Python is awesome, Kubernetes is awesome too. Use the combined power of both to create highly available Python application, declarative data processing task, and all sort of automation tasks.
In diesem Primer erklären wir Data Mesh aus der Engineering-Perspektive.
Rapid-development frameworks across Ruby on Rails, Node.js, PHP, Python, and .NET revolutionized how quickly we can ship software. But what happens when your business domain grows complex? Relying on Active Record and heavy ORM patterns tightly couples your database to your business logic. As your product matures, this coupling creates brittle, difficult-to-maintain codebases that resist change and slow down your team. The solution is the Domain Model Pattern (the foundation of Domain-Driven Design). It isolates business rules from infrastructure, creating a pure, scalable architecture. Historically, however, this pattern required a massive amount of effort and boilerplate, making it too slow for fast-paced development. That changes today. We are at an AI inflection point. Modern AI coding assistants excel at generating boilerplate and wiring infrastructure, effectively eliminating the traditional drawbacks of DDD. AI finally bridges the gap between the rapid speed of framework scaffolding and the architectural purity of a Domain Model. But to harness AI reliably, you cannot simply let it generate code unguided. You need a structured methodology to guide the machine. In this book, you will learn:How to build reliable, maintainable software using a strict, AI-assisted pipeline: Use Cases → Gherkin → Event Storming → Strategic & Tactical DDD.How to create implementation-agnostic class diagrams that serve as universal blueprints, allowing you to generate code in OOP languages (Java, C#, PHP, Python) or Functional languages (Elixir, Clojure, F#).How to future-proof your systems with a timeless methodology that prioritizes the longevity of business logic over the ephemeral nature of web frameworks.How to scale your architecture gracefully from a Majestic Monolith to Microservices without a complete rewrite. Whether you want to accelerate your development velocity, improve your system's resilience, or simply reclaim your craft by building beautiful, majestic systems, this book provides the blueprint. Discover how to combine the timeless principles of DDD with the power of AI. Read the free sample today.
Take your IPv6 skills beyond the basics. Advanced IPv6 Engineering covers real-world network design, routing, security, automation and operations at scale, with practical examples for Linux, enterprise networks, cloud, containers and Kubernetes. Built for engineers who need to deploy, secure and manage IPv6 with confidence.
Linux System Hardening is a practical guide to securing Linux systems from the kernel to the cloud. It explains how threats work, how to apply effective controls and what you give up along the way. Built for admins, security engineers and DevSecOps teams working with real production systems.
Unlock the Power of Google Cloud Platform!"As a professional, I'm not paid just for what I know but for my thought process and the decisions I take to make my architecture optimal." — Sudhanshu Jaiswal🌟 Ever wondered how to harness the full potential of Google Cloud Platform?GCP - A Walkthrough is your ultimate guide to mastering the cloud with expert insights, strategic decision-making, and hands-on best practices. Whether you're migrating workloads, optimizing costs, or building scalable architectures, this book equips you with the knowledge to design, deploy, and manage GCP solutions like a pro.From cost optimization and IAM to big data, AI, and security, dive into a comprehensive walkthrough that transforms your cloud journey. Stop guessing—start optimizing!
Most self-hosted LLM deployments run at 10–30% utilization — full retail price for GPUs that mostly sit idle. Tokens per Dollar is a deliberately short field guide for platform engineers: tune vLLM (2–4x throughput on the same hardware), quantize to halve your GPU count, cache the prompt tokens you keep re-paying for, and autoscale on real token traffic instead of CPU. Working YAML throughout, and a case study that cuts a 70B deployment from $29,200 to $8,600 a month with better latency. Read it in an evening; it pays for itself the first day you apply it.
Infrastructure gets complicated fast. Mastering Terragrunt shows you how to bring order to growing Terraform and OpenTofu environments without adding unnecessary complexity. Learn practical patterns for managing multiple accounts, regions and teams, streamline deployments and build infrastructure that stays maintainable as your organization scales.
What if S3 could be more than a place to put files? Build databases, queues, event logs, Git systems and distributed applications directly on object storage. Through production-grade Go implementations, this book explores what works, what breaks and how to design reliable systems around the real guarantees of S3-compatible storage.
Build the Next Generation of Enterprise AI SystemsCloud-Powered Agentic AI is a practical guide to designing, developing, deploying, and operating production-ready AI applications using Large Language Models (LLMs) and modern cloud-native technologies.From prompt engineering and Retrieval-Augmented Generation (RAG) to AI agents, multi-agent systems, Model Context Protocol (MCP), FastAPI, Docker, Kubernetes, and LLMOps, this book provides a complete roadmap for building scalable, secure, and maintainable AI solutions.Through hands-on examples, architecture diagrams, case studies, and a comprehensive capstone project, you will learn how to move beyond prototypes and engineer enterprise-grade AI systems.Inside this book, you'll learn how to:Build LLM-powered applications from scratchDesign Retrieval-Augmented Generation (RAG) pipelinesDevelop AI agents and multi-agent workflowsIntegrate tools using the Model Context Protocol (MCP)Deploy AI services with FastAPI, Docker, and KubernetesApply LLMOps for monitoring, evaluation, and continuous deliverySecure and govern AI applications in enterprise environmentsBuild a complete cloud-native AI platform from development to productionWhether you are an AI engineer, software developer, cloud architect, or machine learning practitioner, this book will equip you with the practical skills needed to build reliable and scalable AI systems in the era of generative AI.
Cloud networks rarely fail in obvious ways. A DNS lookup breaks, a route disappears or traffic vanishes somewhere between clouds. This book shows you how to understand what is really happening, build networks that hold up under pressure and troubleshoot failures with confidence across AWS, Azure, Google Cloud, Kubernetes and hybrid environments.
Build OpenStack with confidence, from your first deployment to production at scale. This hands-on guide walks you through planning, configuration, security, daily operations and troubleshooting with practical examples and proven techniques. A dependable resource for admins, DevOps engineers and cloud architects.
Ansible has transformed IT automation, but even the most well-designed playbooks can encounter unexpected errors, cryptic logs, or behaviors that defy expectations. "Ansible Troubleshooting: A Practical Guide" is your roadmap to navigating these challenges with ease. , this book provides the insights and techniques you need to diagnose and resolve issues efficiently.
Cloud migration is more than a technical upgrade—it’s a strategic imperative for modern businesses. In "Cloud Migration: A Journey," you’ll discover how to navigate the complexities of moving workloads to the cloud, whether from on-premises, between cloud providers, or through hybrid approaches. This book equips you with the knowledge, strategies, and best practices
The Guide presents more than 12 domains and shows their interactions, roles and responsibilities in a comprehensive format that can be adapted to your organization no matter its size.It includes more than 60 checklists for auditing activities.Register your copy for a free 2027 version. Details inside the book.