High performance in-memory caching through flexible fine-grained services

Abstract

In-memory object caches are extensively used in today's web installations [1, 6]. Most existing systems adopt monolithic storage models and engineer optimizations on specific workload characteristics [3, 6] or operations [4, 5]. Such optimizations are insufficient as large-scale cloud workloads typically exhibit both temporal and spatial shifts - requirements vary within the same deployment over time and different parts of the same workload demonstrate different access patterns. To this end, we propose a caching tier that supports differentiated services in multiple dimensions. Since there is no best "one-size-fits-all" solution for all workload requirements, we argue that a fine-grained modular design will provide both high performance and flexibility in supporting multiple services.