Benefits of Pod dimensioning with best-effort resources in bare metal cloud native deployments

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Název: Benefits of Pod dimensioning with best-effort resources in bare metal cloud native deployments
Autoři: Tonini, Federico, 1990, Natalino Da Silva, Carlos, 1987, Temesgene, Dagnachew, Ghebretensae, Zere, Wosinska, Lena, 1951, Monti, Paolo, 1973
Zdroj: Automation of Network edge Infrastructure & Applications with aRtificiAl intelligence, ANIARA IEEE Networking Letters. 5(1):41-45
Témata: service degradation, Best-effort resources, Pod dimensioning, Pod as a Service, IaaS, soft-hard isolation, Kubernetes, Cloud native services
Popis: Container orchestration platforms automatically adjust resources to evolving traffic conditions. However, these scaling mechanisms are reactive and may lead to service degradation. Traditionally, resource dimensioning has been performed considering guaranteed (or request) resources. Recently, container orchestration platforms included the possibility of allocating idle (or limit) resources for a short time in a best-effort fashion. This paper analyzes the potential of using limit resources as a way to mitigate degradation while reducing the number of allocated request resources. Results show that a 25% CPU reduction can be achieved by relying on limit resources.
Popis souboru: electronic
Přístupová URL adresa: https://research.chalmers.se/publication/543888
https://research.chalmers.se/publication/534218
https://research.chalmers.se/publication/543888/file/543888_Fulltext.pdf
Databáze: SwePub
Popis
Abstrakt:Container orchestration platforms automatically adjust resources to evolving traffic conditions. However, these scaling mechanisms are reactive and may lead to service degradation. Traditionally, resource dimensioning has been performed considering guaranteed (or request) resources. Recently, container orchestration platforms included the possibility of allocating idle (or limit) resources for a short time in a best-effort fashion. This paper analyzes the potential of using limit resources as a way to mitigate degradation while reducing the number of allocated request resources. Results show that a 25% CPU reduction can be achieved by relying on limit resources.
ISSN:25763156
DOI:10.1109/LNET.2023.3235106