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Advanced Spring Boot 4: Event-Driven Architecture (Kafka) · Lesson

Performance Tuning Tips for Kafka

Explore advanced configuration adjustments for Kafka producers and consumers to optimize throughput and latency in high-volume scenarios.

Optimizing Kafka Performance

When dealing with high-volume data streams, default Kafka configurations might not be enough. Performance tuning helps you get the most out of your Kafka setup.

  • Throughput: How many messages can be processed per second?
  • Latency: How long does it take for a message to travel from producer to consumer?

We'll explore key adjustments for producers and consumers to balance these factors.

Producer Batching: `batch.size`

Kafka producers don't send every message individually. They group messages into batches. The batch.size configuration (default 16KB) controls the maximum size of these batches.

  • Increase batch.size: Sends fewer, larger requests to brokers.
  • Benefit: Reduces network overhead, improving overall throughput.
  • Trade-off: Can slightly increase latency for individual messages if batches fill slowly.

Find a size that works well with your typical message size and volume.

All lessons in this course

  1. Performance Tuning Tips for Kafka
  2. Idempotent Producers and Consumers
  3. Deploying Spring Boot Kafka Apps to Cloud
  4. Capacity Planning: Partitions and Replication
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