Overview

TCP/IP Isn't Broken-Your Mental Model IsModern systems fail in ways dashboards can't explain. Latency spikes without packet loss. Retries make outages worse. Everything looks ""healthy,"" yet users suffer. This book shows you why. If you build, run, or debug modern systems, you already rely on TCP/IP networking every day-but most engineers were never taught how it actually behaves under load, time pressure, and partial failure in real environments. You've felt the pain: You've chased network latency and performance issues with more resources-and made them worse You've blamed ""the network"" without having the right network debugging techniques You've watched retries, pools, and load balancers amplify failures You've read networking books that stop at theory and don't help in production This book closes that gap. Instead of protocol trivia, you'll learn how TCP/IP behaves as a living system inside real kernels, clouds, APIs, and distributed architectures. It connects cloud networking fundamentals with what actually happens in production systems-where time, queues, and congestion dominate behavior. You'll gain practical insight into: Distributed systems networking and why partial failures are the norm How TCP congestion control shapes latency, throughput, and system stability Why ""same region"" does not mean low or predictable latency How retries, connection pools, and abstractions quietly break systems What effective API performance optimization looks like when TCP behavior is respected What you'll get from this book: A durable TCP/IP mental model that holds up under real-world pressure Clear explanations of latency, queues, backpressure, and congestion Practical guidance for DevOps networking and SRE networking in cloud-native systems Step-by-step approaches to debugging slow, partial, and cascading failures Design principles for building network-aware, failure-tolerant software Written for developers, DevOps engineers, SREs, and operators, this book gives you the missing intuition that turns networking from guesswork into engineering. If you want fewer outages, faster debugging, and systems you actually understand-start here.

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