Posttransaction processing using Apache Pulsar at Narvar

Davor Bonaci (Kaskada), Anand Madhavan (Narvar)

2:05pm–2:45pm Thursday, September 26, 2019

Location: 1A 15/16

Data Engineering and Architecture, Streaming and IoT

Secondary topics: Data Integration and Data Processing, Data, Analytics, and AI Architecture, Retail and e-commerce, Streaming and IoT

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Who is this presentation for?

Data engineers, managers, and data platform engineers

Level

Beginner

Description

Narvar enables leading retailers to deliver postpurchase experiences that retain, engage, and delight their customers from cart to doorstep and beyond. The Narvar platform allows retailers to engage and communicate with customers, driving customer satisfaction and long-term customer loyalty.

Narvar originally used a large collection of point technologies such as AWS Kinesis, Lambda, and Apache Kafka to satisfy its requirements for pub/sub messaging, message queuing, logging, and processing. After evaluating various technology options to help simplify and consolidate its data processing, Narvar selected Apache Pulsar for its unified messaging and queuing model, ability to process data using lightweight functions, and guaranteed data durability.

Karthik Ramasamy and Anand Madhavan provide an overview of the Narvar use-case patterns and how it implemented those patterns using Apache Pulsar.

Prerequisite knowledge

A basic knowledge of data processing (useful but not required)

What you'll learn

Discover how retail use cases are elegantly mapped into Apache Pulsar and the production experiences

Davor Bonaci

Kaskada

Davor Bio

Website

Anand Madhavan

Narvar

Anand Madhavan is the vice president of engineering at Narvar. Previously, he was head of engineering for the Discover product at Snapchat and director of engineering at Twitter, where we worked on building out the ad serving system for Twitter Ads. He earned an MS in computer science from Stanford University.