What potential difficulties and limitations may arise when using Kafka in systems?

Using Apache Kafka in systems can present the following challenges and limitations:

• State management and scaling: Kafka requires proper configuration of clusters, brokers, and partitions to ensure fault tolerance and performance.

• Delays and performance: misconfiguration or high loads can lead to message delivery delays.

• Delivery guarantees: while Kafka supports different levels of delivery guarantees (at-least-once, at-most-once, exactly-once), implementing exactly-once requires additional configuration and can be complex.

• Data storage: Kafka stores message logs, which requires sufficient disk space and retention management.

• Error handling and re-delivery: it is necessary to plan logic for handling failures and duplicate messages.

• Integration complexity: integrating with other systems and supporting data schemas (e.g., Avro, Protobuf) requires additional infrastructure (Schema Registry).

• Monitoring and administration: tools for monitoring and managing the cluster are necessary for stable operation.

These points require attention when designing systems using Kafka.