Model-Based Self-Aware Performance and Resource Management Using the Descartes Modeling Language

Abstract

We present the results of our recent work published in [Hu17] and summarized in [Ko16]. We introduce a holistic model-based approach for self-aware performance and resource management of modern IT systems and infrastructures. Based on a novel online performance prediction process, we implement a model-based control loop for proactive system adaptation. We evaluate our approach in the context of two representative case studies showing that with the proposed methods, significant resource efficiency gains can be achieved while maintaining performance requirements. These results represent the first end-to-end validation of our approach, demonstrating its potential for self-aware performance and resource management of modern IT systems and infrastructures.