A Logical Extensible Framework Fault Tolerance Monitoring For Cloud Applications

Abstract

The main goal of any Cloud Computing Provider is to increase the availability of their Cloud system in an affordable manner. Industrial consumer demands centrally controlled Quality of Services (QoS) of the Cloud System infrastructure. Artificial Intelligence Failure Tolerance System is a crucial component of Quality of Services (QoS). Currently fault detection in the Cloud System is restricted to the minimal boundary inspection.  This unique and dynamic approach is tested on the real time data generated by the Amazon Web  Services Outgoing API call server on US1-east region infrastructure. To improve the prediction accuracy, the proposed framework utilizes the Markov Chain Algorithm and Resource Scheduling Algorithm for effectiveness.