Real-time inventory and Real-time replenishment use-cases at Walmart, from a practitioner's perspective
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Meet Bill. Bill is a suburban dad who needs to prepare the family dinner ahead of his upcoming business trip. Oh, and he also needs a pair of chinos for said trip. And no, he doesn’t have time to run to the store.
Sound familiar?
Retailers have quickly come to realize that customer expectations have fundamentally changed. They expect their orders to be fulfilled in real-time, whether through an e-commerce app, a website, or in-store, and regardless of their fulfillment preference.
In order to deliver that seamless experience, retailers require real-time data streaming deployed across their organization. That’s where Apache Kafka® comes in.
During his tenure at Walmart, Suman Pattnaik, Director of Engineering at Walmart has built 2 of the applications that continue to play a critical role in customer satisfaction, using Kafka: real-time inventory and real-time replenishment systems:
- The real-time inventory system is at the heart of Walmart’s backend architecture ensuring stores never run out of items for which customers like Bill are looking. This happens through the ingestion of roughly 500 million events per day, and the processing of 1 million online transactions.
- The real-time replenishment system processes more than tens of billions of messages from close to 100 million SKUs in less than 3 hours per day. The system does so by leveraging an array of processors at high throughputs of more than 85GB messages/min to generate an order plan for the entire network of Walmart stores with pinpoint accuracy.
Join us on July 28th, to talk through what “a day in the life” of Suman looks like and best practices for building real-time use cases in retail.
Resources -
- Blog: Walmart’s Real-Time Inventory System Powered by Apache Kafka
- Blog: How Walmart Uses Apache Kafka for Real-time Replenishment at Scale
- Run pre-built ksqlDB recipes for real-time retail use-cases:
