Mazda A. Marvasti

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— We demonstrate an enterprise Dynamic Thresholding System for data-agnostic management of monitoring flows. The dynamic thresholding based on data historical behavior enables adaptive and more accurate control of business environments compared to static thresholding. We manifest the main blocks of a complex analytical engine that is implemented in VMware(More)
We examine the determination of abnormality of streamed data using the statistical structure of the meta-data associated with it. The vital need for such a subject within a heterogeneous log based environment in real-time comes from the fact that most cloud based applications will use text-based logging as a means of reporting application behavior. The(More)
Incorporation of user feedback in enterprise management products can greatly enhance our understanding of modern technology challenges and amplify the ability for those products to home in to user environments. In this paper we present an entropy-based confidence determination approach to process user feedback data (direct or indirect) to automatically rank(More)
Data-agnostic management of today's virtualized and cloud IT infrastructures motivates statistical inference from unstructured or semi-structured data. We introduce a universal approach to the determination of statistically relevant patterns in unstructured data, and then showcase its application to log data of a Virtual Center (VMware's virtualization(More)
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