In a globally distributed system, the challenge of achieving real-time data consistency is addressed by implementing a two-tier caching strategy that enhances the speed of data acquisition beyond the capabilities of CassandraDB's eventual consistency model. The system employs a storage cache to minimize read times and a volatile cache to handle unverified user actions, allowing data updates to occur at a rate of 1/10 of a second, similar to the Pub/Sub service. This new architecture, featuring a list of channels with timestamps and statuses, ensures faster response times while maintaining the database as the ultimate source of truth. However, the volatility and potential for discrepancies in the cache, due to factors like clock skew and simultaneous updates in different regions, require careful management through features like a configurable age-out time and a feature flag mechanism to mitigate risk and reduce memory overhead.