nginx日志grafana展示

input {                                        # 输入组件
    kafka {                                    # 从kafka消费数据
        bootstrap_servers => ["192.168.1.2:9292,192.168.1.3:9292,192.168.1.4:9292"]
        #topics => "%{[@metadata][topic]}"     # 使用kafka传过来的topic
        #topics_pattern => "elk-.*"             # 使用正则匹配topic
        topics => "pokekara_nginx_log"
        codec => plain {
	    format => "%{message}"
        }                       # 数据格式,如果是json直接写json即可。
        consumer_threads => 3                  # 消费线程数量
        decorate_events => true                # 可向事件添加Kafka元数据，比如主题、消息大小的选项，这将向logstash事件中添加一个名为kafka的字段
        auto_offset_reset => "latest"          # 自动重置偏移量到最新的偏移量
        group_id => "logstash-groups1"         # 消费组ID，多个有相同group_id的logstash实例为一个消费组
        client_id => "logstash1"               # 客户端ID
        fetch_max_wait_ms => "1000"            # 指当没有足够的数据立即满足fetch_min_bytes时，服务器在回答fetch请求之前将阻塞的最长时间
  }
}

filter {
  #grok {
    #match => { "message" => "%{IPORHOST:client_ip}:%{NUMBER:client_port}\t-\t%{HTTPDUSER:ident}\t%{HTTPDATE:timestamp}\t%{IPORHOST:server_ip}:%{NUMBER:server_port}\t%{NUMBER:request_duration}\t%{NUMBER:response_duration}\t%{WORD:request_method}\t%{URIPATHPARAM:request_path}\t%{NUMBER:http_version}\t%{NUMBER:response_code}\t%{NUMBER:response_size}\t-\t%{DATA:user_agent}\t%{IPORHOST:source_ip}\t%{WORD:country}\t%{NUMBER:city_code}\t%{WORD:city_name}\t%{NUMBER:unknown_field1}\t%{NUMBER:unknown_field2}\t%{IPORHOST:nginx_ip}\t%{NUMBER:nginx_port}\t%{WORD:destination_country}\t%{WORD:destination_city}" }
  #}
  ruby {
    code => '
      keys = ["remote_addr","remote_user","time_local","upstream_addr","upstream_response_time","request_time","request","status","body_bytes_sent","http_referer","http_user_agent","http_x_forwarded_for","geoip_country_name","geoip_region","geoip_city","upstream_connect_time","upstream_header_time","server_addr","request_length","geoip2_data_country_name","geoip2_data_city_name"]
      values = event.get("message").split("\t")

      parts = values[6].split(" ")
      hmethod = parts[0]
      suri = parts[1].split("?")
      uri = suri[0]

      #新增一个key
      keys << "hmethod"
      #新增一个key的值
      values << hmethod
      keys << "uri"
      values << uri

      merged_values = Hash[keys.zip(values)]

      event.set("[newmess][request]", merged_values["request"])
      event.set("newmess", merged_values)

      #merget_values= Hash[keys.zip(values)]
      #custom_output = merget_values.map { |k, v| "#{k}:#{v}" }.join(",")
      event.remove("message")
    '
  }
  mutate {
    #split => ["[newmess][request]"," "]
    #add_field => {"method" => "%{[newmess][request][0]}"}
    #split => ["%{[newmess][request][1]}","?"]
    #add_field => {"uri" => "%{[newmess][request][1][0]}"}
    remove_field => ["[@version]","[newmess][remote_addr]","[newmess][remote_user]","[newmess][time_local]","[newmess][upstream_addr]","[newmess][request]","[newmess][geoip_country_name]","[newmess][geoip_region]","[newmess][geoip_city]","[newmess][upstream_connect_time]","[newmess][upstream_header_time]","[newmess][request_length]"]
  }

}


output {
    elasticsearch {      # 输出组件
      # Logstash输出到es
      hosts => ["192.168.1.5:9200"]
      #index => "%{[fields][source]}-%{+YYYY-MM-dd}"      # 直接在日志中匹配，索引会去掉elk
      index => "pokekara-nginx-%{+YYYY-MM-dd}"      # 直接在日志中匹配，索引会去掉elk
      user => "elastic"
      password => "passwd"
      action => "create"  #此处使用index模式报错，使用了create
      #document_type => "_doc"
      #document_id => "%{[@metadata][_id]}"
    }
}

#调试模式，输出到屏幕
#output {
#    stdout {
#        codec => rubydebug
#    }
#}