Comparison Of Google App Engine With Bluemix For Smart Applications Development Using PaaS, Essay.

Identify four cloud service providers who offer PaaS (Platform as a Service) to develop applications.Select one of the cloud service providers from your list for further investigation. If necessary, create a trial account and use all the different services it offers. Take screenshots to record some of those services while using them.Compare and contrast between Bluemix (used in this unit) and the PaaS service of the cloud service provider you have chosen.What do you need to submit.

o List all identified cloud service providers who offer PaaS (Platform as a Service) to develop applications Select a service provider out of the list to compare with Bluemix and write two reasons to justify your choice Comparison and contrast with Bluemix – this is the body of the report and should be written as detailed as possible. You can include screenshots and other media to enrich your report (you are not allowed to use screenshots and media content from the internet – they must be your own. It is a good idea to try the environment before your answer this section.

This section must and only include comparison and contrast between IBM Bluemix and your chosen service provider for the following:
o Services offered for smart applications development such as Internet of Things (IoT) applications, Artificial Intelligence (AI) applications and so on.

Cloud Service Providers

Platform as a Service (PaaS) is a cloud model, designed for the software developers and it helps to streamline the development process by the process of shifting of specific aspects of the system management to the service provider (Kim et al. 2016). Use of PaaS is often done to mobile and web applications with the components that are pre-configured and are maintained by service provider, which indulges the programming language, database and the servers.

This report deals with the services provided by various service providers who provide PaaS as the application development tool. It also contains a comparison of one of the Google App Engine with Bluemix. Screenshots have been provided to make the topic more detailed. The report has been divided in sections to provide a clear concept of the topic.

There are various service providers, who offer PaaS as the tool for web or mobile application development. The list of various PaaS service providers are-

• Engine yard- it is designed for the developers of web applications through Ruby on Rails, Node.js and PHP (Jamjoom, Williams and Sharma 2014). This application is for those who tend to get advantages of cloud computing without the responsibility of operation management.
• Red Hat OpenShift- this is the tool which is based on open source applications and it provides a very wide variety of languages, components and database. Here, developers can interface with OpenShift through a web console, integrated development line or a command line.
• Google App Engine- it is designed for development using Java, PHP, Python and Go. The java environment supports various languages, which uses JRE and a SDK present for every of the major four of the supported language and the plugin for Eclipse.
• Heroku- it handles Python, Ruby, Scala, Java and Node.js. Abstract computing service is provided by the platform called dynos, which is a virtualized Unix-Styled container.
• AppFog- it is a multi-language and multi-framework PaaS, which is a good option for multi-cloud deployments indulging the private cloud. It supports Ruby, Java, Node, Python, Erlang and Scala.
• Windows Azure Cloud Services – it is both an IaaS and PaaS. Here, the developers can mix and match the components of IaaS along with the PaaS giving more control to the developer.
• Amazon Web Services (AWS)-here the developers do not have to maintain or create own application servers. It supports Python, Java, Ruby, Perl and various other languages.
• Caspio- here, the service of fully functional software development is not provided in the software development environment. The purpose of Caspio is to create basic database providing data entry forms and generation of reports.

Google app engine was chosen here for comparison with Bluemix as both the brands have name and fame in the industry and the services provided by both of them are appreciated by the customers. There is limited gap between both the applications and thus it was chosen.

 Services offered for smart applications development

The services provided by Google app engine for IoT are that it delivers virtual machines running in the innovative data centers of Google and a worldwide fiber network. The VM of the computer engine boots with a very high speed, has local disk options, comes with high performance persistent, and delivers consistent performance. It has automated container management and it is a powerful cluster manager for running the Docker containers.

Bluemix offers SilverHook Powerboats for the implementation of IoT applications in the device.

Artificial intelligence

Google app engine-the accuracy is impressive. The neural nets are trained by the use of a vast array of machines, which are equipped with the GPU chips. One such example is the Google translate app.

Bluemix- According to Fox et al. (2014), the various services provided are expanding the training of data, diverse classifiers, new feature selection process, improved lexicon support and expanded support for emoticons, slang and emojis.

Google app engine- the cloud services over here are designed for distributed web applications. The Google app engine also manages various implementation details with the PaaS services. Some of the PaaS options such as the RedHat OpenShift offer some IaaS-like features, which allow the user to customize the environment to a greater degree (Kumar 2016). But it is different with Google app engine as, with the Google Paas, user can manage infrastructure and also the runtime environments that are guaranteed to scale as far as the user’s applications follow playbook of Google app engine (Fox et al. 2015).

