Streaming in Action: A Confluent Online Talk Series

Streaming in Action: A Confluent Online Talk Series

Watch On-demand

If you’re new to the world of streaming, the concept itself might be a bit fuzzy. Most new, exciting things are. In this series, we’ll introduce you to the world of streaming platforms and how you might view it as: 

  1. Messaging Done Right
  2. Hadoop Made Fast
  3. ETL as a Platform

Join 3 Apache Kafka® community members as they share how they leverage a streaming platform to speed up development, evolve their infrastructure, and provide real-time streaming applications and data pipelines.

Register for the on-demand recording. 


Part 1: Messaging Done Right

How Yelp Leapt to Microservices with More than a Message Queue

Without seeing what’s wrong with today’s messaging queues, it can be initially confusing to view Apache Kafka as more. By adding additional functionality, true storage, and guarantees it opens opportunities to take full advantage of a publish/subscribe model.

Joined by Yelp’s Justin Cunningham we’ll see how their infrastructure has quickly evolved. Powered by Kafka, Yelp has made the leap to microservices and is seeing the benefits of efficiency and performance.

yelp

Justin Cunningham

Technical Lead, Software Engineer, Yelp

Gehrig Kunz

Technical Product Marketing Manager, Confluent


Part 2: Hadoop Made Fast

Why Virtual Reality Needed Stream Processing to Survive

In this talk, we’ll show how a streaming platform can be considered Hadoop Made Fast. With Apache Kafka and it’s Streams API it’s possible to move much of what you would have done in a batch-oriented, sluggish process into a real-time one. We’ll cover the benefits of bringing concepts of Hadoop to real-time applications.

Then, Greg Fodor will share how he's worked with stream processing to solve hard VR challenges. This includes real-time mirroring, capture, and playback of networked avatars in a shared VR environment. Greg will also cover the design patterns they used for Kafka's Streams API and the lessons they learned along the way.

Greg Fodor

Greg Fodor
Co-founder, AltspaceVR

Gehrig Kunz

Technical Product Marketing Manager, Confluent


Part 3: ETL as a Platform

Pandora Plays Nicely Everywhere with Real-Time Data Pipelines

ETL can be painful with dirty data and outdated batch processes slowing you down; there has to be a better way. In this talk we’ll discuss the benefits of introducing a streaming platform to your architecture including how it can greatly simplify complexity, speed up performance, and help your team deliver the features they need with real-time data integration.

Pandora’s Lawrence Weikum will discuss what they’ve done to bring real-time data integration to the team. We’ll review their Kafka-powered data pipelines and how they make the most of Kafka’s Connect API to make it surprisingly system to keep systems in sync.

Lawrence Weikum

Senior Software Engineer, Pandora

Gehrig Kunz

Technical Product Marketing Manager, Confluent