The carbon footprint of data centers increases further as ever more services are hosted in the cloud, leveraging the need for an efficient management of the available resources. State-of-the-art servers exhibit a linear relationship between resource and power usage, but software optimizations such as intelligent provisioning can increase the energy efficiency, reducing both the energy consumption and operational costs. Furthermore, cloud providers struggle with the heterogeneity of virtualization technologies, cloud management platforms and the underlying physical resources, and with the upcoming popularity of container-based virtualization technologies, the question arises how well these technologies perform regarding performance and isolation compared to traditional VM technologies.
Within IDLab, the Internet Technology and Data Science Lab, we have been working on the development of a highly interoperable platform that supports application deployment on a variety of cloud management frameworks. The platform can be used for developing and evaluating multiple intelligent VM / container / resource allocation algorithms on top of the supported cloud platforms, and allows researchers to quickly setup experiments without having to dive deep into the complex details of the underlying technologies.