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The last couple of years have seen significant change in people's priorities about public cloud computing. The convenience of easy-to-run applications (many of them open source and free to use) running on elastic virtual hardware used to be where people focused their attention. Worrying about where your applications run, and where your data resides, was a concern generally restricted to certain highly-regulated industries. Today, the 'data climate' has changed a lot. The more stringent legal regimes for cloud providers and users have made geo-location a concern for many cloud users in all walks of business.
'Infrastructure as code' has revolutionised the way your organisation should be making use of cloud services. By this approach, you treat your cloud infrastructure as it if were code, and apply the same kinds of techniques and tools that software engineers apply to code: automation, systematic testing, distributed development, version control, and so on.
Ever since I can remember, I’ve always wanted to know. As a child, I’d question many things around me, demanding answers and explanations, and on occasion being told to be quiet when answers weren’t easily given – or not believed. Over time I got better and faster at finding answers for myself. Then, somewhere along the way, the search process changed. Data from accelerometers, heat and humidity components, cameras and microphones that I interact with all flows in to my personal information feed that I can access through various cloud based apps. While it may just seem like seamless flows of numeracy, I’m hopeful about finding answers more easily and making better decisions. And my ten year-old self can’t help but ask, why did this happen and why so fast?
Learn how to interconnect cloud services to practically any device using Docker, Weave and Raspberry Pi.
Programming using many different cloud providers’ APIs to achieve a task can be a difficult and time-consuming task. Therefore developers came up with a great idea to get around this problem. Apache Libcloud is a python library that abstracts differences between cloud provider APIs and allows users to manage their cloud resources using a unified and easy to use interface.  
This post is the seventh (and last) in a series about using the Virtual Data Centre API. Here sparkline graphs are used to display CPU loading data.
This post is the sixth in a series about using the Virtual Data Centre API. The Python program developed here combines a dashboard widget (as in previous posts) with a physical control box (buttons and LEDs) using a Raspberry Pi computer.


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