Gastrodamus

• Developed a dish review microservice of a restaurant reservation application

• Built scalable backend architecture for restaurant menus with 10M+ primary data

• Benchmarked RDBMS(PostgreSQL) and non-RDBMS(Cassandra) performance based on the use cases and implemented PostgreSQL query and optimized query speed to under 10ms

• Wrote and maintained test cases using enzyme + Jest unit test in TDD, implemented CircleCI test framework for automated testing, and achieved 90+% test coverage

• Stress tested app servers with 10K request to simulate high traffic scenario on service and proxy server on AWS EC2

• Optimized request traffic bottleneck issue by utilizing Nginx load-balancer and Redis cache and achieved 1000+RPS, 90ms latency and under 1% error rate

Sigsa.io

restaurant review application

• Implemented a menu micro service component with react and design mongo database schema

• Optimized the page load speed by lightnening bundle file size with utilizing the Brotli text compression algorithm and Gzip compression module, improved the page load speed by 65% (from 3.7 seconds to 1.3 seconds)

• Containerized the react components with Docker and optimized the containerization steps by applying the docker-compose tool and managing multiple dockerfiles in a centralized docker-compose script.

• Implemented test-driven development enzyme + Jest unit test, integrated automated testing by utilizing CircleCI test framework and achieved 90+% test coverage