Posts by Leslie Denson | The Eventador Blog

Podcast: Crushing Apache Flink-based Streaming Systems with special guest Gyula Fóra

In this episode of the Eventador Streams podcast, Kenny and I had the chance to chat with Gyula Fóra, currently a Flink engineer at Cloudera and formerly on the streaming systems team at King, about (candy) crushing Flink-based streaming systems in production.

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Podcast: Getting More Out of Streaming SQL with the Blink Planner in Apache Flink

In this episode of the Eventador Streams podcast, Kenny and I chatted about the Blink planner and all the fun and massively useful SQL functions that it unlocks for streaming pipelines.

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Podcast: A Dive Into Apache Heron & Understanding Streaming Systems with Josh Fischer and Ning Wang

In this episode of the Eventador Streams podcast, Kenny and I chatted with Josh Fischer, Senior DevOps Developer at ScotCro Management Consulting, and Ning Wang, Software Engineer at Amplitutde, about Apache Heron and their new book Grokking Streaming Systems.

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Podcast: The Fun of Stateful Functions and Apache Flink with Stephan Ewen

In this episode of the Eventador Streams podcast, Kenny and I chatted with Stephan Ewen, Co-founder & CTO of Ververica, about the beginnings and growth of Apache Flink as well as the inception and future of Stateful Functions.

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Podcast: Real-time Data Science in a Streaming World with Dustin Garvey

In this episode, we had the chance to talk with Dustin Garvey, head of Machine Learning at Archipelago Analytics to chat about how data science and machine learning pipelines have changed—and should continue changing—with the growth of streaming data.

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Podcast: A Primer for Apache Beam on Flink with Maximilian Michels

In this episode of the Eventador Streams podcast, we had the opportunity to chat with Maximilian Michels, a software engineer at Lyft working on their streaming pipelines, about his rich tenure with both Apache Flink and Apache Beam.

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Podcast: A Look at Modern Data Processing Architectures

In this episode of the Eventador Streams podcast, Kenny and I took a look at today’s data processing architectures, and how, in reality, all data is a data stream today.

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Podcast: True Observability in a Real-time World with Charity Majors

In this episode, we had the chance to chat about another side of data systems as we were joined by Charity Majors, Co-founder and CTO at Honeycomb.io for a fantastic conversation all about observability.

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Podcast: Building a Streaming Data Engine for Killer Apps with Erik Beebe

In this episode of the Eventador Streams podcast and to celebrate Eventador’s fourth birthday (yay!), Kenny and I are joined by Erik Beebe to take a walk down memory lane with how and why Eventador came to be

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Podcast: The Growth & Evolution of Flink with special guest Marton Balassi

In this episode of Eventador Streams, we had the chance to chat with Marton Balassi, manager of the streaming analytics team at Cloudera about his experience as one of the earliest contributors to Apache Flink.

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Podcast: Ditching the Database and Materializing Views of Data Streams

In this episode of Eventador Streams, we chatted in more depth about why materializing views of Kafka data is an increasingly critical part of streaming pipelines and how this reduces reliance on costly databases.

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Podcast: The Anatomy of Successful Streaming Data Teams with special guest Jesse Anderson

In this episode of the Eventador Streams podcast, we had the pleasure of chatting with Jesse Anderson, managing director of the Big Data Institute and author of the upcoming book “Data Teams,” about what the anatomy of a successful streaming data team looks like.

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Podcast: All Things Apache Flink and Why Its Popularity is Rising

In the latest episode of Evenatdor Streams, Kenny and I sat down to chat about a topic that’s fairly central to many of the conversations we have here at Eventador: Apache Flink.

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Unlocking Kafka’s Value for Machine Learning and Data Science Pipelines

It’s a topic that’s come up for us with both current customers and in other conversations we have—data science teams are hungry for better access to Kafka-based streaming data.

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