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General Machine Learning

Best Practices for Regression-free Machine Learning Model Migrations

Migrating functionalities from a legacy system to a new service is a fairly common endeavor, but moving machine learning (ML) models is much more challenging. Successful migrations ensure that the new service works as well or better than its legacy version. But the complexity of ML models makes regressions more likely to happen and harder ...

Ying Chi

Rebuilding our Pricing Framework for Better Auditability, Observability, and Price Integrity

Learn how we migrated our pricing logic to microservices

Irene Lee Menghan Li Yijie Xiao Yujue Wang Zhengli Sun

Using java.time to Increase Code Readability and Reduce Errors

Given the importance of time in our services and the need to scale, java.time works much better than primitives.

Kevin Huang

Using a Decision Engine to Power a First Class Customer Experience

DoorDash's decision engine empowers customer service agents to deliver consistent, effective solutions for customer issues.

Preetha Vijaya Saraswathi Derrick Hu Kevin Nguyen Alex Liu
Backend Culture Data General Machine Learning Mobile Web

2020 Hindsight: Building Reliability and Innovating at DoorDash

DoorDash recaps a number of its engineering highlights from 2020, including its microservices architecture, data platform, and new frontend development.


Future-proofing: How DoorDash Transitioned from a Code Monolith to a Microservice Architecture

In 2019, DoorDash’s engineering organization initiated a process to completely reengineer the platform on which our delivery logistics business is based. This article represents the first in a series on the DoorDash Engineering Blog recounting how we approached this process and the challenges we faced. In traditional web application development, engineers write code, compile it, ...

Cesare Celozzi

Hello Seattle: DoorDash Expands its Engineering Footprint to the Pacific Northwest

DoorDash opens a new tech office in Seattle to support its Drive and DashMart business lines.

David Azose
General Web

Things to Keep in Mind When Integrating a Map Feature to a Web App

Lessons for developing a fast, flexible, and scalable map feature on web

Ying-Chun Wang

Four Challenges When Launching a Product Partnership

From a product engineering perspective, external partnerships can be tricky. Here are four best practices to follow.

Manori Thakur

Scaling DoorDash’s Geospatial Innovation with a Location-Based Delivery Simulator

Learn how we built a discrete event simulator for location data tests

Janice Lee
Backend General

Scaling Splunk Securely by Building a Custom Terraform Provider

Ensure your growing team can search, analyze, and visualize data securely by integrating Splunk with a custom built Terraform provider.

Esha Mallya
Culture General

How DoorDash is Scaling its Merchant Engineering Teams to Meet New Challenges

Learn how the DoorDash merchant team has scaled up to support merchants during the Covid-19 crisis

Varsha Dudani Yvette Martinez

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