April 6, 2020 | Episode 92

How to Run Kafka Streams on Kubernetes ft. Viktor Gamov

  • Notes

There’s something about YAML and the word “Docker” that doesn’t quite sit well with Viktor Gamov (Developer Advocate, Confluent). But Kafka Streams on Kubernetes is a phrase that does.

Kubernetes is an open source platform that allows teams to deploy, manage, and automate containerized services and workloads. Running Kafka Streams on Kubernetes simplifies operations and gets your environment allocated faster.

Viktor describes what that process looks like and how Jib helps build, test, and deploy Kafka Streams applications on Kubernetes for an improved DevOps experience. He also shares about some exciting projects he’s currently working on. 

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Episode 93April 15, 2020 | 55 min

Streaming Data Integration – Where Development Meets Deployment ft. James Urquhart

James Urquhart (Global Field CTO, VMware) is writing a book about worldly mapping and evaluating user needs in order to make event streaming a more economic choice for users. James argues that reducing the cost of integration does not deter people from buying but instead encourages creativity to find more uses for integration.

Episode 94April 16, 2020 | 10 min

Apache Kafka 2.5 – Overview of Latest Features, Updates, and KIPs

Apache Kafka® 2.5 is here, and we’ve got some Kafka Improvement Proposals (KIPs) to discuss! Tim Berglund shares improvements and changes to over 10 KIPs all within the realm of Core Kafka, Kafka Connect, and Kafka Streams, including foundational improvements to exactly-once semantics, the ability to track a connector’s active topics, and adding a new co-group operator to the Streams DSL.

Episode 95April 22, 2020 | 46 min

Making Abstract Algebra Count in the World of Event Streaming ft. Sam Ritchie

During his time at Twitter, Sam Ritchie led the development of Summingbird, a project that helped Twitter ingest and process massive amounts of data, relieving some key pain points for developers at Twitter. In this episode, Sam dives teaches us some abstract algebra and explains how it has informed his attempts to make stream processing programs easy to write in a more general way.

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