The Ultimate Guide to Apache Kafka: Basics, Architecture, and Core Concepts

1. Introduction

Apache Kafka is an open-source distributed publish-subscribe messaging system. Let’s break this down further:

Distributed: Kafka is designed to be fault-tolerant and scalable. It achieves this by allowing multiple Kafka servers (brokers) to work together in a cluster, ensuring system reliability and high availability.
Publish-Subscribe: Kafka has a producer-consumer like model, in that:
Producers publish messages to Kafka.
Consumers subscribe to Kafka topics and consume messages.

To better understand this lets take an example of an e-commerce store. When the store is small, the owner can handle deliveries directly to the customers. However, as the store grows, doing deliveries directly becomes inefficient, causing delays.

Now, imagine using a postal office to handle deliveries. Instead of personally delivering each order, the owner drops off packages at the postal office, and the postal office ensures delivery to customers efficiently.

In this example the e-commerce store represents the producer (sending messages/orders). The postal office represents Kafka (managing and delivering messages). The customers represent consumers (receiving the messages/orders). This approach removes bottlenecks, making the system more scalable—just like Kafka does for data processing.

2. Core Concepts of Apache Kafka

Cluster

A Kafka cluster refers to multiple brokers (Kafka servers) working together to ensure scalability, fault tolerance, and high availability of data.

Broker

A broker is an instance of a Kafka server that stores and manages messages. Multiple brokers form a cluster, ensuring data replication and fault tolerance.

Topic

Kafka organizes data into topics, this is similar to tables in a relational database. Producers write data to topics, and consumers read from them.

Producers

Producers are applications that publish messages to Kafka topics. They determine which topic a message should go to and can also decide how messages are partitioned.

Consumers

Consumers are applications that subscribe to topics and consume messages. Kafka ensures that messages are delivered in an ordered and scalable manner.

Partitions

A Kafka topic is divided into multiple partitions to allow parallel processing and increase scalability. Each partition is stored on multiple brokers for fault tolerance. If a broker storing a partition fails, Kafka can still serve data from its replicas on other brokers.

Kafka Connect

Kafka Connect is a framework that enables integration between Kafka and external systems such as databases, cloud storage, and message queues. It also manages tasks