Unleashing your Kafka Streams Application Metrics!

Kafka Streams has a rich set of metrics for monitoring application health. Through these metrics, you can uncover performance issues, resource allocation concerns, and improve the performance of your application through deployment and configuration changes.

Providing dashboards around all of these metrics can be rather challenging. In addition, the vast amount of metrics is extensive. Which metrics are important depends on the type of application you’re building. Let's uncover what you should be monitoring, why you should be monitoring it, and leave you with properly monitored Kafka Streams applications.

Not only will you gain an understanding of task-id, sub-topology, and partition-id, but you will also see how to visualize that topology in a dashboard. Explore the new metrics added to Kafka Streams, since 3.0 was released, and go in-depth with the awesome end-to-end latency metrics. Finally, learn how to use these metrics to determine the number of instances an application needs when being deployed.

Unleash your Kafka Stream Application metrics making it easier to run your applications effectively.