ELK(Logstash)安装部署应用(图片示例)_2018_lcf

logstash是一个数据采集、加工处理以及传输的工具，目前流行搭配

• logstash 特点:

– 所有类型的数据集中处理
– 不同模式和格式数据的正常化
– 自定义日志格式的迅速扩展
– 为自定义数据源轻松添加插件

https://www.elastic.co/guide/en/logstash/current/input-plugins.html　　／／帮助文档地址

logstash 工作结构

– { 数据源 } ==>input { } ==>filter { } ==>output { } ==>{ ES }

• logstash 数据类型

– 布尔值类型: ssl_enable => true
– 字节类型:bytes => "1MiB"
– 字符串类型: name => "xkops"
– 数值类型: port => 22
– 数组: match => ["datetime","UNIX"]
– 哈希: options => {k => "v",k2 => "v2"}
– 编码解码: codec => "json"
– 路径: file_path => "/tmp/filename"

– 注释: #

• logstash 条件判断

– 等于: ==
– 不等于: !=
– 小于: <
– 大于: >
– 小于等于: <=
– 大于等于: >=
– 匹配正则: =~

– 不匹配正则: !~

– 包含: in
– 不包含: not in
– 且: and
– 否: or
– 非且: nand
– 非或: xor
– 复合表达式: ()

– 取反符合:!()

• logstash 插件(codec类、input类、filter类、output类）

– codec是通用类插件,input(数据来源）、filter(数据过滤）、output（数据输出）

– 对不熟悉的插件，可以网上看帮助文档

logstash-codec-collectd
logstash-codec-dots
logstash-codec-edn
logstash-codec-edn_lines
logstash-codec-es_bulk
logstash-codec-fluent
logstash-codec-graphite
logstash-codec-json
logstash-codec-json_lines
logstash-codec-line
logstash-codec-msgpack
logstash-codec-multiline
logstash-codec-netflow
logstash-codec-oldlogstashjson
logstash-codec-plain

logstash-codec-rubydebug

logstash-filter-anonymize
logstash-filter-checksum
logstash-filter-clone
logstash-filter-csv
logstash-filter-date
logstash-filter-dns
logstash-filter-drop
logstash-filter-fingerprint
logstash-filter-geoip
logstash-filter-grok
logstash-filter-json
logstash-filter-kv
logstash-filter-metrics
logstash-filter-multiline
logstash-filter-mutate
logstash-filter-ruby
logstash-filter-sleep
logstash-filter-split
logstash-filter-syslog_pri
logstash-filter-throttle
logstash-filter-urldecode
logstash-filter-useragent
logstash-filter-uuid

logstash-filter-xml

logstash-input-beats
logstash-input-couchdb_changes
logstash-input-elasticsearch
logstash-input-eventlog
logstash-input-exec
logstash-input-file
logstash-input-ganglia
logstash-input-gelf
logstash-input-generator
logstash-input-graphite
logstash-input-heartbeat
logstash-input-http
logstash-input-http_poller
logstash-input-imap
logstash-input-irc
logstash-input-jdbc
logstash-input-kafka
logstash-input-log4j
logstash-input-lumberjack
logstash-input-pipe
logstash-input-rabbitmq
logstash-input-redis
logstash-input-s3
logstash-input-snmptrap
logstash-input-sqs
logstash-input-stdin
logstash-input-syslog
logstash-input-tcp
logstash-input-twitter
logstash-input-udp
logstash-input-unix
logstash-input-xmpp

logstash-input-zeromq

logstash-output-cloudwatch
logstash-output-cloudwatch
logstash-output-csv
logstash-output-elasticsearch
logstash-output-email
logstash-output-exec
logstash-output-file
logstash-output-ganglia
logstash-output-gelf
logstash-output-graphite
logstash-output-hipchat
logstash-output-http
logstash-output-irc
logstash-output-juggernaut
logstash-output-kafka
logstash-output-lumberjack
logstash-output-nagios
logstash-output-nagios_nsca
logstash-output-null
logstash-output-opentsdb
logstash-output-pagerduty
logstash-output-pipe
logstash-output-rabbitmq
logstash-output-redis
logstash-output-s3
logstash-output-sns
logstash-output-sqs
logstash-output-statsd
logstash-output-stdout
logstash-output-tcp
logstash-output-udp
logstash-output-xmpp
logstash-output-zeromq
logstash-patterns-core // 这个是过滤匹配块

• logstash 安装

– Logstash 依赖 java 环境,需要安装 java-1.8.0-openjdk

– Logstash 没有默认的配置文件,需要手劢配置

– logstash 安装在 /opt/logstash 目录下

[root@logstash ~]# yum -y install logstash-2.3.4-1.noarch.rpm ／／可以网上下载更高的版本

• logstash 的第一个配置文件

[root@logstash ~]# vim /etc/logstash/logstash.conf

input{

　　stdin{}

}

filter{ }

output{

　　stdout{}

}

• 测试

[root@logstash ~]# /opt/logstash/bin/logstash -f /etc/logstash/conf.d/logstash.conf

Settings: Default pipeline workers: 2

Pipeline main started

test

//可以随便输入什么，就会自动输出相同内容

— codec 类插件

input{
    stdin{ codec => "json" }
}
filter{ }
    output{
        stdout{ codec => "rubydebug" }
}
– 我们输入普通数据和 json 对比
– {"a": 11, "c": 13, "b": 12}

—　input file 插件

input {

    file{
        start_position => "beginning"
        sincedb_path => "/var/lib/logstash/sincedb-access"
        path => [“/tmp/alog”, “/tmp/blog”]
        type => 'filelog'

