kafka主题和组
cd logstash
# 新建配置文件
vi logstash-kafka.conf
# 新增以下内容
input {kafka {codec => "json"group_id => "logstash"client_id => "logstash-api"topics_pattern => "api_log"type => "api"bootstrap_servers => "172.16.20.220:9092,172.16.20.221:9092,172.16.20.222:9092"auto_offset_reset => "latest"}kafka {codec => "json"group_id => "logstash"client_id => "logstash-operation"topics_pattern => "operation_log"type => "operation"bootstrap_servers => "172.16.20.220:9092,172.16.20.221:9092,172.16.20.222:9092"auto_offset_reset => "latest"}kafka {codec => "json"group_id => "logstash"client_id => "logstash-debugger"topics_pattern => "debugger_log"type => "debugger"bootstrap_servers => "172.16.20.220:9092,172.16.20.221:9092,172.16.20.222:9092"auto_offset_reset => "latest"}kafka {codec => "json"group_id => "logstash"client_id => "logstash-nginx"topics_pattern => "nginx_log"type => "nginx"bootstrap_servers => "172.16.20.220:9092,172.16.20.221:9092,172.16.20.222:9092"auto_offset_reset => "latest"}
}
output {if [type] == "api"{elasticsearch {hosts => ["172.16.20.220:9200","172.16.20.221:9200","172.16.20.222:9200"]index => "logstash_api-%{+YYYY.MM.dd}"user => "elastic"password => "123456"}}if [type] == "operation"{elasticsearch {hosts => ["172.16.20.220:9200","172.16.20.221:9200","172.16.20.222:9200"]index => "logstash_operation-%{+YYYY.MM.dd}"user => "elastic"password => "123456"}}if [type] == "debugger"{elasticsearch {hosts => ["172.16.20.220:9200","172.16.20.221:9200","172.16.20.222:9200"]index => "logstash_operation-%{+YYYY.MM.dd}"user => "elastic"password => "123456"}}if [type] == "nginx"{elasticsearch {hosts => ["172.16.20.220:9200","172.16.20.221:9200","172.16.20.222:9200"]index => "logstash_operation-%{+YYYY.MM.dd}"user => "elastic"password => "123456"}}
}
  • 启动logstash
# 切换到bin目录
cd /usr/local/logstash/bin
# 启动命令
nohup ./logstash -f ../config/logstash-kafka.conf &
#查看启动日志
tail -f nohup.out

四、安装配置Kibana

  • 解压安装文件
tar -zxvf kibana-8.0.0-linux-x86_64.tar.gzmv kibana-8.0.0 kibana
  • 修改配置文件
cd /usr/local/kibana/config
vi kibana.yml
# 修改以下内容
server.port: 5601
server.host: "172.16.20.220"
elasticsearch.hosts: ["http://172.16.20.220:9200","http://172.16.20.221:9200","http://172.16.20.222:9200"]
elasticsearch.username: "kibana_system"
elasticsearch.password: "123456"
  • 启动服务
cd /usr/local/kibana/bin
# 默认不允许使用root运行,可以添加 --allow-root 参数使用root用户运行,也可以跟Elasticsearch一样新增一个用户组用户
nohup ./kibana --allow-root &
  • 访问http://172.16.20.220:5601/,并使用elastic / 123456登录。

登录页

首页

五、安装Filebeat

Filebeat用于安装在业务软件运行服务器,收集业务产生的日志,并推送到我们配置的Kafka、Redis、RabbitMQ等消息中间件,或者直接保存到Elasticsearch,下面来讲解如何安装配置:

1、进入到/usr/local目录,执行解压命令

tar -zxvf filebeat-8.0.0-linux-x86_64.tar.gzmv filebeat-8.0.0-linux-x86_64 filebeat

2、编辑配置filebeat.yml 配置文件中默认是输出到elasticsearch,这里我们改为kafka,同文件目录下的filebeat.reference.yml文件是所有配置的实例,可以直接将kafka的配置复制到filebeat.yml

