Presented By O'Reilly and Cloudera
Make Data Work
March 28–29, 2016: Training
March 29–31, 2016: Conference
San Jose, CA

Distributed stream processing with Apache Kafka

Jay Kreps (Confluent)
11:00am–11:40am Wednesday, 03/30/2016
IoT and Real-time

Location: 210 C/G
Tags: real-time
Average rating: ****.
(4.17, 24 ratings)

Prerequisite knowledge

Participants will benefit from general knowledge of Kafka or stream processing.


A modern business operates 24/7 and generates data continuously. Shouldn’t we process it continuously too?

A rich ecosystem of real-time data-processing frameworks, tools, and systems has been forming around Apache Kafka that allows data to be processed continuously as it occurs. Jay Kreps introduces Kafka and explains why it has become the de facto standard for streaming data. Jay draws on practical experience building stream-processing applications to discuss the difference between architectures and the challenges each presents. Jay then outlines Kafka Streams, which offers new stream processing functionality in Kafka, and explains how it helps to tame some of the complexity in real-time architectures.

Photo of Jay Kreps

Jay Kreps


Jay Kreps is the cofounder and CEO of Confluent, a company focused on Apache Kafka. Previously, Jay was one of the primary architects for LinkedIn, where he focused on data infrastructure and data-driven products. He was among the original authors of a number of open source projects in the scalable data systems space, including Voldemort (a key-value store), Azkaban, Kafka (a distributed messaging system), and Samza (a stream processing system).

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Jason Tower
03/29/2016 11:44pm PDT

If I’ve read “I heart logs” already is this a worthwhile talk to attend?