ITC458 System Analysis: Cloud Computing Vendors for Health Records

This report provides a system analysis of cloud-based solutions for My Health Record, focusing on vendors like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform. It details the strengths and weaknesses of each platform, highlighting features relevant to the healthcare domain such as security, scalability, and data analytics. The report also discusses suitable SDLC approaches, comparing predictive and adaptive methodologies and their pros and cons in the context of healthcare application development. The analysis considers factors like security requirements, data sensitivity, and the need for flexibility in application development, ultimately recommending the best cloud solution and SDLC approach for My Health Record. Desklib provides access to this document and other solved assignments for students.

System Analysis and Design

Contents
Cloud Solution / Computing Vendors.............................................................................................3
Strengths and Weakness..................................................................................................................6
Strengths.......................................................................................................................................6
Weakness.....................................................................................................................................7
SDLC Approach..............................................................................................................................7
Predictive SDLC pros:.................................................................................................................7
Predictive SDLC cons:.................................................................................................................8
Adaptive SDLC pros:...................................................................................................................8
Adaptive SDLC cons:..................................................................................................................9
References......................................................................................................................................10

Cloud Solution / Computing Vendors
Presently, there are three major cloud -based web services. Those are:
1. Amazon Web Services (AWS)
2. Microsoft Azure and
3. Google Cloud Platform(Software Testing Help, 2018)
First, let us consider AWS (Amazon Web Services) and why it is rated as top in cloud computing
and best provider of cloud based solutions worldwide. These are the six best features that are
present in Amazon Web Services which makes it the best among all others.
 Easy to use – AWS is designed in such a way that the user can use the application with
ease and provide vendors, ISVs to quickly and also securely host the application. The
application might be an existing one or it may be a new SaaS (Software as a Service)
based application. Users are provided to use management console and can also use web
service APIs in order to access AWS’s application hosting service or platform. And, all
these are well documented (Amazon Web Services, 2018).
 Flexibility – AWS will allow its vendors to choose or select any type of operating system,
any type of programming language, databases and application platform as per need. AWS
provides virtual environment in which the software and services can be loaded which are
dependent on the application. This feature will help in migrating process with ease and
also helps in preserving the options of the old application and build new solutions on top
of it.
 Cost-effective –AWS charges only for the power consumption of the computer, storage
and the other extra services that the user uses. And this comes with no contract basis.

 Security groups – By using copy to new feature, it is very easy to create new security
group. This helps while they are working in identical environment but with different
security functionalities (Muppala, 2018).
 Resources events – This feature is utmost important to track the changes that are been
done over the time period, they need to be monitored for backup facility or rollback
facility.
 Scalable and high performance –Elastic load balancing, auto scaling helps the application
to scale up and down which depends on the demand. With the best infrastructure that
AWS provides, a user has flexibility to use data and services on demand basis.
 Healthcare domain – AWS has high level of services that can be utilized in health
domain. For example: genomics, biotech & pharma will be provided with healthcare
domain having much more diverse functionalities that can be used.
 Security –AWS uses end-to-end approach for security reasons and also to harden AWS
infrastructure. This includes operational, physical and software measures.
Second, Microsoft Azure:
 Azure search – This feature allows the user to search in any web-based application.
Considering the web application that is used by doctors and patients to retrieve, write or
read patient details, if the data are too big, then we need a functionality that brings all the
information based on the search terms (Crabtree, 2018).
 Azure machine learning – Machine learning is again one of the key player in modern era.
Machine learning helps to mitigate complex software problems and helps in producing

optimized solution and this is less cost effective. Azure’s machine learning doesn’t need
the user to be of data science background.
 Azure hybrid connections - Hybrid connections help to connect to the Azure websites and
also to the Azure mobile services on the basis of premises resource. For example,
websites and mobile services can access the existing on-premises data and also the
services more securely (Crabtree, 2018).
 Azure website improvements – This provides live testing on production, VPN
integration, and migration assistant.
 Health domain -It provides cyber security threat model, customer responsibility matrix,
deployment scripts, external review and component architecture to completely understand
the flow and functionality of the health data and bring a suitable response on provided
input.
 High performance computing – Performance is utmost important while building the
application. Considering high data flow while accessing and editing data across the whole
platform, cloud -based solution should be adequate to the multithreading functionality
and on the same end, the time it takes to update or edit the data should be minimal (Azure
solutions, 2018).
Third is Google Cloud Platform. Google being late in the race, but it is continuously growing its
market across the globe with AI at its core. Its features are:
 VM Rightsizing recommendations –To avoid overpaying for the application, resizing the
VM is another cool technique that can be followed. With the help of CPU and RAM
usage over time, the suggestion that it provides will help in minimizing the overall cost
(Cloud Platform, 2018).

 Cloud shell – This helps to manage resources, testing and building resources in no time.
This feature comes with many pre-installed tools such as Google cloud SDK, docker,
npm, nvm, pip, iPython, MySQL, Maven etc.
 Custom machine types – Computational engines provide VMs with lots of information
and different sizes and if the suggestions are not fit, this feature allows to custom the
machine type with whatever the number that has to be put in there.
 Automatic storage (data) increase.
 Live migration – Migration of the application can be done from one storage to the other
while the application is still up (SpringPeople, 2018).
 Highly powerful data analytics.
Strengths and Weakness
Strengths
 Cloud based solution provides suitable environment for the application to be hosted. In
order to store the data that has been accumulated (of patient’s) over time, it needs to be
stored so that it cannot be lost. The best solution to overcome this is to store the data on
cloud.
 Cloud based solution allows to install the application and use it 24x7 without any
interruption or without any call interference in between. The hosting is secure.
 The application might have been written in any programming language but the cloud
based solution has the capability to run the application on all the operating systems which
includes mobile devices. This is huge because, support for mobile devices will help the

