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- W1480783376 abstract "As the complexity of large-scale enterprise applications increases, providing performance verification through staging becomes an important part of reducing business risks associated with violating sophisticated service-level agreement (SLA). Currently, performance verification during the staging process is accomplished through either an expensive, cumbersome manual approach or ad hoc automation. This paper describes an automation approach as part of the Elba project supporting monitoring and performance analysis of distributed multi-tiered applications that helps in bottleneck detection. We use machinelearning to determine service-level objectives (SLOs) satisfaction and locate bottlenecks in candidate deployment scenarios. We evaluate our tools with TPC-W, an on-line bookstore, and RUBiS, an on-line auction site." @default.
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- W1480783376 date "2006-01-01" @default.
- W1480783376 modified "2023-10-18" @default.
- W1480783376 title "Detecting Bottleneck in n-Tier IT Applications Through Analysis" @default.
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- W1480783376 doi "https://doi.org/10.1007/11907466_13" @default.
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