Optimizing cloud economics with linear elastic caching

Google Research announces linear elastic caching, a new approach to cache management that treats memory as a variable cost and uses a ski rental formulation to dynamically adjust cache size. The method was tested in Spanner, reducing memory usage by 15.5% and total cost of ownership by approximately 5% with minimal impact on I/O costs. The work was published at CIDR 2026 and evaluated on production workloads and public traces.

From the source
Linear elastic caching minimizes total cache cost by framing page eviction as a ski rental problem, using lightweight machine learning to optimize the trade-off between memory footprint and cache misses.
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Announced: 25 Jun 2026 10:03 UTC
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