Review Article Open Access January 10, 2022

Composable Infrastructure: Towards Dynamic Resource Allocation in Multi-Cloud Environments

1
Cloud AI ML Engineer, Equinix Dallas, USA
2
Research Assistant, USA
3
Data Engineering Lead, Microsoft, USA
Page(s): 1-15
Received
July 12, 2021
Revised
November 03, 2021
Accepted
December 02, 2021
Published
January 10, 2022
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright: Copyright © The Author(s), 2022. Published by Scientific Publications
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APA Style
Vankayalapati, R. K. , Edward, A. , & Yasmeen, Z. (2022). Composable Infrastructure: Towards Dynamic Resource Allocation in Multi-Cloud Environments. Current Research in Public Health, 1(1), 1-15. https://doi.org/10.31586/ujcsc.2022.1222
ACS Style
Vankayalapati, R. K. ; Edward, A. ; Yasmeen, Z. Composable Infrastructure: Towards Dynamic Resource Allocation in Multi-Cloud Environments. Current Research in Public Health 2022 1(1), 1-15. https://doi.org/10.31586/ujcsc.2022.1222
Chicago/Turabian Style
Vankayalapati, Ravi Kumar, Andrew Edward, and Zakera Yasmeen. 2022. "Composable Infrastructure: Towards Dynamic Resource Allocation in Multi-Cloud Environments". Current Research in Public Health 1, no. 1: 1-15. https://doi.org/10.31586/ujcsc.2022.1222
AMA Style
Vankayalapati RK, Edward A, Yasmeen Z. Composable Infrastructure: Towards Dynamic Resource Allocation in Multi-Cloud Environments. Current Research in Public Health. 2022; 1(1):1-15. https://doi.org/10.31586/ujcsc.2022.1222
@Article{crph1222,
AUTHOR = {Vankayalapati, Ravi Kumar and Edward, Andrew and Yasmeen, Zakera},
TITLE = {Composable Infrastructure: Towards Dynamic Resource Allocation in Multi-Cloud Environments},
JOURNAL = {Current Research in Public Health},
VOLUME = {1},
YEAR = {2022},
NUMBER = {1},
PAGES = {1-15},
URL = {https://www.scipublications.com/journal/index.php/UJCSC/article/view/1222},
ISSN = {2831-5162},
DOI = {10.31586/ujcsc.2022.1222},
ABSTRACT = {To ensure maximum flexibility, service providers offer a variety of computing options with regard to CPU, memory capacity, and network bandwidth. At the same time, the efficient operation of current cloud applications requires an infrastructure that can adjust its configuration continuously across multiple dimensions, which are generally not statically predefined. Our research shows that these requirements are hardly met with today's typical public cloud and management approaches. To provide such a highly dynamic and flexible execution environment, we propose the application-driven autonomic management of data center resources as the core vision for the development of a future cloud infrastructure. As part of this vision and the required gradual progress toward it, we present the concept of composable infrastructure and its impact on resource allocation for multi-cloud environments. We introduce relevant techniques for optimizing resource allocation strategies and indicate future research opportunities [1]. Many cloud service providers offer computing instances that can be configured with arbitrary capacity, depending on the availability of certain hardware resources. This level of configurability provides customers with the desired flexibility for executing their applications. Because of the large number of such prerequisite instances with often varying characteristics, service consumers must invest considerable effort to set up or reconfigure elaborate resource provisioning systems. Most importantly, they must differentiate the loads to be distributed between jobs that need to be executed versus placeholder jobs, i.e., jobs that trigger the automatic elasticity functionality responsible for resource allocator reconfiguration. Operations research reveals that the optimization of resource allocator reconfiguration strategies is a fundamentally difficult problem due to its NP-hardness. Despite these challenges, dynamic resource allocation in multi-clouds is becoming increasingly important since modern Internet-based service settings are dispersed across multiple providers [2].},
}
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AB  - To ensure maximum flexibility, service providers offer a variety of computing options with regard to CPU, memory capacity, and network bandwidth. At the same time, the efficient operation of current cloud applications requires an infrastructure that can adjust its configuration continuously across multiple dimensions, which are generally not statically predefined. Our research shows that these requirements are hardly met with today's typical public cloud and management approaches. To provide such a highly dynamic and flexible execution environment, we propose the application-driven autonomic management of data center resources as the core vision for the development of a future cloud infrastructure. As part of this vision and the required gradual progress toward it, we present the concept of composable infrastructure and its impact on resource allocation for multi-cloud environments. We introduce relevant techniques for optimizing resource allocation strategies and indicate future research opportunities [1]. Many cloud service providers offer computing instances that can be configured with arbitrary capacity, depending on the availability of certain hardware resources. This level of configurability provides customers with the desired flexibility for executing their applications. Because of the large number of such prerequisite instances with often varying characteristics, service consumers must invest considerable effort to set up or reconfigure elaborate resource provisioning systems. Most importantly, they must differentiate the loads to be distributed between jobs that need to be executed versus placeholder jobs, i.e., jobs that trigger the automatic elasticity functionality responsible for resource allocator reconfiguration. Operations research reveals that the optimization of resource allocator reconfiguration strategies is a fundamentally difficult problem due to its NP-hardness. Despite these challenges, dynamic resource allocation in multi-clouds is becoming increasingly important since modern Internet-based service settings are dispersed across multiple providers [2].
DO  - Composable Infrastructure: Towards Dynamic Resource Allocation in Multi-Cloud Environments
TI  - 10.31586/ujcsc.2022.1222
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