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- Install Boto3 (AWS SDK for Python) in Visual Studio Code (VS Code) on Windows - Wed, Feb 23 2022
- Automatically mount an NVMe EBS volume in an EC2 Linux instance using fstab - Mon, Feb 21 2022
I wasn't sure if I should put the Docker book in the cloud or the virtualization section. Even though Microsoft sees Docker's container technology as new way of isolating applications in Azure, I decided that the book fits best under "virtualization" because containers essentially introduce a new level above the hardware virtualization layer.
At 60 pages, the book is just ten pages above my minimum size for counting as a book. I treat everything under 50 pages as a white paper and usually don't add such documents to our free admin eBook list.
Nevertheless, if you didn't understand what the recent buzz about Docker is all about, you should have a look at Cesar de la Torre's book because I think it is good introduction of how Docker fits into the Microsoft world. Of course, we also covered Docker before on 4sysops and after reading the book, you may find these articles easier to digest.
I added the other two books already a couple of weeks ago. Actually, John McCabe's Windows Server 2016 book has been on the list for a while. The new link points to the final release of the book. The earlier version of the book was about the Windows Server 2016 Previews. Of course, learning about the new features of Windows Server 2016 is a must for every IT pro. You might also want to skim through our numerous articles covering the topic.
The last book (Data Science with Microsoft SQL Server 2016) is perhaps not a typical sysadmin or devops book. I am not even sure if the average DBA is currently concerned with data science. However, many experts believe that data science is the next big topic in IT. Data science is about data analytics and includes methods such as statistics, machine learning and data mining.
At the moment, only very big organizations have enough data to require data science for extracting useful information. However, considering that the amount of data that humans and machines produce in a given time period is growing exponentially, it is probably only a matter of time until everyone working in IT will be involved in one way or another with data science.
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