Workload Characterization for a Non-Hyperscale Public Cloud Platform
Loïc Pérennou, Mar Callau-Zori, Sylvain Lefebvre, Raka Chiky · 2019
The improvement of automated resource management techniques for cloud computing platforms requires a deep understanding of the workload. Previous works focused on virtual machines (VMs), and neglected complementary virtual resources such as images, volumes, snapshots and security groups. Besides, most attention went to public hyperscale platforms with more than ten thousand servers, or small on-premise platforms. To fill the gap, we perform a holistic workload characterization of a non-hyperscale platform. We have collected a three-month-long trace allowing us to characterize the correlated utilization of virtual resources; the consumption of CPU, memory and disk by VMs; and the CPU interferences between VMs.