使用logstash收集java、nginx、系统等常见日志

 

目录

1、使用codec的multiline插件收集java日志... 1

2、收集nginx日志... 2

3、收集系统syslog日志... 3

4、使用fliter的grok模块收集mysql日志... 4

 

 

1、使用codec的multiline插件收集java日志

对于采用ELK作为应用日志来说，多行消息的友好展示是必不可少的，否则ELK的价值就大大打折了。要正确的处理多行消息，需使用multiline插件

 

比如，对于java日志而言，可以使用：

multiline.pattern:
'^\['

multiline.negate:
true

multiline.match:
after

 

 

这样，下面的日志就算一个事件了。

 

input {

    file {

       
path => "/var/log/elasticsearch/chuck-clueser.log"

       
type => "es-error"

       
start_position => "beginning"

       
codec => multiline {

           
pattern => "^\["    #使用正则表式， 以中括号开头的就是一行日志

           
negate => true

           
what => "previous"

       
}

    }

}

output {

   
if [type] == "es-error" {

       
elasticsearch {

           
hosts => ["192.168.100.163:9200"]

           
index => "es-error-%{+YYYY.MM.dd}"

     
  }

    }

}

 

2、收集nginx日志

使用codec的json插件将日志的域进行分段，使用key-value的方式，使日志格式更清晰，易于搜索，还可以降低cpu的负载 

2.1 更改nginx的配置文件的日志格式，使用json

[root@linux-node1 ~]# vim
/etc/nginx/nginx.conf   #添加日志格式，把自带的格式注释掉

17 http {

 18    
#log_format  main  '$remote_addr - $remote_user [$time_local]
"$request"     '

 19    
#                  '$status
$body_bytes_sent "$http_referer" '

 20    
#                 
'"$http_user_agent" "$http_x_forwarded_for"';

 21    
#access_log  /var/log/nginx/access.log  main;

 22    
log_format json '{ "@timestamp": "$time_local", '

 23                          '"@fields":
{ '

 24                         
'"remote_addr": "$remote_addr", '

 25                         
'"remote_user": "$remote_user", '

 26                         
'"body_bytes_sent": "$body_bytes_sent", '

 27                         
'"request_time": "$request_time", '

 28                          '"status":
"$status", '

 29                          '"request":
"$request", '

 30                         
'"request_method": "$request_method", '

 31                         
'"http_referrer": "$http_referer", '

 32                         
'"body_bytes_sent":"$body_bytes_sent", '

 33                         
'"http_x_forwarded_for": "$http_x_forwarded_for", '

 34                         
'"http_user_agent": "$http_user_agent" } }';

 35    
access_log /var/log/nginx/access_json.log json;

[root@linux-node1 ~]# nginx -t  #检查配置文件

[root@linux-node1 ~]# systemctl start nginx

日志格式如下

 

 

2.2
使用logstash将nginx访问日志收集起来

[root@linux-node1 ~]# cat
log_nginx.conf 4、

input {

    file {

        path =>
"/var/log/nginx/access_json.log"

        codec => "json"

        start_position =>
"beginning"

        type => "nginx-log"

    }

}

output {

    elasticsearch {

        hosts =>
["http://192.168.100.163:9200"]

        index =>
"nginx-%{+YYY.MM.dd}"

        }

}

[root@linux-node1 ~]#
/usr/local/logstash/bin/logstash -f log_nginx.conf

 

 

3、收集系统syslog日志

[root@linux-node1 ~]# vim syslog.conf

input {

   
syslog {

       
type => "system-syslog"

       
#绑定个ip，监听个514端口，启动后，别的机器可以通过网络把日志发过来

       
host => "192.168.100.161"

       
port => "514"

    }

}

output {

   
elasticsearch {

       
hosts => ["192.168.100.161:9200"]

       
index => "system-syslog-%{+YYYY.MM.dd}"

       
}

    }

 

[root@linux-node1 ~]#
/usr/local/logstash/bin/logstash -f syslog.conf

 

修改服务器的syslog配置文件，把日志信息发送到514端口上

[root@linux-node2 ~]# vim /etc/rsyslog.conf

90 *.* @@192.168.100.161:514

[root@linux-node2 ~]# systemctl restart
rsyslog

 

 

 

4、使用fliter的grok模块收集mysql日志

filter插件有很多，在这里就学习grok插件，使用正则匹配日志里的域来拆分。在实际生产中，apache日志不支持jason，就只能使用grok插件匹配；mysql慢查询日志也是无法拆分，只能使用grok正则表达式匹配拆分。

 

在如下链接，github上有很多写好的grok模板，可以直接引用 

https://github.com/logstash-plugins/logstash-patterns-core/blob/master/patterns/grok-patterns

 

 

在装好的logstash中也会有grok匹配规则，直接可以引用，路径如下

[root@linux-node1 patterns]# pwd

/usr/local/logstash/vendor/bundle/jruby/1.9/gems/logstash-patterns-core-4.1.0/patterns

 

 

 

4.1日志文件

[root@linux-node1 ~]# cat slow.log

# Time: 160108 15:46:14

# User@Host: dev_select_user[dev_select_user] @  [192.168.97.86]  Id: 714519

# Query_time: 1.638396 
Lock_time: 0.000163 Rows_sent: 40 
Rows_examined: 939155

SET timestamp=1452239174;

SELECT DATE(create_time) as day,HOUR(create_time) as
h,round(avg(low_price),2) as low_price

    FROM t_actual_ad_num_log
WHERE create_time>='2016-01-07' and ad_num<=10

    GROUP BY
DATE(create_time),HOUR(create_time);

 

4.2编写slow.conf

[root@linux-node1 ~]# cat mysql-slow.conf

input{

   file {

     path =>
"/root/slow.log"

     type =>
"mysql-slow-log"

     start_position =>
"beginning"

     codec => multiline {

        pattern => "^#
User@Host:"

        negate => true

        what =>
"previous"

    }

  }

}

filter {

      # drop sleep events

    grok {

        match => {
"message" =>"SELECT SLEEP" }

        add_tag => [
"sleep_drop" ]

        tag_on_failure =>
[] # prevent default _grokparsefailure tag on real records

      }

     if "sleep_drop"
in [tags] {

        drop {}

     }

     grok {

        match => [ "message",
"(?m)^# User@Host: %{USER:user}\[[^\]]+\] @ (?:(?<clienthost>\S*)
)?\[(?:%{IP:clientip})?\]\s+Id: %{NUMBER:row_id:int}\s*# Query_time:
%{NUMBER:query_time:float}\s+Lock_time: %{NUMBER:lock_time:float}\s+Rows_sent:
%{NUMBER:rows_sent:int}\s+Rows_examined: %{NUMBER:rows_examined:int}\s*(?:use
%{DATA:database};\s*)?SET
timestamp=%{NUMBER:timestamp};\s*(?<query>(?<action>\w+)\s+.*)\n#\s*"
]

      }

      date {

        match => [
"timestamp", "UNIX" ]

        remove_field => [
"timestamp" ]

      }

}

output {

     stdout{

     codec =>
"rubydebug"

   }

}

 

 

执行该配置文件，查看grok正则匹配结果