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Usage of cloud platform in datacenter BITP for resource and energy efficiency

Usage of cloud platform in datacenter BITP for resource and energy efficiency. Oksana Shadura , V.Pelykh , S.Svistynov. Bogolyubov Institute for Theoretical Physics Ukraine. Current status. Small Tier 2 site Supporting ALICE, local scientific jobs, medical information processing

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Usage of cloud platform in datacenter BITP for resource and energy efficiency

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  1. Usage of cloud platform in datacenter BITP for resource and energy efficiency OksanaShadura, V.Pelykh, S.Svistynov Bogolyubov Institute for Theoretical Physics Ukraine

  2. Current status • Small Tier 2 site • Supporting ALICE, local scientific jobs, medical information processing • UA-BITP also supports all core services for NGI_UA • Heterogeneous cluster: from old Xeon to E5-26xx • Now 260 cores in total

  3. Reasons for cloud? • Solution of problem:”3 different clusters for different needs” • Easier support for IT team • Lack of flexibility of management of resources for different projects • Low efficiency of usage resources • Usage for old hardware for special needs (educational, testing, small local jobs) • Reduce energy consumption?

  4. Components of UA-BITP infrastructure

  5. Used utilities • RDO - community of people using and deploying OpenStack on Red Hat and Red Hat-based platforms) • Packstack -> Puppet Packstackis a utility that uses Puppet modules to deploy various parts of OpenStack on multiple pre-installed servers over SSH automatically. Supported by Fedora, Red Hat Enterprise Linux (RHEL), Scientific Linux and other RHEL based systems. • Ceilometer TheCeilometer project is infrastructure to collect measurements within OpenStack. It`s primary targets are monitoring and metering, but the framework is expandable to collect usage for other needs • Plugins: KWAPI Kwapi is in fact infrastructure that connects wattmeters to OpenStack Ceilometer.

  6. Components of Openstack Grizzly Glance-api Ceilometer-api Nova-scheduler, nova-compute, nova-network (linux-bridge), nova-api Cinder -api Keystone-api

  7. Implementation 3 Virtual nodes 68 core

  8. Implementation 20 tasks in queue 68 tasks running Automatical start of new VM

  9. Implementation 69 tasks running New VM with running task

  10. Implementation 69 cores registered in grid

  11. OpenstackCeilometer • Collect data needed for accounting, includes: • Compute - Nova: • instances (type) - hourly usage • cpu - hourly usage • ram - hourly usage • Network (data in/out) - hourly bytes + total bytes • differentiate between internal and external end-points • External floating IP - hourly bytes + total bytes • Image usage in Glance, and etc.

  12. Plugins:KWAPI 1/2 We need strategy which aims to reduce global energy consumption in cloud architectures: • Accurately measuring of the power consumption of all devices in the cloud. • Analysis of collected values, to place virtual machines at optimal location in the cloud. • Turning off unused machines.

  13. Plugins:KWAPI 2/2 Source: http://www.xlcloud.org

  14. High Availability For Openstack Main task is to prevent of availability and data loss problems How we can do this? • Redundant instances of services and requests are load balanced using virtual IPs and load balancer HAProxy. • Replacement of failed services by bringing up online backup/detection of services using monitoring by Pacemaker application,

  15. Scheme of Openstack (with HA deployment)

  16. Plans for future development • Update to Havana release (supporting Neutron, Ceilometer modules and etc.) • Move ALICE cluster to cloud platform (by CernVM tools or organizing own scheme) • Improve Puppet modules/manifests for own usage • Deploy process of contextualization for VMs • Analysis received results considering resource and energy efficiency

  17. Summary • Deployment of cloud is easy and fast… • It is good possibility to small sites to organize better management for resources; • We can dynamically change resource limits for different projects; • We can try to play with better allocation of VM, and as a result, to receive lower energy consumption; • Usage of virtual resources with same A/R.

  18. Thank you for your attention!

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