Benefits of Pod dimensioning with best-effort resources in bare metal cloud native deployments
Saved in:
| Title: | Benefits of Pod dimensioning with best-effort resources in bare metal cloud native deployments |
|---|---|
| Authors: | Tonini, Federico, 1990, Natalino Da Silva, Carlos, 1987, Temesgene, Dagnachew, Ghebretensae, Zere, Wosinska, Lena, 1951, Monti, Paolo, 1973 |
| Source: | Automation of Network edge Infrastructure & Applications with aRtificiAl intelligence, ANIARA IEEE Networking Letters. 5(1):41-45 |
| Subject Terms: | service degradation, Best-effort resources, Pod dimensioning, Pod as a Service, IaaS, soft-hard isolation, Kubernetes, Cloud native services |
| Description: | 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. |
| File Description: | electronic |
| Access URL: | https://research.chalmers.se/publication/543888 https://research.chalmers.se/publication/534218 https://research.chalmers.se/publication/543888/file/543888_Fulltext.pdf |
| Database: | SwePub |
Full Text Finder 
Nájsť tento článok vo Web of Science | Abstract: | 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 |