Name: Fighting Fraud with Apache Kafka® at Stubhub
Start: 2020-01-23T17:00:00-08:00
End: 2020-01-23T19:30:00-08:00
Location: StubHub

Join us for an Apache Kafka® meetup on January 23rd at 5:00pm, hosted at Stubhub in San Francisco! Address, time and agenda can be found below!

5:00pm - 5:30pm: Networking, Pizza and drinks!
5:30pm - 6:15pm: Gautam Dey, Stubhub
6:15pm - 7:00pm: Konstantine Karantasis, Confluent
7:00pm - 7:30pm: Additional Q&A and Networking

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First Talk:
Gautam Dey, Senior Software Engineer, Stubhub

Gautam will talk about how Stubhub are implementing Kafka to help the Fraud use-case within Stubhub.

Second talk:
Konstantine Karantasis

Bio: Konstantine Karantasis is a software engineer at Confluent. He’s a main contributor to Apache Kafka and its Connect API, and an author of widely used software, such as Confluent’s S3 and Replicator connectors, class loading isolation in Kafka Connect, Incremental Cooperative Rebalancing in Kafka, the Confluent CLI and more. Previously, he built scalable open source web services at Yahoo! and researched high-performance computing at the University of Illinois at Urbana-Champaign. Konstantine holds a Ph.D. from the University of Patras.

Talk: Design and Implementation of Incremental Cooperative Rebalancing

Since its initial release, the Kafka group membership protocol has offered Connect, Streams and Consumer applications an ingenious and robust way to balance resources among distributed processes. The process of rebalancing, as it’s widely known, allows Kafka APIs to define an embedded protocol for load balancing within the group membership protocol itself.

Until now, rebalancing has been working under the simple assumption that every time a new group generation is created, the members join after first releasing all of their resources, getting a whole new load assignment by the time the new group is formed. This allows Kafka APIs to provide task fault-tolerance and elasticity on top of the group membership protocol.

However, due to its side-effects on multi-tenancy and scalability this simple approach in rebalancing, also known as stop-the-world effect, is limiting larger scale deployments. Because of stop-the-world, application tasks get interrupted only for most of them to receive the same resources after rebalancing. In this technical deep dive, we’ll discuss the proposition of Incremental Cooperative Rebalancing as a way to alleviate stop-the-world and optimize rebalancing in Kafka APIs.

This talk will cover:

- The internals of Incremental Cooperative Rebalancing
- Uses cases that benefit from Incremental Cooperative Rebalancing
- Implementation in Kafka Connect
- Performance results in Kafka Connect clusters

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Don't forget to join our Community Slack Team! https://launchpass.com/confluentcommunity

If you would like to speak or host our next event please let us know! community@confluent.io

NOTE: We're unable to cater for attendees under the age of 18. Please do not sign up for this event if you're under 18.

Alice Richardson

Joe Shore

Bay Area Apache Kafka® Meetup

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Fighting Fraud with Apache Kafka® at Stubhub

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