In which cases should Kafka be used, and when is direct integration sufficient?

Kafka should be used when a reliable, scalable, and fault-tolerant messaging system with high throughput and the ability to handle large data streams is required. This is relevant for scenarios with asynchronous integration, where message delivery needs to be guaranteed, event history stored, subscribers with different processing speeds supported, and patterns like event sourcing or CQRS implemented.

Direct integration (e.g., REST API calls or synchronous calls between services) is sufficient when:

• The volume of data and load are small.
• Simple and fast communication with minimal latency is needed.
• Guaranteed delivery or message storage is not necessary.
• The architecture does not involve complex asynchronous processing.

In other words, Kafka is justified in distributed systems with high requirements for scalability and message exchange reliability, while direct integration is suitable for simple, synchronous scenarios.