Unfortunately it will not be recorded this time, but we will try to upload the slides after the session.
And for those who can make it, you are NOT required a Strata pass to attend! Guozhang On Tue, Mar 29, 2016 at 9:04 AM, Marina <ppi...@yahoo.com.invalid> wrote: > Sounds like a great Meetup! Unfortunately, not all of us are lucky enough > to be in CA :) - any chance this Meetup will be recorded? > thanks! > > From: Guozhang Wang <wangg...@gmail.com> > To: "d...@kafka.apache.org" <d...@kafka.apache.org>; " > users@kafka.apache.org" <users@kafka.apache.org> > Sent: Tuesday, March 29, 2016 12:00 PM > Subject: Apache Kafka Meetup today, at San Jose Convention Center > > Hello Apache Kafka folks, > > We invite you to join us for the March Apache Kafka Meetup today (Tuesday, > March 29) at San Jose Convention Center, starting at 6pm: > > http://www.meetup.com/http-kafka-apache-org/events/229424437/ > > We have two great talks today: > > ------ > > Title: Introduction to Kafka Streams Abstract (by Guozhang Wang, > Confluent): > > In the past few years Apache Kafka has emerged itself as the world's most > popular real-time data streaming platform backbone. In this talk, we > introduce Kafka Streams, the latest addition to the Apache Kafka project, > which is a new stream processing library natively integrated with Kafka. > > Kafka Streams has a very low barrier to entry, easy operationalization, and > a natural DSL for writing stream processing applications. As such it is the > most convenient yet scalable option to analyze, transform, or otherwise > process data that is backed by Kafka. We will provide the audience with an > overview of Kafka Streams including its design and API, typical use cases, > code examples, and an outlook of its upcoming roadmap. We will also compare > Kafka Streams' light-weight library approach with heavier, framework-based > tools such as Spark Streaming or Storm, which require you to understand and > operate a whole different infrastructure for processing real-time data in > Kafka. > > ------ > > Title: Streaming Analytics at 300 billion events/day with Kafka, Samza, and > Druid (by Xavier Léauté, Metamarkets) > > Abstract: Wonder what it takes to scale Kafka, Samza, and Druid to handle > complex analytics workloads at petabyte size? We will share a high level > overview of the Metamarkets realtime stack, the lessons learned scaling our > real-time processing to over 3 million events per second, and how we > leverage extensive metric collection to handle heterogeneous processing > workloads, while keeping down operational complexity and cost. Built > entirely on open source, our stack performs streaming joins using Kafka and > Samza, feeding into Druid to serve 1 million interactive queries per day. > > ------ > > Thanks, > > -- Guozhang > > > -- -- Guozhang
