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Description of the cloud architecture that would employ to assist SoftArc Engineering to meet the Board’s strategy

Discuss About The Case Study On Soft Arc Engineering?

The report depicts the importance of changing a business platform towards hybrid cloud for increasing the overall business efficiency and for gaining the measurable market revenue. After deep investigation the traditional business and cloud architecture can be compared. In order to assist SoftArc Engineering the most suitable cloud architecture that must be employed is elaborated in this report. In addition to this, the benefits and issues associated to the cloud architecture and the reasons behind its in deployment in SoftArc Engineering are also elaborated in this report.

However different risk also might occur during the implementation. In order to mitigate the challenges in terms of risks certain control strategies are needed to be developed. Those are also illustrated in this report. Apart from the security steps, a brief recommendation including the companies BCP as a result of hybrid cloud adaptation are also discussed. In order to conduct the proposed IaaS and PaaS Remote server administration, Resource management and SLA management processes should be considered. While making movement towards SharePoints instance to AWS cloud different issues and their mitigation strategies are also illustrated in this report.

Software as a Service (SaaS) is referred to as the most suitable cloud architecture that should be employed in SoftArc Engineering (Kaur et al., 2015).  This delivery model provides proper license to the company leader, for using the required software whenever required.  Not only this, but also the overall management cost also get reduced after the implementation of SaaS cloud model in SoftArc Engineering.

After investigating the products and services of SoftArc Engineering it has been found that SaaS is the most suitable cloud architecture for gaining measurable market revenue and competitive advantages as well (Puthal et al., 2015).

Implementation of SaaS model in SoftArc Engineering stands beneficial due to certain reasons. First of all the most frequently rising issue associated to technology that is security can be enhanced with the help of SaaS model (Djemame, et al., 2014). On the other hand, it is not as costlier as the other models and is less time consuming also. For the software adaptation and its maintenance the cloud service model are completely responsible. SaaS model is used due to its customization feature. In addition to this, scalability, reliability and data integrity are the other characteristics that help to upgrade the information system of SoftArc Engineering on each and every session (Durairaj & Manimaran, 2015). The users need not to get any additional training for using this platform and due to the platform proof concept it also offers software testing opportunity to the users.

Description of the architectures that would be used

Reliability: The model is reliable and the users can use the system easily and the due to automated upgrade feature as per the changing technology the system will be updated automatically.

Scalability and flexibility: The system is flexible enough and the resource requirements can be automatically scale up and scale down as per the customer’s demand.

System access: The data stored in the cloud server can be accessed easily and due to high range security none of the external attackers can access information from the server without authorization or permission (Grozev & Buyya, 2014).

High performance: From system analysis it has been found that browser access is easier with the help of accurate internet connection in case of SaaS model whereas; in other model even though high internet connection is served still accessibility is not easier.

Authorization: The system provides authorization or data security to the users while accessing data from the server (Pahl, Xiong & Walshe, 2013).

Security: Due to lack of security, the data stored in the server might get hijacked by the external attackers without permission. In order to mitigate this issue proper encryption algorithm is required to be adapted by SoftArc Engineering.

Performance management: In order to increase the performance level of SaaS model, accurate technologies are required to be adapted by SoftArc Engineering.

The risk associated to SaaS hybrid model and its control measures that are required to be adapted are elaborated in the below section:

Data redundancy: In case of hybrid model the biggest issues mostly raised is the data redundancy (Abbas, Farooq & Afghan, 2015). Due to hybridization single information might get stored in multiple sections. It will grab extra storage and for storage wastage necessary application might not get appropriate value in the system.

Lack of security management: Due to lack of security management, the sensitive information stored in the server might get hijacked by the external attackers and those could be misused by them.

Application error: I order to meet the requirement of the consumer’s; hybrid cloud needs extra attention and supportive diligence as well (Brender & Markov, 2013). It has been analyzed due to lack of infrastructure and support, the authority fails to make appropriate maintenance of the models.

Risks

Mitigation strategy

Data redundancy

In order to mitigate this issue time to time system upgrade is needed. It will help to minimize the rate of data redundancy and storage wastage at the same time (Zhou et al., 2013).

