Technology evolution and the continued innovation in the IT industry has led to the emergence of cloud computing which many institutions, enterprises, and governments are now shifting their IT infrastructure to. The increasing dependence by many organizations has led to the need to have systems and applications that can be accessed by millions of users without affecting the overall performance and productivity while maintaining high level availability (Viswanathan, 2018). This report seeks to propose to Headspace the critical aspects that should be considered when implementing the NewAccess project including non-functional requirements, strengths and weaknesses of cloud computing, security requirements, and the type of system development life cycle approach that Headspace can adopt.
When considering a cloud-based solution, many at times people tend to focus more on the functional requirements which are the features and abilities expected by users to be performed by the system, that is, what the system should do. Functional requirements tend to vary across the different departments and employees. However, every solution has non-functional requirements that are also very crucial and should never be abstracted or overlooked (Crudele & Castiglioni, 2014). an application may have met all the functional requirements but it will be considered a failed project if it does not meet the non-functional requirements. In traditional software development, the developers have often modified the shape and size of the application in order to respond to the non-functional requirements. Non-functional requirements define the features that a cloud solution should have and the functional constraints. They include, but not limited to, security, usability, performance, and reliability.
These requirements have a huge impact on the acceptability of the system by the intended users. For example, a system might have addressed all the functional requirement but the fact that it may not be user friends, have a poorly design interface, or hard to use may lead to it being rejected. The non-functional requirements are discussed below:
Usability: different users have different usability requirements, for instance the requirements of ER departments is totally different from that of the accounting department even though they share a common system. Usability requirements describe how the interface of the various users should look like (Eriksson, 2011). The cloud-based solution being considered by Headspace to accomplish the NewAccess project should be easy to use and allow the users to interact with the system with little or no support.
Reliability: this is a very essential requirements that ensures that users can be able to trust the system that it will be there whenever they need it. The biggest concern in a cloud solution is reliability specifically because it addresses the critical solution to the business. Undesired downtimes of the application may shutter off a lot of customers and lead to the company incurring heavy loses. Headspace being an institution that deals with critical services that they offer to the mentally challenged youth require a cloud solution that over high-level availability and ensure that the services are available whenever they are needed (Jayachandran, 2016).
Performance: users expect an application to process their request using the shortest time possible. With the increasing bandwidth and speed of the internet, users adopting cloud solution expect that the cloud solution should have lighting response from the application. users expect the same performance and processing speed regardless of the amount of processing requirements that they are carrying out. As such, Headspace should ensure that the cloud solution being considered should not have performance bottlenecks and that the cloud provider supports micro services architecture, asynchronous processing, multi-data availability among others (Phalnikar & Jinwala, 2015).
Security: this is a crucial requirement that Headspace should put more emphasis on. This is because Headspace will be dealing with medical data which are very sensitive and should be protected from threats and hackers. The cloud-based solution should guarantee data security and ensure that security features such as two-factor authentication has been implemented to ensure that only authorize users are allowed to access the data
Advances in technology has brought about numerous new opportunities to enterprises to create new services, share data, communicate, and develop new products. Cloud computing provide ubiquitous processing power to process numerous requests every time. This has facilitated the exchange of information and data storage anywhere and anytime at high speed (Avram, 2014). Cloud computing has the capacity to merge data storage and computational power in an IT infrastructure that is dynamically scalable, that is, the application or system is flexible enough to grow when required which has enable business services to be decoupled from the infrastructure. This has changed the paradigm in computing and has led to the emergence of vendors that offer cloud computing on pay-per-use enterprise model, providing the clients with huge storage capacity and high computational power.
Cost Effectiveness: this is the most cost-effective technological solutions for any business. It is cheap to use, upgrade and maintain. Procuring and maintain the traditional applications is expensive because of the numerous licenses that have to be procured and the regular maintenance that the system has to undergo. In cloud computing all the maintenance and upgrades are done by the cloud provider which significantly reduces the costs that Headspace has to incur (Kumar & Salimath, 2012). Additionally, the institution will only pay for what it uses.
Data Availability: cloud-based solutions offer a high rate of service, application, and data availability anytime and anywhere. This is very crucial for the Headspace because the data and records needed to offer the best services of the mental patients should be available at all times. Additionally, Headspace workers working offsite should be able to access the data from any location (Linthicum, 2018). This increases the quality of services offered to the patients.
Unlimited Data storage: Headspace will be handling huge amount of data in which traditionally it would have to procure hard disks with large capacities. However, by adopting cloud solution, this limitation is removed because of the unlimited storage space provided for the customers by the cloud provider (Phalnikar, 2016).
Scalability: cloud computing offers high level of flexibility to facilitate modification and adjustments of the applications and services to meet the growing needs. With cloud computing expansion/scaling IT infrastructure is very simple because of the user-friendly interfaces provided by the loud providers that enables that users to scale their services by a click of a button. Emerging issues and problems that enterprises and institutions normally face as they grow are resolved by employing cloud solutions. Since the cloud environment provide the resources quickly, the need of capacity planning is completely done away with.
One of the major issues that is facing cloud-based solution is data ownership and privacy. By outsourcing the data storage to third parties (cloud provider), the question of who own the data arises. Before choosing a cloud solution it is important that the cloud provider clearly defines the issues of data ownership in the service level agreement (Luís, 2011). The fact that there are no particular standards that govern data ownership in the cloud raises privacy concerns.
