Mukil Kesavan, Irfan Ahmad, Orran Krieger, Ravi Soundararajan, Ada Gavrilovska, Karsten Schwan,
CCM: Scalable, On-Demand Compute Capacity Management for Cloud Datacenters
We present CCM (Cloud Capacity Manager) ˆ 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 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.