When do we need Kafka?

Kafka is needed when a reliable, scalable, and fault-tolerant messaging system with high throughput and low latency is required. Main use cases:

• Stream processing: when there is a need to collect, store, and process large volumes of events in real-time.
• Microservices integration: for asynchronous message exchange between services.
• Buffering and system offloading: Kafka can act as a buffer between data producers and consumers, providing resilience to peak loads.
• Analytics and monitoring: collecting logs and metrics for subsequent analysis.

Example: if you have a system that generates millions of events per second (for example, user clicks on a website), and you want to process and analyze them in real-time, Kafka is an excellent choice for transmitting and storing these events.