Less is not more

Autor: Laurens Versluis, Mehmet Cetin, Caspar Greeven, Kristian Laursen, Damian Podareanu, Valeriu Codreanu, Alexandru Uta, Alexandru Iosup
Přispěvatelé: Computer Science, Computer Systems, Network Institute, Massivizing Computer Systems
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Versluis, L, Cetin, M, Greeven, C, Laursen, K, Podareanu, D, Codreanu, V, Uta, A & Iosup, A 2023, ' Less is not more : We need rich datasets to explore ', Future Generation Computer Systems, vol. 142, pp. 117-130 . https://doi.org/10.1016/j.future.2022.12.022
Future Generation Computer Systems, 142, 117-130. Elsevier
ISSN: 1872-7115
0167-739X
Popis: Traditional datacenter analysis is based on high-level, coarse-grained metrics. This obscures our vision of datacenter behavior, as we do not observe the full picture nor subtleties that might make up these high-level, coarse metrics. There is room for operational improvement based on fine-grained temporal and spatial, low-level metric data. We leverage in this work one of the (rare) public datasets providing fine-grained information on datacenter operations, with over 60 billion measurements captured in 15-second intervals. We show evidence that fine-grained information reveals new operational aspects, that the different metrics cannot be derived from one another (and thus need to be captured), and that many low-level metrics, gathered frequently are key to understanding datacenter operations. We propose a holistic analysis for datacenter operations, providing statistical characterization of node and workload aspects. Our analysis reveals both generic and machine learning-specific aspects, summarized in over 30 observations, providing deep insight into this dataset and the originating cluster. We give actionable insights, surprising findings, and exemplify how our observations support performance-engineering tasks such as workload prediction and long-term datacenter design.
Databáze: OpenAIRE
Externí odkaz: