Apache Kafka Fundamentals

1. Fundamentals of Kafka and Message Queues

You will understand what Kafka is and how it is used in stream and event processing systems. You will learn about the key components of Kafka: topics, messages, consumer groups, and how they interact with each other. You will also learn how a message queue works, how data is written and read from it, and why message order and delivery guarantees are important.

2. Apache Kafka Architecture

We will delve into the key elements of Kafka's architecture. You will learn what topic partitions are, how they relate to brokers, and how data processing takes place within Kafka. I will explain what Zookeeper is, the role it plays, and how it interacts with Kafka brokers and metadata.

3. Setting Up the Development Environment

You will learn how to run Kafka on a Windows environment using Docker. I will provide a step-by-step guide on how to set up a Bitnami Kafka Docker container, and give practical tips for successful installation and launching of the environment.

4. Practicing with Kafka

You will set up your own Kafka topic, master basic commands to work with it. You will also create a producer to write messages and a consumer to read them. We will test their operation using Python and learn to manage consumer offsets using the offset checker.

5. Kafka in Data Processing Platforms

In conclusion, we will explore how Kafka can be integrated into a Data Science platform. You will see three practical scenarios of using Kafka:

• ETL ingest pipeline
• Multiple consumer processes
• Multistage stream processing

These examples will help you start implementing Kafka in your everyday work today.