Apache Kafka Practice

Data lineage in Kafka can be effectively achieved by auditing messages and tracking their flow. This involves monitoring how data moves through the system and identifying every stage of its journey from the producer to the consumer. By keeping detailed records of message events, transformations, and the interactions between various components of the data pipeline, organizations can establish a clear understanding of the source, movement, and changes made to the data over time. This visibility allows for better compliance, troubleshooting, and optimization of data processes.

Other options do not directly contribute to establishing data lineage. Reducing the number of Kafka topics may simplify the architecture but does not enhance the traceability of data. Encrypting message payloads focuses on securing data rather than tracking its lineage, and compressing data before sending primarily optimizes storage and transmission without providing insights into data flow.