Szczegóły publikacji

Opis bibliograficzny

Auto-scaling of scientific workflows in Kubernetes / Bartosz BALIŚ, Andrzej Broński, Mateusz Szarek // W: Computational Science – ICCS 2022 : 22nd international conference : London, UK, June 21–23, 2022 : proceedings, Pt. 2 / eds. Derek Groen, [et al.]. — Cham : Springer Nature Switzerland, cop. 2022. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 13351). — ISBN: 978-3-031-08753-0; e-ISBN: 978-3-031-08754-7. — S. 33–40. — Bibliogr., Abstr. — Publikacja dostępna online od: 2022-06-15


Autorzy (3)


Słowa kluczowe

Kubernetesscientific workflowsauto scaling

Dane bibliometryczne

ID BaDAP140682
Data dodania do BaDAP2022-06-24
DOI10.1007/978-3-031-08754-7_5
Rok publikacji2022
Typ publikacjimateriały konferencyjne (aut.)
Otwarty dostęptak
WydawcaSpringer
Konferencja22nd International Conference on Computational Science
Czasopismo/seriaLecture Notes in Computer Science

Abstract

Kubernetes has gained extreme popularity as a cloud-native platform for distributed applications. However, scientific computations which typically consist of a large number of jobs – such as scientific workflows – are not typical workloads for which Kubernetes was designed. In this paper, we investigate the problem of autoscaling, i.e. adjusting the computing infrastructure to the current resource demands. We propose a solution for auto-scaling that takes advantage of the known workflow structure to improve scaling decisions by predicting resource demands for the near future. Such a predictive autoscaling policy is experimentally evaluated and compared to a regular reactive policy where only the current demand is taken into account. The experimental evaluation is done using the HyperFlow workflow management systems running five simultaneous instances of the Montage workflow on a Kubernetes cluster deployed in the Google Cloud Platform. The results indicate that the predictive policy allows achieving better elasticity and execution time, while reducing monetary cost.

Publikacje, które mogą Cię zainteresować

fragment książki
Cloud infrastructure automation for scientific workflows / Bartosz BALIŚ, Michał ORZECHOWSKI, Krystian Pawlik, Maciej PAWLIK, Maciej MALAWSKI // W: Parallel Processing and Applied Mathematics : 13th international conference, PPAM 2019 : Białystok, Poland, September 8–11, 2019 : revised selected papers, Pt. 1 / eds. Roman Wyrzykowski [et al.]. — Cham : Springer Nature Switzerland, cop. 2020. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 12043. Theoretical Computer Science and General Issues ; ISSN 0302-9743). — ISBN: 978-3-030-43228-7; e-ISBN:  978-3-030-43229-4. — S. 287–297. — Bibliogr. s. 296–297, Abstr. — Publikacja dostępna online od: 2020-03-19
fragment książki
Reproducibility of computational experiments on Kubernetes-managed container clouds with HyperFlow / Michał ORZECHOWSKI, Bartosz BALIŚ, Renata G. SŁOTA, Jacek KITOWSKI // W: Computational Science - ICCS 2020 : 20th International Conference : Amsterdam, The Netherlands, June 3–5, 2020 : proceedings, Pt. 1 / eds. Valeria V. Krzhizhanovskaya, [et al.]. — Cham : Springer Nature Switzerland, cop. 2020. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 12137. Theoretical Computer Science and General Issues ; ISSN 0302-9743). — ISBN: 978-3-030-50370-3; e-ISBN: 978-3-030-50371-0. — S. 220–233. — Bibliogr. s. 232–233, Abstr. — Publikacja dostępna online od: 2020-06-15. — J. Kitowski - dod. afiliacja: ACK Cyfronet AGH