Optimizing Kafka

Yeva Byzek explains different tuning options available within Apache Kafka:

Without needing to make any changes to Kafka configuration parameters, you can setup a development Kafka environment and test basic functionality. Yet the fact that Kafka runs straight off the shelf does not mean you won’t want to do some tuning before you go into production. The reason to tune is that different use cases will have different sets of requirements that will drive different service goals. To optimize for those service goals, there are Kafka configuration parameters that you should change. In fact, the Kafka design itself provides configuration flexibility to users, and to make sure your Kafka deployment is optimized for your service goals, you absolutely should investigate tuning the settings of some configuration parameters and benchmarking in your own environment. Ideally, you should do that before you go to production, or at least before you scale out to a larger cluster size.

We have written a white paper to help you identify those service goals, configure your Kafka deployment to optimize for them, and ensure that you are achieving them through monitoring.

Read the whole thing, especially the part about throughput versus latency.

Related Posts

Event Sourcing On Kafka

Adam Warski shows how you can use Apache Kafka as your event sourcing data source: There’s a number of great introductory articles, so this is going to be a very brief introduction. With event sourcing, instead of storing the “current” state of the entities that are used in our system, we store a stream of events that relate to these […]

Read More

The Basics Of Kafka Security

Stephane Maarek has a nice post covering some of the basics of securing an Apache Kafka cluster: Once your Kafka clients are authenticated, Kafka needs to be able to decide what they can and cannot do. This is where Authorization comes in, controlled by Access Control Lists (ACL). ACL are what you expect them to be: […]

Read More