SpringCloud微服务实战——搭建企业级开发框架(三十八):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。
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 interactive
Enter 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: true
http.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/
- 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。
二、安装Kafka集群
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/zookeeper
mkdir /data/zookeeper/data
mkdir /data/zookeeper/logs
mkdir /data/kafka
mkdir /data/kafka/data
mkdir /data/kafka/logs
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/data
vi myid
#添加内容:1 其他两台主机分别配置 2和3
1
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.gz
mv 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。
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.gz
mv 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true
enabled: 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: 3
index.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]:5601
host: "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$']
# Optional additional fields. These fields can be freely picked
# to add additional information to the crawled log files for filtering
fields:
topic: operation_log
# level: debug
# review: 1
# filestream is an input for collecting log messages from files.
- type: filestream
# Change to true to enable this input configuration.
enabled: true
# Paths that should be crawled and fetched. Glob based paths.
paths:
- /data/gitegg/log/*/*api.log
#- c:\programdata\elasticsearch\logs\*
# Exclude lines. A list of regular expressions to match. It drops the lines that are
# matching any regular expression from the list.
#exclude_lines: ['^DBG']
# Include lines. A list of regular expressions to match. It exports the lines that are
# matching any regular expression from the list.
#include_lines: ['^ERR', '^WARN']
# Exclude files. A list of regular expressions to match. Filebeat drops the files that
# are matching any regular expression from the list. By default, no files are dropped.
#prospector.scanner.exclude_files: ['.gz$']
# Optional additional fields. These fields can be freely picked
# to add additional information to the crawled log files for filtering
fields:
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$']
# Optional additional fields. These fields can be freely picked
# to add additional information to the crawled log files for filtering
fields:
topic: debugger_log
# level: debug
# review: 1
# filestream is an input for collecting log messages from files.
- type: filestream
# Change to true to enable this input configuration.
enabled: true
# Paths that should be crawled and fetched. Glob based paths.
paths:
- /usr/local/nginx/logs/access.log
#- c:\programdata\elasticsearch\logs\*
# Exclude lines. A list of regular expressions to match. It drops the lines that are
# matching any regular expression from the list.
#exclude_lines: ['^DBG']
# Include lines. A list of regular expressions to match. It exports the lines that are
# matching any regular expression from the list.
#include_lines: ['^ERR', '^WARN']
# Exclude files. A list of regular expressions to match. Filebeat drops the files that
# are matching any regular expression from the list. By default, no files are dropped.
#prospector.scanner.exclude_files: ['.gz$']
# Optional additional fields. These fields can be freely picked
# to add additional information to the crawled log files for filtering
fields:
topic: nginx_log
# level: debug
# review: 1
# ============================== Filebeat modules ==============================
filebeat.config.modules:
# Glob pattern for configuration loading
path: ${path.config}/modules.d/*.yml
# Set to true to enable config reloading
reload.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: 3
index.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 ===================================
......
# ================================= 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]:5601
host: "172.16.20.220:5601"
# Optional protocol and basic auth credentials.
#protocol: "https"
username: "elastic"
password: "123456"
......
# ================================= 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.log
echo "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
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
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。
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。
点击日志分析查询菜单Analytics -> Discover,选择logstash_* 进行日志查询
GitEgg-Cloud是一款基于SpringCloud整合搭建的企业级微服务应用开发框架,开源项目地址:
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