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Category: "Resiliency"

Books

  1. System Design Workbook
    System Design Workbook
    Edição 2026
    Matheus Fidelis

    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.

  2. Extreme Reliability
    Extreme Reliability
    Programming like your life depends on it
    Jules May

    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.

  3. Master Apache JMeter From load testing to DevOps.
    Master Apache JMeter From load testing to DevOps.
    Prefaced by Alexander Podelko
    Antonio Gomes Rodrigues, Philippe Mouawad, and Milamber

    Master performance testing and JMeter with this book written by three members of Apache JMeter's team who are also experts in the performance field.You will deeply understand how to get the most out of it, be more productive and integrate it into your Agile/DevOps processes.

  4. The Reconciler's Handbook
    The Reconciler's Handbook
    Designing, Reviewing, and Owning Kubernetes Controllers
    Luca Sepe

    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.

  5. System Design Engineering Handbook
    System Design Engineering Handbook
    A Practical Field Manual for Designing, Reviewing, and Operating Production Software Systems
    Fadi Al-Najar

    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.

  6. Crash-Proof AI Agents
    Crash-Proof AI Agents
    Durable Execution for LLM Agents, Tested in the Lab
    Ground Truth Books

    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.

  7. SRE A Complete Visual Guide
    SRE A Complete Visual Guide
    A Practical Reliability Engineering Guide for Systems Engineers
    Reiner Braun

    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.

  8. Digital Operational Resilience — Practitioner's Handbook
    Digital Operational Resilience — Practitioner's Handbook
    A Working Guide to Regulation (EU) 2022/2554
    William Power
    No Description Available
  9. Payment Reliability Engineering
    Payment Reliability Engineering
    Prevent Duplicate Charges, Recover Unknown States, and Reconcile Money Movement
    Xiaoqing Wang

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

  10. Surviving Distributed Systems: A Practical Field Guide
    Surviving Distributed Systems: A Practical Field Guide
    A Practical Field Guide to Resilience, Concurrency, and Fault Tolerance
    Artur Ostapyshyn

    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.

  11. Chaos Engineering for AI Infrastructure
    Chaos Engineering for AI Infrastructure
    Fault injection and resilience testing for GPUs, model serving, RAG pipelines, and agentic systems on Kubernetes
    GitforGits | Asian Publishing House

    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.

  12. Backpressure in Microservices
    Backpressure in Microservices
    Bounded Queues, Worker Pools, Cancellation, Drop Policies, and Overload Control in Go
    Luca Sepe

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

  13. The Migration Architect's Handbook
    The Migration Architect's Handbook
    Large-Scale Code Migration and Repository Engineering for Modern Software Organizations
    Steve Publications

    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.

  14. The Kubernetes Platform Engineer Interview Guide
    The Kubernetes Platform Engineer Interview Guide
    Advanced Controllers, Syncers, Multi-Tenancy, API Scalability, and Staff-Level System Design
    Luca Sepe

    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.

  15. Introduction to computer   science and programming
    Introduction to computer science and programming
    A beginner’s guide for students
    Anshuman Mishra

    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.