Case study

Creating a large consumer facing Web Application that is transaction heavy

100+

Data points for every customer. A complex consumer facingapplication with many data points and documents stored and indexed online. This as an application has heavy data calculationsbehind the scenes and the amount of data collected for each customer is enormous.

The whole project had a tight deadline and was built using a lot of reusable components, MQ Server, document storage and streaming using AWS services and products. The first 4 weeks was spent building reusable components and that increased the speed in which the UI layer was built in record timeline.

100+ Data points for every customer. A complex consumer facingapplication with many data points and documents stored and indexed online. This as an application has heavy data calculationsbehind the scenes and the amount of data collected for each customer is enormous.

The whole project had a tight deadline and was built using a lot of reusable components, MQ Server, document storage and streaming using AWS services and products. The first 4 weeks was spent building reusable components and that increased the speed in which the UI layer was built in record timeline.

Reusable Components
This is an application that has many data points for each property. And lot of these data that is collected are similar in nature in terms of data types. The team built reusable ReactJS components for all these and also frameworks that are used throughout the application
Future Ready
One of the requirements was for the tech stack and design to be future ready. We have used ReactJS for the front end and Java for the back end. Also used Mongo DB to handle the volume of data that is been generated by the application. AWS is used for document storage and indexing of the documents. RabbitMQ is used for all our task management activities.
Test Automation
QA is always key to any project It is even more key to this project given the amount of data that is collected and the formula's and calculations in them Regression testing cannot be done manual. It had to be automated and it was done using Selenium. This drastically improved our QA cycle given that we had builds coming every 2 weeks.
Continuous Deployment
This project was on a tight deadline where the go to market strategy was much aggressive. In order for this, we have to build the app in a fashion where we kept releasing updates to the QA team and UAT team. This required continuous deployment and automating the testing process and the deployment as well using JENKINS.

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