Episode
How Doordash Rebuilt Delivery Logistics for Peak Demand
- Published
- Jun 23, 2026
- Duration seconds
- 482
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Summary
This episode of The CTO Podcast dives into how Doordash rebuilt its delivery logistics platform to handle peak demand during the COVID-19 pandemic and beyond. Lucas and Luna explore the specific architecture decisions behind Doordash's real-time dispatching system, which processes millions of orders per day with sub-second latency. They discuss the shift from a monolithic Rails backend to a microservices-based system using Kotlin and gRPC, the use of geospatial indexing with PostGIS for proximity search, and the implementation of a custom time-series database for demand forecasting. The conversation also covers how Doordash handles 'dark store' inventory synchronization and the trade-offs between centralized and decentralized routing algorithms. Listeners will learn one concrete insight: how Doordash uses a technique called 'batch optimization with rolling horizons' to balance driver utilization and customer wait times. Perfect for CTOs, engineering leaders, and anyone interested in the operational challenges of real-time logistics at scale. #Doordash #DeliveryLogistics #Microservices #Kotlin #PostGIS #RealTimeDispatching #DemandForecasting #TimeSeriesDatabase #BatchOptimization #RollingHorizons #DarkStore #gRPC #EngineeringLeadership #CTO #BusinessAndTechnology #FexingoBusiness #BusinessPodcast #TheCTOPodcast Keep every episode free: buymeacoffee.com/fexingo