Distributed Systems

Understand microservices through clear diagrams of service boundaries, data ownership, communication, resilience, and operations.

Understand how independent AI agents discover each other, exchange messages, and coordinate tasks. Clear diagrams introduce Agent2Agent architecture, interaction patterns, security, and reliable operation.

Building reliable distributed systems is harder than it looks. This book takes you from the fundamentals of message queues to the realities of distributed transactions, with working code, practical patterns and production lessons to guide you. Learn how to handle failures, maintain consistency and build systems that keep working when things go wrong.

Your AI application works on your machine. What happens when it reaches production? Learn to deploy, monitor, secure, and scale AI systems using Docker, CI/CD, Kubernetes, cloud infrastructure, and practical production engineering. Move beyond prototypes and build AI applications you can operate with confidence.

Modern cloud-native applications generate massive volumes of telemetry data, making observability increasingly expensive and difficult to scale. While OpenTelemetry has become the industry standard for distributed tracing, traditional tail-based sampling architectures often require stateful collector clusters with significant memory and processing overhead. Rethinking OpenTelemetry Tail-Based Sampling explores how Event-Driven Architecture (EDA) and event mesh technologies can be used to address these challenges. Through practical examples, architectural analysis, and implementation considerations, this book examines OpenTelemetry sampling strategies and presents an alternative approach that externalizes trace buffering and sampling coordination beyond the collector layer. Whether you are an observability engineer, platform architect, integration specialist, SRE, or cloud-native practitioner, this book provides practical guidance for designing scalable, resilient, and cost-effective distributed tracing platforms.

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.

Build reliable distributed systems with Spring Boot, RabbitMQ and modern Java. Follow OrderFlow as it grows from a simple service into a production-ready event-driven platform, exploring architecture, messaging, observability, containers and the practical trade-offs behind every design decision.

Build collaborative software that keeps working when the network does not. This practical guide takes you from distributed systems fundamentals to working CRDT implementations and production-ready collaboration. Learn how CRDTs work, where they fit and how to handle scaling, security, metadata growth and failure in real systems.

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.

Build real-time data systems that can keep up with the demands of production. Streaming at Scale takes you under the hood of Apache Flink, covering state, event time, exactly-once processing, performance, Kubernetes and more. With runnable examples and practical lessons, it shows how to build systems that are fast, reliable and ready to scale.

A practical look at how the modern Internet edge really works. Explore DNS, BGP, TLS, HTTP/3 and the architecture behind content delivery, then apply that knowledge to building, securing and optimizing Cloudflare in production. No marketing fluff, just the engineering behind the edge.

AI can write code at machine speed. Can your architecture keep up? Architecture at Machine Speed shows how to build Go systems that remain coherent as humans and AI agents change them at unprecedented velocity. Through a real-world application built from the ground up, you'll learn to turn architectural intent into explicit boundaries, enforceable constraints, and automated safeguards—because when code becomes abundant, coherence becomes the scarce resource.

From containers and Kubernetes to autoscaling, observability, Prometheus, Grafana, SLOs, security, and production failure. Volume III shows how distributed architecture becomes an operable, measurable, evidence-driven production system.

What if your software did not need the cloud to work? Local First Software Development shows you how to build fast, reliable apps that work offline and sync when needed. Learn practical patterns for data, security and synchronization while exploring how local-first systems can grow from simple personal tools into large collaborative applications.