IN-PERSON: Apache Kafka® x Apache Flink® x Apache Iceberg x Grafana

IMPORTANT: PLEASE RSVP @ https://www.meetup.com/grafana-friends-amsterdam/events/310610414/

📕 Agenda
17:30 Open doors.
18:00 Food & Drinks
18:30 Meetup starts

1️⃣ "Supercharging Grafana with Community Plugins" by Imma Valls, Staff Developer Advocate at Grafana Labs.
Grafana is powerful on its own, but its true potential lies in its vibrant community of plugin developers. In this talk, we'll dive into how community plugins extend Grafana's core functionality, enabling you to connect to a broader range of data sources and visualize your data in new ways. We'll introduce the Kafka Data Source plugin as a practical example, demonstrating how it lets you directly query and visualize Kafka topic data in your dashboards, bypassing the need for intermediate storage or external services.

2️⃣ "Which Data Format Should I Use in Apache Kafka?" by Maria Berinde-Tâmpănariu, Staff Solutions Engineer at Confluent.
You're just starting your data streaming journey or are extending it to include Schema Registry and you learned that multiple serialization formats are supported. How do you know which one(s) to choose? What if the choice is not yours? If you are offering the data streaming service as a platform to your internal customers, what kind of guidance should you offer them when choosing a data format? Is everything which is possible advisable? What implications does mixing data formats have? How do different formats differ from each other in terms of limitations, evolution and linking options? How does this affect consumers? In this talk I will share questions, answers and tradeoffs as identified while working with customers who were implementing Confluent Schema Registry.

3️⃣ "Iced Kaf-fee: Chilling Kafka Data into Iceberg Tables" by Danica Fine, Sr Manager, OSS Developer Relations at Snowflake.
Have piping-hot, real-time data in Apache Kafka® but want to chill it down into Apache Iceberg™ tables? Let’s see how we can craft the perfect cup of “Iced Kaf-fee” for you and your needs!

We’ll start by grinding through the motivation for moving data from Kafka topics into Iceberg tables, exploring the benefits that doing so has to offer your analytics workflows. From there, we’ll open up the menu of options available to cool down your streams, including Apache Flink®, Apache Spark™, and Kafka Connect. Each brewing method has its own recipe, so we’ll compare their pros and cons, walk through use cases for each, and highlight when you might prefer a strong Spark roast over a smooth Flink blend—or maybe a Connect cold brew. Plus, we’ll share a sneak peek at future innovations percolating in the community to make sinking your Kafka data into Iceberg even easier.

By the end of the session, you’ll have everything you need to whip up the perfect pipeline and serve up your “Iced Kaf-fee” with confidence.

📍Location
HCS Company: Anthony Fokkerweg 61, Amsterdam | https://maps.app.goo.gl/LPMZKBzB7MutGrZb6
The HCS Company office is easily accessible by both car and public transport. You can park your car on their premises; ample parking is beyond the barrier. If you come by public transport, you can get off at the Henk Sneevlietweg metro station; from there, it is a 10-minute walk.