Article Preview
TopIntroduction
Cloud Computing (CC) is a paradigm that utilizes virtualization and a service-oriented architecture to provide access to hardware, software and data from cloud providers’ datacenters (Namasudra, 2018). It changes the current landscape in which organizations manage their own Information Technology (IT) infrastructure to another where IT is consumed as a service (ISACA 2012).
Cloud has some intrinsic characteristics like the use of a large resource pool, shared by multi tenants, elasticity, pay-per-use and broad access by network (Mell et al, 2011). These characteristics provide benefits to the users: IT cost reduction, agility, support to innovation, several cost models, etc (Armbrust et al., 2010), (Gartner, 2017), (Srivastava & Nanath, 2017). On the other hand, the complex nature of CC introduces potential challenges related to security, trust, privacy, data confidentiality, data security, ethical issues, regulation, organizational change, technical incompatibility and vendor lock-in, among others (Namasudra et al., 2017), (Efremovska & Lago, 2017), (Namasudra & Roy, 2018), (Namasudra, 2019).
The use of cloud services is growing at a rapid pace and several organizations either have started using these services or have planned to do so on the next few months. According to (IDC, 2018), the worldwide spending on public cloud services reached US$160 billion in 2018, an increase of 23.2% over 2017. Considering the period of 2016-2021, the market will achieve a five-year compound annual growth rate (CAGR) of 21.9% with public cloud services spending a total of US$ 277 billion in 2021. The adoption of CC is a subject of several works that have studied its impact in various industries like healthcare (Boiron & Dussaux, 2015) and other business processes (Benmerzoug, 2015).
In the government domain, due to the huge scale of services and population in certain countries, the cloud is an appealing solution to reduce costs and operational effort regarding the IT infrastructure (Kundra, 2011). The expectation is that the adoption of CC in government organizations can also reduce the number of contracts and consequently reduce the opportunities for irregularities while improving efficiency. But, despite the widespread commercial adoption of the cloud, its introduction into government agencies is still a challenge. In the public sector, things are not quite smooth. The needs of governments are unique and specific. User bases have unique requirements bounded by security, internal connectivity, legacy applications, specific authentication needs, auditing mandates, training concerns, and privacy regulations. Significant foresight and planning are required for government cloud transitions (ACT-IAC, 2018).
As stated by (Pahl & Xiong, 2013), migration to the cloud is the process of deploying, in whole or in part, the digital assets, services, IT resources, or systems of an organization on the cloud. There is a trend of increasing the CC usage and government organizations may benefit of using a clear methodology, based on guidelines and methods to migrate legacy systems to the public cloud.
A study in the area of migrating legacy systems to the Cloud (Costa & Solis, 2018) shows the comparison of three migration models using a reference model defined by (Gholami, Daneshgar, Beydoun, & Rabhi, 2017). In that work, a Risk Perception Indicator (RPI) was defined to improve the reference model usage. RPI is based on a subset of reference model’s tasks and can be calculated with little effort. The subset of tasks is defined on a domain basis and that study has proposed the subset that better characterizes the government domain. To use RPI on a migration process, the technical team agrees on a rate of perceived risk to each task on the set (in the case of government domain, there are six tasks). The rate is chosen from a 5-value Likert scale, where 1=High risk, 2=Moderate risk, 3=Average risk, 4=Somewhat risk and 5=Low risk. After that, RPI of the system been evaluated is calculated. This is done to each system that will migrate to the cloud, before any migration has occurred. The benefits of RPI is the creation of a sequence of migration that prioritizes low risk systems, and this is done with little effort. An important parameter to RPI calculus is the weight that is assigned to each task. A previous work of the authors of this paper (Costa & Solis, 2018) has defined empirically the weights of six tasks that compound the RPI calculus on the government domain.
The purpose of this research is to present the defined model and RPI to government organizations, collect the perception of employees about them and adjust RPI’s task weights according to those perceptions.
In this present paper, the work of (Costa & Solis, 2018) is extended with the following new contributions: