EPISODE · Jun 4, 2026 · 9 MIN
How Uber Rebuilt Its Maps for 40 Million Daily Rides
from The CTO Podcast with Fexingo: Technical Leadership, Architecture, and Engineering Org · host Fexingo
Episode 31 of The CTO Podcast digs into how Uber's engineering team rebuilt its mapping and routing stack from scratch between 2019 and 2022 to handle over 40 million daily rides across 10,000 cities. We look at the specific reason they abandoned the old pipeline — vendor lock-in with Google Maps and a 40 percent cost increase in a single quarter — and how they designed a modular routing engine called Michelangelo Maps. Lucas explains the architecture: a C++ kernel for shortest-path that runs in under 50 milliseconds, a tile-based geocoding layer that reduced queries by 80 percent, and a machine learning model that predicts travel time to within 5 percent of actual trip duration. Luna pushes back on whether rebuilding a core piece of infrastructure that touches every single ride was worth the three-year timeline and the hundreds of engineers it took. We also touch on the trade-off between cost savings and reliability during the 2020 ridership drop. No hot takes — just the concrete decisions Uber's technical leadership made and the numbers that justified them. #Uber #Maps #RoutingEngine #MichelangeloMaps #CPlusPlus #Geocoding #MachineLearning #Architecture #Scaling #Infrastructure #CTOPodcast #Fexingo #BusinessAndTechnology #Engineering #TechLeadership #TravelTimePrediction #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo
What this episode covers
Episode 31 of The CTO Podcast digs into how Uber's engineering team rebuilt its mapping and routing stack from scratch between 2019 and 2022 to handle over 40 million daily rides across 10,000 cities. We look at the specific reason they abandoned the old pipeline — vendor lock-in with Google Maps and a 40 percent cost increase in a single quarter — and how they designed a modular routing engine called Michelangelo Maps. Lucas explains the architecture: a C++ kernel for shortest-path that runs in under 50 milliseconds, a tile-based geocoding layer that reduced queries by 80 percent, and a machine learning model that predicts travel time to within 5 percent of actual trip duration. Luna pushes back on whether rebuilding a core piece of infrastructure that touches every single ride was worth the three-year timeline and the hundreds of engineers it took. We also touch on the trade-off between cost savings and reliability during the 2020 ridership drop. No hot takes — just the concrete decisions Uber's technical leadership made and the numbers that justified them. #Uber #Maps #RoutingEngine #MichelangeloMaps #CPlusPlus #Geocoding #MachineLearning #Architecture #Scaling #Infrastructure #CTOPodcast #Fexingo #BusinessAndTechnology #Engineering #TechLeadership #TravelTimePrediction #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo
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How Uber Rebuilt Its Maps for 40 Million Daily Rides
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