  • 配置采集开关和采集路径:
# filestream is an input for collecting log messages from files.
- type: filestream# Change to true to enable this input configuration.# enable改为trueenabled: true# Paths that should be crawled and fetched. Glob based paths.# 修改微服务日志的实际路径paths:- /data/gitegg/log/gitegg-service-system/*.log- /data/gitegg/log/gitegg-service-base/*.log- /data/gitegg/log/gitegg-service-oauth/*.log- /data/gitegg/log/gitegg-service-gateway/*.log- /data/gitegg/log/gitegg-service-extension/*.log- /data/gitegg/log/gitegg-service-bigdata/*.log#- c:\programdata\elasticsearch\logs\*# Exclude lines. A list of regular expressions to match. It drops the lines that are# matching any regular expression from the list.#exclude_lines: ['^DBG']# Include lines. A list of regular expressions to match. It exports the lines that are# matching any regular expression from the list.#include_lines: ['^ERR', '^WARN']# Exclude files. A list of regular expressions to match. Filebeat drops the files that# are matching any regular expression from the list. By default, no files are dropped.#prospector.scanner.exclude_files: ['.gz$']# Optional additional fields. These fields can be freely picked# to add additional information to the crawled log files for filtering#fields:#  level: debug#  review: 1
  • Elasticsearch 模板配置
# ======================= Elasticsearch template setting =======================setup.template.settings:index.number_of_shards: 3index.number_of_replicas: 1#index.codec: best_compression#_source.enabled: false# 允许自动生成index模板
setup.template.enabled: true
# # 生成index模板时字段配置文件
setup.template.fields: fields.yml
# # 如果存在模块则覆盖
setup.template.overwrite: true
# # 生成index模板的名称
setup.template.name: "api_log" 
# # 生成index模板匹配的index格式 
setup.template.pattern: "api-*" 
#索引生命周期管理ilm功能默认开启,开启的情况下索引名称只能为filebeat-*, 通过setup.ilm.enabled: false进行关闭;
setup.ilm.pattern: "{now/d}"
setup.ilm.enabled: false
  • 开启仪表盘并配置使用Kibana仪表盘:
# ================================= Dashboards =================================
# These settings control loading the sample dashboards to the Kibana index. Loading
# the dashboards is disabled by default and can be enabled either by setting the
# options here or by using the `setup` command.
setup.dashboards.enabled: true# The URL from where to download the dashboards archive. By default this URL
# has a value which is computed based on the Beat name and version. For released
# versions, this URL points to the dashboard archive on the artifacts.elastic.co
# website.
#setup.dashboards.url:
# =================================== Kibana ===================================# Starting with Beats version 6.0.0, the dashboards are loaded via the Kibana API.
# This requires a Kibana endpoint configuration.
setup.kibana:# Kibana Host# Scheme and port can be left out and will be set to the default (http and 5601)# In case you specify and additional path, the scheme is required: http://localhost:5601/path# IPv6 addresses should always be defined as: https://[2001:db8::1]:5601host: "172.16.20.220:5601"# Kibana Space ID# ID of the Kibana Space into which the dashboards should be loaded. By default,# the Default Space will be used.#space.id:
  • 配置输出到Kafka,完整的filebeat.yml如下
###################### Filebeat Configuration Example ########################## This file is an example configuration file highlighting only the most common
# options. The filebeat.reference.yml file from the same directory contains all the
# supported options with more comments. You can use it as a reference.
#
# You can find the full configuration reference here:
# https://www.elastic.co/guide/en/beats/filebeat/index.html# For more available modules and options, please see the filebeat.reference.yml sample
# configuration file.# ============================== Filebeat inputs ===============================filebeat.inputs:# Each - is an input. Most options can be set at the input level, so
# you can use different inputs for various configurations.
# Below are the input specific configurations.# filestream is an input for collecting log messages from files.
- type: filestream# Change to true to enable this input configuration.enabled: true# Paths that should be crawled and fetched. Glob based paths.paths:- /data/gitegg/log/*/*operation.log#- c:\programdata\elasticsearch\logs\*# Exclude lines. A list of regular expressions to match. It drops the lines that are# matching any regular expression from the list.#exclude_lines: ['^DBG']# Include lines. A list of regular expressions to match. It exports the lines that are# matching any regular expression from the list.#include_lines: ['^ERR', '^WARN']# Exclude files. A list of regular expressions to match. Filebeat drops the files that# are matching any regular expression from the list. By default, no files are dropped.#prospector.scanner.exclude_files: ['.gz$']# Optional additional fields. These fields can be freely picked# to add additional information to the crawled log files for filteringfields:topic: operation_log#  level: debug#  review: 1
