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The Cloud Adoption Toolkit: Supporting Cloud Adoption Decisions in the Enterprise
Ali Khajeh-Hosseini, David Greenwood, James W. Smith, Ian Sommerville
TL;DR
Enterprise cloud adoption decisions are difficult because costs, suitability, organizational change, and governance are uncertain and interdependent. The paper proposes a Cloud Adoption Toolkit that matches these concerns with decision-support tools and evaluates its mature Cost Modeling component in a case study. The case study finds that cloud cost-effectiveness depends on deployment choices and resource usage, with elasticity needed to reduce costs in the examined scenario.
Problem
Enterprise cloud adoption is difficult because cost estimates, system suitability, organizational change, and governance requirements are uncertain and interconnected.
Method
The paper proposes a Cloud Adoption Toolkit that organizes decision makers’ concerns and matches them with tools for analyzing cloud adoption options.
Results
Cloud cost-effectiveness is situation dependent: the case study recommended buying physical servers when capital was available, or using cloud resources with an elastic re-architecture.
Takeaways & Limitations
Accurate cloud adoption decisions require modeling system-specific resource usage and deployment options rather than relying on generalized provider cost-saving estimates.
Takeaways & Limitations
The toolkit’s components have uneven maturity: Cost Modeling is most mature, some analyses have partial support, and Responsibility Modeling was not yet included.
Abstract
from arXiv · showhide
Cloud computing promises a radical shift in the provisioning of computing resource within the enterprise. This paper describes the challenges that decision makers face when assessing the feasibility of the adoption of cloud computing in their organisations, 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 be able to model the variations in resource usage and their systems deployment options to obtain accurate cost estimates.
1 Introduction
Cloud adoption promises scalable, service-based computing but creates uncertainty about whether its benefits, especially cost savings, will materialize in enterprise settings. The paper introduces a toolkit that organizes adoption concerns and matches them with decision-support tools.
- Cloud computing delivers shared, configurable computing resources as an on-demand service over networks.
- Enterprise cloud adoption is motivated by promised scalability, reliability, and cost-effectiveness, but actual benefits remain ambiguous amid simplistic cost-saving assumptions.
- The paper highlights that migration decisions must consider socio-technical factors alongside cost considerations.
- The Cloud Adoption Toolkit organizes decision makers’ concerns and matches them to tools that model organizational or IT-system attributes.
- The toolkit’s Cost Modeling tool is evaluated through a case study showing that cloud cost savings depend on resource usage and deployment options.
2 Challenges of Cloud Adoption
Enterprise cloud adoption is difficult because suitability, costs, organizational change, governance, and system alignment are interconnected and uncertain. Existing research and industry offerings provide no mature, open toolkit for comprehensive decision support.
- Enterprise cloud adoption is non-trivial because system suitability, cost estimation, organizational change, and governance requirements are difficult to assess together.
- Cost Calculations: Cloud cost estimates vary with consumed resources, deployment choices, and provider pricing, making provider selection and cost-effectiveness uncertain.
- Cost Calculations: Private-cloud operational costs increasingly involve energy costs and carbon emissions, which can become significant over an infrastructure lifecycle.
- Organizational Change: Cloud adoption requires substantial organizational change because legacy interdependencies, political interests, and technical-organizational misalignment complicate transformation.
- Organizational Change: Cloud systems must align with enterprise needs and stakeholder requirements across technical, project, operational, and financial domains.
- A review found no mature techniques or toolkits for enterprise cloud-adoption decision support, while consultancy approaches were closed and limited.
3 The Cloud Adoption Toolkit
The Cloud Adoption Toolkit organizes stakeholder concerns and connects them with tools for evaluating cloud suitability, costs, energy, impacts, and operational responsibilities. Its idealized process is flexible, but implementation maturity varies across tools.
- The toolkit combines a conceptual framework for organizing concerns with supporting tools including suitability, energy, stakeholder, responsibility, and cost analyses.
- Conceptual Framework: Decision makers can assess technology suitability first, then examine public-cloud costs or private-cloud energy use while analyzing stakeholder impacts and operational responsibilities.
- Conceptual Framework: The toolkit’s process is idealized, and users may select whichever components are most appropriate rather than follow an enforced sequence.
- Conceptual Framework: Cost Modeling is the most mature component, while Technology Suitability and Stakeholder Impact Analysis have partial support and Responsibility Modeling is not yet included.
- Technology Suitability Analysis: Technology Suitability Analysis uses an eight-characteristic checklist to recommend whether further analysis should proceed.
- Cost Modeling: The Cost Modeling tool focuses on infrastructure migration and assumes existing software can run unchanged on remote rather than local servers.
- Cost Modeling: Cost Modeling extends UML deployment diagrams to estimate operational costs for software deployed on cloud, traditional, or hybrid infrastructures.
- Stakeholder Impact Analysis: Stakeholder Impact Analysis examines organizational consequences of changed tasks, resources, capabilities, values, status, and satisfaction.
4 Evaluation
The case study evaluates the Cost Modeling tool for cloud migration and finds that cost effectiveness depends on resource usage, deployment choices, and broader organizational factors.
- Evaluation: The evaluation used a higher-education case study to demonstrate the Cost Modeling tool’s full feature set.The tool was the most mature component of the Cloud Adoption Toolkit.
- Cost Modeling: Baseline usage and temporary or permanent usage patterns model the elasticity requirements of computing resources.This allows resource demand to vary over time rather than assuming constant usage.
- Cost Modeling: The model groups costs and supports comparing deployment options, including duplicating system components across clouds for increased availability.Reports provide detailed cost breakdowns for departments, organizations, or entire systems.
- Results: At year 0, buying physical servers cost $22,800, leasing equivalent cloud resources cost $23,300, and the elastic option cost $9,900.In year 1, the elastic option cost $6,700 compared with $1,400 for the buy option’s electricity usage.
- Results: The elastic option was slightly more expensive than buying physical servers, while leaving equivalent cloud resources running 24x7 cost more than twice the buy option.A 15% Amazon price reduction after two years made the elastic option cheapest.
- Discussion: The tool recommended buying physical servers when upfront capital was available; otherwise, cloud leasing required re-architecting for elasticity to avoid higher costs.The elastic option required 60% less upfront capital, so opportunity costs and other situation-specific factors also mattered.
5 Conclusion
Enterprise cloud adoption is difficult because system suitability, cost estimation, organizational change, and governance are not straightforward. The Cloud Adoption Toolkit offers a structured starting point, while its Cost Modeling case study shows that cloud savings depend on resource usage and deployment choices.
- Cloud adoption decisions involve uncertain system suitability, complicated cost calculations, substantial organizational change, and poorly understood governance issues.
- The Cloud Adoption Toolkit addresses these challenges through Technology Suitability, Energy Consumption, Stakeholder Impact, Responsibility, and Cost Modeling techniques.
- Cost Modeling showed that provider-promoted cloud savings cannot be generalized because they depend on resource usage and system deployment options.
- The case study recommended buying physical servers when upfront capital is available, or re-architecting systems for elasticity before leasing cloud resources.
- Future work includes applying Stakeholder Impact Analysis, while some toolkit components were unnecessary for this single-organization public-cloud case study.