Lack of security management

In order to mitigate this problem proper system authorization, authentication and encryption algorithm are required to be adapted by the management authority so that only authorized users could access the server on the required time phase (Oliveira, Thomas & Espadanal, 2014).

Application error

For overcoming this risk the management should adopt accurate industry standards and data security approaches during the system handling phase.

In order to combat the risk associated to system security, proper security steps are needed to be adapted by the authority and the security steps are as follows:

Risk identification: This is the initial phase of risk management processes, in this period the management should identify the risks those might occur during the deployment and implementation phase.

Reason behind the deployment

Risk analysis: In order to implement accurate security the risk are required to analyze well and then based upon the type of the risks the strategies must be developed (Almorsy,  Grundy & Muller, 2016). Both long terms as well as short term system monitoring approaches are needed to analyze the risk so that exact security measure can be implemented.

 Risk ranking: Based on the priority all the identified risks should be ranked by the management authority. After proper ranking of the risks security measures will be implemented for each risk.

Security management: Even after the implementation the system for maintenance also accurate security management is needed (Sanaei et al., 2014).  With the help of system replication, the in house data storage and hybrid cloud both can be maintained well by the security application.

Avoidance of data redundancy: The data redundancy must be avoided. It will help to reduce the rate of storage wastage and even multiple data centers could also be handled properly after the implementation of security system.

Though hybrid cloud is a beneficial technology but still at the same time many vital risks are also associated to the system (Avram, 2014). The recommendations those have been suggested for SoftArc Engineering are as follows:

Application resilience: Application resilience is referred to as the capability of execute an application easily even after the presence of distributed error throughout the system.web infrastructure also lacks this specialized characteristic.

Data backup: If any data get lost from the server then with the help of data backup feature, the information could be retrieved from the server again whenever required by the users (Botta et al., 2014).

Disaster recovery: If any information gets destroyed then ability to recover that data is termed as data recovery. In SaaS model after any disaster also data could be fetched from the server with expertise help. Though, in web infrastructure disaster recovery was not possible. However, hybrid data could be recovered easily with the help of disaster recover feature of hybrid SaaS cloud model.

In order to conduct the needs for SoftArc Engineering in context with the PaaS and IaaS platform or cloud models, the instances that must be included are as follows:

System analysis, system understanding, administrative management process are the components that must be considered for the remote server administration. The system could set up easily and the within less amount of budget the system can even perform for remote server administration (Dinh et al., 2013). It provides different management tools and interactive platform to the users for developing administrative level management system.

Benefits and issues of the deployed architecture

Different resources and needed to develop a system and for the system migrating other associated resources are needed by the system developers. While considering IaaS and PaaS the resources required are differs from each other (Abbas, Farooq & Afghan, 2015).  If proper resources are identified the accessibility, time and cost everything will stand beneficial for SoftArc Engineering.  The company can access required information regardless of time and location if accurate resources are identified and used by the developers.

In order to establish secured relationship between the end users and the service providers of cloud system, Service Level Agreement (SLA) is needed to be adapted for conducting all the system application accurately without any error. SoftArc Engineering Company should consider this feature foe gaining license of the software for both quality and productivity (Grozev & Buyya, 2014). With the help of SLA the users will be able to grab products in affordable price range and the service providers could develop discount strategies also.  Proper alignment among the services and the system could be improved or build up if SLA guidelines are maintained accurately.

The steps needed to be followed are as follows:

  1. Accurate migration plan
  2. Infrastructure implementation
  3. Customization
  4. Testing plan
  5. Up-gradation
  6. Migration through third party products

Planning for migration: System complexity and dependency are the two major issues associated to migration planning phase.  

Implementation of accurate architecture plan: Base on the demand and type of the business the system developers should implement accurate architecture for conducting and running the application (Almorsy, Grundy & Muller, 2016).

Understanding customization and integration: Proper integration and customization are very much important for the system security and planning as well In order to implement the system properly all the features must be integrated properly.

Migration issue: During platform migration information might get lost from the server and if the migration is not validated then applications cloud not run properly on the platform (Sanaei et al., 2014).

