An Empirical Analysis of VM Startup Times in Public IaaS Clouds: An Extended Report
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VM startup time is an essential factor in designing elastic cloud applications. For example, a cloud application with autoscaling can reduce under- and over-provisioning of VM instances with a precise estimation of VM startup time, and in turn, it is likely to guarantee the application's performance and improve the cost efficiency. However, VM startup time has been little studied, and available measurement results performed previously did not consider various configurations of VMs for modern cloud applications. In this work, we perform comprehensive measurements and analysis of VM startup time from two major cloud providers, namely Amazon Web Services (AWS) and Google Cloud Platform (GCP). With three months of measurements, we collected more than 300,000 data points from each provider by applying a set of configurations, including 11+ VM types, four different data center locations, four VM image sizes, two OS types, and two purchase models (e.g., spot/preemptible VMs vs. on-demand VMs). With extensive analysis, we found that VM startup time can vary significantly because of several important factors, such as VM image sizes, data center locations, VM types, and OS types. Moreover, by comparing with previous measurement results, we confirm that cloud providers (specifically AWS) made significant improvements for the VM startup times and currently have much quicker VM startup times than in the past.
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