Apache Kafka and the Rise of The Stream Data Platform

Speaker : Jay Kreps

Abstract: What happens if you take everything that is happening in your company—every click, every database change, every application log—and make it all available as a real-time stream of well structured data?

I will discuss the experience at LinkedIn and elsewhere moving from batch-oriented ETL to real-time streams using Apache Kafka. I’ll talk about how the design and implementation of Kafka was driven by this goal of acting as a real-time platform for event data. I will cover some of the challenges of scaling Kafka to hundreds of billions of events per day at Linkedin, supporting thousands of engineers, applications, and data systems in a self-service fashion.

I will describe how real-time streams can become the source of ETL into Hadoop or a relational data warehouse, and how real-time data can supplement the role of batch-oriented analytics in Hadoop or a traditional data warehouse.

I will also describe how applications and stream processing systems such as Storm, Spark, or Samza can make use of these feeds for sophisticated real-time data processing as events occur.

Bio: Jay Kreps is the CEO of Confluent, Inc. He was formerly the lead architect for data infrastructure at LinkedIn. He is among the original authors of several open source projects including Project Voldemort, a key-value store, Apache Kafka, a distributed messaging system, and Apache Samza a stream processing system.

Agenda:

door opens at 6 pm.

6 pm - 6:30 pm networking
6:30 pm - 6:35 pm introduction
6:35 pm -- 7 :45 pm main talk, Q&A
7:45 pm - 8: 15 pm networking
8:30 pm office close