Usage Report alamo

• Period: January 01 – March 31, 2014
• Hostname: alamo.futuregrid.org
• Services: nimbus, openstack
• 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: January 01 – March 31, 2014

• Cloud(IaaS): nimbus, openstack

• Hostname: alamo

• 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: January 01 – March 31, 2014
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo

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: January 01 – March 31, 2014
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo

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: January 01 – March 31, 2014
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo

Distribution

Figure 5: VM count by wall time

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

• Period: January 01 – March 31, 2014
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo

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: January 01 – March 31, 2014
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo

VMs count by project

Project	Value
fg-224:Nimbus Auto Scale	742
fg-40:Inca	706
fg-367:Optimize rapid deployment and updating of VM images at the remote compute cluster	236
fg-174:RAIN: FutureGrid Dynamic provisioning Framework	197
fg-257:Particle Physics Data analysis cluster for ATLAS LHC experiment	82
fg-165:The VIEW Project	61
fg-152:Karnak Prediction Service	31
fg-175:GridProphet, A workflow execution time prediction system for the Grid	25
fg-110:FutureGrid Systems Development	8
fg-1:Peer-to-peer overlay networks and applications in virtual networks and virtual clusters	5
fg-151:XSEDE Operations Group	4
fg-362:Course: Cloud Computing and Storage (UF)	4
fg-372:Mobile Device Computation Offloading over SocialVPNs	3
fg-392:Using Clouds to Scale GIS Applications	2
fg-382:Reliability Analysis using Hadoop and MapReduce	2
fg-97:FutureGrid and Grid‘5000 Collaboration	2
fg-42:SAGA	1

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: January 01 – March 31, 2014
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo

VMs count by project leader

Projectleader	Value
Pierre Riteau	742
Shava Smallen	706
Jan Balewski	236
Gregor von Laszewski	197
Doug Benjamin	82
Shiyong Lu	61
Warren Smith	31
Thomas Fahringer	25
Gary Miksik	8
Renato Figueiredo	8
Andy Li	4
David Gignac	4
Carl Walasek	2
Kate Keahey	2
Mauricio Tsugawa	2
Shantenu Jha	1

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: January 01 – March 31, 2014
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo

VMs count by institution

Institution	Value
University of Chicago	742
UC San Diego	706
Massachusetts Institute of Technology, Laboratory for Nuclear Sc	236
Indiana University	205
Duke University	82
Wayne State University	61
University of Texas at Austin	31
University of Innsbruck	25
University of Florida	7
University of Florida, Department of Electrical and Computer Eng	4
University of Texas	4
University of Florida, Electrical and Computer Engineering	3
University of Chicago, Computation Institute	2
University of the Sciences , Mathematics, Physics, and Statistic	2
Louisiana State University	1

Figure 9: Wall time (hours) by project leader

This chart illustrates proportionate total run times by project leader.

• Period: January 01 – March 31, 2014
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo

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 (alamo)

This column chart represents VMs count among systems.

• Period: January 01 – March 31, 2014
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo

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

This column chart represents wall time among systems.

• Period: January 01 – March 31, 2014
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo