Infrastructure as code: Managing servers in the cloud


Managing Servers in the cloud.pngInfrastructure as Code.png


The fundamental promise of the book can be summarized by the following (page 258)

Automate Everything
1. Redesign or reconfigure things so the task isn't necessary at all.

2. Implement automation that handles the task transparently, without anyone needing to pay attention.

3. Implement a self-service tool so that the task can be done quickly, by someone who doesn't need to know the details, preferably the user or person who needs it done.

4. Write documentation so that users can easily carry out the task on their own.

As usual, things are easier said than done, "Infrastructure as Code: Managing Servers in the Cloud" manages to describe the challenges, as well as some practical methods to build solutions to deliver in today's fast-paced IT infrastructure building and management.

After the first few introductory chapters that lay down the basic definitions and context, the author goes on to describe patterns and best practices for building server templates, managing configuration and changes to configuration, as well as the pitfalls you might encounter when you move from a traditional system administration mentality to dynamic, automated "infrastructure as code" perspective. You might also find the chapters dedicated to testing infrastructure changes, change management pipelines for infrastructure, and continuity for infrastructure particularly useful.

If you're building / managing a dynamic and flexible information system infrastructure in the cloud or on premise, regardless of your particular tool choice for automation, you'll find yourself facing the challenges described in this book, and therefore the outlined patterns will apply to your problems to a great extent. Therefore, I can easily recommend this book to any IT professional in that position.


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Posted by Emre Sevinç on 3-apr-2017 14:02:54

Emre Sevinç

About the Author

Emre is a senior software engineer and project lead with more than 15 years of experience, and a formal background in mathematics and cognitive science. He gained his experience in varied domains such as space industry, biomedical informatics, and e-learning. When he is not busy with developing software intensive solutions for Big Data systems, writing technical documentation, and engaging with the customer, he follows the latest developments in Data Science.