Skip to Main content Skip to Navigation
Theses

Automatic Resource Management in Geo-Distributed Multi-Cluster Environments

Mulugeta Ayalew Tamiru 1, 2
2 MYRIADS - Design and Implementation of Autonomous Distributed Systems
Inria Rennes – Bretagne Atlantique , IRISA-D1 - SYSTÈMES LARGE ÉCHELLE
Abstract : Geo-distributed computing environments such as hybrid cloud, multi-cloud and Fog Computing need to be managed autonomously at large scales to improve resource utilization, maximize performance, and save costs. However, resource management in these geo-distributed computing environments is difficult due to wide geographical distributions, poor network conditions, heterogeneity of resources, and limited capacity. In this thesis, we address some of the resource management challenges using container technology. First, we present an experimental analysis of autoscaling in Kubernetes clusters at the container and Virtual Machine levels. Second, we propose a proportional controller to dynamically improve the stability of geo-distributed deployments at run-time in Kubernetes Federations. Finally, we develop a container orchestration framework for geo-distributed environments that offers policy-rich placement, autoscaling, bursting, network routing, and dynamic resource provisioning capabilities.
Complete list of metadata

https://hal.inria.fr/tel-03351598
Contributor : Guillaume Pierre Connect in order to contact the contributor
Submitted on : Wednesday, September 22, 2021 - 2:43:13 PM
Last modification on : Tuesday, October 19, 2021 - 11:04:35 AM

File

mulugeta_phd_thesis_final.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : tel-03351598, version 1
`

Citation

Mulugeta Ayalew Tamiru. Automatic Resource Management in Geo-Distributed Multi-Cluster Environments. Operating Systems [cs.OS]. Université de Rennes 1, 2021. English. ⟨tel-03351598⟩

Share

Metrics

Record views

87

Files downloads

310