We dive into Google’s Linear Elastic Caching, a memory-management breakthrough that reframes RAM usage as a ski-rental decision. Each data page dynamically decides whether to rent in fast memory or buy a disk fetch, guided by a tiny decision-tree model that assigns a precise time-to-live. In production, memory usage dropped 15.5% and total cost of ownership fell 5%, while cache misses rose 5.5%—but only for cheap-to-fetch data, keeping compute costs almost unchanged. We unpack the math, the scale (billions of requests per second), and the broader implications for dynamic infrastructure and even real-world systems.

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