Capacity planning and performance modeling: from mainframes to client-server systems
Capacity planning and performance modeling: from mainframes to client-server systems
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DSN '11 Proceedings of the 2011 IEEE/IFIP 41st International Conference on Dependable Systems&Networks
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Performance Evaluation
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Management decisions to achieve peak performance operations, scalability and availability in distributed systems require a continuous statistical characterization of data sets coming from server and network monitors. Due to the increasing sizes of data centers and their continuous dynamic changes, the traditional approaches that work on all data sets in a centralized way are impractical. We propose a strategy for data processing that is able to limit the analysis of the large sets of collected measures to a smaller subset of significant information for a twofold purpose: to classify the collected data sets in few classes characterized by similar statistical behaviors, to evaluate the dynamics of the overall system and its most relevant changes. The proposed strategy works at the level of server resources and of significant aggregation of servers of the overall distributed system. Several experimental results demonstrate the feasibility of the proposed strategy that is validated in real contexts.