Horizontal Autoscaling of Virtual Machines in Hybrid Cloud Infrastructures: Current Status, Challenges, and Opportunities

The deployment of virtual machines (VMs) within the Infrastructure as a Service (IaaS) layer across public, private, or hybrid cloud infrastructures is prevalent in various organisational settings for hosting essential business services. However, achieving rapid elasticity, or autoscaling, and ensur...

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Main Authors: Thushantha Lakmal Betti Pillippuge, Zaheer Khan, Kamran Munir
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Encyclopedia
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Online Access:https://www.mdpi.com/2673-8392/5/1/37
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author Thushantha Lakmal Betti Pillippuge
Zaheer Khan
Kamran Munir
author_facet Thushantha Lakmal Betti Pillippuge
Zaheer Khan
Kamran Munir
author_sort Thushantha Lakmal Betti Pillippuge
collection DOAJ
description The deployment of virtual machines (VMs) within the Infrastructure as a Service (IaaS) layer across public, private, or hybrid cloud infrastructures is prevalent in various organisational settings for hosting essential business services. However, achieving rapid elasticity, or autoscaling, and ensuring quality of service amidst fluctuating service demands and available computing resources present significant challenges. Unlike the Platform as a Service (PaaS) and Software as a Service (SaaS) layers, where cloud providers offer managed elasticity features, the VMs at the IaaS layer often lack such capabilities. This paper scrutinises the constraints surrounding the rapid elasticity of VMs within single and hybrid cloud environments at the IaaS layer. It provides a critical analysis of the existing research gaps, emphasising the necessity for the horizontal elasticity of VMs extended across hybrid clouds, coupled with predictive capabilities integrated into the elasticity mechanism. This paper’s focus is particularly beneficial in scenarios where workloads require VM provisioning from multiple clouds to eliminate vendor lock-in and enhance quality of service (QoS) assurances, especially in instances of platform failures. Through critical examination, several research challenges are identified, delineating the existing research gap and outlining future research directions. This paper contributes to the research challenges of VM elasticity in complex cloud environments and underscores the imperative for innovative solutions to address these challenges effectively.
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spelling doaj-art-6efea37d7c4f49e88851f4a6fe7746302025-08-20T02:42:40ZengMDPI AGEncyclopedia2673-83922025-03-01513710.3390/encyclopedia5010037Horizontal Autoscaling of Virtual Machines in Hybrid Cloud Infrastructures: Current Status, Challenges, and OpportunitiesThushantha Lakmal Betti Pillippuge0Zaheer Khan1Kamran Munir2Computer Science Research Centre (CSRC), School of Computing and Creative Technologies, College of Arts, Technology and Environment, University of the West of England (UWE), Bristol BS16 1QY, UKComputer Science Research Centre (CSRC), School of Computing and Creative Technologies, College of Arts, Technology and Environment, University of the West of England (UWE), Bristol BS16 1QY, UKComputer Science Research Centre (CSRC), School of Computing and Creative Technologies, College of Arts, Technology and Environment, University of the West of England (UWE), Bristol BS16 1QY, UKThe deployment of virtual machines (VMs) within the Infrastructure as a Service (IaaS) layer across public, private, or hybrid cloud infrastructures is prevalent in various organisational settings for hosting essential business services. However, achieving rapid elasticity, or autoscaling, and ensuring quality of service amidst fluctuating service demands and available computing resources present significant challenges. Unlike the Platform as a Service (PaaS) and Software as a Service (SaaS) layers, where cloud providers offer managed elasticity features, the VMs at the IaaS layer often lack such capabilities. This paper scrutinises the constraints surrounding the rapid elasticity of VMs within single and hybrid cloud environments at the IaaS layer. It provides a critical analysis of the existing research gaps, emphasising the necessity for the horizontal elasticity of VMs extended across hybrid clouds, coupled with predictive capabilities integrated into the elasticity mechanism. This paper’s focus is particularly beneficial in scenarios where workloads require VM provisioning from multiple clouds to eliminate vendor lock-in and enhance quality of service (QoS) assurances, especially in instances of platform failures. Through critical examination, several research challenges are identified, delineating the existing research gap and outlining future research directions. This paper contributes to the research challenges of VM elasticity in complex cloud environments and underscores the imperative for innovative solutions to address these challenges effectively.https://www.mdpi.com/2673-8392/5/1/37hybrid cloudreactive autoscalingproactive autoscalingelasticityvirtual machine autoscalingautoscaling at IaaS layer
spellingShingle Thushantha Lakmal Betti Pillippuge
Zaheer Khan
Kamran Munir
Horizontal Autoscaling of Virtual Machines in Hybrid Cloud Infrastructures: Current Status, Challenges, and Opportunities
Encyclopedia
hybrid cloud
reactive autoscaling
proactive autoscaling
elasticity
virtual machine autoscaling
autoscaling at IaaS layer
title Horizontal Autoscaling of Virtual Machines in Hybrid Cloud Infrastructures: Current Status, Challenges, and Opportunities
title_full Horizontal Autoscaling of Virtual Machines in Hybrid Cloud Infrastructures: Current Status, Challenges, and Opportunities
title_fullStr Horizontal Autoscaling of Virtual Machines in Hybrid Cloud Infrastructures: Current Status, Challenges, and Opportunities
title_full_unstemmed Horizontal Autoscaling of Virtual Machines in Hybrid Cloud Infrastructures: Current Status, Challenges, and Opportunities
title_short Horizontal Autoscaling of Virtual Machines in Hybrid Cloud Infrastructures: Current Status, Challenges, and Opportunities
title_sort horizontal autoscaling of virtual machines in hybrid cloud infrastructures current status challenges and opportunities
topic hybrid cloud
reactive autoscaling
proactive autoscaling
elasticity
virtual machine autoscaling
autoscaling at IaaS layer
url https://www.mdpi.com/2673-8392/5/1/37
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