Making Your Service More Resilient to Traffic Spikes

Explore strategies for enhancing service resilience during traffic spikes in this 45-minute conference talk from Conf42 Golang 2024. Delve into the causes of server overload and learn about various rate-limiting algorithms, including fixed window counter, sliding window log, token bucket, and leaky bucket. Examine practical examples of server overload and token bucket algorithm implementation. Discover rate limiter packages and load shedding techniques to manage traffic bursts effectively. Compare results of different approaches and gain insights on building more robust services capable of handling unexpected traffic increases.

intro
preamble
ivan lemeshev
agenda
server overload
common causes of traffic bursts
example of server overload
rate limiting
common rate-limiting algorithms
fixed window counter algorithm
sliding window log algorithm
token bucket algorithm
leaky bucket algorithm
example of token bucket algorithm
comparison of results
rate limiter packages
lead shedding
example of loading shedding
comparison of results
to read: https://aws.amazon.com/builders-library/using-load-shedding-to-avoid-overload/
thank you