In the previous article I shared before, I didn’t show how to implement the error handling in the Kafka consumer for our spring boot application. Since the missing piece is so essential, here I wrote a new article to show how to do the following stuff:
This article will cover the first step for achieving True Continuous Delivery: How to gain more confidence when merging code into the main branch. The answer is always more tests, more specifically, more automated tests. Unlike the unit test, the E2E (End to End) test is more approximate to the real environment, which gives more confidence when it is passed.
In this article, we will introduce a convenient library, Spring-Data-Rest to eliminate your meaningless code in a Spring Boot Application. As we all know, a DB-access API will be implemented as a Controller-Service-Repository stack in a Spring Boot application coding convention. Often, there is no business logic in controllers and services, but only call the next component and return the result. It’s exactly the meaningless code. The Spring-Data-Rest can help us to eliminate it elegantly.
Observability is one of the significant improvements in the Spring Boot 3 (also see how I migrate to spring boot 3), they now provide an effortless, pluggable way to use annotation to observe all the logs, trace, and metrics data for our spring beans.
In this article, we will go through below topics:
Kafka is a well-known event-streaming solution that provides events publish/subscribe stream and persistence. Besides the main strength, very high throughput (approximate million RPS), Kafka also does well on scalability and availability and provides guarantees on event broadcasting.