Finding Optimized Deployment Strategy for Multitenant Services by Iterative Staging

Abstract

A serious challenge that confronts multi-tenant service systems is finding an optimized deployment strategy according to their business scale and operating characteristics. The tenants want to rent high performance services and services providers demand minimizing cost at the same time of meeting the requirements of tenants. But there are often contradictions between high performance and low cost. Therefore, in order to balance the contradiction, this paper proposes a staging-based optimized deployment method. This method performs iterative optimization based on customized workload generation, continuously emulation and evaluation in a benchmark suite. We demonstrate our method by a case study on a multi-tenant Supplier Business Management (SBM) service, as well as evaluate the capability of our benchmark suite through two sets of experiments. Results from these experiments characterized the relationship between workloads and performance, which can help find optimized deployment strategies for multi-tenant applications. In the case study on multi-tenant SBM service system, we gain an optimized strategy that satisfies the requirement of tenants and makes the maximum use of the resources, which can give useful recommendations in real service instances deployment stage.