Understanding the characteristics of cloud workloads is the key to making optimal configuration decisions and improving the system throughput. However workload characterization of cloud, especially in a large-scale production environment, has not been well studied yet. To gain insights on cloud workloads, we collected a one-week workload trace from a 100-node cloud cluster which hosts 1082 virtual machines. We characterized the workload at the granularity of virtual machines and physical nodes, respectively. We concluded with a set of meaningful observations. The results of workload characterization are representative and generally consistent with cloud cluster for public IaaS service providers, which can help other researchers and engineers understand the performance and VM characteristics of the cloud in their production environments.
CITATION STYLE
Ren, Z., Dong, J., Ren, Y., Zhou, R., & You, X. (2016). Workload characterization on a cloud platform: An early experience. International Journal of Grid and Distributed Computing, 9(6), 259–268. https://doi.org/10.14257/ijgdc.2016.9.6.24
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