Performance Interference on Key-Value Stores in Multi-tenant Environments: When Block Size and Write Requests Matter

Abstract

Key-value stores are currently used by major cloud computing vendors, such as Google, Facebook, and LinkedIn, to support large-scale applications with concurrent read and write operations. Based on very simple data access APIs, the key-value stores can deliver outstanding throughput, which have been hooked up to high-performance solid-state drives (SSDs) to boost this performance even further. However, measuring performance interference on SSDs while sharing cloud computing resources is complex and not well covered by current benchmarks and tools. Different applications can access these resources concurrently until becoming overloaded without notice either by the benchmark or the cloud application. In this paper, we define a methodology to measure the problem of performance interference. Depending on the block size and the proportion of concurrent write operations, we show how a key-value store may quickly degrade throughput until becoming almost inoperative while sharing persistent storage resources with other tenants.