Phi: A Generic Microservices-Based Big Data Architecture

We present in this paper Phi, a generic microservices-based Big Data architecture dedicated to complex multi-layered systems, that rallies multiple machine learning jobs, stream and batch processing. We show how to apply our architecture to an adaptive e-learning application that adjusts its recommendation to the emotions of the learner on the spot. We deploy our application on the cloud using AWS services, and perform some performance tests to show its feasibility in a realistic environment.