Listen to Tim Berglund and guests unpack a variety of topics surrounding Apache Kafka®, Confluent, real-time data streaming, and the cloud.
Collecting internal, operational telemetry from Confluent Cloud services and thousands of clusters is no small feat. Traditionally, this data needs to be collected in multiple ways to satisfy all the different requirements. However, this sometimes leads to discrepancies between various systems. With OpenTelemetry, we can collect data in a vendor-agnostic way. Many vendors already integrate with OpenTelemetry, which gives us the flexibility to try out different observability solutions with minimal effort, without the need to rewrite applications or deploy new agents.
Focused on optimizing Kafka performance with maximized efficiency, Confluent’s Product Infrastructure team has been actively exploring opportunities for scaling out Kafka clusters. They are able to run Kafka workloads with half the typical memory usage while saving infrastructure costs, which they have tested and now safely rolled out across Confluent Cloud. In this episode, Adithya Chandra explains how.
When compiling database reports using a variety of data from different systems, obtaining the right data when you need it in real time can be difficult. With cloud connectivity and distributed data pipelines, Pat Helland (Principal Architect, Salesforce) explains how to make educated partial answers when you need to use the Apache Kafka® platform. After all, you can’t get guarantees across a distance, making it critical to consider partial results.
Jason Gustafson and Colin McCabe, Apache Kafka developers, discuss all things KIP-500 adoption, the removal of ZooKeeper, and how that’s played out on the frontlines within the event streaming world. A previous episode of Streaming Audio featured both developers on the podcast before the release of Apache Kafka 2.8. Now they’re back to share how everything is working in reality.
What is the internet of things (IoT), and how does it relate to event streaming and Apache Kafka? In this episode, Kai Waehner, field CTO and global technology advisor at Confluent, discusses the intersection of edge data infrastructure, IoT, and cloud services for Kafka. He also details how businesses get into the sticky situation of not accounting for solutions when data is running dangerously close to the edge.
Tim Berglund is a teacher, author, and technology leader with Confluent, where he serves as the senior director of developer advocacy. He can frequently be found at speaking at conferences in the U.S. and all over the world. Tim is the co-presenter of various O'Reilly training videos on topics ranging from Git to distributed systems, and he is the author of "Gradle Beyond the Basics." He lives in Littleton, CO, U.S., with the wife of his youth.
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