Melbourne Apache Kafka® Meetup by Confluent

Hello everyone! Join us for an Apache Kafka® x Apache Flink® meetup on June 17th from 5:30pm, hosted by Ippon in Melbourne!

The address, agenda, and speaker information can be found below. See you there!

📍Venue:
Ippon Australia Collab Hub
Level 8, 607 Bourke Street
Melbourne VIC 3000

IMPORTANT:
Please note that for security purposes, all attendees are required to sign in at the lobby to get into the building.

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🗓 Agenda:

• 5:30pm: Doors open
• 5:30pm - 6:00pm: Pizza, Drinks, and Networking
• 6:00pm - 6:30pm: Paras Sitoula, Technical Lead, Tabcorp
• 6:30pm - 7:00pm: Bhargav Kosaraju, Practice Director- Data and Streaming, Synapsewerx
• 7:00pm - 7:30pm: Additional Q&A & Networking

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💡 Speaker:
Paras Sitoula, Technical Lead, Tabcorp

Bio:
Paras is a seasoned software/date engineer with significant experience in developing and optimizing realtime scalable systems. At Tabcorp, Paras leads a high-performing team, developing and optimizing real-time transaction monitoring systems utilizing technologies like Apache Kafka and Neo4j. With a robust background in both real-time and batch data processing, Paras has extensive experience across various platforms and tools, including AWS, Databricks, and Spark, which he leverages to deliver high-performance data solutions.

Talk:
Follow the Bets: Event-Driven Fraud Detection with Kafka, Flink, and Graphs

Abstract:
The talk will dive into how event-driven architecture, powered by Kafka and Apache Flink, enables scalable, real-time monitoring of transactional data to detect suspicious betting patterns

Fraud isn’t always obvious in a single event—it’s revealed through patterns of behavior. That’s where Neo4j comes in.
The presentation will showcase some usecases around how these tools can be used together for real-time proactive fraud monitoring.

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💡 Speaker:
Bhargav Kosaraju, Practice Director- Data and Streaming, Synapsewerx

Bio:
Bhargav possess significant experience in distributed technologies, including Spark, Kafka, Flink, Hadoop, and Kubernetes, and he is skilled in developing tools and systems applications across Big Data and Data Warehouse platforms. His professional background features a strong emphasis on Scala and Java programming, especially in developing Apache Spark applications integrated with traditional Big Data tools. Bhargav has implemented Spark on Kubernetes for large batch processing, built cloud data warehouses using various technologies, and configured and optimised Hadoop and Kafka Clusters across the APAC region. His expertise extends to distributed computing, infrastructure automation, CI/CD pipeline automation, and security in the distributed computing space for both batch and streaming use cases.

Talk:
Mastering Real-Time Data with Kafka and Flink with AI

Abstract:
In this session, we will explore how Kafka and Flink can seamlessly capture and manage massive streams of data in real time. Learn how Kafka's robust architecture enables high-throughput, scalable, and reliable data pipelines, forming the backbone of your data-in-motion ecosystem.

We'll then transition to the power of Apache Flink and its integration patterns with LLMs. Witness firsthand how Flink's stateful computations enable complex event processing and real-time analytics that are crucial for timely decision-making.
Our session includes a live demo where we integrate Kafka and Flink to build an end-to-end streaming application. We'll simulate a real-world scenario, showcasing how to build an AI-backed streaming application.

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DISCLAIMER
BY ATTENDING THIS EVENT IN PERSON, you acknowledge that risk includes possible exposure to and illness from infectious diseases including COVID-19, and accept responsibility for this, if it occurs.
NOTE: We are unable to cater for any attendees under the age of 18.