Since 2011, Kafka's been exploding in terms of growth. More than one third of Fortune 500 companies use Apache Kafka. These companies include travel companies, banks, insurance companies, and telecom companies.
Uber, Twitter, Netflix, Spotify, Blizzard, LinkedIn, Spotify, and PayPal process their messages with Apache Kafka every day.
Today, Apache Kafka is used to collect data, do real-time data analysis, and perform real-time data streaming. Kafka is also used to feed events to Complex Event Processing (CEP) architectures, is deployed in microservice architectures, and is implemented in Internet of Things (IoT) systems.
In the realm of streaming, there are several competitors to Kafka Streams, including Apache Spark, Apache Flink, Akka Streams, Apache Pulsar, and Apache Beam. They are all in competition to perform better than Kafka. However, Apache Kafka has one key advantage over them all: its ease of use. Kafka is easy to implement and maintain, and its learning curve is not very steep.
This book is a practical quick start guide. It is focused on showing practical examples and does not get involved in theoretical explanations or discussions of Kafka's architecture. This book is a compendium of hands-on recipes, solutions to everyday problems faced by those implementing Apache Kafka.
