Usage Report sierra

• Period: September 01 – September 30, 2013
• Hostname: sierra.futuregrid.org
• Services: nimbus, openstack, eucalyptus
• 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: September 01 – September 30, 2013

• Cloud(IaaS): nimbus, openstack, eucalyptus

• Hostname: sierra

• 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: September 01 – September 30, 2013
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

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: September 01 – September 30, 2013
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

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: September 01 – September 30, 2013
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

Distribution

Figure 5: VM count by wall time

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

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

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: September 01 – September 30, 2013
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

VMs count by project

Project	Value
fg-172:Cloud-TM	320
fg-54:Investigating cloud computing as a solution for analyzing particle physics data	274
fg-40:Inca	220
fg-224:Nimbus Auto Scale	212
fg-214:Mining Interactions between Network Community Structure and Information Diffusion	172
fg-298:FRIEDA: Flexible Robust Intelligent Elastic Data Management	167
fg-362:Course: Cloud Computing and Storage (UF)	36
fg-372:Mobile Device Computation Offloading over SocialVPNs	31
fg-168:Next Generation Sequencing in the Cloud	27
fg-1:Peer-to-peer overlay networks and applications in virtual networks and virtual clusters	27
fg-82:FG General Software Development	25
fg-364:Course: EEL6871 Autonomic Computing	24
fg-52:Cost-Aware Cloud Computing	18
fg-315:Biome representational in silico karyotyping	17
fg-367:Optimize rapid deployment and updating of VM images at the remote compute cluster	12
fg-264:Course: 1st Workshop on bioKepler Tools and Its Applications	6
fg-97:FutureGrid and Grid‘5000 Collaboration	5
fg-374:Course: Cloud and Distributed Computing	4
fg-244:Course: Data Center Scale Computing	1
fg-69:Investigate provenance collection for MapReduce	1
fg-355:Course: Data Center Scale Computing Class	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: September 01 – September 30, 2013
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

VMs count by project leader

Projectleader	Value
Paolo Romano	320
Randall Sobie	274
Shava Smallen	220
Pierre Riteau	212
Yong-Yeol Ahn	172
Lavanya Ramakrishnan	167
Renato Figueiredo	58
Andy Li	36
Jonathan Klinginsmith	27
Gregor von Laszewski	25
Meng Han	24
David Lowenthal	18
Aaron Lee	17
Jan Balewski	12
Ilkay Altintas	6
Mauricio Tsugawa	5
Philip Rhodes	4
Dirk Grunwald	2
Jiaan Zeng	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: September 01 – September 30, 2013
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

VMs count by institution

Institution	Value
INESC ID	320
University of Victoria	274
Indiana University	224
UC San Diego	220
University of Chicago	212
Lawrence Berkeley National Lab	167
University of Florida, Department of Electrical and Computer Eng	36
University of Florida	32
University of Florida, Electrical and Computer Engineering	31
University of Florida, ACIS	24
University of Arizona	18
Washington University at St Louis, School of Medicine, Departmen	17
Massachusetts Institute of Technology, Laboratory for Nuclear Sc	12
UCSD	6
University of Mississippi, Department of Computer Science	4
Univ. of Colorado, Boulder, Computer Science	1
Computer Science	1
Univ. of Colorado	1

Figure 9: Wall time (hours) by project leader

This chart illustrates proportionate total run times by project leader.

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

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 (sierra)

This column chart represents VMs count among systems.

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

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

This column chart represents wall time among systems.

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