Join us for an Apache Kafka meetup on August 15th at 6:30pm, hosted by Bloomberg in San Francisco! Address, agenda & speaker information can be found below. See you there!
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6:30 pm - 7:00 pm: Entry (networking/food)
7:00 pm - 7:40 pm: Performance Analysis & Optimizations for Kafka Streams Applications, Guozhang Wang, Confluent
7:40 pm - 8:20 pm: Creating explainable KafkaStreams pipelines with a replay framework, Nish Sinha, Bloomberg
8:20 pm - 8:45 pm: More Q&A/Networking
Speaker: Guozhang Wang
Guozhang Wang is a PMC member of Apache Kafka, & also a tech lead at Confluent leading the Streams team. He receives his PhD from Cornell University database group where he worked on scaling iterative data-driven applications. Prior to Confluent, Guozhang was a senior software engineer at LinkedIn, developing & maintaining its backbone streaming infrastructure on Apache Kafka & Apache Samza.
Talk Title: Performance Analysis & Optimizations for Kafka Streams Applications
High-speed & low footprint data stream processing is high in demand for Kafka Streams applications. However, how to write an efficient streaming application using the Streams DSL has been asked by many users in the past since it requires some deep knowledge about Kafka Streams internals. In this talk, I will talk about how to analyze your Kafka Streams applications, target performance bottlenecks & unnecessary storage costs, & optimize your application code accordingly using the Streams DSL.
In addition, I will talk about the new optimization framework that we have been developed inside Kafka Streams since the 2.1 release which replaced the in-place translation of the Streams DSL into a comprehensive process composed of streams topology compilation & rewriting phases, with a focus on reducing various storage footprints of Streams applications, such as state stores, internal topics etc.
Speaker: Nish Sinha
Bio: Nishchay Sinha is senior software engineer at Bloomberg from data pipeline team in San Francisco office. Currently he is leading the effort of building a replay-able data lake solution for streaming/batch market data. He has years of experiences building large scale data processing systems. Nish holds bachelor degree from IIT(Kharagpur) & master degree from Stanford.
Creating explainable KafkaStreams pipelines with a replay framework
Replayability of streaming data pipelines is very useful in many scenarios; in practice, however, it is oftentimes hard to achieve, especially for those stateful applications where simply replaying from the beginning is not always feasible. We set out to simplify this process by building out a custom replay framework that provides a query layer on top of a plug-able storage backend & periodically takes snapshots of an application's states. We envision making use of this framework in general debugging of production issues & additional application analysis.
KAFKA SUMMIT SF 2019: 30th September til the 1st October -
We are able to offer you a 25% discount on the standard priced ticket for Kafka Summit San Francisco (September 30th & October 1st). To redeem it, please go to bit.ly/KSummitMeetupInvite, click register, select Conference Pass & enter the community promo code KS19Meetup.
Don't forget to join our Community Slack Team! https://launchpass.com/confluentcommunity
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NOTE: Please do not sign up for this event if you are under 18.