Migration test development: If platform migration test is not done properly then, huge number of risks might occur and will not allow the users to test the migrated data properly.

Implementation of Microsoft upgrades approach:  Within a specified data base, problems might arise and also could negatively impact the migration.

Conclusion

From the overall discussion it can be concluded that SoftArc Engineering should migrate their platform from the traditional one to the SaaS for increasing the overall business efficiency in terms of productivity and quality as well. The benefits and issues associated to hybrid cloud and the issue mitigation strategies are also illustrated in this report. Apart from this, the features named as application resilience, disaster recovery and data backup are also elaborated in this report. Additionally, the steps required to implement security in the system are depicted in the report minutely.

Risks associated to new Hybrid cloud architecture

References

Abbas, R., Farooq, A., & Afghan, S. (2015). A Security Model for SaaS in Cloud Computing. University of Engineering and Technology Taxila. Technical Journal, 20(4), 103.

Almorsy, M., Grundy, J., & Müller, I. (2016). An analysis of the cloud computing security problem. arXiv preprint arXiv:1609.01107.

Avram, M.G., 2014. Advantages and challenges of adopting cloud computing from an enterprise perspective. Procedia Technology, 12, pp.529-534.

Botta, A., De Donato, W., Persico, V., & Pescapé, A. (2016). Integration of cloud computing and internet of things: a survey. Future Generation Computer Systems, 56, 684-700.

Brender, N., & Markov, I. (2013). Risk perception and risk management in cloud computing: Results from a case study of Swiss companies. International journal of information management, 33(5), 726-733.

Dasic, P., Dasis, J., & Crvenkovic, B. (2016). Service models for cloud computing: Video Surveillance as a Service (VSaaS). Bulletin of the Transilvania, University of Bra?ov, Series I: Engineering Sciences, 9(1).

Dinh, H. T., Lee, C., Niyato, D., & Wang, P. (2013). A survey of mobile cloud computing: architecture, applications, and approaches. Wireless communications and mobile computing, 13(18), 1587-1611.

Djemame, K., Armstrong, D., Kavanagh, R., Juan Ferrer, A., Garcia Perez, D., Antona, D., ... & Guitart Fernández, J. (2014). Energy efficiency embedded service lifecycle: Towards an energy efficient cloud computing architecture. In Joint Workshop Proceedings of the 2nd International Conference on ICT for Sustainability 2014 (pp. 1-6). CEUR-WS. org.

Durairaj, M., & Manimaran, A. (2015). A study on security issues in cloud based e-learning. Indian Journal of Science and Technology, 8(8), 757-765.

Grozev, N., & Buyya, R. (2014). Inter?Cloud architectures and application brokering: taxonomy and survey. Software: Practice and Experience, 44(3), 369-390.

Kaur, J., Garg, S., Principal, R. I. M. T., & Gobindgarh, M. (2015). Survey paper on security in cloud computing. Int. J. Appl. Stud. Prod. Manage, 1, 27-32.

Oliveira, T., Thomas, M., & Espadanal, M. (2014). Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information & Management, 51(5), 497-510.

Pahl, C., Xiong, H., & Walshe, R. (2013, September). A comparison of on-premise to cloud migration approaches. In European Conference on Service-Oriented and Cloud Computing (pp. 212-226). Springer Berlin Heidelberg.

Puthal, D., Sahoo, B. P. S., Mishra, S., & Swain, S. (2015, January). Cloud computing features, issues, and challenges: a big picture. In Computational Intelligence and Networks (CINE), 2015 International Conference on (pp. 116-123). IEEE.

Sanaei, Z., Abolfazli, S., Gani, A., & Buyya, R. (2014). Heterogeneity in mobile cloud computing: taxonomy and open challenges. IEEE Communications Surveys & Tutorials, 16(1), 369-392.

Zhou, J., Leppanen, T., Harjula, E., Ylianttila, M., Ojala, T., Yu, C., ... & Yang, L. T. (2013, June). Cloudthings: A common architecture for integrating the internet of things with cloud computing. In Computer Supported Cooperative Work in Design (CSCWD), 2013 IEEE 17th International Conference on (pp. 651-657). IEEE.

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