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Data leaders today face a familiar challenge: complex pipelines, duplicated systems, and spiraling infrastructure costs. Standardizing around Kafka for real-time and Iceberg for large-scale analytics has gone some way towards addressing this but still requires separate stacks, leaving teams to stitch them together at high expense and risk. This talk will explore how Kafka and Iceberg together form a new foundation for data infrastructure. One that unifies streaming and analytics into a single, cost-efficient layer. By standardizing on these open technologies, organizations can reduce data duplication, simplify governance, and unlock both instant insights and long-term value from the same platform. You will come away with a clear understanding of why this convergence is reshaping the industry, how it lowers operational risk, and advantages it offers for building durable, future-proof data capabilities.

Data leaders today face a familiar challenge: complex pipelines, duplicated systems, and spiraling infrastructure costs. Standardizing around Kafka for real-time and Iceberg for large-scale analytics has gone some way towards addressing this but still requires separate stacks, leaving teams to stitch them together at high expense and risk.

This talk will explore how Kafka and Iceberg together form a new foundation for data infrastructure. One that unifies streaming and analytics into a single, cost-efficient layer. By standardizing on these open technologies, organizations can reduce data duplication, simplify governance, and unlock both instant insights and long-term value from the same platform.

You will come away with a clear understanding of why this convergence is reshaping the industry, how it lowers operational risk, and advantages it offers for building durable, future-proof data capabilities.

By leveraging tools like Jaeger and New Relic, we will uncover how to gain a full view of your microservices, even in the face of Apache Kafka's asynchronous nature. Join us for a live demo with a simple Java Spring-Boot app, where we will walk through both automatic and manual instrumentation to capture rich telemetry. We will also touch on infrastructure-level observability, pulling metrics and traces from Apache Kafka brokers and Apache Flink.

Abstract: TBA

***IMPORTANT: IF YOU RSVP here you don't need to also RSVP to London Kafka Group.***

Date and Time: 🗓️ Wednesday 7th May, ⏰ 18:00 - 21:00 PM 🕘

Venue: Snowflake, One Crown Place, London EC2A 4EF, U.K. 5th & 6th floors · London

Schedule:

• 6:00pm: Doors open
• 6:00pm – 6:30pm: Food/Drinks and networking
• 6:30pm - 7:00pm: Mastering real-time anomaly detection
• 7:00pm - 7:30pm: Iced Kaf-fee: Chilling Kafka Data into Iceberg Tables
• 7:30pm - 8:00pm: Observing all the things: Apache Kafka® and Apache Flink® with OpenTelemetry
• 8:30pm - 9:00pm: Additional Q&A and Networking

🎙️ \~Talk 1\~ Mastering real-time anomaly detection, Olena Kutsenko, Staff Developer Advocate, Confluent

Abstract: Detecting problems as they happen is essential in today's fast-moving world. This talk shows how to build a simple, powerful system for real-time anomaly detection in live data. We'll use Apache Kafka for streaming data, Apache Flink for processing it in real time, and various models to detect unusual patterns. Whether it's monitoring systems, or tracking IoT devices, this solution is flexible and reliable.

We'll start by exploring how Kafka helps collect and manage fast-moving data streams. Then, we'll demonstrate how Flink processes this data in real time and integrates anomaly detection models to uncover events as they occur. We'll dive into the details of how ARIMA and LSTM work, so even if you’re not into mathematics, you can still understand what happens behind the scenes!

This talk is ideal for anyone looking to monitor anomalies in real-time data streams.

🗣️ Speaker 1: Olena is a Staff Developer Advocate at Confluent and a recognized expert in data streaming and analytics. With two decades of experience in software engineering, she has built mission-critical applications, led high-performing teams, and driven large-scale technology adoption at industry leaders like Nokia, HERE Technologies, AWS, and Aiven.

🎙️ \~Talk 2\~ Iced Kaf-fee: Chilling Kafka Data into Iceberg Tables, Danica Fine, Lead Developer Advocate, Open Source at Snowflake

Abstract: 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 that are 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.

