EC2BargainHunter: It's Easy to Hunt for Cost Savings on Amazon EC2!

摘要

Return on investment is a critical decision factor for end-users going for cloud deployments. However, major cloud vendors typically provide a myriad of interdependent cloud service options in a variety of purchasing models, that severely complicates cost estimation and optimization. In this paper, we propose a novel Amazon EC2 cost optimization system, called EC2Bargain Hunter, that innovatively combines services and cloud computing principles with ideas from semantic technologies. The system supports the entire-range of EC2 instance types, and can be used in real-time to perform live cost optimization. We demonstrate that unprecedented cost savings, by a factor of 30, on Amazon EC2 offerings can be found with this system in a few clicks. Furthermore, our approach can be adapted to other IaaS providers, which enables truly real-life cloud cost optimization and thus is a significant step towards making the cloud really cost-effective for the end-users.