Modern IT systems frequently employ virtualization technology to maximize resource efficiency. By sharing physical resources, however, the virtualized storage used in such environments can quickly become a bottleneck. Performance modeling and evaluation techniques applied prior to system deployment help to avoid performance issues. In current practice, however, modeling I/O performance is usually avoided due to the increasing complexity of modern virtualized storage systems. In this paper, we present an automated modeling approach based on statistical regression techniques to analyze I/O performance and interference effects in the context of virtualized storage systems. We demonstrate our approach in three case studies creating performance models with two I/O benchmarks. The case studies are conducted in a real-world environment based on IBM System z and IBM DS8700 server hardware. Using our approach, we effectively create performance models with excellent prediction accuracy for both I/O-intensive applications and I/O performance interference effects with a mean prediction error up to 7%.

Middleware performance models are useful building blocks in the performance models of distributed software applications. We focus on performance models of messaging middleware implementing the Java Message Service standard, showing how certain system design properties -including pipelined processing and message coalescing -interact to create performance behavior that the existing models do not capture accurately. We construct a performance model of the ActiveMQ messaging middleware that addresses the outlined issues and discuss how the approach extends to other middleware implementations.

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