Comparison Of AWS, Microsoft Azure, And Google Cloud Platform: Advantages And Disadvantages

Amazon Web Services

Discuss about the Cloud Solution and 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.

• 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 24×7 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

• 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).

• 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.

• 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 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

• 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: https://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/