Mehmet Ayan

The software developed in this project was the first of its kind. The software's target market is the water and sewerage administration of municipalities. This software enables managing the city water network by collecting data from site devices, CIS, GIS, SCADA, remote metering systems, asset management system, pipe renewal planner, hydraulic modeling software, and workforce management system.

The software was designed with a microservices architecture, following domain-driven design principles. The back end of the project was developed in Node.js and Spring Boot, and the front end of the application was developed in Angular. We used PostgreSQL, MongoDB, and Oracle as database systems, while Redis was utilized for caching. Hibernate, Sequelize, and Mongoose served as ORM tools.

After the project was finalized, the water management system was added to the Siemens product portfolio. The product was deployed on-premise as the water data is recognized as a strategical asset.

I participated in different project stages, including architecture, microservices and integration design, and the back-end and front-end implementation. I also supported the project management team in collecting application requirements from the customer.

All Audi web pages are designed and implemented with micro front-end architecture. With the help of this architecture, teams can work on different features independently. Micro front-end applications were developed with React and GraphQL. The back end of the micro front-end applications is developed with Node.js on AWS Lambda.

I took part in an automotive visualization feature app which enables users to display 2D photos and 3D videos of Audi cars. Users can open or close the trunk and car doors and also turn lights on or off by using this micro front-end application. Another application I contributed to was Audi Dealer Search. With the help of this application, users can search for dealers by geolocation and terms. If users give the application permission to detect their location, they can search their locations.

Developed a platform that enables users to compare car insurance offers and select the best one. The platform's main advantage is serving offers to users while collecting fewer data compared to competitors. The platform is practical and easy to use, as the users only need to answer a few questions to get a customized offer.

The platform is designed with a microservices architecture. The system includes five microservices with the front end in React. All user interactions are transferred to the data layer with Google Tag Manager for the data team's analysis. All the answers are processed by the back end so that the conversation can flow dynamically, following each user's previous answers.

The application runs on the Amazon Elastic Kubernetes Service (EKS). Two microservices were developed with Spring Boot, and the others were developed with Node.js. One of the Node.js microservices was deployed as an AWS Lambda function. The application's database is DynamoDB, the infrastructure on AWS is created using Terraform, and the CI/CD pipeline of the project is GitLab.

I took part in every phase of the project, including system architecture and microservices design, back end and front end implementation, and infrastructure.