Software Architecture

Build financial systems that stay correct when requests repeat, events arrive late, and services fail. Learn practical patterns for money modeling, double-entry ledgers, idempotency, reconciliation, auditability, security, and invariant-driven testing—so every balance and transaction can be explained and trusted.

Most architecture books teach you how to design systems. This one teaches you how to become the person who designs them. This book covers everything the job actually requires: the mindset, the technical depth, the decisions, and the organizational and human dimensions that no purely technical book addresses.

An LLM is not an AI system.Systems Thinking for Agentic AI shows software engineers and architects how to design reliable AI applications with prompts, RAG, tools, memory, orchestration, guardrails, evaluation, observability, and runtime control.Move beyond chatbot demos and learn how to build production-ready agentic AI systems you can reason about, measure, debug, operate, and improve

Modern cloud-native applications generate massive volumes of telemetry data, making observability increasingly expensive and difficult to scale. While OpenTelemetry has become the industry standard for distributed tracing, traditional tail-based sampling architectures often require stateful collector clusters with significant memory and processing overhead. Rethinking OpenTelemetry Tail-Based Sampling explores how Event-Driven Architecture (EDA) and event mesh technologies can be used to address these challenges. Through practical examples, architectural analysis, and implementation considerations, this book examines OpenTelemetry sampling strategies and presents an alternative approach that externalizes trace buffering and sampling coordination beyond the collector layer. Whether you are an observability engineer, platform architect, integration specialist, SRE, or cloud-native practitioner, this book provides practical guidance for designing scalable, resilient, and cost-effective distributed tracing platforms.

Build real-world software by coding a Redis server from scratch.Network programming. The next level of programming is programming for multiple machines. Think HTTP servers, RPCs, databases, distributed systems.Data structures. Redis is the best example of applying data structures to real-world problems. Why stop at theoretical, textbook-level knowledge when you can learn from production software?Low-level C. C was, is, and will be widely used for systems programming and infrastructure software. It’s a gateway to many low-level projects.From scratch. A quote from Richard Feynman: “What I cannot create, I do not understand”. You should test your learning with real-world projects!

Learn Next.js by building a real AI-powered application, from project setup to production deployment. This book covers the complete journey: TypeScript, React, Next.js App Router, Prisma, authentication, the Vercel AI SDK (chat, RAG, tool calling), testing, security, and deployment. One project, 29 chapters, no toy demos.

This book provides an introduction to the high-level concepts behind query engines and walks through all aspects of building a fully working SQL query engine in Kotlin.

This is the classic volume on every variety of technical review of programs, designs, tests, documentation, plans, requirements, ...

La modélisation logicielle DDD (Domain-Driven Design) donne des résultats puissants dans la pratique, non seulement en théorie. C'est la raison pour laquelle les développeurs du monde entier s'orientent rapidement vers son adoption. Maintenant, pour la première fois, il existe un guide français, une traduction officielle du livre DDD Distilled.

MVC showed what the system is. DCI shows what it does—readable Contexts and Roles from Xerox PARC through today’s agent playbooks. Practical TypeScript and Rails examples, end to end.

AI agents are only as good as the loops behind them. This book shows you how to build systems that plan, act, evaluate and improve with every step. Learn the patterns, frameworks and engineering practices behind reliable, self-correcting agents that solve real problems in production.

This book takes you through the most common patterns and frameworks used by developers while creating software based on ROS 2. It's not a programming guide guiding you through the basic APIs, but is meant to help you organizing complex architectural patterns in robotics. It is written with an informal tone that will hopefully keep you entertained.

Stop copying design patterns without understanding the problems that created them.Netflix’s architecture wasn't drawn on a pristine whiteboard; it was forged by critical failures. In this book, we dive into the technical backstage of the world's largest streaming platform to understand the real trade-offs behind microservices, resilience, and global scale.Avoiding the hype and focusing purely on engineering, BehindTheStack dissects how the monolith was shattered, how data persistence evolved, and how a culture of freedom and responsibility shaped the code.Written for Architects, Tech Leads, and Senior Engineers who demand depth beyond shallow tutorials. Grab the Early Access version and follow the making of this scale survival manual.

If you're a developer looking for a foothold into the cloud, this book is for you. The Pulumi Book will teach you all there is to know about Pulumi, the open-source platform that lets you build and manage cloud-based applications and infrastructure with modern programming languages and tools like TypeScript, Node.js, and Visual Studio Code.

STOP building fragile AI wrappers. START designing resilient AI systems. Lots of companies are trying to make their small AI experiments into big products, but they don't have a good plan. Engineers need a practical guide to build these new AI systems the right way - so they can handle scale, be reliable, and won't cost too much. This book is that guide. It explains how to design systems that use AI models. This book breaks down the architecture of real AI applications, like an AI-powered code editor or a smart learning app. It gives you a deep, practical look at the real-world challenges and solutions for building these systems. It discusses system design concepts for systems that use LLMs.