Abstract
When monitoring cloud infrastructure, the monitoring data related to a particular resource or entity are typically produced by multiple distributed producers spread across many individual computing nodes. In order to determine the state and behavior of a particular resource all the relevant data must be collected, processed, and evaluated without overloading the computing resources and flooding the network. Such a task is becoming harder with the ever growing volume, velocity, and variability of monitoring data produced by modern cloud datacenters. In this paper we propose a general distributed event-driven monitoring model enabling multiple simultaneous consumers a real-time collection, processing, and analysis of monitoring data related to the behavior and state of many distributed entities.
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