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Advanced Kafka probe configuration in JProfiler

In our first Kafka screencast, we looked at how JProfiler correlates message flow and CPU usage through producers, consumers, and topic-level call trees.

In this follow-up, we go deeper, showing how to configure custom naming for Kafka messages based on their content.

This enables you to:

• split call trees by semantic message types
• track specific event types in probe views
• add value-level details to single event descriptions
• visualize outliers in event duration histograms

We also trigger a Kafka message spike via an API call and analyze its impact, all without changing the application code.