Unsupervised Real-Time Stream-Based Novelty Detection Technique an Approach in a Corporate Cloud
Anna Vergeles, Alexander Khaya, D. S. Prokopenko, Nataliia Manakova · 2018
A highly loaded cloud application environment requires the highest stability and operability, generates large telemetry data streams. These are obvious and actual prerequisites to develop a workload shift detector for the failures prevention aim. Having studied the previous works, the authors developed an approach to the detection of changepoints based on the specific conditions of the streaming telemetry data. The simulation of data center workload has allowed us to generate telemetry data under specific workload, thus we can evaluate the performance of the detector under various conditions. The conducted experiment has shown the viability of the proposed approach as well as directions for further study and improvement.