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Usage Report hotel

  • Period: July 01 – July 31, 2013
  • Hostname: hotel.futuregrid.org
  • Services: nimbus
  • 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

  • Hostname: hotel

  • 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
  • Hostname: hotel
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
  • Hostname: hotel
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
  • Hostname: hotel

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
  • Hostname: hotel
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
  • Hostname: hotel
VMs count by project
Project Value
fg-54:Investigating cloud computing as a solution for analyzing particle physics data 620
Others 330
fg-172:Cloud-TM 323
fg-136:JGC-DataCloud-2012 paper experiments 123
fg-82:FG General Software Development 98
fg-97:FutureGrid and Grid‘5000 Collaboration 64
fg-52:Cost-Aware Cloud Computing 24
fg-130:Optimizing Scientific Workflows on Clouds 24
fg-201:ExTENCI Testing, Validation, and Performance 3
fg-213:Course: Cloud Computing class - second edition 2
fg-10:TeraGrid XD TIS(Technology Insertion Service) Technology Evaluation Laboratory 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
  • Hostname: hotel
VMs count by project leader
Projectleader Value
Randall Sobie 620
Others 330
Paolo Romano 323
Mats Rynge 123
Gregor von Laszewski 98
Mauricio Tsugawa 64
David Lowenthal 24
Weiwei Chen 24
Preston Smith 3
Massimo Canonico 2
John Lockman 1
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
  • Hostname: hotel
VMs count by institution
Institution Value
University of Victoria 620
Others 330
INESC ID 323
USC 123
Indiana University 98
University of Florida 64
University of Southern California 24
University of Arizona 24
Purdue University 3
University of Piemonte Orientale 2
University of Texas at Austin 1
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
  • Hostname: hotel

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