Validating your Data and Structure
Fluent Bit supports multiple sources and formats. In addition, it provides filters that you can use to perform custom modifications. As your pipeline grows, it's important to validate your data and structure.
Fluent Bit users are encouraged to integrate data validation in their continuous integration (CI) systems.
In a normal production environment, inputs, filters, and outputs are defined in configuration files. Fluent Bit provides the Expect filter, which you can use to validate keys and values from your records and take action when an exception is found.
A simplified view of the data processing pipeline is as follows:
Understand structure and configuration
Consider the following pipeline, which uses a JSON file as its data source and has two filters:
Grep to exclude certain records.
Record Modifier to alter records' content by adding and removing specific keys.
Add data validation between each step to ensure your data structure is correct.
This example uses the Expect filter.
Expect filters set rules aiming to validate criteria like:
Does the record contain key
A
?Does the record not contain key
A
?Does the key
A
value equalNULL
?Is the key
A
value notNULL
?Does the key
A
value equalB
?
Every Expect filter configuration exposes rules to validate the content of your records using configuration parameters.
Test the configuration
Consider a JSON file data.log
with the following content:
{"color": "blue", "label": {"name": null}}
{"color": "red", "label": {"name": "abc"}, "meta": "data"}
{"color": "green", "label": {"name": "abc"}, "meta": null}
The following files configure a pipeline to consume the log, while applying an Expect filter to validate that the
keys color
and label
exist.
The following is the Fluent Bit YAML configuration file:
service:
flush: 1
log_level: info
parsers_file: parsers.yaml
pipeline:
inputs:
- name: tail
path: data.log
parser: json
exit_on_eof: on
# First 'expect' filter to validate that our data was structured properly
filters:
- name: expect
match: '*'
key_exists:
- color
- $label['name']
action: exit
outputs:
- name: stdout
match: '*'
If the JSON parser fails or is missing in the Tail input (parser json
), the Expect filter triggers the exit
action.
To extend the pipeline, add a Grep filter to match records that map label
containing a key called name
with value the abc
, and add an Expect filter to re-validate that condition:
The following is the Fluent Bit YAML configuration file:
service:
flush: 1
log_level: info
parsers_file: parsers.yaml
pipeline:
inputs:
- name: tail
path: data.log
parser: json
exit_on_eof: on
# First 'expect' filter to validate that our data was structured properly
filters:
- name: expect
match: '*'
key_exists:
- color
- $label['name']
action: exit
# Match records that only contains map 'label' with key 'name' = 'abc'
- name: grep
match: '*'
regex: "$label['name'] ^abc$"
# Check that every record contains 'label' with a non-null value
- name: expect
match: '*'
key_val_eq: $label['name'] abc
action: exit
# Append a new key to the record using an environment variable
- name: record_modifier
match: '*'
record: hostname ${HOSTNAME}
# Check that every record contains 'hostname' key
- name: expect
match: '*'
key_exists: hostname
action: exit
outputs:
- name: stdout
match: '*'
Production deployment
When deploying in production, consider removing any Expect
filters from your configuration file. These filters are unnecessary unless you need 100% coverage of checks at runtime.
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