Master the Future of DevOps
Are you ready to evolve from writing endless YAML to architecting intelligent systems?
GenAI for DevOps Engineers: Practical Use Cases & Interviews is the definitive guide for SREs, Platform Engineers, and DevOps professionals looking to leverage the power of Generative AI. This isn’t academic theory; it is a hands-on roadmap built on real-world scenarios across major cloud providers (AWS, Azure, Google Cloud) and essential tooling like Docker, Kubernetes, and Terraform.
This comprehensive resource is structured to take you from core concepts to expert-level architectural strategy, ensuring you have the skills required for the next generation of infrastructure engineering.
What’s Inside the Book?
We cover the entire DevOps lifecycle across multiple detailed domains:
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Core Concepts & IaC: Move beyond simple auto-complete. Learn to use GenAI to refactor massive Terraform monoliths, generate complex Helm charts, and debug Kubernetes manifests without hallucinations.
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CI/CD & Automation: Discover how to build self-healing pipelines in Jenkins and GitLab CI, automate release notes, and predict build failures before they happen.
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Advanced Observability: Learn to use AI to parse eBPF data, generate complex PromQL queries instantly, and perform automated Root Cause Analysis (RCA) on messy logs.
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DevSecOps & Governance: Understand how to secure AI workflows, prevent prompt injection, and use AI to auto-remediate security vulnerabilities.
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MLOps for DevOps: Bridge the gap by learning how to deploy LLMs, manage GPU resources in K8s, and handle model versioning.
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The Ultimate Interview Prep: The book concludes with “The Impossible Questions”—complex, multi-layered architectural scenarios designed to stump even Principal Engineers, complete with detailed answers to help you ace your next interview.
Who Is This Book For?
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Senior DevOps Engineers looking to reduce toil and focus on high-value architecture.
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Junior to Mid-level Engineers needing a fast track to master complex tools and methodologies.
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SREs and Platform Architects responsible for implementing AI strategy at an enterprise scale.
Stop fearing the AI revolution and start leading it. This book will give you the practical skills and the interview confidence to level up your career.
Rohit
Rohit –
This book gave me clarity on how GenAI fits into real DevOps workflows like CI/CD, Kubernetes and Terraform. Felt confident in interviews.
Priya
Priya –
The CI/CD automation and GitOps sections were eye opening. I finally understood ArgoCD and Flux concepts clearly.
Anand
Anand –
Loved how AI-powered troubleshooting and observability were explained with real scenarios.
Swetha
Swetha –
This is not theory. Kubernetes , Docker, Jenkins, and GenAI are explained like how we actually use them at work.
Karthik
Karthik –
The DevSecOps and AI security chapters helped me answer difficult interview questions confidently.
Manish
Manish –
Good structured content and very practical mindset throughout the book.
Deepa
Deepa –
After reading the MLOps and GenAI infrastructure section , I finally understood how LLMs run in production.
Suresh
Suresh –
Observability with OpenTelemetry, eBPF and AI Ops is explained better than many paid courses.
Neeraj
Neeraj –
This book helped me move from buzzwords to real implementation thinking.
Aishwarya
Aishwarya –
Terraform patterns and infrastructure scaling chapters were extremely useful.
Vinod
Vinod –
Good learning experience overall and very relevant to modern DevOps roles.
Sai
Sai –
I used the interview questions section to prepare and cracked my DevOps round.
Megha
Megha –
Clear explanation of how GenAI improves troubleshooting, RCA , and monitoring.
Rakesh
Rakesh –
The Kubernetes deep dive combined with AI tooling is very well done.
Nandini
Nandini –
This book boosted my confidence while switching jobs.
Santosh
Santosh –
Some chapters felt dense but still very informative.
Harish
Harish –
I liked the way cloud-specific GenAI (AWS, Azure GCP) is compared.
Pallavi
Pallavi –
Perfect for DevOps engineers aiming for senior roles.
Aravind
Aravind –
Good balance between architecture , tools and strategy
Divya
Divya –
The leadership and strategy chapters helped me think beyond tools.
Chaitanya
Chaitanya –
Well written and practical from start to end.
Kiran
Kiran –
Helpful insights on databases, RAG and and AI-driven data workflows.
Pranav
Pranav –
A solid reference book for real-world DevOps challenges.
Sonal
Sonal –
Reading this made me confident during system design interviews.
Vikas
Vikas –
The content feels aligned with what companies actually expect.
Mukesh
Mukesh –
Very helpful for understanding production-grade AI systems.
Akash
Akash –
This book helped me crack a senior DevOps interview after multiple attempts.
Rekha
Rekha –
The AI-powered automation examples were inspiring.
Ravi
Ravi –
Clear roadmap for DevOps engineers moving into GenAI roles.
Shreya
Shreya –
I liked how security and compliance were covered practically.
Nikhil
Nikhil –
Very relevant for cloud-native engineers.
Monika
Monika –
Gives confidence to speak about GenAI in interviews.
Abhay
Abhay –
Good explanations with real DevOps mindset.
Shyam
Shyam –
The GitOps and CI/CD sections are worth the price alone.
Keerthi
Keerthi –
Nicely structured learning path.
Mohan
Mohan –
Useful for both interviews and day-to-day work.
Sunil
Sunil –
Some parts required re-reading but overall great.
Anusha
Anusha –
This book changed how I approach automation problems.
Ajith
Ajith –
Very practical content for modern DevOps pipelines.
Puneet
Puneet –
A confidence booster before interviews.
Ritu
Ritu –
Explains complex concepts in a simple way.
Sameer
Sameer –
The database and observability chapters are very strong.
Tanvi
Tanvi –
Good reference for long-term learning.
Jay
Jay –
Helped me answer scenario-based interview questions.
Kavitha
Kavitha –
The architecture and scaling strategies were insightful.
Amit
Amit –
Very useful and career-focused book.
Shruti
Shruti –
This book played a role in my job switch success.
Varsha
Varsha –
Clear practical roadmap for GenAI adoption.
Rajiv
Rajiv –
Content feels relevant to real projects.
Imran
Imran –
Strong practical insights across all chapters.
Santhosh
Santhosh –
The interview questions boosted my confidence a lot.
Usha
Usha –
Very practical content. The GenAI + DevOps use cases are explained in a simple way. Helpful for interview prep.
Srinika
Srinika –
Not just theory 👍 The hands-on interview questions really reflect real DevOps scenarios.
Abhishek
Abhishek –
This book actually focuses on how AI is used in real DevOps pipelines, not just buzzwords
Pooja
Pooja –
Nicely written and easy to follow.
Arun
Arun –
A must-read for DevOps engineers entering GenAI.
Navya
Navya –
Very practical and career-oriented book.