chapter one

1 Getting to know Kafka as an architect

 

This chapter covers

  • Principles of event-driven architecture
  • Overview of the Kafka ecosystem
  • Utilizing Kafka in enterprise environments

Apache Kafka has grown from a high-throughput messaging system into a critical component of modern data architectures. The Kafka ecosystem now powers event-driven systems, large-scale data pipelines, and real-time analytics. It is a widely adopted, open-source streaming platform and its capabilities are impressive. But making the most of Kafka requires more than just getting it to run—it demands thoughtful architectural design.

Kafka plays a crucial role because it bridges the gap between event and action: producers publish once, and many consumers react, with Kafka providing low latency. That decoupling enables business systems to respond to events quickly and without brittle point-to-point integrations. Consider real-time order processing in ­e-commerce, for instance, where one event, a customer placing an order, gets published to a service, and many independent consumers—such as inventory, payment, shipping, and analytics—react in real time without any direct integrations. Kafka’s strength lies in enabling real-time event processing, which has become a business imperative across industries, especially in critical functions where delays mean lost value—like fraud detection, personalized recommendations, and predictive maintenance.

1.1 How an architect sees Kafka

1.1.1 Event-driven architecture

1.1.2 Handling myriads of data

1.2 Field notes: Journey of an event-driven project

1.3 Key players in the Kafka ecosystem

1.3.1 Brokers and clients

1.3.2 Controllers: Managing cluster metadata

1.4 Applying Kafka’s architectural principles

1.4.1 The publish-subscribe pattern

1.4.2 Reliable delivery

1.4.3 The commit log

1.5 Designing and managing data flows

1.5.1 Schema Registry: Handling data contracts

1.5.2 Kafka Connect: Data replication without code

1.5.3 Streaming frameworks: Processing data in real time

1.6 Addressing operations and infrastructure

1.6.1 Kafka tuning and maintenance

1.6.2 On-premises and cloud options

1.6.3 Solutions from other cloud providers