Resource management for service level aware cloud applications

Resource allocation in clouds is mostly done assuming hard requirements, time-sensitive applications either receive the requested resources or fail. Given the dynamic nature of workloads, guaranteeing on-demand allocations requires large spare capacity. Hence, one cannot have a system that is both reliable and efficient. To mitigate this issue, we introduce service-level awareness in clouds, assuming applications contain some optional code that can be dynamically deactivated as needed. We propose a resource manager that allocates resources to multiple service-level-aware applications in a fair manner. To show the practical applicability, we implemented service-level-aware versions of RUBiS and RUBBoS, two popular cloud benchmarks, together with our resource manager. Experiments show that service-level awareness helps in withstanding flash-crowds or failures, opening up more flexibility in cloud resource management