Why Your .NET Rate Limiter Fails at Scale (And How to Fix It)

Summary

The transcript discusses the complexities of building distributed systems, specifically focusing on rate limiting as a critical challenge when scaling multiple API instances. The key topics include protecting APIs from potential abuse, ensuring fair usage across users, and implementing rate limits based on subscription tiers or service credits. The practical takeaway emphasizes that as systems scale, traditional in-memory rate limiting approaches become insufficient, and distributed solutions like Redis become essential for maintaining consistent rate limiting across multiple service instances.