I have logs like this:
{"logId":"57aaf6c8d32fb","clientIp":"127.0.0.1","time":"03:11:29 pm","uniqueSubId":"57aaf6c98963b","channelName":"JSPC","apiVersion":"v1","modulName":null,"actionName":"apiRequest","typeOfError":"","statusCode":"","message":"In Auth","exception":"In Auth","logType":"Info"}
{"logId":"57aaf6c8d32fb","clientIp":"127.0.0.1","time":"03:11:29 pm","uniqueSubId":"57aaf6c987206","channelName":"JSPC","apiVersion":"v2","modulName":null,"actionName":"performV2","typeOfError":"","statusCode":"","message":"in inbox api v2 5","exception":"in inbox api v2 5","logType":"Info"}
I want to push them to kibana
. I am using filebeat to send data to logstash, using following configuration:
filebeat.yml
### Logstash as output
logstash:
# The Logstash hosts
hosts: ["localhost:5044"]
# Number of workers per Logstash host.
#worker: 1
Now using following configuration, I want to change codec type:
input {
beats {
port => 5000
tags => "beats"
codec => "json_lines"
#ssl => true
#ssl_certificate => "/opt/filebeats/logs.example.com.crt"
#ssl_key => "/opt/filebeats/logs.example.com.key"
}
syslog {
type => "syslog"
port => "5514"
}
}
But, still I get the logs in string format:
"message": "{\"logId\":\"57aaf6c96224b\",\"clientIp\":\"127.0.0.1\",\"time\":\"03:11:29 pm\",\"channelName\":\"JSPC\",\"apiVersion\":null,\"modulName\":null,\"actionName\":\"404\",\"typeOfError\":\"EXCEPTION\",\"statusCode\":0,\"message\":\"404 page encountered http:\/\/localjs.com\/uploads\/NonScreenedImages\/profilePic120\/16\/29\/15997002iicee52ad041fed55e952d4e4e163d5972ii4c41f8845105429abbd11cc184d0e330.jpeg\",\"logType\":\"Error\"}",
Please help me solve this.
If you're using ELK as your logging solution, one way to ship these logs is using Filebeat to send the data directly into Elasticsearch. Since Filebeat ships data in JSON format, Elasticsearch should be able to parse the timestamp and message fields without too much hassle.
Beats have a small footprint and use fewer system resources than Logstash. Logstash has a larger footprint, but provides a broad array of input, filter, and output plugins for collecting, enriching, and transforming data from a variety of sources.
To parse JSON log lines in Logstash that were sent from Filebeat you need to use a json filter instead of a codec. This is because Filebeat sends its data as JSON and the contents of your log line are contained in the message
field.
Logstash config:
input {
beats {
port => 5044
}
}
filter {
if [tags][json] {
json {
source => "message"
}
}
}
output {
stdout { codec => rubydebug { metadata => true } }
}
Filebeat config:
filebeat:
prospectors:
- paths:
- my_json.log
fields_under_root: true
fields:
tags: ['json']
output:
logstash:
hosts: ['localhost:5044']
In the Filebeat config, I added a "json" tag to the event so that the json filter can be conditionally applied to the data.
Filebeat 5.0 is able to parse the JSON without the use of Logstash, but it is still an alpha release at the moment. This blog post titled Structured logging with Filebeat demonstrates how to parse JSON with Filebeat 5.0.
From FileBeat 5.x You can do it without using Logstash.
Filebeat config:
filebeat.prospectors:
- input_type: log
paths: ["YOUR_LOG_FILE_DIR/*"]
json.message_key: logId
json.keys_under_root: true
output.elasticsearch:
hosts: ["<HOSTNAME:PORT>"]
template.name: filebeat
template.path: filebeat.template.json
Filebeat is more lightweight then Logstash. Also, even if you need to insert to elasticsearch version 2.x you can use this feature of FileBeat 5.x Real example can be found here
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