Generative Infrastructure-as-Code

"Generative Infrastructure-as-Code" is a comprehensive guide designed to navigate the cutting-edge intersection of Generative AI and modern infrastructure management. It demystifies how Large Language Models (LLMs) and other AI techniques can be used to automate the creation, deployment, and maintenance of cloud infrastructure, transforming a complex, code-intensive process into an intuitive, prompt-driven one.



Key Features:


1. Globally Compatible Syllabus: The content is based on universally recognized concepts and industry-standard tools, making it suitable for computer science curricula worldwide.
2. Progression: A logical, chapter-by-chapter flow that builds knowledge incrementally, making complex topics accessible to all.
3. Practical, Hands-On Approach: Every chapter includes practical examples, code snippets, and hands-on exercises to reinforce learning and build tangible skills.
4. Capstone Project-Driven Learning: A comprehensive final project guides readers through building and deploying a live, real-world application using Generative IaC techniques.
5. Focus on Core Concepts & Latest Tools: Covers timeless principles of architecture and design alongside the latest tools like Terraform, Ansible, GitHub Copilot, and OpenAI's GPT models.


To Whom This Book Is For:

1. B.Tech/M.Tech Students: Primarily aimed at undergraduate and postgraduate students in Computer Science, Information Technology, and related engineering disciplines.
2. Aspiring DevOps and Cloud Engineers: An essential guide for those looking to start or advance their careers in cloud computing and automation.
3. Software Developers: For developers who want to understand and control the infrastructure their applications run on, embracing the "you build it, you run it" philosophy.
4. IT Professionals and System Administrators: A perfect resource for upskilling from traditional system administration to modern, code-driven, AI-enhanced infrastructure management.
5. Educators and Faculty: Provides a structured, ready-to-use resource for teaching modern cloud infrastructure and AI application courses.


The pedagogical style is fully compliant with the skill-oriented framework, emphasizing learning by doing. The final chapter culminates in a complete, end-to-end DIY capstone project, allowing students to synthesize their knowledge and build a portfolio-worthy piece of work.