Validating your Data and Structure

Fluent Bit is a powerful log processing tool that can deal with different sources and formats, in addition it provides several filters that can be used to perform custom modifications. This flexibility is really good but while your pipeline grows, it's strongly recommended to validate your data and structure.

We encourage Fluent Bit users to integrate data validation in their CI systems

A simplified view of our data processing pipeline is as follows:

In a normal production environment, many Inputs, Filters, and Outputs are defined in the configuration, so integrating a continuous validation of your configuration against expected results is a must. For this requirement, Fluent Bit provides a specific Filter called Expect which can be used to validate expected Keys and Values from your records and takes some action when an exception is found.

How it Works

As an example, consider the following pipeline where your source of data is a normal file with JSON content on it and then two filters: grep to exclude certain records and record_modifier to alter the record content adding and removing specific keys.

Ideally you want to add checkpoints of validation of your data between each step so you can know if your data structure is correct, we do this by using expect filter.

Expect filter sets rules that aims to validate certain criteria like:

• does the record contain a key A ?

• does the record not contains key A?

• does the record key A value equals NULL ?

• does the record key A value a different value than NULL ?

• does the record key A value equals B ?

Every expect filter configuration can expose specific rules to validate the content of your records, it supports the following configuration properties:

Start Testing

Consider the following JSON file called 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 Fluent Bit configuration file will configure a pipeline to consume the log above apply an expect filter to validate that keys color and label exists:

[SERVICE]
    flush        1
    log_level    info
    parsers_file parsers.conf

[INPUT]
    name        tail
    path        ./data.log
    parser      json
    exit_on_eof on

# First 'expect' filter to validate that our data was structured properly
[FILTER]
    name        expect
    match       *
    key_exists  color
    key_exists  $label['name']
    action      exit

[OUTPUT]
    name        stdout
    match       *

note that if for some reason the JSON parser failed or is missing in the tail input (line 9), the expect filter will trigger the exit action. As a test, go ahead and comment out or remove line 9.

As a second step, we will extend our pipeline and we will add a grep filter to match records that map label contains a key called name with value abc, then an expect filter to re-validate that condition:

[SERVICE]
    flush        1
    log_level    info
    parsers_file parsers.conf

[INPUT]
    name         tail
    path         ./data.log
    parser       json
    exit_on_eof  on

# First 'expect' filter to validate that our data was structured properly
[FILTER]
    name       expect
    match      *
    key_exists color
    key_exists label
    action     exit

# Match records that only contains map 'label' with key 'name' = 'abc'
[FILTER]
    name       grep
    match      *
    regex      $label['name'] ^abc$

# Check that every record contains 'label' with a non-null value
[FILTER]
    name       expect
    match      *
    key_val_eq $label['name'] abc
    action     exit

# Append a new key to the record using an environment variable
[FILTER]
    name       record_modifier
    match      *
    record     hostname ${HOSTNAME}

# Check that every record contains 'hostname' key
[FILTER]
    name       expect
    match      *
    key_exists hostname
    action     exit

[OUTPUT]
    name       stdout
    match      *

Deploying in Production

When deploying your configuration in production, you might want to remove the expect filters from your configuration since it's an unnecessary extra work unless you want to have a 100% coverage of checks at runtime.