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Data General

Building a Source of Truth for an Inventory with Disparate Data Sources

Learn how DoorDash crowdsources data from a variety of sources to help predict realtime inventory for our new connivence and grocery product

Anubhav Kushwaha
Machine Learning

Leveraging Causal Inference to Generate Accurate Forecasts

Learn how DoorDash captures hard to measure macroeconomic effects like IRS refunds and the effect of Daylight savings in these case studies

Chad Akkoyun Qiyun Pan

DoorDash becomes a sponsor of Hack the Planet Scholarship

DoorDash is very excited to be sponsoring two additional engineers for the Hack the Planet Scholarship and help grow tech diversity

Matt Ranney

Improving Fault Tolerance with RPC Fallbacks in DoorDash’s Microservices

Failures are inevitable, so building fault tolerance through retries, replication, and fallbacks is critical to ensuring a positive user experience

Leart Gjoni

Using Back-Door Adjustment Causal Analysis to Measure Pre-Post Effects

When A/B testing is not recommended we can still quickly implement a new feature and measure its effects in a data-driven way.

Sharon Cui

How the SwiftUI View Lifecycle and Identity work 

we compare UIKit’s event-driven approach to SwiftUI’s data-driven one, then dive into the SwiftUI view cycle, identity, and rendering process

Mike Zaslavskiy Anthony Williams Ryan Zhang
Data Machine Learning

Meet Dash-AB — The Statistics Engine of Experimentation at DoorDash

Learn how DoorDash was able to test uniformly according to established best practices and reuse complex statistical methods with Dash AB

Caixia Huang Yixin Tang

Enabling Faster Financial Partnership Integrations Using Cadence

Read the technology review we conducted to find the right task management technology for Dashpass onboarding. Learn why we chose Cadence

Wenhan Shen Lev Neiman

DoorDash’s May 12th Outage

Learn more about what triggered the DoorDash May12th outage

Ryan Sokol

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.

Sonic Wang Xiaochang Miao Yongshuang Wang
Backend Data

How We Applied Client-Side Caching to Improve Feature Store Performance by 70%

Learn about which caching libraries we considered, the analysis of our system and how we were able to use experiments to validate our approach.

Kornel Csernai

Using Fault Injection Testing to Improve DoorDash Reliability 

When failure is inevitable, building fault tolerance with fault injection testing ensures that failures do not bring the platform down with them

Christopher Meiklejohn

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