Introduction
Kafka uses memory and buffers to handle data efficiently between producers, brokers, and consumers. Proper configuration of these settings helps avoid slowdowns and data loss by managing how much data Kafka holds in memory before writing to disk or sending to clients.
When you want to improve Kafka broker performance by tuning how much memory it uses for caching data.
When producers need to batch messages efficiently before sending to Kafka to reduce network overhead.
When consumers require tuning of fetch buffers to optimize data retrieval speed.
When you face issues like high latency or frequent disk writes in Kafka and want to adjust buffer sizes.
When running Kafka on machines with limited memory and you want to avoid out-of-memory errors.