![]() This section of the config handles how and where logstash outputs the event it's processing. By giving the logmessage field as the source it will map the key-value pairs to fields in the event. The final plugin used inside this branch of the conditional statement is kv, a filter plugin that is useful for parsing messages which have a series of key=value strings. Payara 4.1, thread data in the thread field as tid: _ThreadID=77 _ThreadName=payara-monitoring-service(1) and the log message is stored in the logmessage field.Īfter grok has parsed the event message, the date plugin is used to match the timestamp field and copy it into the field for the event, so that the time the entry was logged is used instead of the time logstash processed the event. ![]() The timestamp gets stored in the l timestamp field as T16:02:40.602+0100, server version in the server_version field as Grok extracts the data from the match of the patterns given to it, such that in this pattern the log message gets placed in a logmessage field, while the timestamp gets placed in a timestamp field. The pattern given to grok should match anything of this structure: First, the mutate plugin is used to remove any newline characters from the message, then the grok plugin is used to match the message against the pattern given and extract data out of it. If the event message does contain it then Logstash should be looking at an event that contains monitoring data. If it doesn't, the event is dropped by Logstash using the drop plugin since we only want monitoring data to be stored. To have Logstash take its input as the server.log file the following can be used for the input section:įilter įirst, this checks that the event message contains the string literal JMX-MONITORING. The config file will use the input, filter and output sections of the config file you can read more about the structure of a Logstash config file here. For simplicity's sake the file created can be called nf and placed in this directory. Next, the logstash configuration file needs to be created. Logstash has the ability to parse a log file and merge multiple log lines into a single event. This blog assumes that Logstash is going to be used through extracting the tar/zip archive for version 2.3.4, so work will be done in the directory which Logstash is extracted to.Īfter extracting the archive you should have a directory containing the files shown below: Stack traces are multiline messages or events. Logstash can be downloaded in a variety of forms from. ![]() This blog post covers how to get monitoring data from your server.log file and store it in Elasticsearch using Logstash. One way of getting the monitoring data from your server.log into one of these datastores is to use Logstash. Often, you might find it useful to store your monitoring data in a search engine such as Elasticsearch or a time series database such as InfluxDB. As mentioned in the introduction of the previous post, the Monitoring Service logs metrics in a way which allows for fairly hassle-free integration with tools such as Logstash and fluentd. Following the first part of this series of blog posts, you should now have a Payara Server installation which monitors the HeapMemoryUsage MBean and logs the used, max, init and committed values to the server.log file. ![]()
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