Microservices From Cloud to Edge: An Analytical Discussion on Risks, Opportunities and Enablers

Abstract

Microservice applications are made of many interacting microservices that can leverage different cloud servers to distribute the computational load horizontally, so these applications are considered cloud-native. The emergence of edge computing has prompted the research of placement strategies that consider the possibility of instantiating microservices in cloud and edge data centers to improve specific performance metrics, such as the time the application spent serving a user request, also referred to as user delay or makespan. Microservice applications differ in many architectural properties, such as the number of microservices, the number of them involved per request, their dependency graph, and the presence of centralized databases. We found that these properties influence the possibility of a placement strategy to exploit edge resources to reduce user delay; therefore, they constitute an application-level optimization space that, however, has not yet been explored in the literature. Accordingly, this paper contributes to filling this knowledge gap by answering the following question: which are the architectural properties of a microservice application that enable it to be more edge-native, that is, to better reduce user delay by using edge computing? Our results are based on a new analytical modeling of the average user delay provided by a microservice application deployed on cloud/edge resources and a new heuristic placement strategy that take into account key aspects of the application, and the supporting cloud and network environment, not considered by previous literature works.