Using the machine learning methods for resource management of high availability broadcasting containerized system.

Most of today applications are built on a micro-service architecture, where a large application is divided into different functional parts that can be deployed on many containers that enable good load balancing. Container management tools need system load forecasting means to timely balance system load. It is an important problem for systems with direct streams of popular events which periodically have large splashes of a load. In this paper, we propose the load prediction method for such systems in two cases: usual and broadcasting workload. Also, we propose an architecture of adaptive infrastructure using our load forecasting method. [ABSTRACT FROM AUTHOR]