Using Splunk Data Stream Processor as a Streaming Engine for Apache Kafka [Splunk Data Fabric Search and Data Stream Processor]

Do you use Kafka but find yourself limited by what Kafka allows you to do with your data? Would you like to enrich, aggregate, and alert on your data as it moves through Kafka, but can’t figure out how? You can overcome these obstacles by integrating Kafka with the Splunk Data Stream Processor. The Splunk DSP is a data streaming platform that helps you transform and enrich your data. With DSP you can make data-driven decisions in real time as data is ingested. DSP also provides simple ways to build data pipelines, and gives you full control and visibility into your data as it flows through the platform. Apache Kafka is now widely adopted as a foundational element for data pipelines. DSP integrates seamlessly with Kafka clusters, and allows data to be read from Kafka, processed in highly scalable ways, and then written back to Kafka. Join us and see how to use DSP as a streaming engine for Kafka clusters.

Speaker(s)
Thor Taylor, Director of Product Management, Splunk
Adam Lamar, Principal Software Engineer, Splunk

Slides PDF link - https://conf.splunk.com/files/2019/slides/FN1987.pdf?podcast=1576909597