In what situations is Kafka suitable for use?

1. Kafka can be used as a message queue for large-scale real-time data processing, such as log collection and real-time monitoring.
2. Communication between distributed systems: Kafka can be used as middleware for communication between distributed systems, enabling message passing and data synchronization between different systems.
3. Log aggregation and data pipeline: Kafka can be used as a tool for aggregating logs, centralizing storage and processing of log data generated by various systems.
4. Kafka offers stream processing capabilities, which can be used for real-time analysis, event handling, and other scenarios.
5. Kafka can serve as middleware for data integration between different systems, enabling the transfer and synchronization of data.

In general, Kafka is suitable for scenarios requiring large-scale real-time data processing, high reliability, and high performance, particularly ideal for applications in the Internet and big data fields.