In the quest to optimize app performance, managing the image cache was crucial. This blog takes us on a journey from a traditional Least Recently Used (LRU) cache to a Time-Aware Least Recently Used (TLRU) cache. This innovative approach reclaimed terabytes of storage across millions of devices while maintaining user experience and controlling server costs. Discover how Grab's TLRU implementation cleverly balances storage optimization and performance, offering a glimpse into the future of app development.

Grab is a leading technology company in Southeast Asia, offering a wide range of services, including ride-hailing, food delivery, and digital payments. Through its platform, Grab provides convenience, accessibility, and reliability to millions of users across the region. From their blog developers can learn from Grab's innovative approach to technology and business, gaining insights into building scalable, customer-centric platforms that address real-world challenges and improve people's lives.

Grab Tech Blog

Grab's Android team evolved their image disk cache from a standard LRU to a Time-Aware LRU (TLRU) to reclaim storage across millions of devices. The standard Glide DiskLruCache had no time-based eviction, leaving stale promotional and feature images on disk indefinitely. TLRU adds three core attributes: a TTL (20 days) to expire old entries, a minimum cache size threshold (20 MB) to protect essential images for returning users, and the inherited maximum size limit (100 MB). Implementation involved cloning Glide's DiskLruCache, extending the journal file format to persist last-access timestamps, and adding time-based eviction logic that leverages LRU ordering for efficiency. A backward-compatible migration strategy avoided cache invalidation for existing users. After full rollout, P95 app storage dropped by ~50 MB with cache hit ratio staying within a 3 percentage point threshold, reclaiming terabytes of storage across 100M+ installs.

Reclaiming Terabytes: Optimizing Android image caching with TLRU