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Episode 265June 15, 2023 | 11 min

Apache Kafka 3.5 - Kafka Core, Connect, Streams, & Client Updates

Apache Kafka 3.5 is here with the capability of previewing migrations between ZooKeeper clusters to KRaft mode. Follow along as Danica Fine highlights key release updates.

Episode 262March 14, 2023 | 31 min

How to use Python with Apache Kafka

Can you use Apache Kafka® and Python together? What’s the current state of Python support? And what are the best options to get started? In this episode, Dave Klein joins Kris to talk about all things Kafka and Python: the libraries, the tools, and the pros & cons. He also talks about the new course he just launched to support Python programmers entering the event-streaming world.

Episode 256February 7, 2023 | 5 min

Apache Kafka 3.4 - New Features & Improvements

Apache Kafka 3.4 is released! In this special episode, Danica Fine (Senior Developer Advocate, Confluent), shares highlights of the Apache Kafka 3.4 release. This release introduces new KIPs in Kafka Core, Kafka Streams, and Kafka Connect.

Episode 255February 1, 2023 | 50 min

How to use OpenTelemetry to Trace and Monitor Apache Kafka Systems

How can you use OpenTelemetry to gain insight into your Apache Kafka event systems? Roman Kolesnev, Staff Customer Innovation Engineer at Confluent, is a member of the Customer Solutions & Innovation Division Labs team working to build business-critical OpenTelemetry applications so companies can see what’s happening inside their data pipelines. In this episode, Roman joins Kris to discuss tracing and monitoring in distributed systems using OpenTelemetry. He talks about how monitoring each step of the process individually is critical to discovering potential delays or bottlenecks before they happen; including keeping track of timestamps, latency information, exceptions, and other data points that could help with troubleshooting.

Episode 252January 12, 2023 | 51 min

Using Kafka-Leader-Election to Improve Scalability and Performance

How does leader election work in Apache Kafka? For the past 2 ½ years, Adithya Chandra, Staff Software Engineer at Confluent, has been working on Kafka scalability and performance, specifically partition leader election. In this episode, he gives Kris Jenkins a deep dive into the power of leader election in Kafka replication, why we need it, how it works, what can go wrong, and how it's being improved.

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Got questions?

If there's something you want to know about Apache Kafka, Confluent or event streaming, please send us an email with your question and we'll hope to answer it on the next episode of Ask Confluent.

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