Drăgan, IoanIuhasz, GabrielPetcu, Dana2020-04-222020-09-012019-09Journal of grid computing 17(3), Pp. 503-5281570-78731572-9184 (online)https://hdl.handle.net/10016/30175ASPIDE: Exascale programIng models for extreme data processingLatest advances in information technology and the widespread growth in different areas are producing large amounts of data. Consequently, in the past decade a large number of distributed platforms for storing and processing large datasets have been proposed. Whether in development or in production, monitoring the applications running on these platforms is not an easy task, dedicated tools and platforms were proposed for this task yet none are specially designed for Big Data frameworks. In this paper we present a distributed, scalable, highly available platform able to collect, store, query and process monitoring data obtained from multiple Big Data frameworks. Alongside the architecture we experimentally show that the solution proposed is scalable and can handle a substantial quantity of monitoring data.26eng© Springer Nature B.V.Big dataCloud computingMonitoringBig data applicationsScalable monitoringresearch articleInformáticahttps://doi.org/10.1007/s10723-019-09483-1open access5033528Journal of grid computing17