An integrated approach for cloud computing service selection and cost estimation

Selecting suitable cloud services and estimating future cloud costs for organizations with a large set of software services is a challenging task. To achieve this, one needs to understand all software applications' cloud service configuration requirements. Further, one needs to estimate how the applications' requirements change over time, e.g., due to scaling with a growing number of application users. Then, one needs to compare for different cloud providers the costs over time of setups matching the requirements. This task, if done manually, is laborious, error prone, and has to be repeated when the organization's business or application requirements change. In my PhD project, I will research an integrated approach that assists users in, on the one hand, finding a cost-optimal selection of cloud services for given requirements and, on the other hand, estimating future costs. I want to achieve this with the support of a software tool integrating existing research on the individual topics and, thereby, allowing to apply and study existing cloud service selection and cost estimation approaches.