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Modern datacenters employ server virtualization and consolidation to reduce the cost of operation and to maximize profit. However, interference among consolidated virtual machines (VMs) has barred mission-critical applications due to unpredictable performance. Through extensive measurements of RUBBoS n-tier benchmark, we found a major source of performance unpredictability: the memory thrashing caused...
Consolidating several under-utilized user applications together to achieve higher utilization of hardware resources is important for cloud vendors to reduce cost and maximize profit. In this paper, we study the impact of tuning software resources (e.g., server thread pool size or connection pool size) on n-tier web application performance in a consolidated cloud environment. By measuring CPU utilizations...
The increasing popularity of clouds drives researchers to find answers to a large variety of new and challenging questions. Through extensive experimental measurements, we show variance in performance and scalability of clouds for two non-trivial scenarios. In the first scenario, we target the public Infrastructure as a Service (IaaS) clouds, and study the case when a multi-tier application is migrated...
Performance unpredictability is one of the major concerns slowing down the migration of mission-critical applications into cloud computing infrastructures. An example of non-intuitive result is the measured n-tier application performance in a virtualized environment that showed increasing workload caused a competing, co-located constant workload to decrease its response time. In this paper, we investigate...
The increasing popularity of computing clouds continues to drive both industry and research to provide answers to a large variety of new and challenging questions. We aim to answer some of these questions by evaluating performance and scalability when an n-tier application is migrated from a traditional datacenter environment to an IaaS cloud. We used a representative n-tier macro-benchmark (RUBBoS)...
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