Bluemix- the layers if the PaaS system for Bluemix are external, integration and internal business application. The external layer is for the trading partners, e-commerce, mobile devices and internet of things.  The integration layer includes the ESB, BPM, IBM WebSphere Cast Iron, IBM WebSphere application server, IBM Sterling commerce, business activity monitoring and the predictive data analytic capability (Ray 2017). The internal business application layer contains the lifecycle management of the product, the customer relationship, the enterprise resource planning, the data warehouse and the digital operation.

Justification of Chosen Service Provider

In Google app engine using java eclipse

The tools used for this purpose are JDK 1.6, Google App Engine Java SDK 1.6.3.1 and Eclipse 3.7 + Google plugin for eclipse

Step 1- the google plugin for eclipse needs to be installed

Step 2- a new web application project needs to be created

Step 3- the generated project directory needs to be reviewed

The extra file over here is “appengine-web.xml“, Google App Engine has to run this and deploy the application.

Coding has to be done in this phase.

Step 4- the project needs to be run as web application by right clicking on it.

Step 5- the user needs to access the https://localhost:8888/ URL in order to view the result.

Step 6- the Google app engine needs to be deployed.

The account needs to be registered on https://appengine.google.com/, and an application id has to be generated for the web application.

Step 1- creation of a project for the app

Login to IBM Bluemix DevOps Services.

In the navigation top, click on My Projects

Click on CREATE PROJECT

On the page for creation of the project-

• Type the name of desired project
• Choose a source control option
• Check the Make this Bluemix Project box.
• Click on create.

Step 2- create a simple webpage

Step 3- create a manifest

Step 4- the deployment phase

Click on the deploy button on the web IDE.

When the app is deployed, click on the open the application URL button and go to web IDE

The app gets deployed.

Google app engine – deployment rises due to stack overflow (Powell and Hollingsworth  2014). Anyone can extract the dwarf info from the binary files. The native code execution can be achieved.

Bluemix-the volumes are slow and only a root user can access the data. There are many blockage factors for the applications, which store the data (Sandhya and Kanth 2016). The developed pipeline is very slow and thus it causes deployment problems.

Bluemix offers the free trail, payment on whatever data the user uses and subscriptions.

These options are available for the Google app engine as well.

Conclusion 

Hence, from the above discussion, it can be concluded that the use of PaaS is done frequently to develop mobile plus the web applications with components which are pre-configured and also are maintained by those who are the service provider which indulges programming language, database and the servers. Between Google app engine and IBM Bluemix, Google app engine is better to use because of the various features provided by it to the users.

References 

Fox, G.C., Qiu, J., Kamburugamuve, S., Jha, S. and Luckow, A., 2015, May. Hpc-abds high performance computing enhanced apache big data stack. In Cluster, Cloud and Grid Computing (CCGrid), 2015 15th IEEE/ACM International Symposium on (pp. 1057-1066). IEEE.

Kim, M., Mohindra, A., Muthusamy, V., Ranchal, R., Salapura, V., Slominski, A. and Khalaf, R., 2016. Building scalable, secure, multi-tenant cloud services on IBM Bluemix. IBM Journal of Research and Development, 60(2-3), pp.8-1.

Kumar, P., 2016. Internet of Things (IoT) development platforms-A case of IBM Bluemix (Doctoral dissertation, Masterarbeit, Koblenz, Universität Koblenz-Landau, Campus Koblenz, 2016).

Ray, P.P., 2017. A Survey of IoT Cloud Platforms. Future Computing and Informatics Journal.

Sandhya, P. and Kanth, G.K., 2016. Sensor Network Accessing Cloud Services for Data Collection and Sharing Using Arduino Yun. International Journal of Scientific Research, 4(9).

Vijaya, A. and Neelanarayanan, V., 2015. Framework for Platform Agnostic Enterprise Application Development Supporting Multiple Clouds. Procedia Computer Science, 50, pp.73-80.

Zhang, C., 2017. Apply on Instance of IBM Watson Cognitive Computing System.

Powell, D. and Hollingsworth, J., 2014, January. Flipping the Classroom by Using Cloud Services and Third Party Online Courses in Traditional Class Settings Enables All Computer Science Students an Equal Education. In Proceedings of the International Conference on Frontiers in Education: Computer Science and Computer Engineering (FECS) (p. 1). The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp).

Jamjoom, H., Williams, D. and Sharma, U., 2014, August. Don't call them middleboxes, call them middlepipes. In Proceedings of the third workshop on Hot topics in software defined networking (pp. 19-24). ACM.

Fox, G.C., Jha, S., Qiu, J. and Luckow, A., 2014, October. Towards an understanding of facets and exemplars of big data applications. In Proceedings of the 20 Years of Beowulf Workshop on Honor of Thomas Sterling's 65th Birthday (pp. 7-16). ACM.