Title :
SmartScale: Automatic Application Scaling in Enterprise Clouds
Author :
Dutta, Sourav ; Gera, Sankalp ; Verma, Akshat ; Viswanathan, Balaji
Author_Institution :
IBM Res., New Delhi, India
Abstract :
Enterprise clouds today support an on demand resource allocation model and can provide resources requested by applications in a near online manner using virtual machine resizing or cloning. However, in order to take advantage of an on demand resource model, enterprise applications need to be automatically scaled in a way that makes the most efficient use of resources. In this work, we present the SmartScale automated scaling framework. SmartScale uses a combination of vertical (adding more resources to existing VM instances) and horizontal (adding more VM instances) scaling to ensure that the application is scaled in a manner that optimizes both resource usage and the reconfiguration cost incurred due to scaling. The SmartScale methodology is proactive and ensures that the application converges quickly to the desired scaling level even when the workload intensity changes significantly. We evaluate SmartScale using real production traces on Olio, an emerging cloud benchmark, running on a kvm-based cloud testbed. We present both theoretical and experimental evidence that comprehensively establish the effectiveness of SmartScale.
Keywords :
business data processing; cloud computing; virtual machines; KVM-based cloud testbed; Olio; SmartScale automated scaling framework; SmartScale methodology; automatic application scaling; enterprise applications; enterprise clouds; horizontal scaling; on demand resource allocation model; reconfiguration cost; resource usage; vertical scaling; virtual machine cloning; virtual machine resizing; Cloud computing; Hardware; Load modeling; Resource management; Servers; Throughput; Virtual machining; Horizontal Scaling; Olio; Vertical Scaling; data-center reconfiguration; enterprise clouds;
Conference_Titel :
Cloud Computing (CLOUD), 2012 IEEE 5th International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4673-2892-0
DOI :
10.1109/CLOUD.2012.12