Analysis of Log Files Intersections for Security Enhancement
ITNG '06 Proceedings of the Third International Conference on Information Technology: New Generations
A break in the clouds: towards a cloud definition
ACM SIGCOMM Computer Communication Review
Future Generation Computer Systems
Computer
On Technical Security Issues in Cloud Computing
CLOUD '09 Proceedings of the 2009 IEEE International Conference on Cloud Computing
Communications of the ACM
Cloud Migration: A Case Study of Migrating an Enterprise IT System to IaaS
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
Advances and challenges in log analysis
Communications of the ACM
The Cloud Adoption Toolkit: supporting cloud adoption decisions in the enterprise
Software—Practice & Experience
Specification and quantitative analysis of probabilistic cloud deployment patterns
HVC'11 Proceedings of the 7th international Haifa Verification conference on Hardware and Software: verification and testing
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Numerous organisations are considering moving at least some of their existing applications to the cloud. A key motivating factor for this fast-paced adoption of cloud is the expectation of cost savings. Estimating what these cost savings might be requires comparing the known cost of running an application in-house with a predicted cost of its cloud deployment. A major problem with this approach is the lack of suitable techniques for predicting the cost of the virtual machines (VMs) that a cloud-deployed application requires in order to achieve a given service-level agreement. We introduce a technique that addresses this problem by using established results from queueing network theory to predict the minimum VM cost of cloud deployments starting from existing application logs. We describe how this formal technique can be used to predict the cost-performance trade-offs available for the cloud deployment of an application, and presents a case study based on a real-world webmail service.