Workload-Aware Resource Reservation for Multi-tenant NoSQL

Cloud hosted NoSQL data stores are for economic reasons often shared amongst multiple tenants simultaneously. The NoSQL provider consolidates multiple tenants access into a shared NoSQL instance and provides a dedicated view for each tenant. This multi-tenancy has tenants' data and workloads coexisting in the same node, which under certain conditions can lead to performance degradation of one tenant caused by another. In this paper, we investigate the multi-tenant interference in a common NoSQL store, HBase, and propose a resource reservation framework that reserves resources for prevention and dynamically adjusts the reservations according to tenant resource demands. The framework enforces cache reservation by splitting the cache space and disk reservation by scheduling requests to a distributed file system (DFS). A stochastic hill climbing algorithm is used to find a near-optimum plan for different resources reservations. Empirical results show that the framework can prevent interference and adapt to dynamic workloads under multi-tenancy.