Today on 07th of April, I created this blog, at about 00:50 a.m.
Performance Tuning of Kafka is critical when your cluster grow in size. Below are few points to consider to improve Kafka performance: Consumer group ID : Never use same exact consumer group ID for dozens of machines consuming from different topics. All of those commits will end up on the same exact partition of __consumer_offsets , hence the same broker, and this might in turn cause performance problems. Choose the consumer group ID to group_id+topic_name . Skewed : A broker is skewed if its number of partitions is greater that the average of partitions per broker on the given topic. Example: 2 brokers share 4 partitions, if one of them has 3 partitions, it is skewed (3 > 2). Try to make sure that none of the brokers is skewed. Spread : Brokers spread is the percentage of brokers in the cluster that has partitions for the given topic. Example: 3 brokers share a topic that has 2 partitions, so 66% of the brokers have partitions for this topic. Try to achieve 100% broker spread...
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