Bangalore Streams In-Person meetup - March 2025

Hello Bengaluru

Platformatory is excited to host a special edition of the Bengaluru Streams meetup on March 22, right after Current Bengaluru. Join us for an evening of exciting talks from Confluent, StarTree, RisingWave and more. This is a great opportunity to talk to, meet and learn from some of the innovators in the data infra space.

📅 When: March 22 2025 10:00am - 02:30pm
📌Where: Smarsh Inc, Bengaluru (4th floor)

Thanks to Confluent and StarTree for sponsoring the meetup!

🕒 Schedule :

9:00 am - 10:00 am: Welcome & registrations
10:00 am - 10:40 am: Creating a realtime data platform with Pinot, Kafka, and Debezium
10:50 am - 11:30 am: Building agent systems with Apache Kafka and Apache Flink
11:30 am - 11:50 am: Networking break
11:50 pm - 12:10 pm: Fun with Flink Stateful Functions
12:15 pm - 1:00 pm: Panel on Streaming databases
1:00 pm - 2:30 pm: Lunch & Networking

🗣Talks:
Building agent systems with Apache Kafka and Apache Flink
Speaker: Olena Kutsenko, Staff Developer Advocate, Confluent
About the talk: AI-powered agent systems are becoming essential for automation, personalization, and real-time decision-making. But how do we ensure that these agents can process information continuously, maintain context, and provide intelligent responses at scale?
This talk explores how Apache Kafka and Apache Flink can be used to build dynamic real-time agent systems. We'll start with the basics of agent-based systems - how they work, how they communicate, and how they retrieve and generate relevant knowledge using Retrieval-Augmented Generation. Then, we'll look into real-time streaming architectures, showing how Kafka handles message passing between agents and Flink processes events to track context and enable intelligent responses.
By the end of this session, you'll have a clear roadmap for designing AI-driven agent systems that are context-aware, efficient and work with a continuous stream of data.
Whether you're working on chatbots, monitoring systems, or intelligent automation, this talk will provide practical insights into bridging streaming data with generative AI to power the next generation of autonomous agents. Perfect for beginners and experts alike, this session offers valuable insights for all skill levels.

Creating a realtime data platform with Pinot, Kafka, and Debezium
Speaker: Fasih Khatib, Developer Advocate, StarTree
About the talk: If you had to move data from an OLTP database to an OLAP database, how would you do it?
In this talk Fasih walks you through creating a realtime data platform using Postgres, Kafka, Debezium and Pinot. Join us as we walk you through the architecture and implementation for the system. You’ll see how to create a table in Postgres, read the change data into Kafka using Debezium, and finally ingest it into Pinot for realtime analytics.

Panel Discussion on Streaming Databases
Speakers: Rayees Pasha, CPO at RisingWave & Ralph Debusmann, Author of O’Reilly book on Streaming Databases & Matthias Sax, Staff Engineer at Confluent & Apache Kafka PMC member
About the talk: Do we need streaming databases at all? Let's discuss the convergence of streaming and databases, and of course the (over-?)hyped Iceberg/Blob Storage and what it means about the future of Kafka.

Fun with Flink Stateful Functions
Speaker: Avinash Upadhyaya, Platformatory
About the talk: Modern architectures often use microservices to separate business logic. This makes it easier for developers to deploy, scale, and manage services independently. Event-driven architecture has become the go-to choice for backend development. It helps create scalable and reliable applications that are simpler to build and maintain. However, the downside is that it can make the developer experience quite challenging, especially with stateful execution.
Apache Flink’s Stateful Functions make it easier to build reliable, event-driven applications by giving you tools to manage state and ensure your workflows run smoothly. Stateful Functions was designed to apply the ideas of stream processing to event-driven applications. In this setup, Flink takes the role of an “event-driven database” that handles dynamic and arbitrary messaging between functions and state consistency in a fault tolerant way, while the functions that build up the application logic exist as separate stateless (micro-)services invoked by Flink.