Tech Blog

Billions of queries require new, smarter alerting features.

A case study demonstrates how eBay's Notification Engineering team optimizes a streaming system in a microservice architecture to support high-throughput broadcast notifications.

Buyers reveal a whole range of behaviors and interests when they browse our pages, so we decided to incorporate these additional purchase intent signals into our machine learning model to improve the relevance of our recommended items.

The new open feature flagging standard enables companies to deliver cloud-native applications more effectively.

For our annual ML competition, we challenged university students to predict how many days a carrier takes to deliver packages.

Under the new machine learning model, buyers are recommended items that are more aligned to their shopping interests on eBay.

A step-by-step guide on how to build a state-of-the-art recommender system in an industrial setting.

A look at how our eBay technologists created an automatic testing solution for batch applications.

At eBay, we’ve focused on improving our staging environment to increase our software delivery speed, which ultimately allows us to launch features faster to our customers. Over the last several months, we’ve raised the quality of our staging data by establishing a dedicated and scalable data migration system.