
UBITECH’s paper entitled “Towards Platform-Agnostic and Autonomous Orchestration of Big Data Services” has been accepted to be presented at the 7th IEEE International Conference on Big Data Computing Service and Machine Learning Applications (BIGDATASERVICE 2021) held online, worldwide from August 23rd to August 26th, 2021. The UBITECH’s Privacy-preserving Distributed Machine Learning research group presents a comprehensive microservices architecture to ease the management and enactment of end-to[1]end big data workflow management processes. It is developed along with intuitive graphical user interfaces to abstract and hide to the end user the specificities of the underlying network, storage and compute infrastructure. Entitled as Big Data Apps Composition Environment, it facilitates the design, composition, configuration, orchestration, enactment, and validation of end[1]to-end big data analytic services actuated into deployment workflows. The approach of Ms. Iatropoulou, Mr. Petrou, Dr Karagiorgou and Dr Alexandrou differentiates to the current engines, as it adopts a big data-driven methodology which is scalable to multiple executors and has embedded notebooks for on-demand and real-time scripting analytics. Therefore, big data services and analytic applications deployment are being accelerated, while semi-automatic scaling through the definition of multiple executors for improved time performance of demanding tasks is supported.
Continue reading UBITECH presents a scientific paper on big data services autonomous orchestration at IEEE BIGDATASERVICE 2021