Friday, May 20, 2022

My Five Favourite Cloud Books of the Year, So Far!

It has taken me some time to come up with a list of favourite books; the production of cloud titles is at its peak, making it very difficult to pick up just a few. Finally, I’ve come up with a list, and I hope it will be helpful for you.

Disclaimer: the books from the list are paperbacks that I’ve read back to back, and gone through most of the examples myself – no cheating here 😉

The order that I’m presenting the books doesn’t reflect the quality; in fact, all are great books; it’s just personal preference 🙂


I know, it’s a book from 2018, and that means it is a bit outdated. It doesn’t matter; I reread it a couple of times for the re-certification, and I still learnt new stuff and completed some of the remaining labs. I can still recommend this book, maybe not at the total price. In this case, you could pick up a digital copy or read it through a digital platform. BTW, I don’t see this as a problem. Everything gets outdated, from books, computers to video courses. Some stuff gets updated; some don’t.

I use a few books for quick reference, and some are old; not that much for video courses; it’s just not practical. I still use a couple of them as refreshers, and I go mainly through the slides; then, I’d pick a few videos. It’s not the same medium, and the experience is different. The intelligent thing to do is to use a combination of other learning materials at your convenience.


“Building Serverless APPs with GCP” is a short but full of content book that builds up as you read it. It’s very well put together so that different audiences can read it.

The only “bad thing” about this book is that it is a niche book and therefore a bit expensive. Still, very recommended.


I was looking for a book to replace my old book about microservices: Manning Spring Microservices, 2017″. Specifically, that covered new tools and deployment in the cloud – I wasn’t that interested in the Spring part.

Well, this book does its job very well. I was so hooked that I read the book a couple of times and went through most examples.

The author took the picture.

If I have to pick a few highlights, for sure, it would be the Kubernetes deployment chapters, Service Mesh and the replacement of Netflix components.

A word of advice. This book is a Packt Publishing release, so it follows its editorial style: very hands-on and includes many code listings. It agrees with me a lot but make sure that’s what you want.


I’ve had this book by Julien SIMON on my reading list for a while – it’s a 2020 release – and when I finally made the time to read it, I couldn’t put it down. Like the previous book, it’s a Pack Publishing release, packed with examples, so you can start prototyping right away.

It’s a hands-on book focused on Sagemaker and AWS services, so it’s not a book to learn Machine Learning in-depth. The good news is that you can learn to train and deploy pre-built models using Sagemaker without that specific knowledge.

The author took the picture.

The book gives you an excellent overview of Sagemaker, but it’s been written before 2020, I’d guess, so it doesn’t cover many new features like Sagemaker Studio, Autopilot, etc…

Not to worry :), a Second Edition will arrive this November, covering all that new shiny stuff.


Finally, my favourite read of the year, so far! Data Science on AWS, O’Reilly, 2021.

I’m waiting for the Second Edition of Julien’s book, “Learn Amazon Sagemaker” to see how they compare, but they are, in essence, different type of books. This one contains more in-depth technical knowledge – covers BERT models, for instance – and focuses on how to implement, end to end, an ML pipeline on AWS. It’s also a more updated book, a 2021 release, so it covers newer features like Autopilot, SageMaker Clarity, Studio etc …

The book also has hands-on content and even includes chapters on Data Analytics, which are very informative.

Again, if you are worried about the book getting outdated, you can always read the digital version, but you’d lose the benefits of having a printed copy. Even if you only use the book for a couple of years, I’d say it’s good value. Furthermore, even if you read it once, the knowledge you could attain justifies the purchase. I can see myself going back to this book or others on the list for a long time, at least for reference.

In summary, an excellent book if you want to learn MLOPS on AWS. It’s not a book for beginners, though. You will need knowledge of Data Science, Analytics, Python, and of course AWS.

The author took the picture.

Adolfo Estevez
A Estevez
Cloud & Digital Evangelist | AWS x 13 Certified | GCP x 6 | Serverless | Machine Learning | Analytics |

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