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Conditional statements can be seamlessly integrated into Fluentd's record_transformer
plugin. Here’s how you can do it:
<filter mylogs>
@type record_transformer
enable_ruby true
<record>
is_successful ${record["status"] == 200 ? "true" : "false"}
</record>
</filter>
In this example, the record_transformer
plugin is employed to add an is_successful
field to the log records. The value of this field is determined by a ternary operator (a concise conditional statement). It sets is_successful
to "true" if the status
field equals 200, and "false" otherwise.
Consider the following dummy log source:
<source>
@type dummy
dummy '{"timestamp":"2024-01-27T08:33:17","severity":"ERROR"}'
format json
tag mylogs
</source>
You can apply a conditional statement to assess the contents of the severity
field as follows:
...
<filter mylogs>
@type record_transformer
enable_ruby true
<record>
has_error ${record["severity"] == "ERROR" ? "true" : "false"}
</record>
</filter>
<match mylogs>
@type stdout
</match>
In this filter directive, the has_error
field will be dynamically populated based on the conditional statement. If the severity
field contains "ERROR", has_error
is set to true
, and false
otherwise.
When Fluentd is executed, the logs will be augmented with the has_error
field, reflecting the result of the conditional check:
2024-01-29 05:26:50.076341943 +0000 mylogs: {"timestamp":"2024-01-27T08:33:17","severity":"ERROR","has_error":"true"}
In cases where the severity
is anything other than "ERROR", the has_error
field would be set to false
:
2024-01-29 05:26:50.076341943 +0000 mylogs: {"timestamp":"2024-01-27T08:33:17","severity":"INFO","has_error":"false"}
For more in-depth knowledge and various techniques on Fluentd, including conditional processing of log data, explore our comprehensive guide on collecting, processing, and shipping log data with Fluentd.
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