Summary

This concludes our section on Kafka producers. This chapter addresses one of the key functionalities of Kafka message flows. The major emphasis in this chapter was for you to understand how Kafka producers work at the logical level and how messages are passed from Kafka producers to Kafka queues. This was covered in the Kafka Internals section. This is an important section for you to understand before you learn how to code with Kafka APIs. Unless you understand the logical working of Kafka producers, you will not be able to do justice to producer application technical designing.

We discussed Kafka Producer APIs and different components around it such as custom practitioners. We gave both Java and Scala examples as both languages are heavily used in enterprise applications. We would suggest you try all those examples on your consoles and get a better grasp of how Kafka producers work. Another important design consideration for Kafka producer is data flows. We covered some commonly used patterns in this chapter. You should have a thorough understanding of these patterns. We covered some of the common configuration parameters and performance tuning steps. These will definitely help you in case you are writing Kafka producer code for the first time.

In the end, we wanted to bring in some of the best practices of using Kafka producers. These best practices will help you in scalable designs and in avoiding some common pitfalls. Hopefully, by the end of this chapter, you have mastered the art of designing and coding Kafka producers.

In the next chapter, we will cover the internals of Kafka consumers, consumer APIs, and common usage patterns. The next chapter will give us a good understanding of how messages produced by producer are being consumed by different consumers irrespective of knowing their producer.