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OpenNebula Conf - December 2-4, 2014 - Berlin 
Managing a Scientific Computing Facility 
with OpenNebula 
! 
Sara Vallero 
on behalf of the INFN-Torino computing team 
The present work is partially funded under contract 20108T4XTM of 
Programmi di Ricerca Scientifica di Rilevante Interesse Nazionale (Italy). 
1
The INFN Torino Computing Centre 
INFN: Italian National Institution for Nuclear Physics 
• fundamental physics studies 
• several units in major Italian cities 
Torino Unit 
STORAGE RESOURCES 
• 1600 TB (gross) total 
COMPUTATIONAL RESOURCES 
• 69 hypervisors (KVM) 
• 1200 job-slots 
• 200 virtual machines 
LAN/WAN 
• 10Gbps links 
Cloud project started in 2009 
OpenNebula Conf - December 2-4, 2014 - Berlin S.Vallero 
2 
Stakeholders 
• WLCG grid Tier2 
(primarily for the ALICE experiment 
at CERN) 
• grid Tier2 for the BESIII experiment 
at IHEP Beijing 
• Computing for upcoming 
experiments: 
• PANDA at FAIR Darmstadt 
• Belle-2 at KEK Tsukuba 
• Virtual Analysis Facility for ALICE 
(interactive analysis, elasticity) 
• Medical Image Processing 
(local research group) 
• Theory (local research group) 
• Virtual farms on-demand
Two clusters for different VM classes 
SERVICES-CLASS VMs (pets) 
• provide critical services 
• in/out-bound connectivity 
• live migration 
• server-class hardware 
• no particular local disk I/O requirements 
• shared image repository 
• resiliency-optimized FS for shared system 
disks (RAID1) 
OpenNebula Conf - December 2-4, 2014 - Berlin S.Vallero 
Storage 
Image Repository Servers 
Datastore 
Services Cluster Workers Cluster 
3 
WORKERS-CLASS VMs (cattle) 
• computational work-force 
(e.g. grid worker nodes) 
• private IP only 
• high storage I/O performance 
• lower-class hardware 
• locally cached image repository 
for fast start-up 
• performance-optimized file system 
Gluster 
Replicated 
Volume 
Shared 
Datastore 
for running 
VMs 
Cache for 
image repo 
Datastore
Current and planned activities 
move to new 
OpenNebula tools 
OpenNebula Conf - December 2-4, 2014 - Berlin S.Vallero 
4 
1. Toolkit for virtual farm on-demand provisioning 
• Virtual Routers (OpenWRT appliances) 
• Elastic public IP 
• iSCSI datastore for persistent disk space 
• EC2 interface 
• CloudInit contextualisation 
2. Elasticity 
• automatic reallocation of VMs according to application’s needs (wherever 
appropriate) 
• though: works only in infinite resources approximation, we usually run in saturation 
• in place only for the Virtual Analysis Facility so far 
3. National federated cloud for scientific computing 
• upcoming INFN-wide project mostly based on OpenStack 
• need to interoperate with OpenStack-based geographical services (e.g. Keystone) 
4. Monitoring as a service 
• based on the ELK stack (ElasticSearch, Logstash, Kibana) 
• uniform monitoring interface for applications/infrastructure

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OpenNebulaConf 2014 - Lightning talk: Managing a Scientific Computing Facility with OpenNebula - Sara Valero

  • 1. OpenNebula Conf - December 2-4, 2014 - Berlin Managing a Scientific Computing Facility with OpenNebula ! Sara Vallero on behalf of the INFN-Torino computing team The present work is partially funded under contract 20108T4XTM of Programmi di Ricerca Scientifica di Rilevante Interesse Nazionale (Italy). 1
  • 2. The INFN Torino Computing Centre INFN: Italian National Institution for Nuclear Physics • fundamental physics studies • several units in major Italian cities Torino Unit STORAGE RESOURCES • 1600 TB (gross) total COMPUTATIONAL RESOURCES • 69 hypervisors (KVM) • 1200 job-slots • 200 virtual machines LAN/WAN • 10Gbps links Cloud project started in 2009 OpenNebula Conf - December 2-4, 2014 - Berlin S.Vallero 2 Stakeholders • WLCG grid Tier2 (primarily for the ALICE experiment at CERN) • grid Tier2 for the BESIII experiment at IHEP Beijing • Computing for upcoming experiments: • PANDA at FAIR Darmstadt • Belle-2 at KEK Tsukuba • Virtual Analysis Facility for ALICE (interactive analysis, elasticity) • Medical Image Processing (local research group) • Theory (local research group) • Virtual farms on-demand
  • 3. Two clusters for different VM classes SERVICES-CLASS VMs (pets) • provide critical services • in/out-bound connectivity • live migration • server-class hardware • no particular local disk I/O requirements • shared image repository • resiliency-optimized FS for shared system disks (RAID1) OpenNebula Conf - December 2-4, 2014 - Berlin S.Vallero Storage Image Repository Servers Datastore Services Cluster Workers Cluster 3 WORKERS-CLASS VMs (cattle) • computational work-force (e.g. grid worker nodes) • private IP only • high storage I/O performance • lower-class hardware • locally cached image repository for fast start-up • performance-optimized file system Gluster Replicated Volume Shared Datastore for running VMs Cache for image repo Datastore
  • 4. Current and planned activities move to new OpenNebula tools OpenNebula Conf - December 2-4, 2014 - Berlin S.Vallero 4 1. Toolkit for virtual farm on-demand provisioning • Virtual Routers (OpenWRT appliances) • Elastic public IP • iSCSI datastore for persistent disk space • EC2 interface • CloudInit contextualisation 2. Elasticity • automatic reallocation of VMs according to application’s needs (wherever appropriate) • though: works only in infinite resources approximation, we usually run in saturation • in place only for the Virtual Analysis Facility so far 3. National federated cloud for scientific computing • upcoming INFN-wide project mostly based on OpenStack • need to interoperate with OpenStack-based geographical services (e.g. Keystone) 4. Monitoring as a service • based on the ELK stack (ElasticSearch, Logstash, Kibana) • uniform monitoring interface for applications/infrastructure