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Kubernetes & Cloud-Native Engineering
Building, Deploying, and Operating Production-Grade Systems
This book is 100% completeLast updated on 2026-09-14
A system-first engineering guide to building, deploying, operating, and securing production-grade Kubernetes clusters, cloud-native platforms, and AI inference workloads.
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About the Book
Master Production-Grade Kubernetes & Cloud-Native Systems
Modern production platforms consist of distributed services, containers, automated deployment pipelines, cloud infrastructure, observability frameworks, and increasingly, complex AI workloads. Managing this scale manually is no longer sustainable.
Kubernetes & Cloud-Native Engineering approaches Kubernetes not as a random collection of commands to memorize, but as a complete declarative system. It bridges the gap between basic container orchestration and engineering resilient, enterprise-ready platforms.
What You Will Master:
- Kubernetes Architecture & Core Abstractions: Master desired state reconciliation, workload management, pods, services, and network routing.
- Reliability & Auto-scaling: Implement health checks, self-healing, resource constraints, horizontal/vertical auto-scaling, and fault-tolerant architectures.
- Cloud-Native Operations & Observability: Set up distributed tracing, logging, metrics, CI/CD pipelines, and automated GitOps workflows.
- Enterprise Security & Compliance: Enforce network policies, RBAC identity management, software supply chain security, and hard infrastructure controls.
- Kubernetes for AI Systems: Deploy LLM and AI workloads, configure GPU scheduling, execute high-throughput model serving, and scale production AI inference platforms.
Who This Book Is For:
This guide is engineered specifically for:
- Software Engineers & Backend Developers scaling distributed systems.
- DevOps, Site Reliability (SRE), & Cloud Engineers building resilient infrastructure.
- Platform Engineers designing internal developer platforms.
- AI Infrastructure Engineers deploying production AI/LLM systems on Kubernetes.
Table of Contents at a Glance:
- Part I: Kubernetes Foundations
- Part II: Application Deployment & Package Management
- Part III: Reliability, Resource Management & Scaling
- Part IV: Cloud-Native Operations, Observability & GitOps
- Part V: Security, Network Policies & Infrastructure
- Part VI: Kubernetes for AI Systems & GPU Orchestration
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About the Author
AhmedAdawy
Anas Ahmed Adawy is an independent author and tech enthusiast passionate about bridging the gap between theoretical science and practical coding. With a focus on applied mathematics, linear algebra, and machine learning, he creates beginner-friendly guides designed to help programmers and students master the core mechanics behind modern AI. His writing breaks down complex academic formulas into clear, actionable Python code.
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