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Real production applications ranging from enterprise applications to large e-commerce sites share a crucial but seldom-noted characteristic: The relative frequencies of transaction types in their workloads are <i>nonstationary</i>, i.e., the transaction mix changes over time. Accurately predicting application-level performance in business-critical(More)
— This work considers the problem of hosting multiple third-party Internet services in a cost-effective manner so as to maximize a provider's business objective. For this purpose, we present a dynamic capacity management framework based on an optimization model, which links a cost model based on SLA contracts with an analytical queuing-based performance(More)
As Internet services become ubiquitous, the selection and management of diverse server platforms now affects the bottom line of almost every firm in every industry. Ideally, such cross-platform management would yield high performance at low cost, but in practice, the performance consequences of such decisions are often hard to predict. In this paper, we(More)
Restoring data operations after a disaster is a daunting task: how should recovery be performed to minimize data loss and application downtime? Administrators are under considerable pressure to recover quickly, so they lack time to make good scheduling decisions. They schedule recovery based on rules of thumb, or on pre-determined orders that might not be(More)
Multicore processors promise continued hardware performance improvements even as single-core performance flattens out. However they also enable increasingly complex application software that threatens to obfuscate application-level performance. This paper applies operational analysis to the problem of understanding and predicting application-level(More)
In the TAO project we develop metrics, models, and infrastructure to effectively manage the performance of Web applications. We use WebMon, a novel instrumentation tool to obtain profile data for web interactions, from end-user and system component perspectives. Our analysis techniques help determine important classes of web users and their transactions.(More)
This brief announcement presents a pair of performance laws that bound the change in aggregate job queueing time that results when the processor speed changes in a parallel computing system. Our laws require only lightweight passive external observations of a black-box system and they apply to many commonly employed scheduling policies. By predicting the(More)