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June 24, 2020 | Episode 106

Growing the Event Streaming Community During COVID-19 ft. Ale Murray

  • Notes

We've all been affected by COVID-19 in one way or another, resulting in big changes in workplace functionality, productivity, and even our relationships within the Apache Kafka® and Confluent communities as meetings and events have needed to turn virtual. 

Ale Murray (Global Community Manager, Confluent) shares interesting trends, changes in community metrics, and what we’ve done to adapt as a response. Ale also explains what makes a comprehensive community program and the value of community meetups in light of the pandemic. 

Despite how much we miss in-person interactions, by digitizing events and focusing on the community, we saw great growth in attendance and engagement across our Slack community, online hackathons, MVP program, and online meetups over the last couple of months, proving that nothing can stop this amazing community from thriving.

Continue Listening

Episode 107June 29, 2020 | 43 min

Open Source Workflow Automation with Apache Kafka ft. Bernd Ruecker

Bernd Ruecker, a co-founder and the chief technologist at Camunda, talks through the company's journey, how he ended up in open source, and all things automation. Bernd also dives into dead letter topics in Kafka, software interacting with software, orchestration tension, and best practices for approaching challenges that pop up along the way. This episode will take you through a thorough introduction of the Komodo Cloud as well as Camunda’s Kafka connector.

Episode 108July 8, 2020 | 46 min

Benchmarking Apache Kafka Latency at the 99th Percentile ft. Anna Povzner

The five components of latency are produce time, publish time, commit time, catch-up time, and fetch time. When consumer pulling adds to latency, Anna Povzner shares some best practices to keep in mind for how to think about partitioning in conjunction with latency. She also discusses client configuration in the cloud, interesting problems she's helped solve for customers, and her top two tips for debugging latency.

Episode 109July 15, 2020 | 54 min

Fault Tolerance and High Availability in Kafka Streams and ksqlDB ft. Matthias J. Sax

Apache Kafka® Committer Matthias J. Sax explains fault tolerance, high-availability stream processing, and Kafka Streams. He explains the differences between changelogging and checkpointing, as well as making changes in Kafka versus hot standbys, explaining what qualifies nodes as a hot standby, why Kafka Streams doesn’t do watermarking, and finally, why Kafka Streams is a library and not infrastructure.

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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