Kafka includes the Producer/Consumer APIs that allow client applications to send/read streams of data to/from topics in a Kafka cluster. While the main Kafka project maintains only the Java clients, there are several open source projects that provide the Kafka client APIs in Python. In this post, I'll demonstrate how to develop producer/consumer applications using the kafka-python package.

Kafka Connect is a tool for scalably and reliably streaming data between Apache Kafka and other systems. In this post, I will illustrate how to set up a data ingestion pipeline using Kafka connectors. Fake customer and order data will be ingested into the corresponding topics using the MSK Data Generator source connector. The topic messages will then be saved into a S3 bucket using the Confluent S3 sink connector.

A Kafka management app can be a good companion for development, which helps monitor and manage resources on an easy-to-use user interface. An app can be more useful if it supports features that are desirable for Kafka development on AWS. Those features cover IAM access control and integration with MSK Connect and Glue Schema Registry. In this post, I'll introduce several management apps that meet those requirements.

Apache Kafka is one of the key technologies for modern data streaming architectures on AWS. Developing and testing Kafka-related applications can be easier using Docker and Docker Compose. In this series of posts, I will demonstrate reference implementations of those applications in Dockerized environments.