Books

Explore the Software, Computing Architectures, Data Pipelines, and High-Performance Systems Behind Modern High-Energy PhysicsCERN is more than a particle physics laboratory. It operates one of the world's most demanding scientific computing environments, bringing together extreme data rates, heterogeneous hardware, distributed storage, high-performance networking, real-time processing, large-scale simulation, machine learning, and advanced software engineering.Coding CERN: A Technical Developer's Guide explores the computing architecture behind experiments at the Large Hadron Collider (LHC), connecting detector electronics and real-time trigger systems with modern C++, ROOT, distributed computing, GPU acceleration, machine learning, high-performance computing, and global scientific infrastructure.The book takes a developer-oriented approach to the complete scientific computing pipeline, examining how physical events become digital signals, how those signals are filtered and reconstructed, and how the resulting data is stored, distributed, simulated, and analyzed across geographically dispersed computing facilities.

Software supply chains are now a critical attack surface. The Software Trust Chain explores how to secure code, dependencies, builds, CI/CD, containers and deployments in the age of generative AI and autonomous coding agents, focusing on practical engineering principles that remain useful as tools and platforms change.

Programming languages are entering a new era. This book explores Vale, Valen, Bend and Revo, showing how they approach memory safety, concurrency, type systems and verification. With runnable examples and clear technical analysis, it offers experienced programmers a grounded look at where systems programming may be headed.

AI is changing how we work, learn and live, but understanding it does not have to be complicated. This practical guide explains how modern AI and LLMs work, what they can do, where they fall short and how to use them effectively without the hype.

Heisenbugs, rubber ducks, spaghetti code, and everything in between. Explore 158 developer terms across 15 chapters in a visual field guide to the language behind the code. Created with AI assistance using scrolloom™.

Unlock NVIDIA GPU performance from Rust. This practical guide takes you from GPU architecture and memory hierarchies to writing and optimizing real CUDA Rust kernels. Explore both official Rust CUDA approaches with runnable examples and learn how to build fast, production-ready GPU code without giving up Rust’s safety and clarity.

Modern Java is more than a collection of new language features—it is a shift from implementing mechanics to expressing intent. Learn how records, sealed types, pattern matching, streams, modules, virtual threads, and other modern capabilities help you build Java software that is clearer, safer, and easier to evolve.

When critical infrastructure degrades, customer-facing applications continue blindly routing users into broken flows because modern architectures lack a dedicated layer for runtime coordination. This book introduces the Operational State Control Plane (OSCP)-formalizing the contracts, distribution mechanics, and zero-network resilience required to govern multi-surface application behavior during active incidents. A practical blueprint for platform architects, principal engineers, and SRE leaders running distributed production estates.

Go beyond writing code that works. Learn what really happens inside .NET, from C# and the JIT to memory, CPU execution and the operating system. This practical guide shows experienced developers how to measure performance, find real bottlenecks and make targeted improvements that hold up in production.

Learn real DevOps by building a production-style environment on your laptop. No cloud bills or subscriptions. Just systems you control end-to-end.

Build AI agents that actually hold up in production. This practical guide covers agent architecture, tool use, multi-agent systems, security, reliability, observability and operations, with working code throughout. Learn how to build agents that are dependable, cost-aware and ready for the real world.

Concurrency is where small mistakes become serious problems. This practical guide takes you from hardware and memory models to locks, atomics and lock-free algorithms, with a focus on building fast, reliable systems that hold up under real production workloads.

​A system-first engineering guide to building, deploying, operating, and securing production-grade Kubernetes clusters, cloud-native platforms, and AI inference workloads.

Rapid-development frameworks across Ruby on Rails, Node.js, PHP, Python, and .NET revolutionized how quickly we can ship software. But what happens when your business domain grows complex? Relying on Active Record and heavy ORM patterns tightly couples your database to your business logic. As your product matures, this coupling creates brittle, difficult-to-maintain codebases that resist change and slow down your team. The solution is the Domain Model Pattern (the foundation of Domain-Driven Design). It isolates business rules from infrastructure, creating a pure, scalable architecture. Historically, however, this pattern required a massive amount of effort and boilerplate, making it too slow for fast-paced development. That changes today. We are at an AI inflection point. Modern AI coding assistants excel at generating boilerplate and wiring infrastructure, effectively eliminating the traditional drawbacks of DDD. AI finally bridges the gap between the rapid speed of framework scaffolding and the architectural purity of a Domain Model. But to harness AI reliably, you cannot simply let it generate code unguided. You need a structured methodology to guide the machine. In this book, you will learn:How to build reliable, maintainable software using a strict, AI-assisted pipeline: Use Cases → Gherkin → Event Storming → Strategic & Tactical DDD.How to create implementation-agnostic class diagrams that serve as universal blueprints, allowing you to generate code in OOP languages (Java, C#, PHP, Python) or Functional languages (Elixir, Clojure, F#).How to future-proof your systems with a timeless methodology that prioritizes the longevity of business logic over the ephemeral nature of web frameworks.How to scale your architecture gracefully from a Majestic Monolith to Microservices without a complete rewrite. The methodology is language agnostics but in this edition all codes samples are in TypeScript. Whether you want to accelerate your development velocity, improve your system's resilience, or simply reclaim your craft by building beautiful, majestic systems, this book provides the blueprint.Discover how to combine the timeless principles of DDD with the power of AI.

It is three in the morning and something is wrong with your LLM application. This is the book you open. Not a tutorial — a reference manual, organised by symptom, for the moment something you built has already broken.