WEBINAR REPLAY | Reactive, fast-data,

Fast Data: Selecting The Right Streaming Technologies For Data Sets That Never End

With Dr. Dean Wampler, Office of the CTO and Fast Data Architect at Lightbend, Inc.

Why have stream-oriented data systems become so popular, when batch-oriented systems have served big data needs for many years? Batch-mode processing isn’t going away, but exclusive use of these systems is now a competitive disadvantage. You’ll learn that, while fast data architectures are much harder to build, they represent the state of the art for dealing with mountains of data that require immediate attention.

In this webinar, Lightbend’s Big Data Architect, Dr. Dean Wampler, examines the rise of streaming systems for handling time-sensitive problems. We’ll explore the characteristics of fast data architectures, and the open source tools for implementing them.

We’ll also take a brief look at Lightbend’s upcoming Fast Data Platform (FDP), a comprehensive solution of OSS and commercial technologies. FDP includes installation, integration, and monitoring tools tuned for various deployment scenarios, plus sample applications to help you sort out which tools to use for which purposes.

We’ll cover:

  • Learn step-by-step how a basic fast data architecture works
  • Understand why event logs are the core abstraction for streaming architectures, while message queues are the core integration tool
  • Use methods for analyzing infinite data sets, where you don’t have all the data and never will
  • Take a tour of open source streaming engines, and discover which ones work best for different use cases
  • Get recommendations for making real-world streaming system responsive, resilient, elastic, and message driven
  • Explore an example streaming application for the IoT: telemetry ingestion and anomaly detection for home automation systems



WEBINAR REPLAY | Reactive, fast-data,

Fast Data: Selecting The Right Streaming Technologies For Data Sets That Never End

With Dr. Dean Wampler, Office of the CTO and Fast Data Architect at Lightbend, Inc. and Justin Pihony, Developer Support Engineer at Lightbend, Inc.

Why have stream-oriented data systems become so popular, when batch-oriented systems have served big data needs for many years? Batch-mode processing isn’t going away, but exclusive use of these systems is now a competitive disadvantage. You’ll learn that, while fast data architectures are much harder to build, they represent the state of the art for dealing with mountains of data that require immediate attention.

In this webinar, Lightbend’s Big Data Architect, Dr. Dean Wampler, examines the rise of streaming systems for handling time-sensitive problems. We’ll explore the characteristics of fast data architectures, and the open source tools for implementing them.

We’ll also take a brief look at Lightbend’s upcoming Fast Data Platform (FDP), a comprehensive solution of OSS and commercial technologies. FDP includes installation, integration, and monitoring tools tuned for various deployment scenarios, plus sample applications to help you sort out which tools to use for which purposes.

We’ll cover:

  • Learn step-by-step how a basic fast data architecture works
  • Understand why event logs are the core abstraction for streaming architectures, while message queues are the core integration tool
  • Use methods for analyzing infinite data sets, where you don’t have all the data and never will
  • Take a tour of open source streaming engines, and discover which ones work best for different use cases
  • Get recommendations for making real-world streaming system responsive, resilient, elastic, and message driven
  • Explore an example streaming application for the IoT: telemetry ingestion and anomaly detection for home automation systems



About Presenter

Dr. Dean Wampler, Office of the CTO and Fast Data Architect at Lightbend, Inc.

Dean Wampler, Ph.D., is a member of the Office of the CTO and the Architect for Big Data Products and Services at Lightbend. He uses Scala and Functional Programming to build Big Data systems using Spark, Mesos, Hadoop, the Lightbend Reactive Platform, and other tools. Dean is the author or co-author of three O'Reilly books on Scala, Functional Programming, and Hive. He contributes to several open source projects (including Spark) and he co-organizes and speaks at many technology conferences and Chicago-based user groups. He has B.S. and M.S. degrees in Physics from the University of Virginia and a Ph.D. in Theoretical Physics from the University of Washington.

About Presenters

Dr. Dean Wampler, Office of the CTO and Fast Data Architect at Lightbend, Inc.

Dean Wampler, Ph.D., is a member of the Office of the CTO and the Architect for Big Data Products and Services at Lightbend. He uses Scala and Functional Programming to build Big Data systems using Spark, Mesos, Hadoop, the Lightbend Reactive Platform, and other tools. Dean is the author or co-author of three O'Reilly books on Scala, Functional Programming, and Hive. He contributes to several open source projects (including Spark) and he co-organizes and speaks at many technology conferences and Chicago-based user groups. He has B.S. and M.S. degrees in Physics from the University of Virginia and a Ph.D. in Theoretical Physics from the University of Washington.

Justin Pihony, Developer Support Engineer at Lightbend, Inc.

Justin is the frontline defense providing support for all technical questions related to our products. Justin likes  to refer to it as StackOverflow++.  Until Lightbend Justin’s  professional career has been Microsoft based (SQL and C#). However, he has used Scala in teaching (Pluralsight) and side projects for the past 4+ years. Justin has been especially deep into Spark for the past 1-2 years.

About Lightbend

Lightbend (Twitter: @Lightbend) is dedicated to helping developers build Reactive applications on the JVM. With the Lightbend Reactive Platform, developers can create message-driven applications that scale on multicore and cloud computing architectures by using projects like Lagom, Play Framework, Akka, Scala, Java, and Apache Spark. To help our customers succeed, Lightbend partners with technology pioneers such as Databricks, IBM, and Mesosphere.