Title :
Practical Compute Capacity Management for Virtualized Datacenters
Author :
Kesavan, Mukil ; Ahmad, Ishtiaq ; Krieger, Orran ; Soundararajan, Ravi ; Gavrilovska, Ada ; Schwan, Karsten
Author_Institution :
Coll. of Comput., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
We present CCM (Cloud Capacity Manager) - a prototype system and its methods for dynamically multiplexing the compute capacity of virtualized datacenters at scales of thousands of machines, for diverse workloads with variable demands. Extending prior studies primarily concerned with accurate capacity allocation and ensuring acceptable application performance, CCM also sheds light on the tradeoffs due to two unavoidable issues in large scale commodity datacenters: (i) maintaining low operational overhead given variable cost of performing management operations necessary to allocate resources, and (ii) coping with the increased incidences of these operations´ 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 common alternative approach of multiplexing capacity within multiple independent smaller datacenter partitions.
Keywords :
capacity management (computers); cloud computing; computer centres; resource allocation; virtualisation; CCM; VMware vSphere virtualization platform; capacity allocation; cloud capacity manager; compute capacity management; data center utilization; industry-strength cloud infrastructure; large scale commodity data centers; management operations; multiplexing capacity; operations failures; physical host data center; pragmatic cloud-wide nature; representative cloud applications; resources allocation; variable cost; virtualized data centers; workload traces; workloads; Cloud computing; Data processing; Distributed processing; Fault tolerance; Hierarchical systems; Resource management; Virtualization; Data processing; Distributed processing; Distributed systems; Fault tolerance; Fault-tolerance; Hierarchical design; Hierarchical systems; Measurements; Resource management; Virtualization;
Journal_Title :
Cloud Computing, IEEE Transactions on