In this post, we will show how we write gRPC endpoints using the functional-core, imperative-shell pattern in Kotlin
Google maps is a leading mapping platform but some of their features are not ideal for delivery and require augmentation. Learn what we did
Learn how DoorDash scaled our campaign based fan out problem by evaluating S2, H3, Elastic search, and Geohash.
Learn how DoorDash used Signadot and multi tenancy to create a fast feedback loop for our Kubernetes port forward deployment strategy
Failures are inevitable, so building fault tolerance through retries, replication, and fallbacks is critical to ensuring a positive user experience
Read the technology review we conducted to find the right task management technology for Dashpass onboarding. Learn why we chose Cadence
Focusing on delivery allowed DoorDash to build a food search engine, but expanding beyond food with more SKUs and merchants requires a substantial upgrade.
Learn about which caching libraries we considered, the analysis of our system and how we were able to use experiments to validate our approach.
When failure is inevitable, building fault tolerance with fault injection testing ensures that failures do not bring the platform down with them
Is functional programming a good paradigm to use for Kotlin development? Read this guide for direct coding comparisons between FP and OOP
Learn how we used multi-tenancy to improve production testing standards, speed and effectiveness in this new technical blog post
Learn how we unified our chat across all our platforms by leveraging common UI components and an extensible backend and automated it with NLP
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