Rewrite Tag

Powerful and flexible routing

Tags are what makes routing possible. Tags are set in the configuration of the Input definitions where the records are generated, but there are certain scenarios where might be useful to modify the Tag in the pipeline so we can perform more advanced and flexible routing.

The rewrite_tag filter, allows to re-emit a record under a new Tag. Once a record has been re-emitted, the original record can be preserved or discarded.

How it Works

The way it works is defining rules that matches specific record key content against a regular expression, if a match exists, a new record with the defined Tag will be emitted. Multiple rules can be specified and they are processed in order until one of them matches.

The new Tag to define can be composed by:

  • Alphabet characters & Numbers

  • Original Tag string or part of it

  • Regular Expressions groups capture

  • Any key or sub-key of the processed record

  • Environment variables

Configuration Parameters

The rewrite_tag filter supports the following configuration parameters:




Defines the matching criteria and the format of the Tag for the matching record. The Rule format have four components: KEY REGEX NEW_TAG KEEP. For more specific details of the Rule format and it composition read the next section.


When the filter emits a record under the new Tag, there is an internal emitter plugin that takes care of the job. Since this emitter expose metrics as any other component of the pipeline, you can use this property to configure an optional name for it.


Define a buffering mechanism for the new records created. Note these records are part of the emitter plugin. This option support the values memory (default) or filesystem. If the destination for the new records generated might face backpressure due to latency or slow network, we strongly recommend enabling the filesystem mode.


Set a limit on the amount of memory the tag rewrite emitter can consume if the outputs provide backpressure. The default for this limit is 10M. The pipeline will pause once the buffer exceeds the value of this setting. For example, if the value is set to 10M then the pipeline will pause if the buffer exceeds 10M. The pipeline will remain paused until the output drains the buffer below the 10M limit.


A rule aims to define matching criteria and specify how to create a new Tag for a record. You can define one or multiple rules in the same configuration section. The rules have the following format:



The key represents the name of the record key that holds the value that we want to use to match our regular expression. A key name is specified and prefixed with a $. Consider the following structured record (formatted for readability):

"name": "abc-123",
"ss": {
"s1": {
"s2": "flb"

If we wanted to match against the value of the key name we must use $name. The key selector is flexible enough to allow to match nested levels of sub-maps from the structure. If we wanted to check the value of the nested key s2 we can do it specifying $ss['s1']['s2'], for short:

  • $name = "abc-123"

  • $ss['s1']['s2'] = "flb"

Note that a key must point a value that contains a string, it's not valid for numbers, booleans, maps or arrays.


Using a simple regular expression we can specify a matching pattern to use against the value of the key specified above, also we can take advantage of group capturing to create custom placeholder values.

If we wanted to match any record that it $name contains a value of the format string-number like the example provided above, we might use:


Note that in our example we are using parentheses, this teams that we are specifying groups of data. If the pattern matches the value a placeholder will be created that can be consumed by the NEW_TAG section.

If $name equals abc-123 , then the following placeholders will be created:

  • $0 = "abc-123"

  • $1 = "abc"

  • $2 = "123"

If the Regular expression do not matches an incoming record, the rule will be skipped and the next rule (if any) will be processed.

New Tag

If a regular expression has matched the value of the defined key in the rule, we are ready to compose a new Tag for that specific record. The tag is a concatenated string that can contain any of the following characters: a-z,A-Z, 0-9 and .-,.

A Tag can take any string value from the matching record, the original tag it self, environment variable or general placeholder.

Consider the following incoming data on the rule:

  • Tag =

  • Record = {"name": "abc-123", "ss": {"s1": {"s2": "flb"}}}

  • Environment variable $HOSTNAME = fluent

With such information we could create a very custom Tag for our record like the following:


the expected Tag to generated will be:

We make use of placeholders, record content and environment variables.


If a rule matches the criteria the filter will emit a copy of the record with the new defined Tag. The property keep takes a boolean value to define if the original record with the old Tag must be preserved and continue in the pipeline or just be discarded.

You can use true or false to decide the expected behavior. There is no default value and this is a mandatory field in the rule.

Configuration Example

The following configuration example will emit a dummy (hand-crafted) record, the filter will rewrite the tag, discard the old record and print the new record to the standard output interface:

Flush 1
Log_Level info
NAME dummy
Dummy {"tool": "fluent", "sub": {"s1": {"s2": "bit"}}}
Tag test_tag
Name rewrite_tag
Match test_tag
Rule $tool ^(fluent)$ from.$$tool.$sub['s1']['s2'].out false
Emitter_Name re_emitted
Name stdout
Match from.*

The original tag test_tag will be rewritten as

$ bin/fluent-bit -c example.conf
Fluent Bit v1.x.x
* Copyright (C) 2019-2020 The Fluent Bit Authors
* Copyright (C) 2015-2018 Treasure Data
* Fluent Bit is a CNCF sub-project under the umbrella of Fluentd
[0] [1580436933.000050569, {"tool"=>"fluent", "sub"=>{"s1"=>{"s2"=>"bit"}}}]


As described in the Monitoring section, every component of the pipeline of Fluent Bit exposes metrics. The basic metrics exposed by this filter are drop_records and add_records, they summarize the total of dropped records from the incoming data chunk or the new records added.

Since rewrite_tag emit new records that goes through the beginning of the pipeline, it exposes an additional metric called emit_records that summarize the total number of emitted records.

Understanding the Metrics

Using the configuration provided above, if we query the metrics exposed in the HTTP interface we will see the following:


$ curl | jq

Metrics output:

"input": {
"dummy.0": {
"records": 2,
"bytes": 80
"emitter_for_rewrite_tag.0": {
"records": 1,
"bytes": 40
"filter": {
"rewrite_tag.0": {
"drop_records": 2,
"add_records": 0,
"emit_records": 2
"output": {
"stdout.0": {
"proc_records": 1,
"proc_bytes": 40,
"errors": 0,
"retries": 0,
"retries_failed": 0

The dummy input generated two records, the filter dropped two from the chunks and emitted two new ones under a different Tag.

The records generated are handled by the internal Emitter, so the new records are summarized in the Emitter metrics, take a look at the entry called emitter_for_rewrite_tag.0.

What is the Emitter ?

The Emitter is an internal Fluent Bit plugin that allows other components of the pipeline to emit custom records. On this case rewrite_tag creates an Emitter instance to use it exclusively to emit records, on that way we can have a granular control of who is emitting what.

The Emitter name in the metrics can be changed setting up the Emitter_Name configuration property described above.