CCM: Scalable, On-Demand Compute Capacity Management for Cloud Datacenters

dc.contributor.author Kesavan, Mukil
dc.contributor.author Ahmad, Irfan
dc.contributor.author Krieger, Orran
dc.contributor.author Soundararajan, Ravi
dc.contributor.author Gavrilovska, Ada
dc.contributor.author Schwan, Karsten
dc.contributor.corporatename Georgia Institute of Technology. Center for Experimental Research in Computer Systems en_US
dc.contributor.corporatename Georgia Institute of Technology. College of Computing en_US
dc.contributor.corporatename CloudPhysics en_US
dc.contributor.corporatename Boston University en_US
dc.contributor.corporatename VMware
dc.date.accessioned 2015-06-04T19:44:45Z
dc.date.available 2015-06-04T19:44:45Z
dc.date.issued 2013
dc.description.abstract We present CCM (Cloud Capacity Manager) – a prototype system, and, methods for dynamically multiplexing the compute capacity of cloud datacenters at scales of thousands of machines, for diverse workloads with variable demands. This enables mitigation of resource consumption hotspots and handling unanticipated demand surges, leading to improved resource availability for applications and better datacenter utilization levels. Extending prior studies primarily concerned with accurate capacity allocation and ensuring acceptable application performance, CCM also focuses on the tradeoffs due to two unavoidable issues in large scale commodity datacenters: (i) maintaining low operational overhead, and (ii) coping with the increased incidences of management operation failures. CCM is implemented in an industry-strength cloud infrastructure built on top of the VMware vSphere virtualization platform and is currently deployed in a 700 physical host datacenter. Its experimental evaluation uses production workload traces and a suite of representative cloud applications to generate dynamic scenarios. Results indicate that the pragmatic cloud-wide nature of CCM provides up to 25% more resources for workloads and improves datacenter utilization by up to 20%, compared to the alternative approach of multiplexing capacity within multiple smaller datacenter partitions. en_US
dc.embargo.terms null en_US
dc.identifier.uri http://hdl.handle.net/1853/53368
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.relation.ispartofseries CERCS ; GIT-CERCS-13-01 en_US
dc.subject Cloud capacity manager en_US
dc.subject Cloud datacenters en_US
dc.subject Datacenters en_US
dc.subject Virtualization platform en_US
dc.subject Workloads en_US
dc.title CCM: Scalable, On-Demand Compute Capacity Management for Cloud Datacenters en_US
dc.type Text
dc.type.genre Technical Report
dspace.entity.type Publication
local.contributor.author Gavrilovska, Ada
local.contributor.author Schwan, Karsten
local.contributor.corporatename Center for Experimental Research in Computer Systems
local.relation.ispartofseries CERCS Technical Report Series
relation.isAuthorOfPublication 74b4106d-3b1c-40a5-993e-dea3eecbdba3
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relation.isSeriesOfPublication bc21f6b3-4b86-4b92-8b66-d65d59e12c54
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