KPI-agnostic Control for Fine-Grained Vertical Elasticity
(2017) 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing p.589-598- Abstract
- Applications hosted in the cloud have become indispensable in several contexts, with their performance often being key to business operation and their running costs needing to be minimized. To minimize running costs, most modern virtualization technologies such as Linux Containers, Xen, and KVM offer powerful resource control primitives for individual provisioning - that enable adding or removing of fraction of cores and/or megabytes of memory for as short as few seconds. Despite the technology being ready, there is a lack of proper techniques for fine-grained resource allocation, because there is an inherent challenge in determining the correct composition of resources an application needs, with varying workload, to ensure deterministic... (More)
- Applications hosted in the cloud have become indispensable in several contexts, with their performance often being key to business operation and their running costs needing to be minimized. To minimize running costs, most modern virtualization technologies such as Linux Containers, Xen, and KVM offer powerful resource control primitives for individual provisioning - that enable adding or removing of fraction of cores and/or megabytes of memory for as short as few seconds. Despite the technology being ready, there is a lack of proper techniques for fine-grained resource allocation, because there is an inherent challenge in determining the correct composition of resources an application needs, with varying workload, to ensure deterministic performance.
This paper presents a control-based approach for the management of multiple resources, accounting for the resource consumption, together with the application performance, enabling fine-grained vertical elasticity. The control strategy ensures that the application meets the target performance indicators, consuming as less resources as possible. We carried out an extensive set of experiments using different applications - interactive with response-time requirements, as well as non-interactive with throughput desires - by varying the workload mixes of each application over time. The results demonstrate that our solution precisely provides guaranteed performance while at the same time avoiding both resource over- and under-provisioning. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/44a48b1a-55e6-42cc-a590-30883dcbc602
- author
- Bayuh Lakew, Ewnetu ; Papadopoulos, Alessandro Vittorio LU ; Maggio, Martina LU ; Klein, Cristian and Elmroth, Erik
- organization
- publishing date
- 2017
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID 2017)
- pages
- 589 - 598
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
- conference location
- Madrid, Spain
- conference dates
- 2017-05-14 - 2017-05-17
- external identifiers
-
- scopus:85027250578
- ISBN
- 978-1-5090-6611-7
- DOI
- 10.1109/CCGRID.2017.71
- project
- LCCC
- Cloud Control
- WASP: Autonomous Cloud
- language
- English
- LU publication?
- yes
- id
- 44a48b1a-55e6-42cc-a590-30883dcbc602
- date added to LUP
- 2017-02-23 13:48:06
- date last changed
- 2022-05-02 17:48:28
@inproceedings{44a48b1a-55e6-42cc-a590-30883dcbc602,
abstract = {{Applications hosted in the cloud have become indispensable in several contexts, with their performance often being key to business operation and their running costs needing to be minimized. To minimize running costs, most modern virtualization technologies such as Linux Containers, Xen, and KVM offer powerful resource control primitives for individual provisioning - that enable adding or removing of fraction of cores and/or megabytes of memory for as short as few seconds. Despite the technology being ready, there is a lack of proper techniques for fine-grained resource allocation, because there is an inherent challenge in determining the correct composition of resources an application needs, with varying workload, to ensure deterministic performance.<br/><br/>This paper presents a control-based approach for the management of multiple resources, accounting for the resource consumption, together with the application performance, enabling fine-grained vertical elasticity. The control strategy ensures that the application meets the target performance indicators, consuming as less resources as possible. We carried out an extensive set of experiments using different applications - interactive with response-time requirements, as well as non-interactive with throughput desires - by varying the workload mixes of each application over time. The results demonstrate that our solution precisely provides guaranteed performance while at the same time avoiding both resource over- and under-provisioning.}},
author = {{Bayuh Lakew, Ewnetu and Papadopoulos, Alessandro Vittorio and Maggio, Martina and Klein, Cristian and Elmroth, Erik}},
booktitle = {{17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID 2017)}},
isbn = {{978-1-5090-6611-7}},
language = {{eng}},
pages = {{589--598}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{KPI-agnostic Control for Fine-Grained Vertical Elasticity}},
url = {{https://lup.lub.lu.se/search/files/21810272/main.pdf}},
doi = {{10.1109/CCGRID.2017.71}},
year = {{2017}},
}