Resiliency

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.

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

As global legislation and procurement rules increasingly mandate that high-level AI systems must "recover from incidents", the critical challenge has shifted from conceptual policy to verifiable evidence. Assessing AI Resilience bridges this gap by establishing a mathematically grounded, evidentiary framework for evaluating how complex and agentic AI systems recover their operational condition. Drawing on international standards and rigorous signal-processing principles, this 660-page monograph provides policymakers, enterprise risk leaders, and assessors with the actionable methods, governance guardrails, and measurement models required to turn compliance into defensible engineering discipline.

A controller is a promise you keep making. Learn when to build one, how to design for failure, and what it takes to own it.

Master practical system design with 62 parts covering distributed systems, scalability, databases, security, and production architecture. A comprehensive engineering handbook with real-world examples, diagrams, and decision frameworks.

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.

Make production services dependable with a practical visual guide to reliability engineering. Connect SLOs, observability, safe change, incident response, resilience, capacity, recovery, and reliability economics through worked examples and verification.

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

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.

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.

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