Apache Kafka® Meetup Mumbai- Nov 2025

Hello everyone! Join us for an IN PERSON Apache Kafka® meetup on Nov 8th from 11 am in Mumbai.

📍Venue:
006 Ground Floor, Lecture Hall Complex, Academic Section, Kanwal Rekhi Building, Institute of Technology, opp. Academic Section, IIT Area, Powai, Mumbai, Maharashtra 400076

IMPORTANT!!!
Please fill in the form here for venue entry purposes. A gate pass will be sent to your email which will be needed to enter the venue.

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Agenda:

• 11:00- 11:15: Welcome & Introduction
• 11:15- 12:00: Susmit Vengurlekar, Founding Team Member, AIDAX
• 12:00- 12:45: Rohit Singh, Solutions Engineer, Confluent
• 12:45- 13:45: Lunch

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💡 Speaker:
Susmit Vengurlekar, Founding Team Member, AIDAX

Talk:
Real-Time Click-Through Rate Analysis with Flink & Kafka

Abstract:
In the fast-moving world of digital advertising, real-time Click-Through Rate (CTR) computation is critical for campaign optimization.

This talk offers a hands-on, end-to-end walkthrough of building a robust stream processing pipeline using PyFlink, Kafka, and a Go-based data producer, all containerized with Docker.

We’ll start by grounding attendees in stream processing fundamentals — what streams and windows are, how event time differs from processing time, and how watermarks help Flink handle out-of-order events. We’ll also explore allowed lateness (late firing) and discuss what happens when no watermark arrives.

From there, we’ll dive into the PyFlink job that correlates impressions and clicks using Interval Joins and Tumbling Windows, calculates CTR in real time, and ensures exactly-once consistency through checkpointing.
The session concludes with a live demo showing the entire pipeline in action — from Kafka ingestion to CTR computation and visualization.

Github Repo that will be used for live demo - https://github.com/susmitpy/stream_analytics_adtech_ctr

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💡 Speaker:
Rohit Singh, Solutions Engineer, Confluent

Talk:
From Streams to Tables: Exploring Tableflow in Confluent Cloud

Abstract:
Learn how Confluent Cloud’s Tableflow automatically turns Kafka topics into analytics-ready tables — no ETL or stream processing needed. We’ll explore how Tableflow uses Apache Iceberg under the hood to deliver fresh, queryable data while managing schema evolution and compaction seamlessly.

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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.
As the classroom is a mask-on setting, please be reminded that masks should still be worn at all times unless actively eating or drinking
NOTE: We are unable to cater for any attendees under the age of 18.
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If you would like to speak or host our next event please let us know! community@confluent.io