MOS: Workload-aware Elasticity for Cloud Object Stores

Abstract

The use of cloud object stores has been growing rapidly in recent years as they combine key advantages such as HTTP-based RESTful APIs, high availability, elasticity with a "pay-as-you-go" pricing model that allows applications to scale as needed. The current practice is to either use a single set of configuration parameters or rely on statically configured storage policies for a cloud object store deployment, even when the store is used to support different types of applications with evolving requirements. This crucial mismatch between the different applications requirements and capabilities of the object store is problematic and should be addressed to achieve high efficiency and performance. In this paper, we propose MOS, a Micro Object Storage architecture, which supports independently configured microstores each tuned dynamically to the needs of a particular type of workload. We also design an enhancement, MOS++, that extends MOS's capabilities through fine-grained resource management to effectively meet the tenants' SLAs while maximizing resource efficiency. We have implemented a prototype of MOS ++ in OpenStack Swift using Docker containers. Our evaluation shows that MOS ++ can effectively support heterogeneous workloads across multiple tenants. Compared to default and statically configured object store setups, for a two-tenant setup, MOS++ improves the sustained access bandwidth by up to 79% for a large-object workload, while reducing the 95th percentile latency by up to 70.2% for a small-object workload.