Boreas – A Service Scheduler for Optimal Kubernetes Deployment

Torgeir Lebesbye, Jacopo Mauro, Gianluca Turin*, Ingrid Chieh Yu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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The advent of cloud computing radically changed the way organisations operate their applications and allows them to achieve high availability of services at affordable cost. Most cloud-computing platforms fostered Kubernetes for their container orchestration and service management. The scheduler is a key component of Kubernetes, as it is responsible for finding the placement of new service containers when they are deployed. The default scheduler is very fast, although often suboptimal. This can lead to inefficient placement of services, or more severely, inability to deploy. We present a custom Kubernetes scheduler, dubbed Boreas, which is designed to evaluate bursts of deployment requests concurrently. Boreas finds the optimal placements for service containers with their deployment constraints by utilising a configuration optimiser. Results show that Boreas is able to find placements where the default Kubernetes scheduler fails, wasting less computing resources, or proving that no feasible deployment solution is possible.

Original languageEnglish
Title of host publicationService-Oriented Computing - 19th International Conference, ICSOC 2021, Proceedings
EditorsHakim Hacid, Odej Kao, Massimo Mecella, Naouel Moha, Hye-young Paik
PublisherSpringer Science+Business Media
Publication date2021
ISBN (Print)9783030914301
Publication statusPublished - 2021
Event19th International Conference on Service-Oriented Computing, ICSOC 2021 - Virtual, online
Duration: 22. Nov 202125. Nov 2021


Conference19th International Conference on Service-Oriented Computing, ICSOC 2021
CityVirtual, online
SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13121 LNCS

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.


  • Cloud service management
  • Kubernetes
  • Scheduling
  • Services on the Cloud


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