Stream Processing

Designing Data-Intensive Applications - Chapter 12 - The Future of Data Systems

Designing Data-Intensive Applications - Chapter 12 - The Future of Data Systems

Translations: RU
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 12 is a summary of the book and a visionary view of the future. Data Integration. Overview of the ways we have to integrate data. Causality and why we need Total Order and Idempotency.
Designing Data-Intensive Applications - Chapter 11 - Stream Processing

Designing Data-Intensive Applications - Chapter 11 - Stream Processing

Translations: RU
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 11 discovers all aspects about Stream Processing. If your system needs to process some data on-the-fly then your DEV team should learn this info. Approaches for transmitting events: Direct messaging, Messaging Systems and Partitioned Logs.
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.