transcript
show notes
In this episode of Tech Interview Prep, we explore the essential role of a rate limiter in controlling network traffic and blocking excess API requests to prevent server overload and denial-of-service (DoS) attacks. Following our 4-step system design framework, we first establish the design scope—ensuring our limiter provides low latency, uses minimal memory, and remains highly fault-tolerant even if a cache server goes offline.We conduct a thorough comparison of popular algorithms, from the flexible Token Bucket used by Amazon to the Leaking Bucket employed by Shopify, discussing which methods best handle bursts of traffic. As we move into the technical deep dive, we'll explain how to implement high-speed counters using Redis and how to tackle advanced distributed challenges like race conditions and synchronization issues.Finally, we’ll discuss the "insider" details of communicating with clients through HTTP 429 status codes and essential response headers like X-Ratelimit-Remaining. Whether you are defending a global infrastructure or prepping for a senior-level interview, this episode provides the "solid knowledge" needed to master traffic management at scale