# filestream is an input for collecting log messages from files.
- type: filestream# Change to true to enable this input configuration.enabled: true# Paths that should be crawled and fetched. Glob based paths.paths:- /data/gitegg/log/*/*api.log#- c:\programdata\elasticsearch\logs\*# Exclude lines. A list of regular expressions to match. It drops the lines that are# matching any regular expression from the list.#exclude_lines: ['^DBG']# Include lines. A list of regular expressions to match. It exports the lines that are# matching any regular expression from the list.#include_lines: ['^ERR', '^WARN']# Exclude files. A list of regular expressions to match. Filebeat drops the files that# are matching any regular expression from the list. By default, no files are dropped.#prospector.scanner.exclude_files: ['.gz$']# Optional additional fields. These fields can be freely picked# to add additional information to the crawled log files for filteringfields:topic: api_log#  level: debug#  review: 1
# filestream is an input for collecting log messages from files.
- type: filestream# Change to true to enable this input configuration.enabled: true# Paths that should be crawled and fetched. Glob based paths.paths:- /data/gitegg/log/*/*debug.log#- c:\programdata\elasticsearch\logs\*# Exclude lines. A list of regular expressions to match. It drops the lines that are# matching any regular expression from the list.#exclude_lines: ['^DBG']# Include lines. A list of regular expressions to match. It exports the lines that are# matching any regular expression from the list.#include_lines: ['^ERR', '^WARN']# Exclude files. A list of regular expressions to match. Filebeat drops the files that# are matching any regular expression from the list. By default, no files are dropped.#prospector.scanner.exclude_files: ['.gz$']# Optional additional fields. These fields can be freely picked# to add additional information to the crawled log files for filteringfields:topic: debugger_log#  level: debug#  review: 1
# filestream is an input for collecting log messages from files.
- type: filestream# Change to true to enable this input configuration.enabled: true# Paths that should be crawled and fetched. Glob based paths.paths:- /usr/local/nginx/logs/access.log#- c:\programdata\elasticsearch\logs\*# Exclude lines. A list of regular expressions to match. It drops the lines that are# matching any regular expression from the list.#exclude_lines: ['^DBG']# Include lines. A list of regular expressions to match. It exports the lines that are# matching any regular expression from the list.#include_lines: ['^ERR', '^WARN']# Exclude files. A list of regular expressions to match. Filebeat drops the files that# are matching any regular expression from the list. By default, no files are dropped.#prospector.scanner.exclude_files: ['.gz$']# Optional additional fields. These fields can be freely picked# to add additional information to the crawled log files for filteringfields:topic: nginx_log#  level: debug#  review: 1# ============================== Filebeat modules ==============================filebeat.config.modules:# Glob pattern for configuration loadingpath: ${path.config}/modules.d/*.yml# Set to true to enable config reloadingreload.enabled: false# Period on which files under path should be checked for changes#reload.period: 10s# ======================= Elasticsearch template setting =======================setup.template.settings:index.number_of_shards: 3index.number_of_replicas: 1#index.codec: best_compression#_source.enabled: false# 允许自动生成index模板
setup.template.enabled: true
# # 生成index模板时字段配置文件
setup.template.fields: fields.yml
# # 如果存在模块则覆盖
setup.template.overwrite: true
# # 生成index模板的名称
setup.template.name: "gitegg_log" 
# # 生成index模板匹配的index格式 
setup.template.pattern: "filebeat-*" 
#索引生命周期管理ilm功能默认开启,开启的情况下索引名称只能为filebeat-*, 通过setup.ilm.enabled: false进行关闭;
setup.ilm.pattern: "{now/d}"
setup.ilm.enabled: false# ================================== General ===================================# The name of the shipper that publishes the network data. It can be used to group
