Delivering accurate delivery promises in real time at national scale

Wayfair is one of the world’s largest online destinations for furniture and home goods, offering more than 30 million items from over 20K suppliers. With millions of daily visitors and a dynamic fulfillment model, Wayfair’s competitive edge depends on providing fast, accurate delivery promises at the top of the customer funnel. Their supply chain tech organization spans transportation planning, supplier and carrier selection, and real-time customer delivery commitments.

Delivering accurate, real-time delivery promises

Wayfair needed to precompute and update delivery promises with high precision and low latency, despite operating a decentralized, drop-shipping-based supply chain.

• No room for shallow promises

  Each promise must consider supplier, carrier, capacity, inventory, and cutoff times before the customer clicks “buy.”

• Dropshipping model demands highly dynamic fulfillment decisions

  Wayfair utilizes a dynamic supply chain, leveraging fulfillment from both dropship suppliers and their own CastleGate network. As a result, accurate fulfillment paths must be computed ahead of time with full supply chain context to provide customer promises that will remain consistent throughout the customer’s order journey.

• Nationwide permutations create large complexity

  Delivery routes vary by item, supplier location, customer ZIP code, carrier, cutoff times, and transportation capacity. The system must evaluate hundreds of millions of origin-to-destination permutations across hundreds of millions of product configurations, resulting in tens of millions of fulfillment plans calculated per second during peak system load. Each plan is working out the optimal supplier facility, the optimal carrier, the optimal route, and the estimated delivery date for the product.

• Every disruption changes the game

  A single late truck, broken warehouse conveyor, or carrier outage can change hundreds of delivery options. The system must react within minutes to prevent false promises and customer disappointment.

• Real-time recalculations required on every event

  The architecture streams updates from across the network—new inventory, capacity shifts, disruptions—and identifies and recomputes only the affected promises at lightning speed.

• Customer-facing latency and data freshness matter

  With thousands of storefront API requests per second, delivery estimates must remain current, personalized, and responsive even as the underlying fulfillment reality changes in real time.

A stream-join architecture powered by Aerospike

Wayfair architected a real-time, precomputed promise engine using Aerospike, Kafka, and a microservices-based topology to deliver and update delivery guarantees with sub-second precision.

• Stream-join pipeline triggers recalculations

  Supply chain events—inventory updates, truck departures, carrier capacity changes—flow through a stream-join engine based on Kafka and Aerospike. Any change triggers selective recalculation of affected delivery promises.

• Aerospike powers the stream join

  As events stream in, the stream-join engine consults and updates Aerospike stores to build complete joined events. This demands stronger write performance than a typical caching workload.

• Precomputed fulfillment options at zone level

  Wayfair groups ZIP codes into dynamic delivery zones to reduce storage and compute costs, while ensuring accuracy. The zone system balances performance with granularity.

• Fast writes and reads prevent queue buildup

  With dozens of microservices working in parallel, any latency in Aerospike would cause queues to back up. Aerospike’s low-latency characteristics ensure smooth streaming and compute pipelines, avoiding the need of additional infrastructure overhead.

• Integrated with AI/ML-based promise prediction

  A machine learning model refines day-level delivery estimates. Aerospike enables sub-ms inference at scale by supporting the model’s real-time feature inputs.

Fast, reliable, and resilient delivery promise platform

Aerospike enables Wayfair’s supply chain systems to meet customer expectations at national scale, with high precision, real-time responsiveness, and operational resilience.

• Sub-millisecond latency for reads and writes

  Aerospike supports low-latency access to fulfillment and delivery promise data, even at peak scale and under heavy recomputation loads.

• Millions of requests served per second

  Wayfair handles thousands of delivery promise API calls per second and writes updates across a high-throughput pipeline involving dozens of microservices and Kafka topics.

• Catalog-wide recalculation in under one hour

  What once took two days can now be recomputed in less than 60 minutes, restoring data integrity faster after major outages or data errors.

• Delivery promise updates reflected in under 2 minutes

  When a truck closes or capacity shifts, the streaming architecture adopted by Wayfair allows them to update the delivery estimates shown on the website within minutes, preventing bad customer experiences.

• Unlocks reliable ML-based promise visibility

  With access times under 1 ms, Aerospike makes it possible to support complex ML delivery models with real-time inference at customer-facing scale.