IN PERSON Apache Kafka® Workshop Chennai - April 2025

Hello everyone! Join us for an IN PERSON Apache Kafka® workshop on April 19th from 9:30 am.

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Form: https://forms.office.com/r/z9Get8YSJ3

📍 Venue:
Saama Technologies, OLYMPIA TECH PARK, Chennai

Agenda:

09:30 AM - 09:45 AM | Registration and Welcome
09:45 AM - 10:45 AM | Kafka in Practice : Practical Applications & Insights
10:45 AM - 11:00 AM | Break & Networking
11:00 AM - 01:00 PM | Kafka Workshop
01:00PM - 01:30 PM | Lunch & Networking

Session 01:

💡 Speaker :
Dinesh Retnaswamy, Saama Technologies

Talk:
Kafka in Practice : Practical Applications & Insights

Abstract:
Modern clinical trials require data infrastructure that is not only performant but also scalable, fault-tolerant, and adaptable. Apache Kafka excels as a core component in building such systems. This technical meetup dives into practical patterns and use cases for applying Kafka within the clinical trial data lifecycle.

Session 02:
💡 Speaker :
Jegan Nagarajan, Senior Customer Success Architect, Confluent
Shivsundar R, Software Engineer, Confluent

Workshop:
Kafka Workshop Meetup

Note: Internet will not be provided. Please bring your own

Abstract:
In this hands-on Kafka meetup, we will walk through the installation and setup of Apache Kafka using Docker, making it quick and reproducible for participants. Once the environment is up and running:
1. Kafka Setup (Dockerized)

• Step-by-step guide to install and run Kafka in a Docker environment. https://developer.confluent.io/confluent-tutorials/kafka-on-docker/
• Verify Kafka broker and Zookeeper status.

2. Producer & Consumer Demo

• Showcase a sample Kafka producer and consumer to illustrate message flow.
• Real-time message exchange to demonstrate Kafka basics.

3. Producer Config Deep-Dive

• Discuss critical Kafka producer configurations like acks, compression.type, linger.ms, batch.size, retries, and more.
• Run performance benchmarking using the script:

kafka-producer-perf-test.sh
to evaluate throughput and latency across different settings.

4. Consumer Config Deep-Dive

• Show how tuning these values impacts data consumption behavior and performance.
• Cover key consumer configs such as auto.offset.reset, enable.auto.commit, max.poll.records, and fetch.min.bytes

[Optional, Time Permitting] Flink Integration

• Quick setup of Apache Flink.
• Demonstrate consuming Kafka data into Flink for stream processing use cases.

sample:acks=all: Ensure all in-sync replicas acknowledge the message to achieve data durability.

• enable.idempotence=true: Enable idempotence to prevent duplicate messages.
• retries: Set retries to ensure messages are retried upon transient errors.
• max.in.flight.requests.per.connection: Check the value to balance retry attempts and message order.
• linger.ms: Ensure efficient batching of messages.
• batch.size: Optimize the batch size for better throughput.
• delivery.timeout.ms: Configure appropriately to ensure messages do not timeout before being delivered.
• compression.type: Use compression to reduce the size of the message payloads and improve throughput.

#### Consumer Configuration Checks:

• group.id: Ensure the group ID is set correctly for proper load balancing between consumers.
• enable.auto.commit: Decide on auto-commit or manual commit based on requirements.
• max.poll.records: Adjust the number of messages fetched from the broker in one poll.
• auto.offset.reset: Set to "earliest" or "latest" based on message consumption needs.
• fetch.min.bytes: Configure the minimum amount of data to fetch.

***
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.

***
If you would like to speak or host our next event please let us know! community@confluent.io