Database

System Design Interview - Chapter 1 - Scale from zero to millions of users

System Design Interview - Chapter 1 - Scale from zero to millions of users

Translations: RU
A great generic plan for scaling any app from zero to millions of users. Single server setup Selection and usage of database Vertical scaling vs horizontal scaling approaches. And why you should prefer horizontal Adding load balancer for horizontal scaling Adding database replication for horizontal scaling Adding cache Adding CDN Stateless vs Stateful architecture and using external state storage Adding extra Data Centers Adding Message queue Adding Logging, Metrics, and Automation Scaling database (sharding) and futher steps… All of these is carefully but briefly disclosed in the Chapter 1 of the book:
Clean Architecture - PART VI - Details

Clean Architecture - PART VI - Details

Translations: RU
The book club of our company has chosen a new wonderful book for reading: Robert Martin - Clean Architecture - a Craftsman’s Guide to Software Structure and Design 👍 The part VI undermines some foundations 😀: Do you know that Database is a “detail”? An unimportant minor low-level non-essential feature that can be neglected in architecture design! Do you know the same about the Web? It is just an unimportant IO device that should also be neglected in architecture design!
Designing Data-Intensive Applications - Chapter 1 - Reliable, Scalable, and Maintainable Applications

Designing Data-Intensive Applications - Chapter 1 - Reliable, Scalable, and Maintainable Applications

Translations: RU
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.