While most systems are read-heavy, some of the most challenging problems in distributed systems involve handling massive write loads. Every GPS ping from an Uber driver, every click tracked by analytics, every log line from a server, every IoT sensor reading, these are all writes that must be captured reliably at enormous scale.

Here's the uncomfortable truth about writes: you can't cache your way out of them. With reads, you can add more replicas, layer caches in front of caches, and serve slightly stale data when needed. Writes don't offer the same luxury.

Every write must eventually hit persistent storage, and that storage becomes your bottleneck. The strategies that work brilliantly for reads simply don't apply. The architecture that scales reads horizontally hits a wall when you try to scale writes the same way.

Where This Pattern Shows Up