As such, Headspace should consider this issue before deciding on the cloud solution. Other weaknesses that cloud computing faces include data security because of the increases cyber threats and cybercriminals which can lead to denial of service attacks and technical issues which may cause service unavailability
The SDLC offers a logical process for developing and producing software applications from start to end. It is a method used to create, design and examine high quality software. It consists of various stages such as planning stage, assessment stage, design stage, implementation stage and maintenance stage. There are two different methodologies of SDLC namely adaptive SDLC and predictive SDLC. The practices connected to adaptive methodology provides potential to adjust to changes and are fully flexible in the complex environments with various products emerging with little planning and learning. Various stages of adaptive methodology involve collaborate, speculate and learn. On the other hand, predictive approach is a method that initially considers project planning before beginning the project. Various processes involved in predictive SDLC include initiation, planning, assessment, design, implementation and deployment.
Adaptive SDLC provides a design model that is flexible, promoting evolutionary development and adaptive planning. The project is divided into small modules. Client feedback and software testing occurs concurrently with development. As such, many benefits are acquired particularly in project environments where the ability to respond effectively and rapidly to requirement changes is needed (Karim, Albuolayan, Saba & Rehman, 2016).
In addition, adaptive methodology facilitates communication and interaction. Collaboration is more essential than design. Since communication between various stakeholders and designers is key, it is particularly favorable for teamwork-oriented environments (Ed, 2013). Various developers work on various modules throughout the process of development and then, at the end of the project, they combine together all the modules into a single software piece.
Although the adaptive approach is highly adaptable, it lacks the structure that the predictive approach has and thus, present some disadvantages. It is difficult to project the timelines and budget in projects that uses adaptive methodology. Without a solid plan, everything appears to be nebulous and vague (Beyer, 2010). First, the adaptive method consumes more time than predictive method. As such, designers need to be fully dedicated from the start to the end of the project. If a designer leaves in the process of development, then it could cause a lot of problems.
The most important thing in predictive method is the project plan and hence before starting any kind of development, a clear vision and plan should be established. Since the predictive approach requires direct and detailed planning, software can be launched quickly. Besides, budgets and timetables can be estimated more accurately (Sharma & Singh, 2015). Since the final outcome is known, predictive is more secure as compared to adaptive approach and a new designer or developer can easily take over the project with minimal interruptions to the budget and timeline.
Predictive approach is characterized by rigidness and inflexibility because the end outcome of the project is known and gives little room for modification and adjustments. With this approach the project may fail if some requirements are interfered with in the early stages. In this approach testing of the software product is done in the later stages thus if the product being develop doesn’t meet the requirements the company will incur loses and would have wasted a lot of time and human resource.
The best methodology for Headspace is adaptive SDLC as it is helpful for small and large projects. The adaptive approach is the best because it is flexible and it involves extensive user involvement. Therefore, the end product is usually of high quality and customers are satisfied with it. Besides, adaptive methodologies tend to be faster since all involved parties see consistent progress in small observable sprints. With continuous and increased user input, an appropriate solution is likely to be developed and deployed.
Conclusion
Adoption of cloud computing is significantly increasing every day and this can be considered as a natural data center evolution to support more scalable and flexible storage and computing resources. The main benefits that the cloud-based solution will offer include wide availability, cost effectiveness, backup and disaster, and high scalability. However, it is also faced with numerous challenges concerning data privacy, ownership, interoperability, technical issues, and trust. As such, it is recommended that Headspace adopt cloud-based solution.
References
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Beyer, H. (2010). User-centered agile methods. [San Rafael, Calif.]: Morgan & Claypool Publishers.
Crudele, M., & Castiglioni, F. (2014). Manage non-functional requirements for cloud applications. Retrieved from https://www.ibm.com/developerworks/cloud/library/cl-bluemix-nfr/index.html
Ed, K. (2013). Agile methodology for developing & measuring learning. [Bloomington, Indiana]: Authorhouse.
Eriksson, U. (2011). What are Non-functional requirements?. Retrieved from https://reqtest.com/requirements-blog/what-are-non-functional-requirements/
Jayachandran, J. (2016). Top 10 Critical NFR for SaaS Applications. Retrieved from https://blog.techcello.com/2016/04/top-10-critical-nfr-for-saas-applications-part-1/
Karim, N., Albuolayan, A., Saba, T., & Rehman, A. (2016). The practice of secure software development in SDLC: an investigation through existing model and a case study. Security And Communication Networks, 9(18), 5333-5345. doi: 10.1002/sec.1700
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Linthicum, D. (2018). Approaching Cloud Computing Performance. IEEE Cloud Computing, 5(2), 33-36. doi: 10.1109/mcc.2018.022171665
Luís, B. (2011). Strengths and Weaknesses of Using Cloud Computing. Retrieved from https://healthmanagement.org/c/imaging/issuearticle/strengths-and-weaknesses-of-using-cloud-computing
Phalnikar, R. (2016). Validation of Non-functional Requirements in Cloud Based Systems (Short Paper). 2016 5Th IEEE International Conference On Cloud Networking (Cloudnet). doi: 10.1109/cloudnet.2016.18
Phalnikar, R., & Jinwala, D. (2015). Analysis of Conflicting User Requirements in Web Applications Using Graph Transformation. ACM SIGSOFT Software Engineering Notes, 40(2), 1-7. doi: 10.1145/2735399.2735414
Sharma, P., & Singh, D. (2015). Comparative Study of Various SDLC Models on Different Parameters. International Journal Of Engineering Research, 4(4), 188-191. doi: 10.17950/ijer/v4s4/405
Viswanathan, P. (2018). Cloud Computing: Know the Pros and Cons. Retrieved from https://www.lifewire.com/cloud-computing-explained-2373125
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