In modern computer systems, rate limiting is an essential technique that helps prevent system overloads and ensures stable service, especially in high-traffic situations. For example, during a flash sale on an e-commerce website, rate limiting can prevent too many users from accessing the system at once and causing it to crash. In API services, rate limiting ensures that the service remains stable by preventing any single user from overloading the system and disrupting access for others. Additionally, rate limiting algorithms are common topics in technical interviews, testing a candidate’s understanding of traffic management and system performance optimization.
In this video, we will explore five common rate limiting algorithms: the Leaky Bucket Algorithm, the Token Bucket Algorithm, the Fixed Window Counter Algorithm, the Sliding Window Log Algorithm, and the Sliding Window Counter Algorithm. By learning these algorithms, you’ll gain insights into how to choose the right rate limiting strategy based on your system’s needs, enabling efficient traffic management.
00:00 - Intro
01:11 - Leaky Bucket Algorithm
03:53 - Token Bucket Algorithm
07:07 - Fixed Window Counter Algorithm
11:15 - Sliding Window Log Algorithm
14:00 - Sliding Window Counter Algorithm
16:40 - Outro
Hashtags:
#systemdesign #bytevigor #ratelimiting #api
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