Abstract

Cloud computing promises a radical shift in the provisioning of computing resources within the enterprise. This paper describes the challenges that decision makers face when assessing the feasibility of the adoption of cloud computing in their organizations, and describes our Cloud Adoption Toolkit, which has been developed to support this process. The toolkit provides a framework to support decision makers in identifying their concerns, and matching these concerns to appropriate tools/techniques that can be used to address them. Cost Modeling is the most mature tool in the toolkit, and this paper shows its effectiveness by demonstrating how practitioners can use it to examine the costs of deploying their IT systems on the cloud. The Cost Modeling tool is evaluated using a case study of an organization that is considering the migration of some of its IT systems to the cloud. The case study shows that running systems on the cloud using a traditional 'always on' approach can be less cost effective, and the elastic nature of the cloud has to be used to reduce costs. Therefore, decision makers have to model the variations in resource usage and their systems' deployment options to obtain accurate cost estimates.

This paper describes two tools that aim to support decision making during the migration of IT systems to the cloud. The first is a modeling tool that produces cost estimates of using public IaaS clouds. The tool enables IT architects to model their applications, data and infrastructure requirements in addition to their computational resource usage patterns. The tool can be used to compare the cost of different cloud providers, deployment options and usage scenarios. The second tool is a spreadsheet that outlines the benefits and risks of using IaaS clouds from an enterprise perspective; this tool provides a starting point for risk assessment. Two case studies were used to evaluate the tools. The tools were useful as they informed decision makers about the costs, benefits and risks of using the cloud.Comment: To appear in IEEE CLOUD 201

-In Cloud Computing platforms the addition of hardware monitoring devices to gather power usage data can be impractical or uneconomical due to the large number of machines to be metered. CloudMonitor, a monitoring tool that can generate power models for software-based power estimation, can provide insights to the energy costs of deployments without additional hardware. Accurate power usage data leads to the possibility of Cloud providers creating a separate tariff for power and therefore incentivizing software developers to create energy-efficient applications.

Motivation -Bainbridge highlighted some of the ironies of automation 30 years ago and identified possible solutions. Society is now highly dependent on complex technological systems, so we assess our performance in addressing the ironies in these systems.Research approach -A critical reflection on the original ironies of automation, followed by a review of three domains where technology plays a critical role using case studies to identify where ironies persist.Findings/Design -The reliability and speed of technology have improved, but the ironies are still there. New ironies have developed too, in cloud computing where the cheaper cost of computing resources can lead to systems that are less dependable when developers bypass company procedures.Research limitations/Implications -The work relies on published or reported cases. This makes it difficult to precisely determine how widespread the issues are.Originality/Value -The research re-iterates the importance of the need to regularly consider the ironies of automation in systems development so that we can mitigate against any potential adverse consequences.Take away message -The more we depend on technology and push it to its limits, the more we need highly-skilled, welltrained, well-practised people to make systems resilient, acting as the last line of defence against the failures that will inevitably occur.