Brisk Logic’s product engineers were tested to make a simple-to-utilize stage highlighted by enhanced performance, improved information revelation and perception.
To guarantee the accomplishment of the created product Brisk Logic team included not just experienced engineers grasping the most forefront advancements and QA engineers who dealt with the product quality. Gifted budgetary experts of Brisk Logic were likewise included.
They needed to team both physically and naturally every one of those tremendous volumes of data series. Furthermore, they helped the development team in search optimization, which made possible the display of applicable data and as-you-type recommendations.
To provide high up-time different Amazon web services were used such as E2 and Spot Instances, S3, LoadBalancer, CloudFront, VPC, etc. Node.js was used as the main app server. Intermediate data caching was implemented with MongoDB.
Redis was applied as the innovation to process lines of information. Python was utilized to empower download to Excel and different configurations of reports.
Solr empowered powerful search capacities of the stage on MySQL and MongoDB levels. Phantom.js was applied to create thumbnails and to download pictures of representation parts. HighCharts assisted with building outlines and charts in the application.
Gulp and Webpack were used to assemble the application and for the deployment process. SASS helped to create the beautiful frontend of the application. WebSockets were used to enable the collaborative work of multiple users. Microservices was selected as the main architecture pattern.