logstash提取日志字段到kibana仪表盘展示

章工运维

发布于 2023-05-19 19:52:59

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发布于 2023-05-19 19:52:59

# 一、日志分析

# 需要处理的日志

{"@timestamp":"2023-04-16T00:03:36.946+08:00","caller":"logic/sendticklogic.go:37","content":"recv tick err: rpc error: code = Canceled desc = context canceled","level":"error","span":"1e4c82625afe0758","trace":"2b96e538e67df5cc7c8218ee35c11d71"}

创建一个Grok模式来匹配日志中的各个字段

日志

2023-04-16T00:03:36.946+08:00|logic/sendticklogic.go:37|recv tick err: rpc error: code = Canceled desc = context canceled|error|1e4c82625afe0758|2b96e538e67df5cc7c8218ee35c11d71

grok模式

%{TIMESTAMP_ISO8601:@timestamp}\|%{DATA:caller}\|%{GREEDYDATA:content}\|%{DATA:level}\|%{DATA:span}\|%{DATA:trace}

将这个日志示例和Grok模式粘贴到在线Grok调试器中，您应该能够看到以下匹配结果：

@timestamp: "2023-04-16T00:03:36.946+08:00"
caller: "logic/sendticklogic.go:37"
content: "recv tick err: rpc error: code = Canceled desc = context canceled"
level: "error"
span: "1e4c82625afe0758"
trace: "2b96e538e67df5cc7c8218ee35c11d71"

这个结果与之前所述的字段相匹配。使用Grok调试器，您可以测试和优化Grok模式，以便准确地匹配您的日志数据

# 二、logstash提取日志字段

# 在filter中使用grok过滤器

具体内容如下

input {
 kafka {
    type => "pro-ait0-go-error"
    bootstrap_servers => ["xxx:9093, xxx:9094, xxx:9095"]
    client_id => "pro-ait0-go-error"
    group_id => "pro-ait0-go-error"
    auto_offset_reset =>"latest"
    topics => ["pro-ait0-go-error"]
    consumer_threads => 6
    codec => "json"
  }
}

filter {
    grok {
    match => { "message" => '"content":"%{GREEDYDATA:content_value}"' }
    }
}


output {


if [type] == "pro-ait0-go-error" {

    elasticsearch {
      hosts => ["http://xxx:9200"]
          user => "elastic"
      password => "t1Nc9SSHBiFOQK01R44l"
      index => "pro-ait0-go-error-%{+YYYY.MM.dd}"
    }

  }

}