Statistical Characterization of Business-Critical Workloads Hosted in Cloud Datacenters

Siqi Shen, Vincent van Beek, Alexandru Iosup

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review


Business-critical workloads - web servers, mail servers, app servers, etc. - are increasingly hosted in virtualized data enters acting as Infrastructure-as-a-Service clouds (cloud data enters). Understanding how business-critical workloads demand and use resources is key in capacity sizing, in infrastructure operation and testing, and in application performance management. However, relatively little is currently known about these workloads, because the information is complex - larges-scale, heterogeneous, shared-clusters - and because datacenter operators remain reluctant to share such information. Moreover, the few operators that have shared data (e.g., Google and several supercomputing centers) have enabled studies in business intelligence (MapReduce), search, and scientific computing (HPC), but not in business-critical workloads. To alleviate this situation, in this work we conduct a comprehensive study of business-critical workloads hosted in cloud data enters. We collect two large-scale and long-term workload traces corresponding to requested and actually used resources in a distributed datacenter servicing business-critical workloads. We perform an in-depth analysis about workload traces. Our study sheds light into the workload of cloud data enters hosting business-critical workloads. The results of this work can be used as a basis to develop efficient resource management mechanisms for data enters. Moreover, the traces we released in this work can be used for workload verification, modelling and for evaluating resource scheduling policies, etc.
Original languageEnglish
Title of host publication15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2015, Shenzhen, China, May 4-7, 2015
PublisherInstitute of Electrical and Electronics Engineers, Inc.
Number of pages10
ISBN (Electronic)9781479980062
Publication statusPublished - 7 Jul 2015
Externally publishedYes
Event15th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2015 - Shenzhen, China
Duration: 4 May 20157 May 2015


Conference15th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2015


  • Characterization
  • Datacenters
  • Workload


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