KubeKlone: A Digital Twin for Simulating Edge and Cloud Microservices
Ayush Bhardwaj, Theophilus Benson · 2022
Microservices are terraforming the computing landscape with web-scale infrastructures (e.g., Facebook, Google, Amazon) and telecom infrastructures (e.g., ATT, Ericsson) adopting them. At it’s core, the microservices paradigm promotes a decoupling of applications into multiple services – a decoupling that promotes better scalability, fault-tolerance, and deployability. Unfortunately, this decoupling significantly increases the space of configuration options and performance problems, rendering traditional approaches to management ineffective. Recent efforts to address this problem embrace Artificial Intelligence for IT Operations (AIOps). However, training effective AI models requires significant amounts of data and, in some instances, a framework for quickly exploring or analyzing model performance. Digital twins, or simulators, have effectively enabled AI-based management frameworks within other domains (e.g., manufacturing, industrial and automotive).