Axiomatic Cloud Computing Architectural Design

Abstract

Modern cloud computing makes available a plethora of scalable cloud computing offerings. The cloud is increasingly becoming the backbone of the highly complex modern knowledge-economy that includes Social, Mobile, IoT, Big-Data and AI. Knowledge-based products and services follow fat-tail distributions such as the power-law that poses major opportunities and challenges for the designer. The Axiomatic Designer is uniquely positioned in designing for the de-novo situations that the fat-tailed distributions expose. Also, the cloud frees-up the architectural decision-making away from the legacy compatibility-burden, and towards various cloud-native (i.e., de-novo/solution-neutral) as well as hybrid (on-prem/cloud & cloud/cloud) architectures. Further more, the competitive landscape around the cloud is not static; it is adaptive and evolving rapidly. Here again, Axiomatic Design (AD) is uniquely positioned in rising upto the various de-novo challenges This, however, requires contributions from frameworks such as Knowledge-as-Heterarchically-Hierarchical (KA|h|H), Stigmergy, Complex Adaptive Systems (CAS), Cynefin, Boyd’s OODA-Loop Theory of asymmetric fast-transients, Axiomatic-Maturity-Diagram (AMD), as well as Weick’s Loose-Coupling approach to help unify and strengthen the Axiomatic approach. This paper unifies the above approaches in order to tackle the architectural challenges of cloud computing.