Apache Kafka is a distributed streaming platform that is used to build real-time data pipelines and streaming applications. It is designed to handle high throughput, low latency, and fault tolerance, making it a popular choice for large-scale data processing.

1. Distributed System: Kafka is a distributed system, meaning it runs on a cluster of servers working together to provide high availability and scalability.
2. Streaming Platform: Kafka is designed to handle real-time data streams, allowing for the continuous processing of data as it arrives.
3. Publish-Subscribe Messaging: Kafka uses a publish-subscribe messaging model, where producers publish messages to topics, and consumers subscribe to those topics to receive messages.

1. Producers: Applications that send data to Kafka topics.
2. Consumers: Applications that read data from Kafka topics.
3. Topics: Categories or feed names to which records are sent by producers.
4. Partitions: Sub-divisions of topics that allow for parallel processing.
5. Brokers: Kafka servers that store data and serve client requests.
6. Clusters: Groups of brokers working together to provide high availability and scalability.

1. Producers send messages to Kafka topics: Producers are responsible for sending data to Kafka. Each message is sent to a specific topic.
2. Messages are stored in partitions: Each topic is divided into partitions, and messages are distributed across these partitions.
3. Consumers read messages from topics: Consumers subscribe to topics and read messages from the partitions.

Let's look at a simple example of how Kafka works in practice.

Before we can use Kafka, we need to set it up. This involves downloading Kafka, starting the Kafka server, and creating a topic.

Next, we will produce some messages to the topic we just created.

Finally, we will consume the messages from the topic.

In this section, we introduced Apache Kafka, a distributed streaming platform used for building real-time data pipelines and streaming applications. We covered its key concepts, core components, and how it works. We also provided a practical example of setting up Kafka, producing messages, and consuming messages. This foundational knowledge will prepare you for the more advanced topics covered in the subsequent modules.