Profiling Kafka #1 – Message Flow & Hot Spots

Kafka-based applications are notoriously hard to profile. Message flow happens in background threads, stack traces don’t reveal the full picture, and it’s hard to know which topic contributes to which hot spot.

JProfiler’s Kafka probes give you deep insight—producers, consumers, and message-level details are all captured and correlated with performance data.

This screencast walks through profiling a Spring Kafka application, showing how:

• consumer call trees are split by topic
• producers link directly into probe views
• you can correlate CPU hot spots with Kafka topics
• Kafka events are filterable, inspectable, and aggregatable