# all the transactions sent by a single shipper in the web interface.
#name:# The tags of the shipper are included in their own field with each
# transaction published.
#tags: ["service-X", "web-tier"]# Optional fields that you can specify to add additional information to the
# output.
#fields:
#  env: staging # ================================= Dashboards =================================
# These settings control loading the sample dashboards to the Kibana index. Loading
# the dashboards is disabled by default and can be enabled either by setting the
# options here or by using the `setup` command.
setup.dashboards.enabled: true# The URL from where to download the dashboards archive. By default this URL
# has a value which is computed based on the Beat name and version. For released
# versions, this URL points to the dashboard archive on the artifacts.elastic.co
# website.
#setup.dashboards.url:# =================================== Kibana ===================================# Starting with Beats version 6.0.0, the dashboards are loaded via the Kibana API.
# This requires a Kibana endpoint configuration.
setup.kibana:# Kibana Host# Scheme and port can be left out and will be set to the default (http and 5601)# In case you specify and additional path, the scheme is required: http://localhost:5601/path# IPv6 addresses should always be defined as: https://[2001:db8::1]:5601host: "172.16.20.220:5601"# Optional protocol and basic auth credentials.#protocol: "https"username: "elastic"password: "123456"# Optional HTTP path#path: ""# Optional Kibana space ID.#space.id: ""# Custom HTTP headers to add to each request#headers:#  X-My-Header: Contents of the header# Use SSL settings for HTTPS.#ssl.enabled: true# =============================== Elastic Cloud ================================# These settings simplify using Filebeat with the Elastic Cloud (https://cloud.elastic.co/).# The cloud.id setting overwrites the `output.elasticsearch.hosts` and
# `setup.kibana.host` options.
# You can find the `cloud.id` in the Elastic Cloud web UI.
#cloud.id:# The cloud.auth setting overwrites the `output.elasticsearch.username` and
# `output.elasticsearch.password` settings. The format is `<user>:<pass>`.
#cloud.auth:# ================================== Outputs ===================================# Configure what output to use when sending the data collected by the beat.# ---------------------------- Elasticsearch Output ----------------------------
#output.elasticsearch:# Array of hosts to connect to.hosts: ["localhost:9200"]# Protocol - either `http` (default) or `https`.#protocol: "https"# Authentication credentials - either API key or username/password.#api_key: "id:api_key"#username: "elastic"#password: "changeme"# ------------------------------ Logstash Output -------------------------------
#output.logstash:# The Logstash hosts#hosts: ["localhost:5044"]# Optional SSL. By default is off.# List of root certificates for HTTPS server verifications#ssl.certificate_authorities: ["/etc/pki/root/ca.pem"]# Certificate for SSL client authentication#ssl.certificate: "/etc/pki/client/cert.pem"# Client Certificate Key#ssl.key: "/etc/pki/client/cert.key"
# -------------------------------- Kafka Output --------------------------------
output.kafka:# Boolean flag to enable or disable the output module.enabled: true# The list of Kafka broker addresses from which to fetch the cluster metadata.# The cluster metadata contain the actual Kafka brokers events are published# to.hosts: ["172.16.20.220:9092","172.16.20.221:9092","172.16.20.222:9092"]# The Kafka topic used for produced events. The setting can be a format string# using any event field. To set the topic from document type use `%{[type]}`.topic: '%{[fields.topic]}'# The Kafka event key setting. Use format string to create a unique event key.# By default no event key will be generated.#key: ''# The Kafka event partitioning strategy. Default hashing strategy is `hash`# using the `output.kafka.key` setting or randomly distributes events if# `output.kafka.key` is not configured.partition.hash:# If enabled, events will only be published to partitions with reachable# leaders. Default is false.reachable_only: true# Configure alternative event field names used to compute the hash value.# If empty `output.kafka.key` setting will be used.# Default value is empty list.#hash: []# Authentication details. Password is required if username is set.#username: ''#password: ''# SASL authentication mechanism used. Can be one of PLAIN, SCRAM-SHA-256 or SCRAM-SHA-512.# Defaults to PLAIN when `username` and `password` are configured.