Join us for an Apache Kafka® meetup on May 23rd from 5:30pm, hosted at Wayfair in Boston. The address, agenda and speaker information can be found below. See you there!
"* IMPORTANT: For security reasons, the venue requires first and last name. Please make sure you provide this data within this form: https://docs.google.com/forms/d/e/1FAIpQLSed57NFh_H_jQoYVC7GhoVRAGvlZI75OXUrYaFvXVM3fig2lQ/viewform
This will help to ensure entrance to the building. Thank you!*"
5:30pm-6:00pm: Doors Open, Networking, Pizza and Drinks
6:00pm - 6:45pm: Bill Bejeck, Confluent
6:45pm-7:00 pm: Break/Networking
7:00pm - 7:45pm: Bill Scott, Jacob Zweifel & Srinivas of Tribal Scale, Cupcakes, Kafka, and .NET Core
7:45pm - 8:00pm: Additional Q&A and Networking
Bill Bejeck/ Confluent/ @bbejeck
Kicking Your Database to the Curb
In typical microservice applications, you'd need to send the state of that microservice to a relational database -- i.e., manage remote state -- then use another app to view the results as the microservice updates the database. Unfortunately, this common approach has few downsides: increased complexity and code management among them. But there is an alternative for your microservices: The Streams API of Apache Kafka is a state-of-the-art stream processing library to write large-scale, fault-tolerant, elastic, scalable applications. It includes powerful local state management functionality, which eliminates the need for remote state storage in many use cases.
Kafka Streams eases that burden by providing a mechanism, Interactive Queries or IQ, to view the state across all streams instances. What's compelling about Interactive Queries is that you don't need to know which application instance contains the information required. You query one Kafka Streams instance, and if it does not hold the desired record(s), it asks the other Kafka Streams instances on your behalf.
So with Interactive Queries, you can build, for example, dashboard functionality without the need of adding another storage technology, you can directly query Kafka Streams itself and retrieve all of the state you need directly as records are arriving.
In this talk, I'll give the audience some background context on event streams and update streams, and how update streams use state. From there, the audience will learn how to enable interactive queries, how to implement IQ, and some best practices and the tradeoffs of using IQ.
Bill Scott (@BillScottCoder),Jacob Zweifel (@jacob_zweifel) & Srinivas (@srigumm)/ Tribal Scale
Title of Talk:
Cupcakes, Kafka, and .NET Core
The tech world has been lit on fire by event sourcing and micro services, and by this time, you’ve probably heard of all of the benefits, perhaps even a few of the pitfalls, and have been impressed by the scale at which others are using Kafka in their environment and the solving of complex operational problems. You’re fired up and ready to start implementing your first Kafka-based solution using .NET Core… but struggling to find example architectures to use as a point of reference!
In this talk, we’ll take the audience through a tour of some common implementation patterns that we’ve seen when implementing .NET Core micro-services and Kafka through the lens of an interactive cupcake factory (real cupcakes sadly not included). We will introduce common implementation patterns such as Kafka Connect, Streaming topics, CDC, Log Compaction …other patterns that Bill Scott and Srini implementing in the Cupcake factory… The Cupcake Factory is our open-source reference implementation. You’ll leave with access to a reference architecture, .NET code samples, and a appetite for a dozen of everyone’s favorite cake-based sweet treat.
Don't forget to join our Community Slack Team! https://launchpass.com/confluentcommunity
NOTE: We're unable to cater for attendees under the age of 18.