Performance Isolation in Cloud Storage Systems

Abstract

Cloud computing enables data centres to provide resource sharing across multiple tenants. This sharing, however, usually comes at a cost in the form of reduced isolation between tenants, which can lead to inconsistent and unpredictable performance. This variability in performance becomes an impediment for clients whose services rely on consistent, responsive performance in cloud environments. The problem is exacerbated for applications that rely on cloud storage systems as performance in these systems is a ffected by disk access times, which often dominate overall request service times for these types of data services. In this thesis we introduce MicroFuge, a new distributed caching and scheduling middleware that provides performance isolation for cloud storage systems. To provide performance isolation, MicroFuge's cache eviction policy is tenant and deadline-aware, which enables the provision of isolation to tenants and ensures that data for queries with more urgent deadlines, which are most likely to be a ffected by competing requests, are less likely to be evicted than data for other queries. MicroFuge also provides simplifi ed, intelligent scheduling in addition to request admission control whose performance model of the underlying storage system will reject requests with deadlines that are unlikely to be satisfi ed. The middleware approach of MicroFuge makes it unique among other systems which provide performance isolation in cloud storage systems. Rather than providing performance isolation for some particular cloud storage system, MicroFuge can be deployed on top of any already deployed storage system without modifying it. Keeping in mind the wide spectrum of cloud storage systems available today, such an approach make MicroFuge very adoptable. In this thesis, we show that MicroFuge can provide signifi cantly better performance isolation between tenants with di fferent latency requirements than Memcached, and with admission control enabled, can ensure that more than certain percentage of requests meet their deadlines.