July 8, 2020 | Episode 108

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

  • Notes

Real-time stock trades, GPS location, and website click tracking are just a few industries that heavily rely on Apache Kafka®'s real-time messaging and data delivery functions. As such, Kafka's latency is incredibly important.

Anna Povzner (Software Engineer, Confluent) gives you the breakdown and everything you need to know when it comes to measuring latency. 

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 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. 

Continue Listening

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.

Episode 110July 20, 2020 | 41 min

Modernizing Inventory Management Technology ft. Sina Sojoodi and Rohit Kelapure

Inventory management systems are crucial for reducing real-time inventory data drift, improving customer experience, and minimizing out-of-stock events. Kafka provides seamless inventory tracking at scale, saving billions of dollars in the supply chain, making modernized data architectures more important to retailers now more than ever. In this episode, we’ll discuss how Kafka enables stateful event streaming on a cloud-native platform for application and architecture modernization, leveraging Spring Boot, Kafka Streams, and Apache Cassandra.

Episode 111July 27, 2020 | 54 min

How to Measure the Business Value of Confluent Cloud ft. Lyndon Hedderly

Learn about the five different parts to a business value framework: (1) baseline, (2) target state, (3) quantified benefits, (4) unquantified benefits, and (5) proof points; cost effectiveness with Confluent Cloud; how to measure ROI vs. TCO; and a retail example from a customer that details their implementation of an event streaming platform.

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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