Modern Kafka apps: Customer 360, Real-time AI, & data streaming for enterprises

Modern Kafka applications: From Customer 360 to Real-time AI, to Crafting data streaming products for modern enterprises

This meetup focuses on using Apache Kafka to solve critical data challenges in today’s enterprises. Speakers from SAS, Bytewax and Shadowtraffic will share how to accelerate development, implement real-time ML/ AI systems, and optimize stream processing performance.

Join us to stay ahead in the ever-evolving world of data streaming.

## part 1-SAS: SAS accelerates Customer 360 on Kafka with Lenses

With changes in their cloud operations, SAS needed to deploy and manage Kafka clusters more efficiently. Learn how this leading SaaS analytics company sped up their time-to-market of products like CI360, by giving +2000 developers Kafka access and observability via Lenses

Bio :
Randy Wilcox is the Global Leader of Data Platform Technologies for SAS Cloud.
https://www.linkedin.com/in/randalljwilcox/
Subhash Donthineni is manager of Data Platform Technologies for SAS Cloud
https://www.linkedin.com/in/sdonthineni/

## part 2-Bytewax: Intelligence, Online: Designing Real-time ML/AI Systems for a Streaming World

Zander will cover the rising importance of streaming data in an increasingly ML/AI driven world including architecture, a case study and a short demo of how Bytewax is used to develop real-time machine learning systems.

Zander Matheson, CEO and founder at Bytewax
Zander is a seasoned data engineer who founded and currently heads Bytewax. He has worked in the data space since 2014 at Heroku, GitHub, and an NLP startup. Before that, he attended business school at UT Austin and HEC Paris in Europe.

## part 3 - Shadowtraffic: Generating Deterministic, Synthetic Workloads for Stream Processing

Do you want to kick the tires on Apache Kafka, Flink, or Spark? Do you want to make sure it can perform well for your target use case? How can you do that?

Unlike batch systems, repeatably testing stream processors is not as easy as downloading files out of an S3 bucket. You need continuous streams of data that reflect the current wallclock time, have commonality across their identifiers, and have a bit of real-world jitter like delayed arrival.
In this talk, we look at the design techniques you can use to test these systems yourself. We'll cover how to test with deterministic randomness, deterministic time, stable event ordering, and more.

Attendees will walk away with the tools to exercise stream processing systems with repeatable synthetic workloads.

Michael is the founder of ShadowTraffic, a synthetic data generator service. Previously, he founded a stream-native data warehouse company that was acquired by Confluent. An east-coast native, he now lives in Seattle, Washington.