Feature Flag Tracking

Feature flags are a powerful way to roll out changes safely, but they can also introduce hidden performance regressions or failures if left unmonitored.

Laritor now supports feature flag tracking, allowing you to understand:

How often a feature flag is evaluated
How frequently it is active
Whether it impacts performance or error rates
Where it is being used across your application

This data is automatically aggregated and visualized in the Laritor dashboard.

Getting started

Update Laritor to the latest version

First, make sure you are running the latest version of the Laritor ingest package.

composer update binarybuilds/laritor-client

Automatic tracking with Laravel Pennant

If your application uses Laravel Pennant, Laritor will automatically track all feature flag evaluations without any additional configuration.

Laritor hooks into Pennant and records:

Each feature flag check
Whether the flag evaluated to active or inactive
The context in which the flag was checked, such as requests, queued jobs, commands, or scheduled tasks

No code changes are required.

Tracking custom or non-Pennant feature flags

If you are using a different feature flag provider or a home-grown feature flag system, you can manually report feature flag checks to Laritor using a single line of code.

Recording a feature flag check

\BinaryBuilds\LaritorClient\Recorders\FeatureFlagRecorder::recordFeatureCheck(
    'feature-flag-name',
    true
);

Example usage

if (feature_enabled('new-ui')) {

    \BinaryBuilds\LaritorClient\Recorders\FeatureFlagRecorder::recordFeatureCheck(
        'new-ui',
        true
    );

} else {

    \BinaryBuilds\LaritorClient\Recorders\FeatureFlagRecorder::recordFeatureCheck(
        'new-ui',
        false
    );
}

What Laritor tracks

Total number of checks
Number of active evaluations
Activation rate
Performance metrics such as average duration and latency percentiles
Error counts when the flag is active vs inactive

Summary

With feature flag tracking in Laritor, you gain real visibility into how feature flags affect your application in production. If you have feedback or ideas for improving feature flag insights, feel free to reach out via [email protected]. We are actively expanding this feature based on user input.