Enabling Space Elasticity in Storage Systems

Storage systems are designed to never lose data. However, modern applications increasingly use local storage to improve performance by storing soft state such as cached, prefetched or precomputed results. Required is elastic storage, where cloud providers can alter the storage footprint of applications by removing and regenerating soft state based on resource availability and access patterns. We propose a new abstraction called a motif that enables storage elasticity by allowing applications to describe how soft state can be regenerated. Carillon is a system that uses motifs to dynamically change the storage space used by applications. Carillon is implemented as a runtime and a collection of shim layers that interpose between applications and specific storage APIs; we describe shims for a filesystem (Carillon-FS) and a key-value store (Carillon-KV). We show that Carillon-FS allows us to dynamically alter the storage footprint of a VM, while Carillon-KV enables a graph database that accelerates performance based on available storage space.