For any operations-intensive business, accurate forecasting is essential but is made more difficult by hard-to-measure factors that can disrupt the normal flow of business.
Category Archives: engineering
DoorDash becomes a sponsor of Hack the Planet Scholarship
TLDR: DoorDash is very excited to be sponsoring two additional engineers for the Hack the Planet Scholarship, which actively contributes to growing tech diversity within the distributed systems tech domain.
Improving Fault Tolerance with RPC Fallbacks in DoorDash’s Microservices
Failures in a large, complex microservice architecture are inevitable, so built-in fault tolerance — retries, replication, and fallbacks — are a critical part of preventing system-wide outages and a negative user experience.
Using Back-Door Adjustment Causal Analysis to Measure Pre-Post Effects
When A/B testing is not recommended because of regulatory requirements or technical limitations to setting up a controlled experiment, we can still quickly implement a new feature and measure its effects in a data-driven way.
How the SwiftUI View Lifecycle and Identity work
While UIKit has been the go-to framework for iOS engineers to build user interfaces in their applications over the years, SwiftUI has been steadily gaining traction as an alternative framework that rectifies many downsides of UIKit.
Meet Dash-AB — The Statistics Engine of Experimentation at DoorDash
For any data-driven company, it’s key that every change is tested by experiments to ensure that it has a positive measurable impact on the key performance metrics.
Enabling Faster Financial Partnership Integrations Using Cadence
Financial partnerships are tricky to manage which is why DoorDash needed the right technology stack to be able to quickly onboard new Dashpass partners.
DoorDash’s May 12th Outage
On May 12th DoorDash had a system-wide outage that lasted three and a half hours.
3 Changes to Expand DoorDash’s Product Search Beyond Delivery
Focusing on delivery allowed DoorDash to build a food search engine, but expanding beyond food with more SKUs and merchants requires a substantial upgrade.
How We Applied Client-Side Caching to Improve Feature Store Performance by 70%
At DoorDash, we make millions of predictions every second to power machine learning applications to enhance our search, recommendation, logistics, and fraud areas, and scaling these complex systems along with our feature store is continually a challenge.