jose castro leon cern – it/ois
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Infrastructure as a Service. Jose Castro Leon CERN – IT/OIS. Cloud Computing. On-Demand Self-Service Scalability and Efficiency Resource Pooling Rapid elasticity. Infrastructure as a Service. Objectives 90% of hardware virtualized 300,000 VMs needed - PowerPoint PPT PresentationTRANSCRIPT
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Jose Castro LeonCERN – IT/OIS
CERN Agile Infrastructure
Infrastructure as a Service
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Cloud Computing
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• On-Demand Self-Service• Scalability and Efficiency• Resource Pooling• Rapid elasticity
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Infrastructure as a Service
• Objectives– 90% of hardware virtualized– 300,000 VMs needed– Merge the 2 IT evaluation projects in this area
• Lxcloud & CVI
• Infrastructure as a Service (IaaS)– More efficient use of our hardware– Better tracking of usage– Enable remote management for new data centre– Consolidate support to a single service– Support potential new use cases (PaaS)
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Openstack
• Openstack provides an operating platform, or toolkit, for orchestrating clouds.
• Features– Multi Site– Scalable– Cloud interfaces
• Position ourselves as another Cloud Provider
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Openstack Community
• >150 companies supporting Openstack
• Find the complete list at:http://www.openstack.org/community/companies/
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Openstack @ CERN
Compute Scheduler
NetworkVolume
Registry Image
KEYSTONE HORIZON
NOVA
GLANCE
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Nova @ CERN
• Nova– Instance & Volume Management
• 2 APIs: OpenStack and Amazon EC2• Scheduler decides the Hypervisor
• Nova @ CERN– KVM as Hypervisor– GlusterFS for High Availability– Integration with existing network DB (LanDB)
• MAC to IP mapping• Instance to Network IP subset mapping
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Glance @ CERN
• Images Management• Configurable storage backend
– Local Storage– Openstack Swift– GlusterFS
• Multi-format image registry– RAW– VHD (Hyper-V)– VDI (VirtualBox)– QCOW2 (Qemu/KVM)– VMDK (VMWare)– OVF (VMWare, others)
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Keystone @ CERN
• Cloud Identity Service– Authentication– Authorization– Service Catalog
• Role Based Access Control• Identity Backends
– LDAP: Integrate with CERN Active Directory– SQL Database possible
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Horizon @ CERN
• Graphical UI for Openstack– Django application– Plug-in architecture– Highly integrated with Keystone– Self-service for end-users
• Integrate with CERN SSO– Shibboleth authentication
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Applications
• Different services consume IaaS resources– Server consolidation, "user VMs"– Batch services– Pilot frameworks– BOINC
• With different requirements (QoS)– Management, Storage, Availability, Flexibility– Disaster Recovery
• Scheduler is needed for automation• Monitor the resource usage
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Scheduling Architecture
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Scheduling & Accounting
• One single entry point for all services• Decouple applications from the IaaS• Distributed Computer Centre• Resource usage tracking
– Hardware usage (CPU,Memory,Disk)– Software usage (Process monitoring)
• Auditing & Billing
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IaaS Configuration
• Production nodes based on SLC6 + EPEL– Test deployment based on Fedora 16
• All hypervisors are registered in Foreman– Automatic hypervisor provisioning
• Hypervisors use Puppet to configure themselves– Puppetlabs modules for Openstack
• CERN Customization– Network DB registration
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Experiences
• Maintain the project linked with upstream• Openstack
– Participate in Openstack Design Summit• Fedora
– RPMs for F16/F17 are quickly released• Essex EPEL6 expected end of April
– Bugzilla, Wiki, IRC: we participate & benefit– Essex Test day (March 08) good experience
• Issues– Sometimes ahead of upstream
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Summary
• Agile Infrastructure– Convergence of our infrastructures and virtual
technologies– Implement specific modules for internal use– Participate in the Community– Production ready in time for new Data Centre
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Questions
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Backup Slides
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Openstack Architecture
Compute Scheduler
NetworkVolume
Registry Image
KEYSTONE
HORIZON
NOVAGLANCE
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IaaS Configuration Use Case
• Hypervisor Configuration Workflow1. Machine is physically installed and registered2. It’s started by the operator3. It boots from the network and OS is installed4. It is configured by Puppet5. It registers itself to the Cloud Controller6. It is ready to accept VMs
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VM Configuration
• Use the same tools as IaaS– Puppet– Foreman
• Instance could be managed or not– User decides
• Several OS supported– Image selection in Horizon– Customization of the image
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Openstack Architecture
keystone
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CERN Deployment
keystone
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Industry Context - Cloud
• Cloud computing models are now standardising– Facilities as a Service – such as Equinix, Safehost– Infrastructure as a Service - Amazon EC2, CVI or lxcloud– Platform as a Service - Microsoft Azure or CERN Web Services– Software as a Service – Salesforce, Google Mail, Service-Now, Indico
• Different customers want access to different layers– Both our users and the IT Service Managers
Applications
Platform
Infrastructure
Facilities
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Industry Context - DevOps
• DevOps community adopting tool chains with small tools interlinked for particular functions
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IaaS Approach Benefits• More efficient use of our hardware
– Use machines throughout their lifetime– Reduce impact of hardware failure– Pack server workload for day/night, batch and I/O intensive
workload• Better tracking of usage
– Consistent accounting and provisioning• Enable remote management for new data centre
– Only ‘smart hands’ locally– System administrator procedures simplified
• Consolidate support to a single service– Reach critical mass for coverage
• Easily exploit work done in industry such as load balancers– We are not special
• Support potential new use cases– PaaS, cloud APIs, bursting
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Current situation
• IT has two projects in this area– Lxcloud based on OpenNebula providing EC2 services
for physics users to validate concepts and test– CERN Virtual Infrastructure on Hyper-V providing long
lived server consolidation workloads such as desktop replacements, VO Boxes and other production/test/dev workloads
• Neither solution is felt to be ideal from long term self-sustainability and scalability– O(300K) VMs needed– Currently two teams of 1.5 FTE each
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