Print Email Facebook Twitter Capelin Title Capelin: Data-Driven Compute Capacity Procurement for Cloud Datacenters using Portfolios of Scenarios Author Andreadis, G. (TU Delft Algorithmics) Mastenbroek, Fabian Mastenbroek (Student TU Delft) van Beek, V.S. (TU Delft Dataintensive Systems; Solvinity) Iosup, A. (TU Delft Dataintensive Systems) Date 2021 Abstract Cloud datacenters provide a backbone to our digital society. Inaccurate capacity procurement for cloud datacenters can lead to significant performance degradation, denser targets for failure, and unsustainable energy consumption. Although this activity is core to improving cloud infrastructure, relatively few comprehensive approaches and support tools exist for mid-tier operators, leaving many planners with merely rule-of-thumb judgement. We derive requirements from a unique survey of experts in charge of diverse datacenters in several countries. We propose Capelin, a data-driven, scenario-based capacity planning system for mid-tier cloud datacenters. Capelin introduces the notion of portfolios of scenarios, which it leverages in its probing for alternative capacity-plans. At the core of the system, a trace-based, discrete-event simulator enables the exploration of different possible topologies, with support for scaling the volume, variety, and velocity of resources, and for horizontal (scale-out) and vertical (scale-up) scaling. Capelin compares alternative topologies and for each gives detailed quantitative operational information, which could facilitate human decisions of capacity planning. We implement and open-source Capelin, and show through comprehensive trace-based experiments it can aid practitioners. The results give evidence that reasonable choices can be worse by a factor of 1.5-2.0 than the best, in terms of performance degradation or energy consumption. Subject Cloudcapacity planningdatacenterpractitioner surveyprocurementsimulation To reference this document use: http://resolver.tudelft.nl/uuid:34e49fb3-f3b0-48b4-9762-78420da42605 DOI https://doi.org/10.1109/TPDS.2021.3084816 ISSN 1045-9219 Source IEEE Transactions on Parallel and Distributed Systems, 33 (1), 26-39 Bibliographical note Accepted author manuscript Part of collection Institutional Repository Document type journal article Rights © 2021 G. Andreadis, Fabian Mastenbroek Mastenbroek, V.S. van Beek, A. Iosup Files PDF 09444213.pdf 1.95 MB Close viewer /islandora/object/uuid:34e49fb3-f3b0-48b4-9762-78420da42605/datastream/OBJ/view