Microsoft azure came into existence in 2009 after few months announcement in 2008. It services were limited to providing windows infrastructure with combination of awkward tools of management(Mahmood, 2011, August). A true IaaS solution based on a user friendly web management portal and persistence virtual machines was added in 2012 and in April 2013, the system moved from just preview to a more to general availability and included VM and virtual network features. Azure now grows faster and since April 2014 during TechEd conference it has added several features in an effort to move its shops easily to Microsoft cloud.
Azure uses any language, tool, or frameworkand quickly turns ideas into solutions (Wetherington, ET AL., 2010). It helps individuals or companies to build applications with the language they want, including Java,Node.js, .NET as you use what you know and love. It helps in writing great codes. Azure has the application useful in mobile phones such as iOS, and Android(Mahmood, 2011, August).
In addition to building and deploying application consistently, Azure go beyond connecting your data center to the cloud. It ensures that your on-premises work together consistently cloud environment across your entire organization (Tsai, Sun &Balasooriya, 2010, April). Azure also increases productivity of the developers with a common building application approach and flexibility in deploying those apps on the premises or in clouds using Azure Stack (Sefraoui, Aissaoui&Eleuldj, 2012). There is an increase in end-user productivity by use of azure active directory even by single sign-on applicable to both cloud and on-premises application.
It builds breakthrough apps with built-in intelligence to take advantage to comprehensive set of infrastructure, tools to build Al-powered experiences and services. For human-like experiences in your app it uses a rich set of Azure Al service and data such as Azure Cosmos DB, Azure Databricks, Azure Bot Service, and Cognitive Services Tsai, Sun &Balasooriya, 2010, April).
It is the industry world leading in providing cloud clear security and privacy requirement. Azure is also consistence when it comes to meeting these requirements. The reason why it is trustable it can meet a broad set of industry-specific and international standards of compliance (Tsai, Sun &Balasooriya, 2010, April). The standard compliances associated with Azure is ISO 27001, SOC 1 and SOC 2, General Data Protection Regulation (GDPR), FedRAMP, HIPAA, as well as having specific standards of a country such like UK G-Cloud, Australia IRAP, and Singapore MTCS. Azure also offers rigorous third-party audits for verification their adherence to Azure’s strict security controls like those done by British Standard Institute (Tsai, Sun&Balasooriya, 2010, April).
The following are the features of Amazon and the reason it could best suit these healthcare systems.
Amazon stores and retrieve use photos, profile information and settings fast. It can store and synchronize user data like settings, user files like photos and user profile. Amazon Cognito and Amazon S3 empower this feature (storage).
Amazon operates fast and flexible NoSQL databases that scale through the use of fully managed cloud databases that provide consistency at fast service at any scale. Amazon DynamoDB supports this feature (Lup?e, Vida &Tivadar, 2012).
Amazon has deep features like identity federation, integrated tools and dedicated connectivity that will enable you to run on-premises and cloud services using hybrid applications (Lup?e, Vida &Tivadar, 2012).
Deep visibility into compliance and Governance
Auditing, managing identity, controlling and configuration and usage is very useful in the current IT infrastructure setting. AWS Cloud helps you with these capabilities to meet your governance, compliance and regulatory requirements (Gong, Liu, Zhang, Chen & Gong, 2010, September).
A Platform for Virtually Every Use Case
Here Amazon prides itself on providing more than 50 services in a just single mouse click.
It provides with several infrastructure services like storage options, computing power and delivery utility such as when it is demanded it is made available in seconds and with pay-as-you-go pricing (Gong, Liu, Zhang, Chen & Gong, 2010, September).
IBM is characterized by offering cloud delivery options in terms of public solely cloud, solely private cloud, and the differences between the two (Langer, Persons, Erickson &Blezek, 2013). The following are some features that are inclusive of IBM cloud computing and include:
Private cloud, owned and operated by the client without being in the help of IBM, private cloud owned by the customer but operated by the IBM or another provider, private cloud owned and operated by IBM or another provider (Gong, Liu, Zhang, Chen & Gong, 2010, September).
There is also another known as virtual private cloud services owned (based on multi-tenanted support for individual enterprises) and Public cloud services (based on the provision of functions to individuals) (Tsai, Sun &Balasooriya, 2010, April).