#sasl.mechanism: ''# Kafka version Filebeat is assumed to run against. Defaults to the "1.0.0".#version: '1.0.0'# Configure JSON encoding#codec.json:# Pretty-print JSON event#pretty: false# Configure escaping HTML symbols in strings.#escape_html: false# Metadata update configuration. Metadata contains leader information# used to decide which broker to use when publishing.#metadata:# Max metadata request retry attempts when cluster is in middle of leader# election. Defaults to 3 retries.#retry.max: 3# Wait time between retries during leader elections. Default is 250ms.#retry.backoff: 250ms# Refresh metadata interval. Defaults to every 10 minutes.#refresh_frequency: 10m# Strategy for fetching the topics metadata from the broker. Default is false.#full: false# The number of concurrent load-balanced Kafka output workers.#worker: 1# The number of times to retry publishing an event after a publishing failure.# After the specified number of retries, events are typically dropped.# Some Beats, such as Filebeat, ignore the max_retries setting and retry until# all events are published.  Set max_retries to a value less than 0 to retry# until all events are published. The default is 3.#max_retries: 3# The number of seconds to wait before trying to republish to Kafka# after a network error. After waiting backoff.init seconds, the Beat# tries to republish. If the attempt fails, the backoff timer is increased# exponentially up to backoff.max. After a successful publish, the backoff# timer is reset. The default is 1s.#backoff.init: 1s# The maximum number of seconds to wait before attempting to republish to# Kafka after a network error. The default is 60s.#backoff.max: 60s# The maximum number of events to bulk in a single Kafka request. The default# is 2048.#bulk_max_size: 2048# Duration to wait before sending bulk Kafka request. 0 is no delay. The default# is 0.#bulk_flush_frequency: 0s# The number of seconds to wait for responses from the Kafka brokers before# timing out. The default is 30s.#timeout: 30s# The maximum duration a broker will wait for number of required ACKs. The# default is 10s.#broker_timeout: 10s# The number of messages buffered for each Kafka broker. The default is 256.#channel_buffer_size: 256# The keep-alive period for an active network connection. If 0s, keep-alives# are disabled. The default is 0 seconds.#keep_alive: 0# Sets the output compression codec. Must be one of none, snappy and gzip. The# default is gzip.compression: gzip# Set the compression level. Currently only gzip provides a compression level# between 0 and 9. The default value is chosen by the compression algorithm.#compression_level: 4# The maximum permitted size of JSON-encoded messages. Bigger messages will be# dropped. The default value is 1000000 (bytes). This value should be equal to# or less than the broker's message.max.bytes.max_message_bytes: 1000000# The ACK reliability level required from broker. 0=no response, 1=wait for# local commit, -1=wait for all replicas to commit. The default is 1.  Note:# If set to 0, no ACKs are returned by Kafka. Messages might be lost silently# on error.required_acks: 1# The configurable ClientID used for logging, debugging, and auditing# purposes.  The default is "beats".#client_id: beats# Use SSL settings for HTTPS.#ssl.enabled: true# Controls the verification of certificates. Valid values are:# * full, which verifies that the provided certificate is signed by a trusted# authority (CA) and also verifies that the server's hostname (or IP address)# matches the names identified within the certificate.# * strict, which verifies that the provided certificate is signed by a trusted# authority (CA) and also verifies that the server's hostname (or IP address)# matches the names identified within the certificate. If the Subject Alternative# Name is empty, it returns an error.# * certificate, which verifies that the provided certificate is signed by a# trusted authority (CA), but does not perform any hostname verification.#  * none, which performs no verification of the server's certificate. This# mode disables many of the security benefits of SSL/TLS and should only be used# after very careful consideration. It is primarily intended as a temporary# diagnostic mechanism when attempting to resolve TLS errors; its use in# production environments is strongly discouraged.# The default value is full.#ssl.verification_mode: full# List of supported/valid TLS versions. By default all TLS versions from 1.1# up to 1.3 are enabled.