Headspace System Design Project: Cloud-based Solutions

The system’s nonfunctional requirements

Discuss about the Headspace System Design Project for Storage.

Cloud computing has in the past few years revolutionized the methods of accessing IT resources through the leasing services it offers to end users. This outcome has increased the benefits of virtualization where today many organizations are shifting their resource requirements online owing to the increased accessibility and availability benefits. Moreover, cloud computing adequately minimizes the cost of operation because the resources are implemented and maintained by service providers while they (the end users) apply them. Therefore, in cases where IT infrastructure such as computing power, storage and networks are needed, the users simply subscribes to service providers while considering their immediate requirements (Huth & Cebula, 2011). Similarly, Headspace requires a similar approach to its service systems where a lot of information is needed which increases the resource requirement. Furthermore, the organization requires efficient resources that are readily available to the users at any given time. Now, this report highlights these feature/requirements and how they can be fulfilled by cloud computing. In addition to this, the different implementation procedures are given based on the non-functional requirements of the proposed system.

In comparison with the functional requirements, non-functional requirements highlight the characteristics and attributes of systems that enhance the interactions between the users and the developed platforms. Therefore, they have minimal technical components but will determine the overall rate of system satisfaction. In this case, security and data ownership are critical components which should be reflected in these requirements (Chung, 2012).

Let’s highlight some of the key components of the non-functional requirements:

1. Performance – technically speaking, a multitude of components determine the overall performance of the system. These components should have an adequate interaction to facilitate the actions of the user e.g. compatibility with all operating systems and other computing resources.
2. ii. Usability – system practicality, the system should not be simple to use but yet have poor security features. A balance between security, privacy and practicality must be exhibited.

iii.    Security – system authentication and encryption must be incorporated to offer an end to end system protection and encryption, functionalities that will improve the access limitations i.e. data security and ownership (Taylor, 2000).

Now, based on the outline of the non-functional requirements, the system qualities will define the overall attributes that will yield a favourable system for the health department as given by the Headspace project. Therefore, it should be easy to use based on its performance, an outcome that requires the balance between reliability and functionality. In essence, the system technicality must cater for the end user who will have varying literacy levels. Finally, the security should protect the data in use and critically outline the ownership conditions (Gorton, 2011).

While there a lot of background services executed by the system, the end user tends to judge systems based on the visual displays i.e. the graphical user interface (GUI). Therefore, the system at hand must exhume the following attributes:

1. Easy accessibility regardless of the platform or network used.
2. Reliability-based on a consistent performance.

System qualities

Pleasing i.e. good aesthetic beauty and representation (Hassan, 2015).

Now, to meet these attributes the UI must implement its elements carefully based on the demands of the user. These UI elements include the system’s background, icons, colours and fonts. In this case, the design should incorporate versatility and adaptability features as many users are set to use the system, for instance, the background, colours and fonts should be adjustable to meet the user’s preferences. On the other hand, the icons should be permanent but based on the user specifications. In essence, icons will form a key component of guiding the system usage thus, their location and operation are critical for variation instances (Gorton, 2011).

Two general constraints are set to affect the implementation and usage of the system, they are:

Functional restrictions – consider the deployment languages and operating systems to be used. The developer will compromise on some functionalities to satisfy the needs of these elements.

Business restrictions – the budget and most importantly the time of development will never be enough (Dettmer, 2006).

Cloud resources and services have existed for a very long time, from online mailing service (E-mails) to document storage facilities as supported by the various search engine providers. In essence, although they were never deliberately outlined as cloud resources, their deployment structure is the basic definition of cloud computing. The same outcome is also exhibited by organizations who share resources among many employees through a centralized server (models, 2016). In all, cloud-based solutions are designated by leased resources given to a user or organization from a third party member. Therefore, the common notion of “there is no cloud but someone else’s computer is born’’. Now, the Headspace project is in great need for this technology owing to the resources it requires to serve its patients. For one, very many patients are attended to by this organization which increases the size of the storage facilities needed. Secondly, the data from the patients must be readily available to all practitioners in order to improve the effectiveness of the treatments. Finally, these resources must also adapt to the changes of the organization which include changes in personnel, data storage and user location (service, 2017).