patient to input their details personally so that the data gets linked to their profile and that
can be viewed by the individual and the person with whom the data has been shared.
 Cloud based solution provides best security so that the data cannot be breached in
between. The data that’s been stored are more sensitive and hence encryption of data
should be taken care of.
 Disaster recovery (Baiju, 2018)
 Less costly
Weakness
 Loss of data while migrating from platform to platform or from one cloud service to the
other.
 Requires experts to handle the configuration details and use the API’s been provided for
use.
 Deployment issues.
 Encryption of data over network (Levelcloud, 2018).
SDLC Approach
Predictive SDLC pros:
 In predictive SDLC, phase wise development takes place because of which there can’t
happen coding when the design phase isn’t completed yet. It is more of waterfall model.
 This methodology is good if the application doesn’t get changed often either adding
functionality wise or on configuration level.

 Predictive SDLC will be best for the healthcare project because there are very less
chances that the application functionality changes over time. The application is one time
development and gets installed in the cloud to access the application (Johnson, 2018).
 Each phase can be tested before going to the next phase and hence, less errors and more
productivity.
 It is less costly because the processors and services are only used when deployed. As
there would not be continuous deployment of the application which require processors,
data usage decreases resulting in reduced cost.
Predictive SDLC cons:
 Changes to the application require time and, cost increases because of usage of resources.
 Extreme programming does not have scope.
 Feature driven development does not take place.
Adaptive SDLC pros:
 Adaptive methodology follows agile development methodology. This methodology is
dependent on feature -driven development, crystal methodology, extreme programming
and scrum.
 This methodology allows doing repetitive changes as per the business requirements.
 Extreme programming allows pair programming and also helps in writing less error code
and the code is well tested before deployment.
 The first and foremost priority of this methodology is to satisfy the client.
 High level of understanding and discussions are more welcomed to point out the idea to
develop the application.

 Agile methodology helps in distributive application development for business (Butt,
2016).
 Data sharing
 Formulating benefits for clients
Adaptive SDLC cons:
 Cost for development and deployment of the application is high because of the
continuous monitoring and using the resources over cloud.
 The application needs highly motivated users to develop the functionalities.
 High chances of data lose because of continuous deployment and bandwidth issues might
arise.
 Late changes will increase the development time and the releases will affect the overall
strategy of the application.
To summarize, each and every cloud based solution have advantages and disadvantages. Google
cloud computing is much more cost effective while compared to AWS and Microsoft Azure and
moreover, Google Cloud Computing has larger network and it is increasing much more than that
of AWS. So, Google Cloud Computing becomes the best choice (Jackson, 2018).
In SDLC approach, if the application have security level checkups such as the patient can give
access to only those doctors which have right to access the patient’s data then, there has to be
security configurations and also there will be limitations in the data flow in the methodology. If
the data are public then it is good to follow predictive SDLC approach and if there is security in
between then, adaptive SDLC is the best approach because in adaptive SDLC we can branch the
code and update the application in branches with cloud configuration with which only patient can
give rights to the doctor to access the patient’s data and rest can’t.

References
Azure solutions. (2018, May 23). Azure solutions. Retrieved from Azure.microsoft.com/en-in:
https://azure.microsoft.com/en-in/solutions/
Baiju, N. (2018, May 23). 5 advantages and disadvantages of Cloud Storage. Retrieved from
Bigdata-madesimple.com: http://bigdata-madesimple.com/5-advantages-and-
disadvantages-of-cloud-storage/
Butt, S. (2016). Study of agile methodology with the cloud. Pacific Science Review B:
Humanities and Social Sciences, 2(1), 22-28.
Cloud Platform. (2018, May 2018). Six Google Cloud Platform features that can save you time
and money. Retrieved from Cloudplatform.googleblog.com:
https://cloudplatform.googleblog.com/2016/09/six-Google-Cloud-Platform-features-that-
can-save-you-time-and-money.html
Crabtree, J. (2018, May 23). 10 Best Microsoft Azure Features For 2015. Retrieved from
Blogs.perficient.com/: https://blogs.perficient.com/2015/01/07/10-best-microsoft-azure-
features-for-2015/
https://aws.amazon.com/application-hosting/benefits/. (2018, May 23). Retrieved from
https://aws.amazon.com/: https://aws.amazon.com/application-hosting/benefits/
Jackson, B. (2018, May 23). Top 7 Advantages of Choosing Google Cloud Hosting. Retrieved
from Kinsta.com/: https://kinsta.com/blog/google-cloud-hosting/
Johnson, D. W. (2018, May 23). Waterfall or Agile? Differences between predictive and
adaptive software methodologies. Retrieved from Searchsoftwarequality.techtarget.com/:
https://searchsoftwarequality.techtarget.com/tip/Waterfall-or-Agile-Differences-between-
predictive-and-adaptive-software-methodologies

Levelcloud. (2018, May 23). Advantages and Disadvantages of Cloud Computing. Retrieved
from Levelcloud.net: https://www.levelcloud.net/why-levelcloud/cloud-education-
center/advantages-and-disadvantages-of-cloud-computing/
Muppala, P. K. (2018, May 23). Amazon Web Services: 6 Features that Can Make the
Difference. Retrieved from https://cloudacademy.com:
https://cloudacademy.com/blog/author/pravinmuppala/
Software Testing Help. (2018, May 23). 15 Top Cloud Computing Service Provider Companies.
Retrieved from Softwaretestinghelp.com: https://www.softwaretestinghelp.com/cloud-
computing-service-providers/
SpringPeople. (2018, May 23). Google Cloud Computing – Elements, Features and Benefits.
Retrieved from Springpeople.com: https://www.springpeople.com/blog/google-cloud-
computing-elements-features-benefits/