#ssl.supported_protocols: [TLSv1.1, TLSv1.2, TLSv1.3]# List of root certificates for HTTPS server verifications#ssl.certificate_authorities: ["/etc/pki/root/ca.pem"]# Certificate for SSL client authentication#ssl.certificate: "/etc/pki/client/cert.pem"# Client certificate key#ssl.key: "/etc/pki/client/cert.key"# Optional passphrase for decrypting the certificate key.#ssl.key_passphrase: ''# Configure cipher suites to be used for SSL connections#ssl.cipher_suites: []# Configure curve types for ECDHE-based cipher suites#ssl.curve_types: []# Configure what types of renegotiation are supported. Valid options are# never, once, and freely. Default is never.#ssl.renegotiation: never# Configure a pin that can be used to do extra validation of the verified certificate chain,# this allow you to ensure that a specific certificate is used to validate the chain of trust.## The pin is a base64 encoded string of the SHA-256 fingerprint.#ssl.ca_sha256: ""# A root CA HEX encoded fingerprint. During the SSL handshake if the# fingerprint matches the root CA certificate, it will be added to# the provided list of root CAs (`certificate_authorities`), if the# list is empty or not defined, the matching certificate will be the# only one in the list. Then the normal SSL validation happens.#ssl.ca_trusted_fingerprint: ""# Enable Kerberos support. Kerberos is automatically enabled if any Kerberos setting is set.#kerberos.enabled: true# Authentication type to use with Kerberos. Available options: keytab, password.#kerberos.auth_type: password# Path to the keytab file. It is used when auth_type is set to keytab.#kerberos.keytab: /etc/security/keytabs/kafka.keytab# Path to the Kerberos configuration.#kerberos.config_path: /etc/krb5.conf# The service name. Service principal name is contructed from# service_name/hostname@realm.#kerberos.service_name: kafka# Name of the Kerberos user.#kerberos.username: elastic# Password of the Kerberos user. It is used when auth_type is set to password.#kerberos.password: changeme# Kerberos realm.#kerberos.realm: ELASTIC# Enables Kerberos FAST authentication. This may# conflict with certain Active Directory configurations.#kerberos.enable_krb5_fast: false
# ================================= Processors =================================
processors:- add_host_metadata:when.not.contains.tags: forwarded- add_cloud_metadata: ~- add_docker_metadata: ~- add_kubernetes_metadata: ~# ================================== Logging ===================================# Sets log level. The default log level is info.
# Available log levels are: error, warning, info, debug
#logging.level: debug# At debug level, you can selectively enable logging only for some components.
# To enable all selectors use ["*"]. Examples of other selectors are "beat",
# "publisher", "service".
#logging.selectors: ["*"]# ============================= X-Pack Monitoring ==============================
# Filebeat can export internal metrics to a central Elasticsearch monitoring
# cluster.  This requires xpack monitoring to be enabled in Elasticsearch.  The
# reporting is disabled by default.# Set to true to enable the monitoring reporter.
#monitoring.enabled: false# Sets the UUID of the Elasticsearch cluster under which monitoring data for this
# Filebeat instance will appear in the Stack Monitoring UI. If output.elasticsearch
# is enabled, the UUID is derived from the Elasticsearch cluster referenced by output.elasticsearch.
#monitoring.cluster_uuid:# Uncomment to send the metrics to Elasticsearch. Most settings from the
# Elasticsearch output are accepted here as well.
# Note that the settings should point to your Elasticsearch *monitoring* cluster.
# Any setting that is not set is automatically inherited from the Elasticsearch
# output configuration, so if you have the Elasticsearch output configured such
# that it is pointing to your Elasticsearch monitoring cluster, you can simply
# uncomment the following line.
#monitoring.elasticsearch:# ============================== Instrumentation ===============================# Instrumentation support for the filebeat.
#instrumentation:# Set to true to enable instrumentation of filebeat.#enabled: false# Environment in which filebeat is running on (eg: staging, production, etc.)#environment: ""# APM Server hosts to report instrumentation results to.#hosts:#  - http://localhost:8200# API Key for the APM Server(s).# If api_key is set then secret_token will be ignored.#api_key:# Secret token for the APM Server(s).#secret_token:# ================================= Migration ==================================# This allows to enable 6.7 migration aliases
#migration.6_to_7.enabled: true
  • 执行filebeat启动命令
./filebeat -e -c filebeat.yml

