Apache Kafkaยฎ๏ธ ๋น„์šฉ ์ ˆ๊ฐ ๋ฐฉ๋ฒ• ๋ฐ ์ตœ์ ์˜ ๋น„์šฉ ์„ค๊ณ„ ์•ˆ๋‚ด ์›จ๋น„๋‚˜ | ์ž์„ธํžˆ ์•Œ์•„๋ณด๋ ค๋ฉด ์ง€๊ธˆ ๋“ฑ๋กํ•˜์„ธ์š”

Online Talk

How Walmart Made Real-Time Inventory & Replenishment a Reality

์ง€๊ธˆ ์‹œ์ฒญํ•˜๊ธฐ

Available On-demand

The game has changed for retailers. Customers wonโ€™t wait for exceptional service. In fact, they expect order fulfillment in real time, whether through e-commerce apps, websites, or in-store.

In order to meet these high expectations and create a seamless (and often personalized) experience, retailers need access to real-time data from multiple sources across their organization. Thatโ€™s where Apache Kafkaยฎ and real-time data streaming come in.

Tune in to hear from Suman Pattnaik, Head of Merchandising Engineering- Dollar General (Former Director of Engineering- Walmart), about what it took to build two applications that play a critical role in customer satisfaction. Youโ€™ll learn about:

  • Walmartโ€™s real-time inventory system:
    • How Apache Kafka is used to power their entire core data architecture, ingesting ~500M events and processing 1M online transactions daily for a seamless single source of truth across all their distributed systems
  • Walmartโ€™s real-time replenishment system:
    • It processes tens of billions of messages from ~100M SKUs in less than three hours per day. It also uses an array of processors with throughputs of more than 85GB messages/min to generate an order plan for the entire network of Walmart stores with pinpoint accuracy.

Register now and come away with best practices for building real-time use cases in retail.