Use CCLOUD50 to get an additional $50 of free Confluent Cloud- (details)
June 17, 2020 | Episode 105

From Monolith to Microservices with Sam Newman

  • Notes

Author Sam Newman catches up with Tim Berglund (Senior Director of Developer Advocacy, Confluent) in the virtual studio on what microservices are, how they work, the drawbacks of microservices, what splitting the monolith looks like, and patterns to look for. 

The pair talk through Sam's book “Monolith to Microservices” chapter by chapter, looking at key components of microservices in more detail. Sam also walks through database decomposition, integrating with new technology, and performing joins in event streaming architecture. Lastly, Sam shares what he’s excited for in the future, which includes “Monolith to Microservices Volume II.”

Continue Listening

Episode 106June 24, 2020 | 40 min

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

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 shares interesting trends, changes in community metrics, and what we’ve done to adapt as a response.

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.

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.

Email Us

Never miss an episode!

Be the first to get updates and new content

We will only share developer content and updates, including notifications when new content is added. We will never send you sales emails. 🙂 By subscribing, you understand we will process your personal information in accordance with our Privacy Statement.