Pro Java EE 5 Performance Management and Optimization (Pro)
Pro Java EE 5 Performance Management and Optimization (Pro)
Why cloud computing will never be free
Communications of the ACM
An evaluation of alternative architectures for transaction processing in the cloud
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
USENIX'09 Proceedings of the 2009 conference on USENIX Annual technical conference
Runtime measurements in the cloud: observing, analyzing, and reducing variance
Proceedings of the VLDB Endowment
EC2 performance analysis for resource provisioning of service-oriented applications
ICSOC/ServiceWave'09 Proceedings of the 2009 international conference on Service-oriented computing
Performance Analysis of High Performance Computing Applications on the Amazon Web Services Cloud
CLOUDCOM '10 Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science
Using reinforcement learning for controlling an elastic web application hosting platform
Proceedings of the 8th ACM international conference on Autonomic computing
Intelligent management of virtualized resources for database systems in cloud environment
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
On the Performance Variability of Production Cloud Services
CCGRID '11 Proceedings of the 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
What Are You Paying For? Performance Benchmarking for Infrastructure-as-a-Service Offerings
CLOUD '11 Proceedings of the 2011 IEEE 4th International Conference on Cloud Computing
Variations in Performance and Scalability When Migrating n-Tier Applications to Different Clouds
CLOUD '11 Proceedings of the 2011 IEEE 4th International Conference on Cloud Computing
Performance evaluation of scheduling algorithms for database services with soft and hard SLAs
Proceedings of the second international workshop on Data intensive computing in the clouds
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Infrastructure as a Service (IaaS) providers, such as Amazon Web Services, offer on-demand access to computing resources at pay-as-you-go prices. The key benefit of IaaS is elasticity, i.e., the ability to provision and de-provision resources at will. This feature makes IaaS infrastructure as the best platform for hosting web applications, e.g. e-business, that are subjected to highly-variable request patterns. However, elasticity can be triggered either on the basis of resource utilization or for meeting service level objectives (SLOs). In this paper, we extensively evaluate these two types of elasticity rules using the TPC-W benchmark on Amazon IaaS infrastructure. From this experimental data, we evaluate the performance of these rules against the primary metric of service level satisfaction for web applications, and secondary metrics such as resource utilization and cost. Through our inferences, we present a number of recommendations that would enable practitioners and cloud consumers using Amazon to define appropriate elasticity rules to meet their SLOs and other metrics.