后台启动命令

nohup ./filebeat -e -c filebeat.yml >/dev/null 2>&1 &

停止命令

ps -ef |grep filebeat
kill -9 进程号

六、测试配置是否正确

1、测试filebeat是否能够采集log文件并发送到Kafka

  • 在kafka服务器开启消费者,监听api_log主题和operation_log主题
./kafka-console-consumer.sh --bootstrap-server 172.16.20.221:9092 --topic api_log./kafka-console-consumer.sh --bootstrap-server 172.16.20.222:9092 --topic operation_log
  • 手动写入日志文件,按照filebeat配置的采集目录写入
echo "api log1111" > /data/gitegg/log/gitegg-service-system/api.logecho "operation log1111" > /data/gitegg/log/gitegg-service-system/operation.log
  • 观察消费者是消费到日志推送内容

api_log

operation_log

2、测试logstash是消费Kafka的日志主题,并将日志内容存入Elasticsearch - 手动写入日志文件

echo "api log8888888888888888888888" > /data/gitegg/log/gitegg-service-system/api.log
echo "operation loggggggggggggggggggg" > /data/gitegg/log/gitegg-service-system/operation.log
  • 打开Elasticsearch Head界面
  • http://172.16.20.220:9100/?auth_user=elastic&auth_password=123456

    查询Elasticsearch是否有数据。

自动新增的两个index,规则是logstash中配置的

image.png

数据浏览页可以看到Elasticsearch中存储的日志数据内容,说明我们的配置已经生效。

image.png

七、配置Kibana用于日志统计和展示

  • 依次点击左侧菜单Management -> Kibana -> Data Views -> Create data view , 输入logstash_* ,选择@timestamp,再点击Create data view按钮,完成创建。

image.png

Kibana

image.png

image.png

  • 点击日志分析查询菜单Analytics -> Discover,选择logstash_* 进行日志查询

分析菜单

这篇关于搭建ELK日志采集与分析系统的文章就介绍到这儿,希望我们推荐的文章对编程师们有所帮助!



http://www.chinasem.cn/article/1095549

相关文章

不懂推荐算法也能设计推荐系统

本文以商业化应用推荐为例,告诉我们不懂推荐算法的产品,也能从产品侧出发, 设计出一款不错的推荐系统。 相信很多新手产品,看到算法二字,多是懵圈的。 什么排序算法、最短路径等都是相对传统的算法(注:传统是指科班出身的产品都会接触过)。但对于推荐算法,多数产品对着网上搜到的资源,都会无从下手。特别当某些推荐算法 和 “AI”扯上关系后,更是加大了理解的难度。 但,不了解推荐算法,就无法做推荐系

基于人工智能的图像分类系统

目录 引言项目背景环境准备 硬件要求软件安装与配置系统设计 系统架构关键技术代码示例 数据预处理模型训练模型预测应用场景结论 1. 引言 图像分类是计算机视觉中的一个重要任务,目标是自动识别图像中的对象类别。通过卷积神经网络(CNN)等深度学习技术,我们可以构建高效的图像分类系统,广泛应用于自动驾驶、医疗影像诊断、监控分析等领域。本文将介绍如何构建一个基于人工智能的图像分类系统,包括环境

