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Backend

Backend

Improving Scalability, Reliability, and Efficiency of a Python Service with Gevent

When trying to scale a distributed system a common obstacle is not that there aren’t enough resources available, it’s that they are not being used efficiently. At DoorDash we found a similar opportunity when working to scale our point-of-sale system (POS). We were experiencing outages because our POS system could not scale to meet peak ...

Simone Restelli Devavrath Subramanyam
Backend

Building a gRPC Client Standard with Open Source to Boost Reliability and Velocity

In a microservice architecture, cross-service communication happens under a set of global rules that are hard to effectively enforce across all services without standardizing client-service communication. Relying on individual service client implementations to adhere to these rules means a lot of additional repeated work on individual teams, which has a negative impact on developer velocity. ...

Haitham Gabr
Backend

Platform Optimization Through Better API Design

As DoorDash migrated to a microservices architecture, we found an opportunity to redesign our APIs, resulting in better overall client performance.

Maggie Fang
Backend

Tailoring Gradle and Docker for Rapid Local Development

As technology companies race to release their next features, any delay in productivity can be extremely detrimental, making an efficient development build process essential.  Companies that use Kubernetes and Docker in production environments most likely use Docker for local development. Docker-compose, a tool for defining and running multi-container Docker applications, ensures consistent local development processes, ...

Marvin Flores
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.

WayneCunningham
Backend

Minimizing Risk for API Extraction in a Major Migration Project

DoorDash engineering describes its three step process for safely migrating business logic as APIs.

David Chen
Backend

Building an Image Upload Endpoint in a gRPC and Kotlin Stack

Learn how we automated image uploads in gRPC and Kotlin

Abdalla Salia
Backend

Using Display Modules to Enable Rapid Experimentation on DoorDash’s Homepage

Learn how a flexible UI that utilized display modules enabled rapid experimentation

Danial Asif
Backend Data

Integrating a Search Ranking Model into a Prediction Service

Learn how moving ML models to a prediction service can free up RAM and CPU for more scalable development

Sarah Chen
Backend

Eliminating Task Processing Outages by Replacing RabbitMQ with Apache Kafka Without Downtime

Learn how we utilized a custom Kafka solution to reduce outages and enable horizontal scalability for task processing

Saba Khalilnaji Ashwin Kachhara
Backend

Building Reliable Workflows: Cadence as a Fallback for Event-Driven Processing

Reengineering our event-driven delivery service for DoorDash Drive into Kotlin, we added the open source Cadence as a fallback for retries.

Alan Lin
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

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