Best of gRPC — January 2026

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   Video

   Philipp Lackner·18w

   The Genius System Behind the Uber App’s Real-Time Map

   Uber's real-time map system evolved from inefficient polling (80% of requests) to a push-based architecture called Ramen, built on gRPC. The system uses three components: Fireball (decides when to push), API Gateway (enriches data), and Ramen server (delivers updates). To handle millions of location updates, Uber developed H3, an open-source hexagonal spatial indexing system that reduces time complexity from O(N) to O(K²) + O(M) by dividing the world into hexagons instead of calculating distances to all drivers. Edge servers minimize latency by serving users from geographically close locations, while dead reckoning and Kalman filters smooth location updates during network instability.

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   9
2. 2
   Article

   Arcjet·17w

   Arcjet's tech stack

   Arcjet's architecture combines WebAssembly modules written in Rust embedded in SDKs, a Go-based gRPC decision API for low-latency security decisions, and a region-aware data pipeline using AWS SNS, SQS, and ClickHouse. The stack includes TypeScript/Python SDKs, Valkey for rate limiting, DynamoDB for dynamic rules, and runs on AWS EKS with isolated regional deployments. Development uses devcontainers with Docker Compose and LocalStack for AWS emulation, while security is layered with automated scanning tools and dependency management.

   45

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