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...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Encyclopedia |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-8392/5/1/37 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|---|
| ISSN: | 2673-8392 |