Books

Infrastructure automation in 2026 is about building intelligent, resilient, and cloud-native systems at scale. Server Automation with Python: The 2026 Edition explores modern Python-driven workflows spanning GitOps, immutable infrastructure, cloud SDKs, chaos engineering, and AI-assisted development, providing practical guidance for creating secure, scalable, and self-healing platforms.

How does code actually run under the hood? Stop guessing and master the hidden physics of execution. Learn how Python and Java truly manage memory, layout data structures, and drive high-performance algorithms.

Oracle Cloud Infrastructure is powering more enterprise workloads than ever, and this practical guide helps you get the most from it. Covering core infrastructure, networking, security, automation, AI, analytics and disaster recovery, it gives architects, administrators, developers and DevOps professionals the skills to design, deploy and manage solutions on OCI.

Google Cloud Platform Essentials is a practical guide to Google Cloud, covering compute, storage, networking, databases, Kubernetes, serverless, security, AI/ML and more. With hands-on examples and practical best practices, you'll learn to build scalable, reliable and cost-effective cloud applications while preparing for GCP certifications.

Whether you're deploying your first AWS application or managing cloud infrastructure at scale, The Practical AWS Guide helps you design, build, secure, automate and operate reliable AWS environments. Through practical examples, real-world architectures and proven best practices, you'll learn the skills needed to build scalable, secure and cost-effective solutions with confidence.

Go from an empty cluster to a self-deploying GitOps pipeline, doing every step yourself: Applications, sync policy, hooks, RBAC, Helm, ApplicationSets, and a setup that ships every branch on push. You finish with a pipeline you can explain line by line, not a demo you watched run.

In this book, you build a production-grade system with a multi-stage pipeline that compiles, tests, scans, provisions infrastructure with Terraform and Bicep, deploys with zero downtime, validates with Newman, manages packages through Azure Artifacts, and instruments every stage with the security controls that modern AI-era applications require.

If you're a systems administrator looking to update your skills, a developer wanting to understand infrastructure better, or someone who's new to both infrastructure and Terraform, this book has got you covered. The examples are really helpful. The explanations are crystal clear. The progression is deliberate. This book will teach you everything you need to know about building, managing and evolving infrastructure.

Set up a secure Elasticsearch and Prometheus setup in Kubernetes that can be used in any production environment!

Stop being the on-call engineer for your own house. Build a homelab that monitors, alerts, and fixes itself — entirely managed as code.

A beginner-friendly introduction to TypeScript for no-code and AI-assisted developers. Learn the fundamentals properly and build confidence beyond copy-paste code.

Terraform is easy—until teams, compliance, and day-2 reality arrive. This hands-on playbook shows how to scale IaC with GitOps, CI/CD, policy, and operational safety.

You know how to code, but everyone else seems to "just get it" while you secretly Google and ChatGPT everything. The Software Realm DECODED is the patient mentor conversation you've been searching for, Peter asks the questions you're afraid to ask, and the Ultra Senior Developer explains what bootcamps skip and seniors assume you know. By the final chapter, the imposter syndrome disappears and systems finally make sense.

Build a real AI platform on OpenShift, not just “another Kubernetes cluster.” This guide walks you through air-gapped installs, Quay mirroring, GPUs, InfiniBand, GitOps, and benchmarking—so platform and SRE teams can deliver a secure, observable, high-performance OpenShift AI environment that app teams actually want to use.

Master Generative AI from Theory to ProductionYou don't learn Gen AI from tutorials — you learn from solving real problems. How does ChatGPT handle context and avoid hallucinations? How does Perplexity build RAG at scale? How does GitHub Copilot generate accurate code? System Design Mastery - Generative AI teaches through real-world scenarios and production patterns. 116 scenario-driven case studies covering:✅ RAG with vector databases and hybrid search✅ Prompt engineering with Chain-of-Thought reasoning✅ Document processing with multi-format parsing✅ Multi-modal AI with vision and audio✅ Production deployment with monitoring and cost optimization Every scenario includes: production problem, architectural approaches, Gen AI patterns, decision frameworks, tool implementations, and interview-ready explanations. Learn through case studies from OpenAI, Anthropic, Google, Meta, and top AI-companies. Your journey from developer to Gen AI architect begins here — with scenarios you'll face and tools you can deploy.