Apache Kafka: A Streaming Data Platform

We are incredibly privileged to welcome back Tim Berglund, Director of Developer Experience at Confluent, the company that brings you the distributed messaging system and streaming data platform, Apache Kafka.

Tim is Presenting....

Apache Kafka: A Streaming Data Platform

and

Heraclitus, the Metaphysics of Change, and Streaming Data

Doors Open 18:15 / Doors Close and Presentation Begins 19:00

Tim can frequently be found at speaking at conferences in the United States and all over the world. He is the co-presenter of various O’Reilly training videos on topics ranging from Git to Distributed Systems, and is the author of Gradle Beyond the Basics. He is also the co-host of the http://devrelrad.io podcast, and lives in Littleton, CO, USA with the wife of his youth and their youngest child; the other two having mostly grown up.

You can follow him on twitter at @tlberglund. .

Apache Kafka: A Streaming Data Platform

When it comes time to choose a distributed messaging system, everyone knows the answer: Apache Kafka. But how about when you’re on the hook to choose a world-class, horizontally scalable stream data processing system? When you need not just publish and subscribe messaging, but also long-term storage, a flexible integration framework, and a means of deploying real-time stream processing applications at scale without having to integrate a number of different pieces of infrastructure yourself? The answer is still Apache Kafka.

In this talk, we’ll make a rapid-fire review of the breadth of Kafka as a streaming data platform. We’ll look at its internal architecture, including how it partitions messaging workloads in a fault-tolerant way. We’ll learn how it provides message durability. We’ll look at its approach to pub/sub messaging. We’ll even take a peek at how Kafka Connect provides code-free, scalable, fault-tolerant integration, and how the Streams API provides a complete framework for computation over all the streaming data in your cluster . .

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Heraclitus, the Metaphysics of Change, and Streaming Data

Hailing from the Persian city of Ephesus in around 500 BC, the Greek philosopher Heraclitus is famous for his trenchant analysis of stream processing systems, saying “You never step into the same river twice.” Central to his philosophy was the idea that all things change constantly. His close readers also know him as the Weeping Philosopher—perhaps because dealing with constantly changing data at low latency is actually pretty hard. It doesn’t need to be that way.

Almost as famous as Heraclitus is Apache Kafka, the de facto standard open-source distributed stream processing system. Many of us know Kafka’s architectural and pub/sub API particulars as well as we know the philosophy of Heraclitus, but that doesn’t mean we’re equipped to build the kind of real-time streaming data systems that the next generation of business requirements are doing to demand. Like Heraclitus was telling us 2,500 years ago: we need to get on board with streams.

This talk is a thorough introduction to the Streams API, an important recent addition to Kafka that lets us build sophisticated stream processing systems that are as scalable and fault-tolerant as Kafka itself, and also happen to align quite well with the microservices sensibilities that are so common in contemporary architectural thinking. We’ll talk about how to deploy Streams applications and look at actual working code that will bring your thinking about streaming data systems from the ancient history of pub/sub paradigms into the current era.

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By the power of Tito