🗣️ Speaker 2: Danica began her career as a software engineer in financial services and pivoted to developer relations, where she focussed primarily on open source technologies under the Apache Software Foundation umbrella such as Apache Kafka and Apache Flink. She now leads the open source advocacy efforts at Snowflake, supporting Apache Iceberg and Apache Polaris (incubating).

🎙️ \~Talk 3\~ Observing all the things: Apache Kafka® and Apache Flink® with OpenTelemetry, Mehreen Tahir Software Engineer, New Relic

🗣️ Speaker 3: Mehreen specializes in machine learning, data science, and artificial intelligence. Mehreen is passionate about observability and the use of telemetry data to improve application performance. She actively contributes to developer communities and has a keen interest in edge analytics and serverless architecture.

*** DISCLAIMER NOTE: We are unable to cater for any attendees under the age of 18. If you would like to speak or host our next event please let us know! [email protected]

Join us for an a range of talks including Kafka to Apache Iceberg in London hosted by Snowflake!

Date and Time: 🗓️ Wednesday 7th May, ⏰ 18:00 - 21:00 PM 🕘 Venue: Snowflake, One Crown Place, London EC2A 4EF, U.K. 5th & 6th floors · London

Schedule:

• 6:00pm: Doors open
• 6:00pm – 6:30pm: Food/Drinks and networking
• 6:30pm - 7:00pm: Mastering real-time anomaly detection
• 7:00pm - 7:30pm: Iced Kaf-fee: Chilling Kafka Data into Iceberg Tables
• 7:30pm - 8:00pm: Observing all the things: Apache Kafka® and Apache Flink® with OpenTelemetry
• 8:30pm - 9:00pm: Additional Q&A and Networking

🎙️ \~Talk 1\~ Mastering real-time anomaly detection, Olena Kutsenko, Staff Developer Advocate, Confluent

Abstract: Detecting problems as they happen is essential in today's fast-moving world. This talk shows how to build a simple, powerful system for real-time anomaly detection in live data. We'll use Apache Kafka for streaming data, Apache Flink for processing it in real time, and various models to detect unusual patterns. Whether it's monitoring systems, or tracking IoT devices, this solution is flexible and reliable. We'll start by exploring how Kafka helps collect and manage fast-moving data streams. Then, we'll demonstrate how Flink processes this data in real time and integrates anomaly detection models to uncover events as they occur. We'll dive into the details of how ARIMA and LSTM work, so even if you’re not into mathematics, you can still understand what happens behind the scenes!

This talk is ideal for anyone looking to monitor anomalies in real-time data streams.

🗣️ Speaker 1: Olena is a Staff Developer Advocate at Confluent and a recognized expert in data streaming and analytics. With two decades of experience in software engineering, she has built mission-critical applications, led high-performing teams, and driven large-scale technology adoption at industry leaders like Nokia, HERE Technologies, AWS, and Aiven.

🎙️ \~Talk 2\~ Iced Kaf-fee: Chilling Kafka Data into Iceberg Tables, Danica Fine, Lead Developer Advocate, Open Source at Snowflake

Abstract: 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 that are 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.

🗣️ Speaker 2: Danica began her career as a software engineer in financial services and pivoted to developer relations, where she focussed primarily on open source technologies under the Apache Software Foundation umbrella such as Apache Kafka and Apache Flink. She now leads the open source advocacy efforts at Snowflake, supporting Apache Iceberg and Apache Polaris (incubating).

🎙️ \~Talk 3\~ Observing all the things: Apache Kafka® and Apache Flink® with OpenTelemetry, Mehreen Tahir Software Engineer, New Relic

🗣️ Speaker 3: Mehreen specializes in machine learning, data science, and artificial intelligence. Mehreen is passionate about observability and the use of telemetry data to improve application performance. She actively contributes to developer communities and has a keen interest in edge analytics and serverless architecture.