Toward a doctrine of containment: grid hosting with adaptive resource control
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Sharing networked resources with brokered leases
ATEC '06 Proceedings of the annual conference on USENIX '06 Annual Technical Conference
Active and accelerated learning of cost models for optimizing scientific applications
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Automatic virtual machine configuration for database workloads
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Automatic virtual machine configuration for database workloads
ACM Transactions on Database Systems (TODS)
SLA-Driven Adaptive Resource Management for Web Applications on a Heterogeneous Compute Cloud
CloudCom '09 Proceedings of the 1st International Conference on Cloud Computing
ActiveSLA: a profit-oriented admission control framework for database-as-a-service providers
Proceedings of the 2nd ACM Symposium on Cloud Computing
Triple-A: a Non-SSD based autonomic all-flash array for high performance storage systems
Proceedings of the 19th international conference on Architectural support for programming languages and operating systems
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Utility computing delivers compute and storage resources to applications as an 'on-demand utility', much like electricity, from a distributed collection of computing resources. There is great interest in running database applications on utility resources (e.g., Oracle's Grid initiative) due to reduced infrastructure and management costs, higher resource utilization, and the ability to handle sudden load surges. Virtual Machine (VM) technology offers powerful mechanisms to manage a utility resource infrastructure. However, provisioning VMs for applications to meet system performance goals, e.g., to meet service level agreements (SLAs), is an open problem. We are building two systems at Duke - Shirako and NIMO - that collectively address this problem. Shirako is a toolkit for leasing VMs to an application from a utility resource infrastructure. NIMO learns application performance models using novel techniques based on active learning, and uses these models to guide VM provisioning in Shirako. We will demonstrate: (a) how NIMO learns performance models in an online and automatic fashion using active learning; and (b) how NIMO uses these models to do automated and on-demand provisioning of VMs in Shirako for two classes of database applications - multi-tier web services and computational science workflows.