Usage Report hotel

• Period: August 01 – August 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)

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: August 01 – August 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)

Figure 2: Users count

This time series chart represents daily active user count for cloud services and shows historical changes during the period.

• Period: August 01 – August 31, 2014
• Cloud(IaaS): nimbus
• Hostname: hotel

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: August 01 – August 31, 2014
• Cloud(IaaS): nimbus
• Hostname: hotel

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: August 01 – August 31, 2014
• Cloud(IaaS): nimbus
• Hostname: hotel

Distribution

Figure 5: VM count by wall time

This chart illustrates usage patterns of VM instances in terms of running wall time.

• Period: August 01 – August 31, 2014
• Cloud(IaaS): nimbus
• Hostname: hotel

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: August 01 – August 31, 2014
• Cloud(IaaS): nimbus
• Hostname: hotel

VMs count by project

Project	Value
fg-418:Course: Cloud Computing Class - fourth edition	843
fg-97:FutureGrid and Grid‘5000 Collaboration	134
fg-314:User-friendly tools to play with cloud platforms	30
fg-54:Investigating cloud computing as a solution for analyzing particle physics data	19
fg-224:Nimbus Auto Scale	14

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: August 01 – August 31, 2014
• Cloud(IaaS): nimbus
• Hostname: hotel

VMs count by project leader

Projectleader	Value
Massimo Canonico	873
Mauricio Tsugawa	134
Randall Sobie	19
Pierre Riteau	14

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: August 01 – August 31, 2014
• Cloud(IaaS): nimbus
• Hostname: hotel

VMs count by institution

Institution	Value
University of Piemonte Orientale, Computer Science Department	873
University of Florida	134
University of Victoria	19
University of Chicago	14

Figure 9: Wall time (hours) by project leader

This chart illustrates proportionate total run times by project leader.

• Period: August 01 – August 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.

Figure 10: VMs count by systems (compute nodes) in Cluster (hotel)

This column chart represents VMs count among systems.

• Period: August 01 – August 31, 2014
• Cloud(IaaS): nimbus
• Hostname: hotel

Figure 11: Wall time (hours) by systems (compute nodes) in Cluster (hotel)

This column chart represents wall time among systems.

• Period: August 01 – August 31, 2014
• Cloud(IaaS): nimbus
• Hostname: hotel