Architecture

This is a continuation of my previous post Real Projects with Ethereum) - about how to setup a development infrastructure around real-life smart contract.

How to build a complex blockchain smart contract? What standard issues will you face with arrays, gas, different types of variables, deployment of contracts, etc? And how to solve them?

What is the right architecture for the app that should work with blockchain (and how it differs from traditional web architecture)? What libraries to use? How to configure environment?

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!

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 👍 Fifth part of the book contains A LOT of useful information: What is software architecture? What type of interdependencies can exist? How to draw borderlines between components? What type of borders exist? How to distribute policies by the levels? What are business rules, entities and use cases?

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.

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.

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 10 discovers all aspects about big data Batch Processing. If your system needs to process some data then your DEV team should learn this info. Unix tools for batch processing and brilliant concept of pipes.

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 9 tells about Consistency and Consensus in distributed systems. It covers the following topics: What is consistency and eventual consistency Linearizability. Why it is needed. Difference from Serializability.

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.