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Usage Report hotel

  • Period: July 01 – July 31, 2014
  • 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, 2014

  • 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, 2014
  • 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, 2014
  • 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, 2014
  • 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, 2014
  • 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, 2014
  • Cloud(IaaS): nimbus
  • Hostname: hotel
VMs count by project
Project Value
fg-54:Investigating cloud computing as a solution for analyzing particle physics data 1337
fg-418:Course: Cloud Computing Class - fourth edition 1008
fg-97:FutureGrid and Grid‘5000 Collaboration 142
fg-314:User-friendly tools to play with cloud platforms 103
fg-213:Course: Cloud Computing class - second edition 8
fg-445:Deployment of Virtual Clusters on a Commercial Cloud Platform for Molecular Docking 6
fg-341:Course: Parallel Computing 3
fg-224:Nimbus Auto Scale 1
fg-13:FutureGrid Systems Development and Prototyping 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, 2014
  • Cloud(IaaS): nimbus
  • Hostname: hotel
VMs count by project leader
Projectleader Value
Randall Sobie 1337
Massimo Canonico 1119
Mauricio Tsugawa 142
Anthony Nguyen 6
Wilson Rivera 3
Sharif Islam 1
Pierre Riteau 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, 2014
  • Cloud(IaaS): nimbus
  • Hostname: hotel
VMs count by institution
Institution Value
University of Victoria 1337
University of Piemonte Orientale, Computer Science Department 1111
University of Florida 142
University of Piemonte Orientale 8
University of California, San Diego, PRIME/PRAGMA 6
University of Puerto Rico, Electrical and Computer Emgineering D 3
University of Chicago 1
Indiana University 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, 2014
  • 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, 2014
  • 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, 2014
  • Cloud(IaaS): nimbus
  • Hostname: hotel