Estimating the Deployment Time for Cloud Applications using Novel Google Kubernetes Cloud Service over Microsoft Kubernetes Cloud Service

Abstract

Aim: The aim of the study is to estimate the time to deploy cloud applications using novel google kubernetes cloud service over microsoft kubernetes cloud service. Materials and Methods: Sample groups that are considered in the project can be classified into two each has 20 samples, one for Novel google kubernetes cloud service and other for Microsoft kubernetes cloud service, which are tested using 0.80 for G-power to determine the sample size and for t-test analysis. 20 cloud applications have been used in each group for estimating deployment time. Results: The novel google kubernetes cloud service with efficient accuracy of 83.40%, which by far seems to be better than the Microsoft kubernetes cloud service which gives around 61.60%. The significance is around 0.222 (p>0.05) and therefore there is a statistical insignificant difference among the study group. Conclusion: Novel Google kubernetes cloud service seems to be better in deploying cloud applications over the Microsoft kubernetes cloud service.