The organization “SoftArc Engineering Ltd” can utilize either Cloud Computing or Big Data in order to provide office automation to the civil engineering staff. The use of both the approaches will help in providing ability of accessing office automation which includes email, word processing, online storage for files whether they are present in their home or at office.
Benefits and issues of utilizing cloud computing
Benefits of utilizing Cloud computing includes:
Easy Implementation: Cloud hosting helps in allowing business to retain the same applications as well as business processes without dealing with backend technicalities (Rittinghouse & Ransome, 2016).
Accessibility: The data of SoftArc Engineering can be access from anywhere at any time. It helps in maximizing the productivity as well as efficiency of the organization
Efficient Recovery: With the help of cloud, computing approach the SoftArc Engineering will be able to retrieve accurate applications as well as data (Provost & Fawcett, 2013).
The issues of utilizing cloud computing includes:
No longer in control: The services of cloud cannot be managed properly by the in-house staff.
No redundancy: A cloud server is neither redundant nor backed up.
Bandwidth Issues: in order to have ideal performance, the customers need to plan properly and they should not pack large amount of storage as well as servers in small data centers (Hashem et al., 2015).
Benefits and issues of utilizing Big Data
Benefits: By utilizing the approach of Big Data, the SoftArc Engineering can provide office automation facility to its civil engineers. There are number of benefits of using big data in an organization (Arora, Parashar & Transforming, 2013). It can be used in business for detecting errors as well as fraud very quickly. It assists in developing effective strategies towards competition in real time. It also helps in accessing data from anywhere at any time.
Issues: The significant challenges that organizations mainly faces while utilizing big data approach include finding signal in the noise, data silos and inaccuracy of data. Due to inaccuracy of data, the decision-making procedure in the business gets affected (Whaiduzzaman et al., 2014). The big data is incapable of meeting the need of speed for various operations in the organizations.
The company, “SoftArc Engineering Ltd” must utilize the cloud computing approach. It is quite advantageous as it helps the company to provide the facility of office automation to the civil engineers (Wei et al., 2014). Cloud computing helps in providing proper cloud-based backup as well as recovery solutions for retrieving accurate applications as well as data. It also helps in enhancing the manageability of the organization.
Difference between locally hosted infrastructure and infrastructure provided using an IaaS provider in a public cloud
The differences between locally hosted infrastructures and infrastructure provided by utilizing an IaaS provider in public cloud include:
Security: Locally hosted infrastructure helps in providing higher degree of security as compared to the infrastructure that utilizes IaaS provider in a public cloud (Tao et al., 2014). The information as well as data shared by cloud sources does not help in providing the same amount of control.
Accessibility: For accessibility, infrastructure provided by utilizing IaaS provider in a public cloud is very much superior as compared to locally hosted infrastructure. Rather than limiting, it helps in enhancing as well as improving the ability to reach data.
Cost: One of the significant differences between locally hosted infrastructure and cloud infrastructure provided by IaaS provider in public cloud is cost (Xiao, Song & Chen, 2013). Infrastructure using an IaaS provider is quite expensive as compared to locally hosted infrastructure.
Discuss the critical issues and factors that occurs due to migrating the Web Infrastructure to an IaaS provider
The critical issues as well as factors that occurs due to migrating the Web infrastructure to IaaS Provider includes:
Privacy and security in the cloud: One of the biggest concerns for SoftArc Engineering is the security of various confidential as well as private data and information (Kar & Rakshit, 2014). The organization needs to trust their vendors for protecting confidential data and information from unauthorized access.
Downtime and Technical difficulties: Outage as well as downtime is the two challenges that organizations faces while using an IaaS Infrastructure. The entire set up is connected with the help of Internet and any connectivity or network related issues helps in making the system useless.
Dependency on Vendor-lock-in: One of the most significant concerns is the dependency on the service provider (Bruneo, 2014). It is often referred to as vendor lock-in and the businesses find it quite difficult as well as sometimes impossible to switch from one service provider to another.
Limited Control and Flexibility: The softArc engineering must be concerned about the fact that they have to exercise limited control over the execution of both hardware and software because the applications as well as services run on a third party.
Enhanced Vulnerability: The migration of Web Infrastructure to an IaaS provider enhances the risk of being exploited by malicious hackers as well as users (Leppink et al., 2013). Due to interdependency on the cloud system, a compromise on one of the servers where data is stored may lead to leakage of personal information.
