Resiliency

We just accept that software is inherently imperfect, that all software must contain bugs, and we design our development processes around that. But what if it were possible to write correct software? What if we could consistently develop clean, maintainable software that works perfectly, all the time? And what if it were cheaper, faster and easier to write correct code than to write the buggy variety? What then? Flawless software, delivered faster.

System Design Workbook – Edição 2026 é uma obra que traduz, organiza e conecta os principais fundamentos da engenharia de sistemas distribuídos sob uma perspectiva prática, moderna e orientada à realidade de produção.

Build bulletproof Spring Boot microservices—from monolith migration to domain-driven design and event-driven patterns—while mastering the production essentials of resilience, observability, and zero‑downtime delivery. Turn complex domains into clean, scalable services with bounded contexts, aggregates, repositories, and domain events, then ship faster with rate‑limited APIs, backoff‑retries, and Kubernetes rollouts. If leading Java teams to reliable, cloud‑ready microservices is the goal, this is the hands‑on guide that gets systems into production with confidence.

Happy-path architecture is a myth. When downstream dependencies degrade, naive retries trigger thundering herds, thread pools exhaust in seconds, and dual-writes silently corrupt financial balances. Surviving Distributed Systems is an unvarnished, production-tested field guide for senior backend engineers. Packed with architectural diagrams and modern Java 21 code, this book teaches you how to design, isolate, and harden high-concurrency systems so they survive catastrophic cascading failures.

A pattern language for event sourced applications and reliable distributed systems. Examples are written in the Python programming language. Now includes event-oriented introductions to the pattern language scheme of Christopher Alexander, the process philosophy of Alfred North Whitehead, and the person-centred psychology of Rogers and Rosenberg.

Kill an AI agent mid-refund and the retry bills every model call again and refunds twice. This book crashes one agent on purpose and recovers it on DBOS, Temporal, Restate and Prefect, with the real output of every run.

Build a practical foundation in Site Reliability Engineering. Clear diagrams connect service maps, reliability objectives, observability, incident response, safe releases, and recovery.

Design payment systems that stay explainable when responses disappear, webhooks arrive late, and refunds race with fulfillment.

This book is all about testing and closing the gap between infrastructure health and output quality, and how easily that gap can be filled for weeks by a failure that's gone unnoticed.This book looks at the less obvious side of the problem. In the next few chapters, we're going to run 41 experiments on one application. About half of them will give you a result that the system doesn't report. It's not a dig at anyone's engineering, since the systems in question are competently built and mostly behave well.

Stop overload from becoming unbounded queues, goroutines, and downstream calls. Build bounded backpressure that fails predictably.

Big migrations rarely fail because of code alone. The Migration Architect’s Handbook shows how to untangle dependencies, design the right repository strategy and move complex systems forward without bringing the organization to a halt. Built on real-world lessons, it turns daunting modernization efforts into practical, manageable work.

Prepare for Kubernetes platform engineering interviews like a Staff Engineer. Learn how controllers, informers, syncers, finalizers, API scalability and multi-tenancy behave in real systems, then put it all into practice with a hands-on workspace-syncer capstone project. A practical guide to reasoning, designing, debugging, and explaining Kubernetes control-plane systems.

6.1 Knowledge-Based Benefits • Students will understand the fundamentals of computer science including architecture, number systems, and data representation. • They will learn the core concepts of programming languages and how they work. • They will acquire problem-solving skills using algorithms, pseudocode, and flowcharts. • They will gain knowledge of object-oriented programming, data structures, and file handling, which form the backbone of computer science. 6.2 Skill-Based Benefits • Ability to write, compile, and debug programs in a structured way. • Development of logical and analytical thinking skills. • Hands-on experience with coding exercises, lab sessions, and projects. • Skills in handling data, designing programs, and solving practical problems. • Ability to design small software applications using modular programming. 6.3 Career-Based Benefits • Students preparing for university exams, competitive exams (like UGC NET, GATE, or coding tests) will find this book extremely useful. • Beginners aspiring to become software developers, web developers, or data analysts will get their first foundation here. • Non-technical students will develop digital literacy, making them more employable in all sectors. • For those aiming to pursue advanced studies in computer science, this book acts as a stepping stone toward data science, AI, and machine learning. 7. How to Use This Book Effectively 1. Start with the theory sections to understand the concepts. 2. Work through the examples and illustrations provided in each chapter. 3. Solve the end-of-chapter exercises to reinforce your understanding. 4. Try to implement the coding examples on your computer using an IDE or programming environment. 5. Progress toward mini-projects that challenge your creativity. This active-learning approach ensures students move from passive reading to active programming practice. 8. Future Scope After Studying This Book Once students complete this book, they will be ready to explore advanced areas such as: • Data Science and Analytics – Using programming to analyze large datasets. vii | P a g e • Artificial Intelligence and Machine Learning – Writing algorithms that learn and make decisions. • Web Development – Creating interactive websites using HTML, CSS, JavaScript, and backend programming. • Cybersecurity – Understanding how to protect systems from attacks. • Mobile App Development – Designing apps for Android or iOS. • Cloud Computing – Learning how modern software runs on distributed systems. Thus, the book serves as a foundation for a lifelong journey in computer science.

After more than twenty years at IBM — including roles as Regional Technical Leader for Security Technologies and Tivoli Software across Central and Eastern Europe — I have seen many SOC modernization projects. Organizations consistently face the same dilemma: substantial existing investments in SIEM, SOAR, processes, and human expertise versus the urgent need to keep pace with AI-powered threats.Most vendors pushed rip-and-replace cloud solutions. I took a different path.The Brownfield Agentic SOC concept was born from the realization that modernization does not require replacement. It is possible — and often far more effective — to intelligently augment existing infrastructure with multi-level AI agents, dynamic business context, structured investigation, and strong governance, while preserving data sovereignty and human judgment.This book is intentionally practical and conceptual. Certain advanced techniques (self-healing patterns, zero-visible-downtime adaptation, tamper-evident intelligent audit) are subject to pending patent protection and are presented here at architectural level only.I wrote this book for three audiences:CISOs and SOC leaders in regulated industries seeking realistic modernizationSecurity architects responsible for next-generation operationsTeams that prioritize sovereignty, compliance, and human-AI collaborationMy goal is to provide a clear, actionable blueprint that respects real-world constraints while delivering measurable improvement.I hope this book inspires and equips you to build more resilient, intelligent, and sovereign Security Operations Centers.Zsolt L. Kocsis, M.Sc., MBA Associate Professor honoris causa Budapest University of Technology and Economics (BME) May 2026

A governance framework for taming complexity in distributed systems. From solo platforms to AI agents.