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Usage Report sierra

  • Period: July 01 – July 31, 2013
  • Hostname: sierra.futuregrid.org
  • Services: nimbus, openstack, eucalyptus
  • Metrics: VMs count, Users count, Wall time (hours), Distribution by wall time, project, project leader, and institution, and systems

Histogram

Summary (Monthly)

Average Monthly Usage Data (Wall time, Launched VMs, Users)
Figure 1: Average monthly usage data (wall time (hour), launched VMs, users)
This mixed chart represents average monthly usage as to wall time (hour), the number of VM instances and active users.
  • Period: July 01 – July 31, 2013

  • Cloud(IaaS): nimbus, openstack, eucalyptus

  • Hostname: sierra

  • Metric:
    • Runtime (Wall time hours): Sum of time elapsed from launch to termination of VM instances
    • Count (VM count): The number of launched VM instances
    • User count (Active): The number of users who launched VMs

Summary (Daily)

Users count (daily)
Figure 2: Users count
This time series chart represents daily active user count for cloud services and shows historical changes during the period.
  • Period: July 01 – July 31, 2013
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
VMs count (daily)
Figure 3: VMs count
This time series chart represents the number of daily launched VM instances for cloud services and shows historical changes during the period.
  • Period: July 01 – July 31, 2013
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
Wall time (hours, daily)
Figure 4: Wall time (hours)
This time series chart represents daily wall time (hours) for cloud services and shows historical changes during the period.
  • Period: July 01 – July 31, 2013
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra

Distribution

VM count by wall time
Figure 5: VM count by wall time
This chart illustrates usage patterns of VM instances in terms of running wall time.
  • Period: July 01 – July 31, 2013
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
VMs count by project
Figure 6: VMs count by project
This chart illustrates the proportion of launched VM instances by project groups. The same data in tabular form follows.
  • Period: July 01 – July 31, 2013
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
VMs count by project
Project Value
fg-52:Cost-Aware Cloud Computing 568
fg-40:Inca 241
fg-54:Investigating cloud computing as a solution for analyzing particle physics data 202
fg-224:Nimbus Auto Scale 196
fg-346:Course: Example Course On Advanced Cloud Computing 144
fg-214:Mining Interactions between Network Community Structure and Information Diffusion 95
fg-168:Next Generation Sequencing in the Cloud 43
fg-316:Course: Cloud Computing Class - third edition 33
fg-82:FG General Software Development 21
fg-97:FutureGrid and Grid‘5000 Collaboration 10
fg-1:Peer-to-peer overlay networks and applications in virtual networks and virtual clusters 7
fg-264:Course: 1st Workshop on bioKepler Tools and Its Applications 5
fg-356:IPython pipelines for training life sciences researchers on NGS data analysis 3
fg-298:FRIEDA: Flexible Robust Intelligent Elastic Data Management 3
fg-251:Course: Fall 2012 B534 Distributed Systems Graduate Course 3
fg-244:Course: Data Center Scale Computing 2
fg-314:User-friendly tools to play with cloud platforms 1
VMs count by project leader
Figure 7: VMs count by project leader
This chart also illustrates the proportion of launched VM instances by project Leader. The same data in tabular form follows.
  • Period: July 01 – July 31, 2013
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
VMs count by project leader
Projectleader Value
David Lowenthal 568
Shava Smallen 241
Randall Sobie 202
Pierre Riteau 196
Albert Elfstein 144
Yong-Yeol Ahn 95
Jonathan Klinginsmith 43
Massimo Canonico 34
Gregor von Laszewski 21
Mauricio Tsugawa 10
Renato Figueiredo 7
Ilkay Altintas 5
Lavanya Ramakrishnan 3
Todd Blevins 3
Judy Qiu 3
Dirk Grunwald 2
VMs count by institution
Figure 8: VMs count by institution
This chart illustrates the proportion of launched VM instances by Institution. The same data in tabular form follows.
  • Period: July 01 – July 31, 2013
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
VMs count by institution
Institution Value
University of Arizona 568
UC San Diego 241
University of Victoria 202
University of Chicago 196
Indiana University 162
Indiana University, Computer Science Department 144
University of Piemonte Orientale, Computer Science Department 34
University of Florida 17
UCSD 5
Indiana University, Depts of Biology and Molecular and Cellular 3
Lawrence Berkeley National Lab 3
Univ. of Colorado 2
Wall time (hours) by project leader
Figure 9: Wall time (hours) by project leader
This chart illustrates proportionate total run times by project leader.
  • Period: July 01 – July 31, 2013
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra

System information

System information shows utilization distribution as to VMs count and wall time. Each cluster represents a compute node.

VMs count by systems in Cluster (sierra)
Figure 10: VMs count by systems (compute nodes) in Cluster (sierra)
This column chart represents VMs count among systems.
  • Period: July 01 – July 31, 2013
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
Wall time (hours) by systems in Cluster (sierra)
Figure 11: Wall time (hours) by systems (compute nodes) in Cluster (sierra)
This column chart represents wall time among systems.
  • Period: July 01 – July 31, 2013
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra