Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK

Report card on streaming microservices

Ted Dunning (MapR)
12:0512:45 Wednesday, 1 May 2019
Data Engineering and Architecture, Expo Hall, Streaming and IoT
Location: Expo Hall 2 (Capital Hall N24)
Average rating: ****.
(4.67, 6 ratings)

Who is this presentation for?

  • Data engineers, machine learning engineers, architects, and developers

Level

Intermediate

Prerequisite knowledge

  • Familiarity with microservice concepts
  • Experience building or designing data systems

What you'll learn

  • Get a reality check on the effectiveness of streaming architectures

Description

Streaming architectures are clearly very fashionable. But are they effective?

Ted Dunning shares several real-world case histories that illustrate how the promise of streaming—and especially streaming microservices—has paid off. Of particular interest, Ted explains how teams new to big data fared by jumping straight to an architecture based on streaming microservices armed with not a whole lot more than basic good sense and some inspirational literature. Join in to learn what worked, what didn’t, and how these teams rendered these architectures.

Topics include:

  • How these teams deploy new versions of systems
  • How they manage schemas in a streaming system embedded in a changing world
  • How machine learning plays with streaming systems
  • How all of this works in a Kubernetes-based multicloud environment
Photo of Ted Dunning

Ted Dunning

MapR

Ted Dunning is the chief technology officer at MapR. He’s also a board member for the Apache Software Foundation; a PMC member and committer of the Apache Mahout, Apache Zookeeper, and Apache Drill projects; and a mentor for various incubator projects. Ted has years of experience with machine learning and other big data solutions across a range of sectors. He’s contributed to clustering, classification, and matrix decomposition algorithms in Mahout and to the new Mahout Math library and designed the t-digest algorithm used in several open source projects and by a variety of companies. Previously, Ted was chief architect behind the MusicMatch (now Yahoo Music) and Veoh recommendation systems and built fraud-detection systems for ID Analytics (LifeLock). Ted has coauthored a number of books on big data topics, including several published by O’Reilly related to machine learning, and has 24 issued patents to date plus a dozen pending. He holds a PhD in computing science from the University of Sheffield. When he’s not doing data science, he plays guitar and mandolin. He also bought the beer at the first Hadoop user group meeting.