When building the microservices for the data analytics application, the data engineer needs to be prepared to deal with a diversity of data sources and data exchange formats. These microservices need to collaborate, and as a result, they might need to coordinate and synchronize their activities either through a shared memory or by using a data communication protocol. Use an example to illustrate the producer$-$consumer concurrency design pattern in which one microservice $($producer$)$ is responsible for data collection and the other microservice $($consumer$)$ is responsible for the ETL processing.