Architecture for IoT applications based on reactive microservices: A performance evaluation

The Internet has evolved from a network interconnecting computers to a complex ecosystem integrating devices of the most varied types, and enabling the amalgamation of the physical and virtual worlds. Integrating these heterogeneous devices fosters novel services and applications that generate value-added information and actionable knowledge for the end-user. Several challenges are involved in the design and building of IoT ecosystems, which have fostered research in the field, in search of patterns, guidelines, methods and tools that support such activities. In terms of architectural patterns, the microservice architectural style has been increasingly adopted in the development of IoT applications and services. Its adoption promotes some essential properties in IoT, such as scalability and extensibility. As there are always tradeoffs involved in every architectural decision, it is important to analyze whether the benefits brought by the use of microservices do not come at the expense of some loss or degradation of application performance. Recent research has analyzed the performance interference of microservices based on edge computing applications. However, a comprehensive assessment of the performance impact of characteristics inherent to the use of reactive microservices on IoT applications is still missing in the literature. In this paper, we present an experimental evaluation of the performance of IoT applications that make use of an architecture based on reactive microservices. The architecture was proposed by our group in a previous work and was tailored for reliable IoT applications running at the edge of the network. The experiments presented in this paper analyze the application performance based on various benchmark scenarios. In addition, we performed load and scalability testing of an IoT application that adopts the architecture components in a hybrid scenario (real devices and emulated devices). The results obtained were promising. The architecture had a good response to the increase in the workload, not presenting errors, crashes or instabilities due to the increase in IoT data traffic. Moreover, analyzing the overhead generated by the architecture components, there was no performance reduction or service unavailability. Such results point to the fact that the adoption of microservices in the construction of IoT systems can bring effective benefits without jeopardizing their performance due to eventually generated overheads.