Redis

Every popular software should have a Rate Limiter. It prevents DDOS attack, reduces cost and prevents servers from being overloaded.

There are some tricky questions to be considered during implementation of Rate Limiter:

• Where to put Rate Limiter: client-side, server-side, gateway?
• Algorithms for rate limiting. There are many algorithms with pros and cons: Token bucket, Leaking bucket, Fixed window counter, Sliding window log, Sliding window counter. Your business needs will define the right algorithm.
• How are rate limiting rules created?
• Where are the rules stored?
• How to handle requests that are rate limited?

These questions are disclosed in a very interesting Chapter 4 of the book:

🚆✈️🚌🛳 + Math + Highload + Machine Learning…

Two and a half years ago we’ve got a request from the Travel-business IT company, whose B2C IT solution is the basis for one of the world’s largest travel companies that serves over 1 billion passengers every year.

What did they want to achieve?

They wanted to quickly design and implement an “internal startup” - an innovative B2B/B2C solution for the travel industry.