Kafka producer tuning: Data that producers must provide to brokers is kept in a batch. The producer transmits the batch to the broker when it's ready. To adjust the producers for latency and throughput, two parameters must be considered: batch size and linger time. The batch size must be chosen with great care. If the producer is constantly delivering messages, a bigger batch size is recommended to maximize throughput. However, if the batch size is set to a huge value, it may never fill up or take a long time to do so, affecting the latency. The batch size must be selected based on the nature of the volume of messages transmitted by the producer. The linger duration is included to create a delay while more records are added to the batch, allowing for larger records to be transmitted. More messages can be transmitted in one batch with a longer linger period, but latency may suffer as a result. A shorter linger time, on the other hand, will result in fewer messages being transmitted faster, resulting in lower latency but also lower throughput.

Tuning the Kafka broker: Each partition in a topic has a leader, and each leader has 0 or more followers. It's critical that the leaders are appropriately balanced, and that some nodes aren't overworked in comparison to others.

Tuning Kafka Consumers: To ensure that consumers keep up with producers, the number of partitions for a topic should be equal to the number of consumers. The divisions are divided among the consumers in the same consumer group