Cloud-based solutions are online facilities that deliver IT resource to users based on their demands. This outcome enables a service delivery system that uses a pay per use model. This model would adequately serve Headspace as their resource requirements will vary from time to time. However, at the same time, cloud computing does also present several challenges particularly those of security and privacy (Primault, 2016).

System and user interface (UI)

1. Resource flexibility and mobility – patients during their treatment may see a general health worker, medical practitioner and a psychologist. This outcome will require a mobile infrastructure to enable the accessibility of resources at all time. Cloud resources are online systems that can be accessed at all time and in any given location.
2. Cost effective – the storage, network and processing power is provided by the service provider, a cost reduction for the user.
3. Future advancement – cloud computing encourages innovation and technological advancements(Alton, 2015).

1. Data security and privacy – data is stored in unknown locations and using unknown techniques. Moreover, it’s difficult for users to track their resource which increases the security threats.
2. Loss of system control – no physical manipulation of resources can be done and including the tagging of general data traffic(Bauerle, 2014).

After considering the requirements of the system including its access and hosting in cloud facilities, its design is the next logical step. Now, there is a multitude of factors to consider, from time to user preferences. Therefore, a project like procedure should be used to implement the project having identified the requirements of the users. SDLC defines this procedure and will provide several logical structures to implement the final solutions. In this case, two approaches are highlighted adaptive and predictive SDLC (architects, 2017).

This approach makes several assumptions in its design process, for one, it assumes that all the parameters of development are known. Furthermore, it assumes that these parameters will remain constant through the implementation process (life cycle). Therefore, a clear-cut procedure is outlined, having all the resources of the system such as personnel, functional and non-functional requirements, and even time. Moreover, the approach also provides a logical guideline of the implementation procedure where each and every step of development is given in a sequential manner. This outcome necessities the need to follow a systematic approach where each design and implementation stage is executed without any form of overlap (Okoli & Carillo, 2010). Now, unlike other SDLC methods, the violation of these terms (sequence and changes) result in complete do-overs of projects as the system structure is violated.

1. It’s a simple approach because all the steps are usually clearly outlined.
2. Secondly, it requires minimal resources as they are budgeted for before the implementation process.
3. Furthermore, it’s an accountable approach as comparisons can be made using the systemic procedures.

1. Rigid and lacks any form of flexibility.
2. Time intensive as all steps must be followed sequential without overlap(Okoli & Carillo, 2010).

A complete opposite of the predictive approach where the conventional model of system development is completely avoided. In essence, the adaptive approach will live up to its name by employing agile procedures in system development. Therefore, the procedures used will adapt to change and even give room for any system variations. Furthermore, the approach will split the implementation process into several stages which can be executed simultaneously thus minimize the time of development. After dividing the stages of development, the approach will then use several assembly techniques to deploy the final solution. Now, iteration methods are commonly used for this step, where several recurring assembly steps are executed to perfect the final solution. In all, the final system is usually as a result of several prototyping instances (MIS, 2015).

1. A flexible approach that adapts to any changes and variations.
2. Time efficient as several implementation stages can be executed at once.
3. Thirdly, produces better systems as the design is based on the user’s needs as reflected on the prototypes.

1. Adaptive SDLC method is resource intensive, from expenditures to expertise requirement.
2. It is also difficult to estimate timelines as the system continuously adapts to the existing conditions(Okoli & Carillo, 2010).

First, predictive SDLC approach highlights the traditional or conventional method of implementing systems. Therefore, while it may hold several benefits including design accountability, its feature limits the development processes of modern systems that are agile and versatile. On the other hand, adaptive SDLC approach is the haven for modern systems, incorporating conveniences such as flexibility, mobility and scalability. Therefore, in case the Headspace project requires a change in personnel, the design is able to adapt (architects, 2017). Moreover, the approach drastically minimizes the development time, a key component of any system today more so, those used in service delivery. For these reasons, the adaptive approach is the best method for designing and implementing the Headspace project.

Conclusion

This report has given the various considerations for implementing the Headspace project. In essence, an analysis of cloud computing and its integration into a modern system have been given where its agility and flexibility have been highlighted as a key component of the system’s requirements. Moreover, the non-functional requirements which basically outline the system’s interaction with the user have outlined the importance of secure facilities as supported by clear data ownership guidelines. Finally, the report has also given a detailed comparison between the predictive and adaptive SDLC approach methods, where the adaptive approach has been chosen owing to its benefits which are majorly favoured by its agility features.

References

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