It is not every day that my work as an editor crosses paths with someone who shares both my roots and my love for technology. Banibrata and I are both Bengalis, and if you know anything about Bengalis, you know how seriously we take books, ideas, and conversations. Working with him on Hands-On MLOps on Azure felt like the most natural collaboration.
This project began when Marylou spotted a clear market gap. There were plenty of resources explaining MLOps concepts in theory, and vendor docs that describe individual Azure services. What was missing was a practical guide that ties it all together, one that shows professionals how to manage the entire lifecycle of machine learning and large language models on Azure, step by step. Banibrata De, with his experience in Microsoft’s Core AI group, was the perfect author to bring that vision to life. His background in building and scaling AI products ensured this book would be rooted in real-world practice and not just theory.
From there, the book took shape as a hands-on, project-based journey that goes beyond documentation and helps readers put MLOps into practice. It is written for DevOps engineers, SREs, cloud professionals, and decision-makers who want clarity and confidence in running ML and LLM workloads. What makes it stand out is that it covers not just traditional ML but also the growing space of LLMOps, something very few books attempt today. While Azure Machine Learning is at the core, the practices and lessons are broadly applicable across environments.
As the editor, it has been deeply rewarding to help shape this book and bring its vision to life. I am glad to have had Prachi alongside me to make sure it connects with the audience it was meant for.
If this resonates with you, show the book some love. Use MLOPSAZ15P to get 15% off the print version. If you’re the type who grumbles about book prices while sipping on a fancy coffee, use MLOPSAZ25E to get 25% off the ebook version. The discounts are available until 30th September, so yes, you can procrastinate a little before buying. But I’d recommend not waiting. Your next MLOps project will thank you.
(Amazon link in the 1st comment)
