
The main feature of a cloud application is its scalability. Major IaaS cloud services providers (CSP) employ autoscaling on the level of virtual machines (VM). Other virtualization solutions (e.g. containers, pods) can also scale. An application scales in response to change in observed metrics, e.g. in CPU utilization. Occasionally, cloud applications exhibit the inability to meet the Quality of Service (QoS) requirements during the scaling caused by the reactivity of autoscaling solutions. This paper provides the results of the autoscaling performance evaluation for two-layered virtualization (VMs and Kubernetes pods) conducted in the public clouds of AWS, Microsoft and Google using the approach and the Autoscaling Performance Measurement Tool developed by the authors.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 17 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
