Usage Report alamo

• Period: July 01 – September 30, 2013
• 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: July 01 – September 30, 2013

• 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: July 01 – September 30, 2013
• 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: July 01 – September 30, 2013
• 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: July 01 – September 30, 2013
• 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: July 01 – September 30, 2013
• 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: July 01 – September 30, 2013
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo

VMs count by project

Project	Value
fg-40:Inca	730
fg-257:Particle Physics Data analysis cluster for ATLAS LHC experiment	119
fg-82:FG General Software Development	89
fg-10:TeraGrid XD TIS(Technology Insertion Service) Technology Evaluation Laboratory	17
fg-360:XSEDE Software Development and Integration Testing	14
fg-110:FutureGrid Systems Development	12
fg-224:Nimbus Auto Scale	9
fg-151:XSEDE Operations Group	9
fg-152:Karnak Prediction Service	6
fg-97:FutureGrid and Grid‘5000 Collaboration	5
fg-54:Investigating cloud computing as a solution for analyzing particle physics data	4
fg-175:GridProphet, A workflow execution time prediction system for the Grid	3
fg-312:Sensor-Rocks: A novel integrated framework to improve software Operations and Management (O&M) and power management in environmental observing systems	3
fg-20:Development of an information service for FutureGrid	3
fg-367:Optimize rapid deployment and updating of VM images at the remote compute cluster	2
fg-1:Peer-to-peer overlay networks and applications in virtual networks and virtual clusters	2
fg-172:Cloud-TM	1
fg-90:Unicore and Genesis Experimentation	1
fg-136:JGC-DataCloud-2012 paper experiments	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: July 01 – September 30, 2013
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo

VMs count by project leader

Projectleader	Value
Shava Smallen	745
Doug Benjamin	119
Gregor von Laszewski	89
John Lockman	17
Gary Miksik	12
David Gignac	9
Pierre Riteau	9
Warren Smith	6
Mauricio Tsugawa	5
Randall Sobie	4
Sameer Tilak	3
Hyungro Lee	3
Thomas Fahringer	3
Jan Balewski	2
Renato Figueiredo	2
Mats Rynge	1
Paolo Romano	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: July 01 – September 30, 2013
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo

VMs count by institution

Institution	Value
UC San Diego	731
Duke University	119
Indiana University	104
University of Texas at Austin	23
UC San Diego, San Diego Supercomputer Center	14
University of Chicago	9
University of Texas	9
University of Florida	7
University of Victoria	4
University of Innsbruck	3
UCSD, Calit2, UCSD	3
Massachusetts Institute of Technology, Laboratory for Nuclear Sc	2
INESC ID	1
USC	1

Figure 9: Wall time (hours) by project leader

This chart illustrates proportionate total run times by project leader.

• Period: July 01 – September 30, 2013
• 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: July 01 – September 30, 2013
• 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: July 01 – September 30, 2013
• Cloud(IaaS): nimbus, openstack
• Hostname: alamo