Built and utilized Microservices Pipeline and RESTful APIs in order to send information of clothes such as brand, material, style and size from web services by Spring Boot, Spring Cloud, which has capability of handling 150+ QPS in benchmark.

Managed raw data by creating a microservice of Data Preprocessor to control the manipulations for acceptance and published to RabbitMQ. Handled QPS peak hour and decoupling by using RabbitMQ as buffer and broker.

Established a microservice of Data Handler as a consumer gathered from RabbitMQ for validation by utilizing Rule Engine with REST call, and implemented JPA to insert valuable data into MySQL.

Simulated continuously and randomly clothes data with a microservice of Data Provider to test Data APIs.

Configured Spring Cloud Eureka Server Cluster for registration and discovery to accomplish a goal of high practicability.

Developed a dashboard backend for screening out appropriate candidates per customers’requirements with RESTful APIs and Java Spring.

Generated highly scalable RESTful APIs to manage and classify candidate background including technical skills, education level and performance reviews through Dashboard, and using Spring Boot and MySQL.

Applied Redis as cache to improve average speed of data retrieval greatly with 0.4s latency.

Implemented automatic configuration and deployment on Docker to advance isolation of the application and development process.