Evolvability

Designing Data-Intensive Applications - Chapter 4 - Encoding and Evolution

Designing Data-Intensive Applications - Chapter 4 - Encoding and Evolution

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 I prepared an overview and mind-map. Chapter 4: What is evolvability. Backward and Forward compatibility Approaches to encode data: JSON, XML, and their binary variants Thrift and Protobuf Apache Avro Models of data flow Through databases Through services: REST, SOAP, RPC and the future Through message brokers - when they are better and when they are not Much more details in the mind-map:
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.