Mimir: Finding Cost-efficient Storage Configurations in the Public Cloud

Abstract

Public cloud providers offer a diverse collection of storage types and configurations with different costs and performance SLAs. As a consequence, it is difficult to select the most cost-efficient allocations for storage backends, while satisfying a given workload's performance requirements, when moving data-heavy applications to the cloud. We present Mimir, a tool for automatically finding a cost-efficient virtual storage cluster configuration for a customer's storage workload and performance requirements. Importantly, Mimir considers all block storage types and configurations, and even heterogeneous mixes of them. In our experiments, compared to state-of-the-art approaches that consider only one storage type, Mimir finds configurations that reduce cost by up to 81% for real-application-based key-value store workloads.