Is cloud computing suitable for service and product developer?


The topic of cloud computing has been widely discussed in the literature and has been examined from many different perspectives. Many reasons for moving to the cloud have been identified. However, the majority of the literature focuses on reasons concerned with a technology and infrastructure perspective. This literature review will show that these may not be the only reasons for moving to the cloud. In addition, almost all the literature aims at cloud users or providers and many overlook the importance of cloud service and product developers. They are positioned between the cloud provider and cloud user. This review focuses on reasons related to new business models and services in the cloud from the perspective of cloud service/product developer. After the term ‘cloud computing’ is defined, reasons for moving to the cloud from a business perspective will be discussed. In the end different decision models for moving to the cloud will be compared.

Defining cloud computing

There are many definitions for cloud computing (Creeger 2009, Hai Jin, Ibrahim, Bell and Gao 2010, Liao, Chih & Fu 2011, Rayport and Heyward 2009, Vouk 2008, Youseff, Butrico and Da Silva 2008, etc..). The reason for the existence of different cloud computing definitions is, according to Zhang, Cheng and Boutaba, that cloud computing is a new operations model and not a new technology (2010). Vaquero et al. created a table with all the different definitions that exist, with a total of 22 definitions (2009). The definition by the National Institute of Standards and Technology (NIST), however, covers the majority of aspects. This definition states that cloud computing is “a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable devices” (Mell and Grance 2009). These devices can be hardware devices or services. Furthermore these devices “can be rapidly provisioned and released with minimal management effort or service provider interaction” (Mell and Grance 2009). In addition to this rather abstract definition NIST also define five characteristics, four deployment methods and three service models. The characteristics are (Mell and Grance 2009)

  • on-demand self-service,
  • broad network access,
  • resource pooling,
  • rapid elasticity, and
  • measured service.

The four deployment methods that exist are (Mell and Grance 2009)

  • private clouds (resources are made available to a closed group),
  • community clouds (resources are shared by several organisations with common interests),
  • public clouds (resources are made available to the general public by a cloud provider), and
  • hybrid clouds (resources are made available through two or more of the above methods).

The three existing service models are (Mell and Grance 2009)

  • Software as a Service (SaaS – software is provided via the cloud),
  • Platform as a Service (PaaS – software is created using tools and libraries from the cloud provider), and
  • Infrastructure as a Service (Iaas – computing power is provided via the cloud).

These three service models are widely accepted across the literature (Hobson 2012 or Youseff, Butrico and Da Silva 2008). Figure 1 shows the relationship between the four deployment methods and the three service models.

Figure 1 – Cloud computing model with the three service models and four deployment methods (adapted from Sriram and Khajeh-Hosseini 2010)

Reasons for moving to the cloud

A total of 21 reasons for moving to the cloud have been identified. This list does not claim to be comprehensive but covers most of the reasons. Only 7 of these reasons are related to new business models and services. This suggests that there is a lack in studying the aspects for moving to the cloud from a perspective that enables the development of new business models and services. The 7 reasons that support the development of new business models and services are (in no particular order):

  1. New technology trends and business models (Armbrust et al. 2009)
  2. New applications opportunities (Armbrust et al. 2009)
  3. Improves business processes (Aymerich, Fenu and Surcis 2008)
  4. Can lower IT barriers to innovation (Marston et al. 2011)
  5. Delivers services that were not possible before (Marston et al. 2011)
  6. IT shifts from trouble-shooting to business driver (Hobson 2012)
  7. Makes IT organisation more agile (Nichols and Sprague 2012)

This list shows that cloud computing can be an enabler for new business models and services and demonstrate that it is a business problem and not a technology problem that cloud computing hasn’t been investigated from this perspective. When taking a closer look at these reasons it is possible to identify an area of research that helps to investigate the topic from this angle: service engineering.

Service engineering is the integration of software engineering, underlying infrastructure and enterprise-level decision makers to develop electronic services (Cardoso, Voigt & Winkler 2009, Margaria & Steffen 2006). The essences for this kind of service orientation are according to Margaria & Steffen: mature environments supporting domain specificity, virtualisation, loose coupling and seamless vertical integration (2006). Cardoso, Voigt & Winkler point out that for successful service integration the virtual and horizontal dependencies have to be considered (2009). Virtual dependencies mean the synchronisation of dependencies on different layers of abstraction. Horizontal dependencies mean the synchronisation of dependencies on the same layer of abstraction. This description makes the point that the main goal of service engineering is to improve the efficiency and quality of services that are developed and delivered (Chen 2008, Tomiyama 2001).

Decision making

When considering the transition to the cloud and the associated decision models a consistent picture can be found. Most of the decision models examine only how to move existing applications and services to the cloud. Two areas that are needed for the development of new business models and services are revenues and costs. A review of the factors to be considered before making a decision about moving to the cloud showed that revenue and cost issues are often closely related or even the same. For example the factor ‘availability of a service’ affects the revenue as well as costs. Having a higher availability from a cloud provider generally costs more but lets the service/product developer sell the service for a higher price (Armbrust et al. 2009). Elasticity is another example of a factor affecting revenue and cost. The revenue is improved because there is no up-front capital investment for infrastructure necessary. But cloud providers often demand a much higher price when the usage exceeds the agreed limit (Armbrust et al. 2009). What does this mean for the decision models? Because the factors affect revenues as well as costs decisions about moving to the cloud have to be carefully considered. A total of eight different decision models have been identified. Although this list is not complete it shows an important fact: also for decision models (about moving to the cloud) the literature focuses on existing applications and services to move but misses to discuss the development of new business models and services for the cloud (Buyya, Ranjan and Calheiros 2009, Ferguson-Boucher 2011, Gandhi, Moe, and Sprague 2012, Hobson 2012, Marston et al. 2011, Nichols and Sprague 2012, Wyld 2009). By combining elements of the different decision models it is possible to outline a framework that supports the development of new business models and services:

  1. Adopt new mind-sets and capabilities because IT staff no longer have to procure hardware and software, and install and configure it, but can focus on improving business processes and developing new kinds of applications (Huxford 2012, Marston et al. 2011)
  2. Audit what does and doesn’t work about the current IT (Hobson 2012) to identify areas which need development
  3. Identify the features needed now and in the near future for the identified development areas (Ferguson-Boucher 2011). It is especially worth considering:
    • Capacity
    • Security
    • Disaster recovery
    • Performance
  4. Choose a service model to determine the optimal cloud service for the identified development (Nichols and Spague 2012)
    • IaaS
    • PaaS
    • SaaS
  5. Select the right deployment model based on the nature, roles and individuals, and infrastructure requirements for the identified development (Nichols and Sprague 2012)
    • Traditional IT
    • Virtualised data centre
    • Private cloud
    • Hybrid cloud
    • Community cloud
    • Public cloud

This framework emphasises that service developers need to think about their customers and projects. Especially important to them is that they will evaluate using the cloud on a project basis and not just once. In addition, they always need to evaluate consequences for themselves and their customers.


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