OSμS: An Open-Source Microservice Prototyping Platform.

One major advantage of microservice cloud architectures is the agility with which microservices can be replicated to help improve the overall quality of service and meet service-level contracts. Their challenge is to carefully balance the horizontal microservice replicas with the vertical resources of CPU, memory, and IO that are allocated to each microservice. The objective of such balancing act is, of course, to avoid both service bottlenecks and resource wastage. In this paper, we present OSμS, a new open-source microservice prototyping platform that has been developed and instrumented from the ground up with the objective of collecting fine-grained, non-proprietary metrology on microservice mesh performance. We will illustrate the use of OSμS for developing and evaluating machine-learning algorithms for the horizontal and vertical autoscaling of microservice architectures. A hybrid algorithm based on decision-tree learning will be implemented on OSμS and compared with the academic state of the art and existing cloud-provider solutions. The advantages of such algorithm in improving horizontal and vertical resource utilization will be highlighted.