Also, IBM IBM SmartCloud Notes will come with a competitively priced solution payable per user on monthly bases quarterly or annually. It is also usable in several browsers enabling the users to enjoy the services almost on all devices (Gong, Liu, Zhang, Chen & Gong, 2010, September).
Calendaring is available which will enable you to manage time which easily enables in scheduling meetings, appointments, and reminders at all times (Langer, Persons, Erickson &Blezek, 2013). The features available for calendaring include free-time search and calendar delegation.
Archive; SmartCloud of IBM will enable you to archive your emails immediately you will realize that it has been achieved (Abbas & Khan, 2015). However, IBM SmartCloud Archive Essentials is a different thing and is charged separately since it is not with other providers.
Health IT expert believes that cloud-based solution (EHRs) would help overcome interoperability woes through lowering of costs and encouraging a connected ecosystem between environments and clouds (Jadeja&Modi, 2012, March).
Cloud-based solution lowers the cost of operation. Kelly, a principal business advisor at Edifecs, based in Belluvue in Wash, states that interoperable systems cut the initial costs of operation (Lup?e, Vida &Tivadar, 2012). “Cloud-based solutions systems could go hand in hand with value-based care and population health efforts, both of which rely on aggregate data (Gong, Liu, Zhang, Chen & Gong, 2010, September).
Own data control increases privacy and data collection, storage, protection and as well as the distribution of information to the required destination (Abbas & Khan, 2015). The organization is enabled to use its own privacy choices and to manage the data and store them responsibly (Lup?e, Vida &Tivadar, 2012).
Weaknesses
Inability to keep up with the next generation with features that tend to promote interoperability. For instance, Veterans Affairs department of U.S. Tried to do complete changes when the opted to change due to inability to be updated to the current one (Jadeja&Modi, 2012, March).
Some IT professionals believe that “sensitive data in the cloud creates a safety risk to storage and access.” Kelly says that “there is still a lot of resistance and inertial with data residency” (Kuo, Sahama, Kushniruk, Borycki&Grunwell, 2014). There is fear of pulling patients data from a local network (Abbas & Khan, 2015). Many organizations especially those in health care believe that cloud storage of data raises too many privacy risks and adding interoperability activities will even multiply the risks to greater heights (Jadeja&Modi, 2012, March).
Pros and Cons of approaching the project using the ‘Predictive’ SDLC
Easy to understand and follow due to specified stages to be followed from the initiation state to the final stage of software development. The Specified stages stating what to do will enable the software developers to save time when developing the software. This comes in line with the required quality and as well as time-saving and stick to the estimated budget (Wetherington, ET AL., 2010).
Predictive SDCL as it sounds enables the prediction of the budget and the time likely to be taken. This is because result is already known and developers can determine the finish date required.
It is easy to manage since there are specific deliverables and timelessness. It is also simple to correct any mistake done at every stage before going to the next stage of development.
There are clearly defined stages that enable process by process at a time offering the developers a rigid development lifecycle to understand and follow (Bhat, Shah & Ahmad, 2011).
Cons of using predictable SDLC
No working software is produced until the final stage of the software development. This is because testing is done only in the last stages to see whether it works. This may be tiresome in case a mistake or mismatch may be noticed at the later stage making the whole process to be repeated (Suresh Kute, &Thorat, 2014).
This approach is not usable in complex object-Oriented projects but only usable for smaller projects. This is because the procedures may not be simple to follow in a more complex project without involving the stakeholders (Bhat, Shah, & Ahmad, 2011).
Allows for transparency
The clients and team developers work together at every stage when using this approach. A client pays close attention to the status of the project given by the developers before and after every stage (Suresh Kute, &Thorat, 2014). This discussion helps the client to gain abstract view of what is expected and seek clarification as well as give their opinion to the development team.
Early delivery
Extensive involvement of the client before, during and after each stage of software development, the delivery is fastened due to speedy development of the software (Suresh Kute, &Thorat, 2014). The software also is delivered faster than planned due to, significant client satisfaction when they realize the significant value during the explanation and development stage. This is so because this approach focuses on business value (Akinbi, 2015).
User-focused methodologies
The development involving client at every stage enables the development team to get feedback from client and translate it to value addition to the coming software (Suresh Kute, &Thorat, 2014). The user or client involvement in focused on ensuring that all the needs stated and implied are catered for, and the final product can satisfy the end user (Akinbi, 2015).