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IaaS |
PaaS |
SaaS |
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Infrastructure as a service is a form of cloud computing that helps in providing virtualized computing resources over the internet (Wu et al., 2014). |
Platform as a Service is one of the category of cloud computing services that helps in providing a platform, which helps in allowing customers to run, manage as well as develop applications without any complexity. |
It is one of the software licensing as well as delivery model in which the software is licensed on a subscription basis for hosting it centrally |
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One of the significant benefits of IaaS infrastructure model is that it is cost effective. The organization does not have to ensure uptime, hardware maintenance and maintaining hardware as well as networking equipment. |
With the help of PaaS, development teams are able to try various configurations, different machines for accessing compatibility, performance in a local environment (Marz & Warren, 2015). |
SaaS solutions help in residing in the environment of cloud, which are scalable and have integration with other SaaS offerings (Provost & Fawcett, 2013). |
SaaS is the model, which is considered as the most appropriate for SoftArc Engineering Ltd. This is because Software as a service helps in delivering various applications over the internet as a service. Instead of maintaining as well as installing the software, one can simply access it with the help of the Internet (Kar & Rakshit, 2014). It helps in freeing an individual from complex software as well as hardware management. As SoftArc engineering wants to provide an ability to the civil engineering staff to access office automation which includes e-mail, word processing as well as spreadsheet capabilities from anywhere (Bruneo, 2014). Therefore, SaaS is the best model as it helps in providing all the applications with the help of software for managing as well as accessing various applications including availability as well as performance. The organization does not have to install, maintain as well as update hardware as well as software as they only need proper internet connection.
The most likely problems that SoftArc Engineering Company will encounter with the SaaS model include:
Data Security: One of the most significant problems that SoftArc Engineering will encounter is data security. With the help of SaaS model, data breaches can occur which can put the organization into risk (Whaiduzzaman et al., 2014).Whenever a computer as well as an application is compromised then the customer application, which is supported by SaaS, can be exposed to the hackers. Hacking significant as well as confidential data bring some negative impact on the organization.
Ongoing business concerns: Sometimes, the organizations have no option before and as a result, they outsource certain tasks including IT. However, outsourcing It task will assit in losing control over the activities if the service provider and as a result it open up various types of risks for them.
Availability: The organization “SoftArc Engineering” wants to access the various resources of the office but with the use of SaaS model, different types of issues like internet as well as power outrages can occur (Arora, Parashar & Transforming, 2013).
The SoftArc Engineering will deal with the issues by following some of the steps below:
End to end reporting as well as logging: The data that is stored with the help of SaaS model must be monitored closely. This is very much to analyze the person who is accessing various information of the organization.
Authentication as well as authorization: Proper authentication as well as authorization helps in securing the data and it helps in minimizing Data Loss Prevention (Rittinghouse & Ransome, 2016). It is analyzed that only password as well as name is not a proper authentication procedure. Therefore, it is quite important to have tiering access policies that must be based on the level of trust.
Infrastructure Hardening: VM as well as VM templates required to be hardened as well as cleaned. This can be done when the images are created. On proper basis, testing of the master images required to be completed.
References
Arora, R., Parashar, A., & Transforming, C. C. I. (2013). Secure user data in cloud computing using encryption algorithms. International journal of engineering research and applications, 3(4), 1922-1926.
Bruneo, D. (2014). A stochastic model to investigate data center performance and qos in iaas cloud computing systems. IEEE Transactions on Parallel and Distributed Systems, 25(3), 560-569.
Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, 98-115.
Kar, A. K., & Rakshit, A. (2014). Pricing of Cloud IaaS Based on Feature Prioritization-A Value Based Approach. In Recent Advances in Intelligent Informatics (pp. 321-330). Springer International Publishing.
Leppink, J., Paas, F., Van der Vleuten, C. P., Van Gog, T., & Van Merriënboer, J. J. (2013). Development of an instrument for measuring different types of cognitive load. Behavior research methods, 45(4), 1058-1072.
Marz, N., & Warren, J. (2015). Big Data: Principles and best practices of scalable realtime data systems. Manning Publications Co..
Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big Data, 1(1), 51-59.
Rittinghouse, J. W., & Ransome, J. F. (2016). Cloud computing: implementation, management, and security. CRC press.
Tao, F., Cheng, Y., Da Xu, L., Zhang, L., & Li, B. H. (2014). CCIoT-CMfg: cloud computing and internet of things-based cloud manufacturing service system. IEEE Transactions on Industrial Informatics, 10(2), 1435-1442.
Wei, L., Zhu, H., Cao, Z., Dong, X., Jia, W., Chen, Y., & Vasilakos, A. V. (2014). Security and privacy for storage and computation in cloud computing. Information Sciences, 258, 371-386.
Whaiduzzaman, M., Sookhak, M., Gani, A., & Buyya, R. (2014). A survey on vehicular cloud computing. Journal of Network and Computer Applications, 40, 325-344.
Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2014). Data mining with big data. ieee transactions on knowledge and data engineering, 26(1), 97-107.
Xiao, Z., Song, W., & Chen, Q. (2013). Dynamic resource allocation using virtual machines for cloud computing environment. IEEE transactions on parallel and distributed systems, 24(6), 1107-1117.
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