Apache Kafka is commonly used wherever an application needs to move or process large volumes of data in real time between multiple systems or services.
Key Points: • Real-time analytics and dashboards, where events are aggregated and visualized as they happen. • Change data capture (CDC), streaming database row changes into Kafka so other systems stay in sync. • Event-driven microservices, where services communicate asynchronously through topics instead of direct calls. • Log aggregation, collecting logs from many services into a central pipeline for processing and storage. • Messaging and notification systems that need to fan out events (like order updates) to multiple downstream consumers.
Example: An e-commerce site might use Kafka to stream "item viewed" and "item purchased" events into a recommendation engine that updates in near real time, while the same events also flow into a separate analytics topic for business dashboards.
Interview Tip: A concise interview answer is:
"Kafka is commonly used for real-time analytics, change data capture, event-driven microservice communication, log aggregation, and any scenario where multiple systems need to react to the same stream of events with low latency."