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Usage Report sierra

  • Period: May 01 – May 31, 2014
  • 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)

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: May 01 – May 31, 2014

  • 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)

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: May 01 – May 31, 2014
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
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: May 01 – May 31, 2014
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
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: May 01 – May 31, 2014
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra

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: May 01 – May 31, 2014
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
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: May 01 – May 31, 2014
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
VMs count by project
Project Value
fg-389:Investigating the Apache Big Data Stack 69
fg-174:RAIN: FutureGrid Dynamic provisioning Framework 55
fg-367:Optimize rapid deployment and updating of VM images at the remote compute cluster 30
fg-371:Characterizing Infrastructure Cloud Performance for Scientific Computing 21
fg-224:Nimbus Auto Scale 20
fg-362:Course: Cloud Computing and Storage (UF) 6
fg-264:Course: 1st Workshop on bioKepler Tools and Its Applications 2
fg-1:Peer-to-peer overlay networks and applications in virtual networks and virtual clusters 2
fg-172:Cloud-TM 2
fg-136:JGC-DataCloud-2012 paper experiments 2
fg-298:FRIEDA: Flexible Robust Intelligent Elastic Data Management 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: May 01 – May 31, 2014
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
VMs count by project leader
Projectleader Value
ibrahim hallac 69
Gregor von Laszewski 55
Jan Balewski 30
Theron Voran 21
Pierre Riteau 20
Andy Li 6
Mats Rynge 2
Ilkay Altintas 2
Renato Figueiredo 2
Paolo Romano 2
Lavanya Ramakrishnan 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: May 01 – May 31, 2014
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
VMs count by institution
Institution Value
Firat University, Computer Science Department 69
Indiana University 55
Massachusetts Institute of Technology, Laboratory for Nuclear Sc 30
University of Colorado at Boulder, Computer Science Department 21
University of Chicago 20
University of Florida, Department of Electrical and Computer Eng 6
USC 2
University of Florida 2
INESC ID 2
UCSD 2
Lawrence Berkeley National Lab 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: May 01 – May 31, 2014
  • 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.

VMs count by systems in Cluster (sierra)
Figure 10: VMs count by systems (compute nodes) in Cluster (sierra)
This column chart represents VMs count among systems.
  • Period: May 01 – May 31, 2014
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra
Wall time (hours) by systems in Cluster (sierra)
Figure 11: Wall time (hours) by systems (compute nodes) in Cluster (sierra)
This column chart represents wall time among systems.
  • Period: May 01 – May 31, 2014
  • Cloud(IaaS): nimbus, openstack, eucalyptus
  • Hostname: sierra