Cloud Migration: A Case Study of Migrating an Enterprise IT System to IaaS

This case study illustrates the potential benefits and risks associated with the migration of an IT system in the oil & gas industry from an in-house data center to Amazon EC2 from a broad variety of stakeholder perspectives across the enterprise, thus transcending the typical, yet narrow, financial and technical analysis offered by providers. Our results show that the system infrastructure in the case study would have cost 37% less over 5 years on EC2, and using cloud computing could have potentially eliminated 21% of the support calls for this system. These findings seem significant enough to call for a migration of the system to the cloud but our stakeholder impact analysis revealed that there are significant risks associated with this. Whilst the benefits of using the cloud are attractive, we argue that it is important that enterprise decision-makers consider the overall organizational implications of the changes brought about with cloud computing to avoid implementing local optimizations at the cost of organization-wide performance.Comment: Submitted to IEEE CLOUD 201

Decision Support Tools for Cloud Migration in the Enterprise

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

Diagnostic Work in Cloud Computing: Discussion Forums, Community and Troubleshooting

ABSTRACT As systems scale, systems management often becomes partially reliant on web forums and other social media. This paper examines the use of web forums for diagnostic work in cloud computing. We argue that forums are not simply used to communicate information but that (with users attempting to negotiate and manage the attention of providers, forming coalitions, criticizing others, and framing problems in particular ways) forums are socially organised, value laden venues for information. We conclude that providers should focus not on improving communication, but more broadly on managing community

The Cloud Adoption Toolkit: Addressing the Challenges of Cloud Adoption in Enterprise

Cloud computing promises a radical shift in the provisioning of computing resource within the enterprise. This paper: i) describes the challenges that decision makers face when attempting to determine the feasibility of the adoption of cloud computing in their organisations; ii) illustrates a lack of existing work to address the feasibility challenges of cloud adoption in the enterprise; iii) introduces the Cloud Adoption Toolkit that 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. The paper adopts a position paper methodology such that case study evidence is provided, where available, to support claims. We conclude that the Cloud Adoption Toolkit, whilst still under development, shows signs that it is a useful tool for decision makers as it helps address the feasibility challenges of cloud adoption in the enterprise

Supporting system deployment decisions in public clouds

Decisions to deploy IT systems on public Infrastructure-as-a-Service clouds can be complicated as evaluating the benefits, risks and costs of using such clouds is not straightforward. The aim of this project was to investigate the challenges that enterprises face when making system deployment decisions in public clouds, and to develop vendor-neutral tools to inform decision makers during this process. Three tools were developed to support decision makers: 1. Cloud Suitability Checklist: a simple list of questions to provide a rapid assessment of the suitability of public IaaS clouds for a specific IT system. 2. Benefits and Risks Assessment tool: a spreadsheet that includes the general benefits and risks of using public clouds; this provides a starting point for risk assessment and helps organisations start discussions about cloud adoption. 3. Elastic Cost Modelling: a tool that enables decision makers to model their system deployment options in public clouds and forecast their costs. These three tools collectively enable decision makers to investigate the benefits, risks and costs of using public clouds, and effectively support them in making system deployment decisions. Data was collected from five case studies and hundreds of users to evaluate the effectiveness of the tools. This data showed that the cost effectiveness of using public clouds is situation dependent rather than universally less expensive than traditional forms of IT provisioning. Running systems on the cloud using a traditional 'always on' approach can be less cost effective than on-premise servers, and the elastic nature of the cloud has to be considered if costs are to be reduced. Decision makers have to model the variations in resource usage and their systems' deployment options to obtain accurate cost estimates. Performing upfront cost modelling is beneficial as there can be significant cost differences between different cloud providers, and different deployment options within a single cloud. During such modelling exercises, the variations in a system's load (over time) must be taken into account to produce more accurate cost estimates, and the notion of elasticity patterns that is presented in this thesis provides one simple way to do this