At every stage of development, the project is broken down into component, high concentration paid to enable quality development and testing is done time and time the results are high-quality product. Testing at every stage also helps to improve quality of the end product (Suresh Kute, &Thorat, 2014). This is because there is, finding and fixing of defects at every stage, and remove of any mismatch.
It demands extensive user involvement consuming a lot of time of the user representative in the project lifetime (Suresh Kute, &Thorat, 2014).
The project takes longer than expected due to a briefing at every stage of explanation, opinion, and testing must be done properly. In other times project is delayed due to it exceedingly becoming bigger than anticipated (Balaji&Murugaiyan, 2012).
The testing at every stage with the aim of improving the project increases the cost of the project that also was anticipated (Langer, Persons, Erickson &Blezek, 2013).
The best SDCL approach for the project is adaptive SDCL Approach due to;
The My Heath project will be used by many local clinics and therefore requires adaptive SDCL approach because adaptive approach applies extensive user involvement before, during and after the software development (Kuo, Sahama, Kushniruk, Borycki&Grunwell, 2014).
This approach encourages completeness of the user requirement which is a very crucial requirement for My Health Record Project which needs to have complete recording among the clinics across Australia (Balaji&Murugaiyan, 2012).
Adaptive SDLC approach will be important approach because my health record is a complex project to improve the design and development (Kuo, Sahama, Kushniruk, Borycki&Grunwell, 2014).
References
Abbas, A., & Khan, S. U. (2015). E-Health cloud: privacy concerns and mitigation strategies. In Medical Data Privacy Handbook (pp. 389-421).Springer, Cham.
Akinbi, O. A. (2015). An Adaptive Security Framework for Evaluating and Assessing Security Implementations in PaaS Cloud Models (Doctoral dissertation, Edge Hill University).
Balaji, S., &Murugaiyan, M. S. (2012). Waterfall vs. V-Model vs. Agile: A comparative study on SDLC. International Journal of Information Technology and Business Management, 2(1), 26-30.
Bhat, M. A., Shah, R. M., & Ahmad, B. (2011). Cloud Computing: A solution to Geographical Information Systems(GIS). International Journal on Computer Science and Engineering, 3(2), 594-600
Gong, C., Liu, J., Zhang, Q., Chen, H., & Gong, Z. (2010, September). The characteristics of cloud computing. In Parallel Processing Workshops (ICPPW), 2010 39th International Conference on (pp. 275-279).IEEE.
Jadeja, Y., &Modi, K. (2012, March).Cloud computing-concepts, architecture and challenges.In Computing, Electronics and Electrical Technologies (ICCEET), 2012 International Conference on (pp. 877-880).IEEE
Kuo, M. H., Sahama, T., Kushniruk, A. W., Borycki, E. M., &Grunwell, D. K. (2014). Health big data analytics: current perspectives, challenges, and potential solutions. International Journal of Big Data Intelligence, 1(1-2), 114-126.
Langer, S. G., Persons, K., Erickson, B. J., &Blezek, D. (2013). Towards a more cloud-friendly medical imaging applications architecture: a modest proposal. Journal of digital imaging, 26(1), 58-64.
Lup?e, O. S., Vida, M. M., &Tivadar, L. S. (2012).Cloud computing and interoperability in healthcare information systems.INTELLI 2012, 90.
Mahmood, Z. (2011, August). Cloud computing: Characteristics and deployment approach. In Computer and Information Technology (CIT), 2011 IEEE 11th International Conference on (pp. 121-126). IEEE.
Sefraoui, O., Aissaoui, M., &Eleuldj, M. (2012).OpenStack: toward an open-source solution for cloud computing. International Journal of Computer Applications, 55(3).
Suresh Kute, S., &Thorat, S. D. (2014).A Review of Various Software Development Life Cycle (SDLC) Models. IJRCCT, 3(7), 776-781.
Tsai, W. T., Sun, X., &Balasooriya, J. (2010, April). Service-oriented cloud computing architecture. In Information Technology: New Generations (ITNG), 2010 Seventh International Conference on (pp. 684-689). IEEE.
Wetherington, J. D., Pfister, M., Banfield, C., Stone, J. A., Krishna, R., Allerheiligen, S., &Grasela, D. M. (2010). Model?Based Drug Development: Strengths, Weaknesses, Opportunities, and Threats for Broad Application of Pharmacometrics in Drug Development. The Journal of Clinical Pharmacology, 50(S9).
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