What you’ll learn
- Understand Apache Kafka Ecosystem, Architecture, Core Concepts and Operations
- Master Concepts such as Topics, Partitions, Brokers, Producers, Consumers
- Start a personal Kafka development environment
- Learn major CLIs: kafka-topics, kafka-console-producer, kafka-console-consumer, kafka-consumer-groups, kafka-configs
- Create your Producers and Consumers in Java to interact with Kafka
- Program a Real World Twitter Producer &ElasticSearch Consumer
- A recent Windows / Mac / Linux machine with minimum 4GB of RAM, 5 GB of disk space
- Some understanding of Java Programming
- Good to have knowledge about Linux command line
- Desire to learn something awesome and new!
Apache Kafka has become the leading distributed data streaming enterprise big data technology. Kafka is used in production by over 33% of the Fortune 500 companies such as Netflix, Airbnb, Uber, Walmart, and LinkedIn.
To learn Kafka easily, step-by-step, you have come to the right place! No prior Kafka knowledge is required.
If you look at the documentation, you can see that Apache Kafka is not easy to learn…
Thanks to my several years of experience in Kafka and Big Data, I wanted to make learning Kafka accessible to everyone.
We’ll take a step-by-step approach to learn all the fundamentals of Apache Kafka.
At the end of this course, you’ll be productive and you’ll know the following:
- The Apache Kafka Ecosystem Architecture
- The Kafka Core Concepts: Topics, Partitions, Brokers, Replicas, Producers, Consumers, and more!
- Launch your own Kafka cluster in no time using native Kafka binaries Windows / MacOS X / Linux
- Learn and Practice using the Kafka Command Line Interface (CLI)
- Code Producer and Consumers using the Java API
- Real-world project using Twitter as a source of data for a producer and ElasticSearch as a sink for our consumer
Note: The hands-on section is based on Java, which is the native Kafka programming language. But, good news! Your learning in Java will be completely applicable to other programming languages, such as Python, C#, Node.js or Scala, and Big Data frameworks such as Spark, NiFi or Akka.