水位雨量在线监测系统概述及应用介绍

在当今社会,随着科技的飞速发展,各种智能监测系统已成为保障公共安全、促进资源管理和环境保护的重要工具。其中,水位雨量在线监测系统作为自然灾害预警、水资源管理及水利工程运行的关键技术,其重要性不言而喻。 一、水位雨量在线监测系统的基本原理 水位雨量在线监测系统主要由数据采集单元、数据传输网络、数据处理中心及用户终端四大部分构成,形成了一个完整的闭环系统。 数据采集单元:这是系统的“眼睛”,

性能分析之MySQL索引实战案例

文章目录 一、前言二、准备三、MySQL索引优化四、MySQL 索引知识回顾五、总结 一、前言 在上一讲性能工具之 JProfiler 简单登录案例分析实战中已经发现SQL没有建立索引问题,本文将一起从代码层去分析为什么没有建立索引? 开源ERP项目地址:https://gitee.com/jishenghua/JSH_ERP 二、准备 打开IDEA找到登录请求资源路径位置

嵌入式QT开发:构建高效智能的嵌入式系统

摘要: 本文深入探讨了嵌入式 QT 相关的各个方面。从 QT 框架的基础架构和核心概念出发,详细阐述了其在嵌入式环境中的优势与特点。文中分析了嵌入式 QT 的开发环境搭建过程,包括交叉编译工具链的配置等关键步骤。进一步探讨了嵌入式 QT 的界面设计与开发,涵盖了从基本控件的使用到复杂界面布局的构建。同时也深入研究了信号与槽机制在嵌入式系统中的应用,以及嵌入式 QT 与硬件设备的交互,包括输入输出设

JAVA智听未来一站式有声阅读平台听书系统小程序源码

智听未来,一站式有声阅读平台听书系统 🌟&nbsp;开篇:遇见未来,从“智听”开始 在这个快节奏的时代,你是否渴望在忙碌的间隙,找到一片属于自己的宁静角落?是否梦想着能随时随地,沉浸在知识的海洋,或是故事的奇幻世界里?今天,就让我带你一起探索“智听未来”——这一站式有声阅读平台听书系统,它正悄悄改变着我们的阅读方式,让未来触手可及! 📚&nbsp;第一站:海量资源,应有尽有 走进“智听

【区块链 + 人才服务】可信教育区块链治理系统 | FISCO BCOS应用案例

伴随着区块链技术的不断完善,其在教育信息化中的应用也在持续发展。利用区块链数据共识、不可篡改的特性, 将与教育相关的数据要素在区块链上进行存证确权,在确保数据可信的前提下,促进教育的公平、透明、开放,为教育教学质量提升赋能,实现教育数据的安全共享、高等教育体系的智慧治理。 可信教育区块链治理系统的顶层治理架构由教育部、高校、企业、学生等多方角色共同参与建设、维护,支撑教育资源共享、教学质量评估、

搭建Kafka+zookeeper集群调度

前言 硬件环境 172.18.0.5        kafkazk1        Kafka+zookeeper                Kafka Broker集群 172.18.0.6        kafkazk2        Kafka+zookeeper                Kafka Broker集群 172.18.0.7        kafkazk3

软考系统规划与管理师考试证书含金量高吗?

2024年软考系统规划与管理师考试报名时间节点: 报名时间:2024年上半年软考将于3月中旬陆续开始报名 考试时间:上半年5月25日到28日,下半年11月9日到12日 分数线:所有科目成绩均须达到45分以上(包括45分)方可通过考试 成绩查询:可在“中国计算机技术职业资格网”上查询软考成绩 出成绩时间:预计在11月左右 证书领取时间:一般在考试成绩公布后3~4个月,各地领取时间有所不同

【IPV6从入门到起飞】5-1 IPV6+Home Assistant(搭建基本环境)

【IPV6从入门到起飞】5-1 IPV6+Home Assistant #搭建基本环境 1 背景2 docker下载 hass3 创建容器4 浏览器访问 hass5 手机APP远程访问hass6 更多玩法 1 背景 既然电脑可以IPV6入站,手机流量可以访问IPV6网络的服务,为什么不在电脑搭建Home Assistant(hass),来控制你的设备呢?@智能家居 @万物互联