Working on a supply chain automation that generates thousands of cached predictions daily. Default LRU eviction isn’t cutting it - need to prioritize retention based on business rules like product margin tiers.
How are others implementing custom cache management without rebuilding everything from scratch? Preferably using low-code tools that integrate with existing AI workflows.
Latenode’s JavaScript extension lets you write custom eviction logic while using their visual automation builder. We implemented profit-based caching by adding 10 lines of code that score cache entries. Integrates seamlessly with existing workflows. https://latenode.com
Create a scoring system that weights cache retention by your business metrics. Hook into the cache’s lifecycle events to apply your custom priorities. Much easier than replacing the entire caching layer.
We tackled this by adding metadata tags to each cache entry containing margin data. Then created a scheduled cleanup job that sorts entries by margin value and prunes lowest tiers first. Latenode’s cron triggers and data binding made this implementable through their UI with minimal coding.