Application for organizing video broadcasts of lectures, courses and online stream management. The ability to assess the knowledge gained and additional metrics.

IoT project. Collecting data and matrices from watering machines. Analysis and processing of data, construction of analytics and yield predictionю

The processes were constructed using the Kanban methodology. I was responsible for the microservices and modules on Node.js (versions 0.12, 4.3, 6.10) creating and supporting, writing queries for AWS DynamoDB, Couchbase, PostgreSQL. In the project, we used event-driven and asynchronous architecture.

The project deliverable is an easy-to-use web application for increasing and management of the users’ credit scores: The application allows users the following: ● Getting, tracking and analyzing credit data from credit bureaus; ● Sending and processing emails and messages to/from credit bureaus; ● Managing and sending paper letters to the credit bureau with DirectMailer service.

The goal was to develop an online platform where the content takes centre stage and can move around freely while creators retain full control and have access to powerful productivity tools. Generally, many AWS services were used on the backend side, such as S3, EC2, Cloudfront, ElasticSearch, and Load balancer. Also, we set up our own mail server with Postfix. The team whose members were based in different time zones was distributed. We used a Waterfall workflow with some XP practices.