In this article, we break down how Uber built this system, the challenges they faced, and the innovative solutions they developed.

ByteByteGo provides tutorials, articles, and resources for learning and mastering the Go programming language, covering topics such as syntax, concurrency, and best practices. Developers can learn about Go programming fundamentals, web development with Go, and building scalable applications using Go's powerful features and standard library.

ByteByteGo

Uber's CacheFront system serves over 150 million database reads per second using Redis while maintaining strong consistency. The system uses a three-layer architecture with Query Engine, Storage Engine, and integrated caching. Initial challenges included cache invalidation delays and stale data from conditional updates. Uber solved this by implementing soft deletes, monotonic timestamps, and synchronous write-path invalidation alongside asynchronous CDC (Flux) and TTL expiration. This triple-defense strategy achieves 99.9%+ cache hit rates with near-zero stale values, even with 24-hour TTLs.

How Uber Serves over 150 Million Reads per Second from Integrated Cache

How Coinbase made incident investigations 72% faster (Sponsored)

The Architecture: Three Layers Working Together

The Breakthrough: Making Conditional Updates Trackable

🚀 Learn AI in the New Year: Become an AI Engineer Cohort 3 Now Open