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.
A very short Chapter 2 is about how to make rough estimates to start from the most important parts when designing the software.
Some concepts that EVERY software developer should know:
“Power of two” Standard latency numbers! How fast is memory, how slow is disk, etc… Availability numbers What are key metrics you should think about These concepts and numbers are disclosed in chapter two of the book:
Earlier the book club of our company has studied excellent book:
Martin Kleppmann - Designing Data-Intensive Applications
This is the best book I have read about building complex scalable software systems. 💪
As usually I prepared an overview and mind-map.
Chapter 8 discovers non-database related problems of distributed systems. DEV teams should consider them when designing distributed software.
Faults and Partial Failures. The need to build a reliable system from unreliable components.
Earlier the book club of our company has studied excellent book:
Martin Kleppmann - Designing Data-Intensive Applications
This is the best book I have read about building complex scalable software systems. 💪
As usually I prepared an overview and mind-map.
Chapter 5:
Intro. How to scale apps. Replicating and partitioning. Three algos of replicating Single-leader Replication Leaders and Followers Sync and async replication Adding new Followers Handling node outages Technical implementations and all potential problems Multi-Leader Replication Use-cases when it is good Handling write conflicts Three topologies and potential problems Leaderless Replication Writing to the database when a node is down Quorums and problems with them Detecting concurrent writes and how to resolve them Download full mind map (PDF)
Earlier this year the book club of our company has studied excellent book:
Martin Kleppmann - Designing Data-Intensive Applications
This is the best book I have read about building complex scalable software systems. 💪
As usually (to better learn) I prepared an overview and mind-map.
Chapter 1:
Building blocks of the apps What is Reliability, Scalability and Maintainability. Examples and definitions. Faults and Failures Performance, Load, Latency and Response Time Operability, Simplicity, Evolvability Why you should randomly kill your servers 😅 How Twitter delivers 12,000 tweets per second to 300,000 readers per second.
