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BURN: Enabling Workload Burstiness in Customized Service Benchmarks

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4 Author(s)
Giuliano Casale ; Imperial College London, London ; Amir Kalbasi ; Diwakar Krishnamurthy ; Jerry Rolia

We introduce BURN, a methodology to create customized benchmarks for testing multitier applications under time-varying resource usage conditions. Starting from a set of preexisting test workloads, BURN finds a policy that interleaves their execution to stress the multitier application and generate controlled burstiness in resource consumption. This is useful to study, in a controlled way, the robustness of software services to sudden changes in the workload characteristics and in the usage levels of the resources. The problem is tackled by a model-based technique which first generates Markov models to describe resource consumption patterns of each test workload. Then, a policy is generated using an optimization program which sets as constraints a target request mix and user-specified levels of burstiness at the different resources in the system. Burstiness is quantified using a novel metric called overdemand, which describes in a natural way the tendency of a workload to keep a resource congested for long periods of time and across multiple requests. A case study based on a three-tier application testbed shows that our method is able to control and predict burstiness for session service demands at a fine-grained scale. Furthermore, experiments demonstrate that for any given request mix our approach can expose latency and throughput degradations not found with nonbursty workloads having the same request mix.

Published in:

IEEE Transactions on Software Engineering  (Volume:38 ,  Issue: 4 )