}

– sincedb_path 记录读取文件的位置
– start_position 配置第一次读取文件从什么地方开始

—　 input tcp 和 udp 插件

input {

tcp{

        host => "0.0.0.0"
        port => 8888
        type => "tcplog"
    }
    udp{
        host => "192.168.4.16"
        port => 9999
        type => "udplog"
    }

}

— syslog 插件

input {

    syslog{
        host => "192.168.4.10"
        port => 514
        type => "syslog"

}

– rsyslog.conf 配置向进程发送数据 //要传送log的主机上

／／rsyslog.conf @@192.168.4.10:514(TCP模式传送）@192.168.4.10:514（ＵＤＰ模式传送）

／／要输出哪个，直接复制默认例如local0.info（名字），再写上传送地址就可以了

local0.info　　　@@192.168.4.10:514

– 写 syslog ,查看状态

logger -p local0.info -t test_logstash 'test message'

[root@web2 bin]# cat /etc/logstash/conf.d/logstash.conf

input {
file{
path => ["/tmp/a.log","/tmp/b.log"]
sincedb_path => "/var/lib/logstash/since.db"
start_position => "beginning"
type => "filelog"
}
}
filter { }
output {
stdout{ codec => "rubydebug" }

}

—　filter grok插件

– 解析各种非结构化的日志数据插件
– grok 使用正则表达式把飞结构化的数据结构化
– 在分组匹配,正则表达式需要根据具体数据结构编写
– 虽然编写困难,但适用性极广

– 几乎可以应用于各类数据

filter {

grok{

match => [“message”,“%{IP:ip}, (?<key>reg)”]

}

– grok 正则分组匹配

匹配 ip 时间戳和请求方法

"(?<ip>(\d+\.){3}\d+) \S+ \S+(?<time>.*\])\s+\"(?<method>[A-Z]+)"]
使用正则宏
%{IPORHOST:clientip} %{HTTPDUSER:ident} %{USER:auth}\[%{HTTPDATE:timestamp}\] \"%{WORD:verb}
最终版本

%{COMMONAPACHELOG} \"(?<referer>[^\"]+)\"\"(?<UA>[^\"]+)\"

– output ES 插件

output {

    if [type] == "filelog"{
        elasticsearch {
        hosts => ["192.168.4.15:9200"]
        index => "weblog"
        flush_size => 2000

idle_flush_time => 10

}

//调试成功后,把数据写入 ES 集群

— input filebeats 插件

//要配合发送日志的主机上安装filebeats 插件使用，接受装有filebeats插件发过来的日志数据

//logstash服务器上设置

input {

beats {

port => 5044

}

– 这个插件主要用来接收 beats 类软件发送过来的数据,
由于 logstash 依赖 java 环境,而且占用资源非常大,
我们往往不希望所有集群的机器都部署 java 环境安装

logstash,而使用更轻量的 filebeat 替代

— filebeat 数据发送端

／／安装到要发送日志数据的机子上

– 使用 rpm 安装 filebeat
# yum -y install filebeat-1.2.3-x86_64.rpm

– 修改配置文件 /etc/filebeat/filebeat.yml

document_type: weblog
..

paths:

- /var/log/httpd/access_log //可以多目录，再下一行直接写就行如：- /var/log/httpd/data.log

...

input_type: apache_log

document_type: apachelog

output:

#elasticsearch: //记得注释这一行

#hosts: ["localhost:9200"]　 //记得注释这一行

...

logstash:

hosts: ["192.168.4.10:5044"]

设置开机运行
# systemctl enable filebeat
开启服务

# systemctl start filebeat

／／重启服务后，客户机部署就完成了

／／浏览这台机的web服务器后（多刷新几下，稍等几秒）

／／会有记录写入access_log这个日志，然后就会自动发送给logstash主机上

－－－－－查看logstash服务主机

[root@web2 ~]# /opt/logstash/bin/logstash -f /etc/logstash/conf.d/logstash.conf
Settings: Default pipeline workers: 2
Pipeline main started
{
"message" => "192.168.1.254 - - [06/Jul/2018:20:10:31 +0800] \"GET / HTTP/1.1\" 304 - \"-\" \"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/60.0.3112.113 Safari/537.36\"",
"@version" => "1",
"@timestamp" => "2018-07-06T12:10:40.727Z",
"input_type" => "log",

"count" => 1,

／／已经接收到日志数据了

－－－－－－综合应用ＥＬＫ

１）logstash服务器配置文件（ＩＰ：192.168.1.134）

[root@logstash bin]# cat /etc/logstash/conf.d/logstash.conf
input {
tcp {
port => 8888
type => "test"
}
beats {
port => 5044
}
}

filter {
if [type] == "apachelog" {
grok {
match => {
"message" => "%{COMBINEDAPACHELOG}"
}
}
}
}

output {
stdout {
codec => "rubydebug"
}
if [type] == "apachelog" {
elasticsearch {
hosts => ["192.168.1.200:9200","192.168.1.203:9200"]
index => "apachelog"
flush_size => 2000
idle_flush_time => 10
}
}

}

２）Elasticsearch服务搭建好后基本不用什么配置(ＩＰ:http://192.168.1.200:9200/_plugin/head/)

３）Kibana连接到ES数据库后做好视图和面板就可以了。

／／到这里实现的效果是，实时监测web日志并实时图形化分类展示

ELK(Logstash)安装部署应用(图片示例)_2018_lcf

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