There are some considerations and potential limitations when using Laravel Pennant with Laravel Spark, mainly due to how feature flags and subscription states (like trials) interact:
- Feature Flags and Trial Periods: Laravel Spark manages subscription states including trials, which often require enabling or disabling features based on whether a user is in a trial period or not. Laravel Pennant can handle feature flags dynamically, but integrating it to reflect trial states requires custom logic. For example, enabling features while on trial and disabling them after trial expiration is not automatic and must be implemented explicitly in your feature flag definitions or scopes[2].
- Scope Handling and Default Scopes: Pennant allows defining a default scope for feature checks (e.g., the authenticated user's team). In Spark, where subscription and user states are central, you must ensure that the scope used by Pennant correctly reflects the user's subscription status or team. Misconfiguration here can lead to incorrect feature flag evaluations, especially for users on trial or with different subscription tiers[1].
- Performance Considerations: Pennant caches feature flag results in-memory per request but can face performance issues if feature checks are done repeatedly in loops without eager loading. Since Spark applications often handle many users and subscription states, failing to use Pennant's eager loading capabilities can cause database query overhead and slowdowns[1].
- Caching and Storage Drivers: By default, Pennant uses a database driver to persist feature flag states, which fits well with Sparkâs persistent user data. However, if you want feature flags to be computed fresh on every request (e.g., reflecting real-time subscription changes), you may need to disable caching or use the array driver. This requires configuration and may impact performance[7].
- Compatibility and Updates: Laravel 11 dropped support for Laravel Spark Stripe 4.x, requiring an update to Spark Stripe ^5.0. While this is not a direct Pennant limitation, it affects overall application compatibility and should be considered when integrating Pennant with Spark on Laravel 11 or newer[8].
- No Built-in Spark Integration: Laravel Pennant is a general-purpose feature flag package and does not provide built-in integration specifically for Laravel Spark. Therefore, you must manually define how feature flags correspond to Spark subscription states, trials, and billing cycles, which can add complexity.
In summary, while Laravel Pennant can be used with Laravel Spark, limitations arise around the need for custom logic to sync feature flags with subscription/trial states, potential performance issues without eager loading, and configuration of scopes and caching to reflect Spark's user model accurately. There is no out-of-the-box seamless integration, so developers must carefully design the interaction between Pennantâs feature flags and Sparkâs subscription management to avoid inconsistencies and performance bottlenecks.
Citations:
[1] https://laravel.com/docs/11.x/pennant
[2] https://github.com/laravel/pennant/issues/52
[3] https://www.reddit.com/r/laravel/comments/g8203f/what_are_the_problems_with_using_laravel_spark/
[4] https://stackoverflow.com/questions/78993755/why-pennant-feature-in-laravel-11-is-not-called
[5] https://github.com/laravel/pennant/issues
[6] https://rkyadav.blog/2018/12/30/scala-and-spark-compatibility-issues/
[7] https://stackoverflow.com/questions/77078816/how-to-disable-caching-for-laravel-pennant-in-db
[8] https://laravel.com/docs/11.x/upgrade
[9] https://wpwebinfotech.com/blog/laravel-pennant-guide/
[10] https://www.honeybadger.io/blog/a-guide-to-feature-flags-in-laravel/