Data Science is an emerging field that is plagued by lurid, often inconsequential reports of success. The press has been all too happy to predict the future demise of the human race. But sifting through chaff, we do see some genuinely interesting reports of work that affects both bottom-line profit and top-line revenue. Location discovery service Foursquare, using a range of data science techniques, predicted that Chipotle’s Q1 2016 revenue would drop by 30%, compared to the previous year (Chipotle is a US fast-food outlet) .
Cloud-Native, a collection of tools and best practices, disrupts the ideas behind traditional software development. I am a firm believer of the core concepts, which include visibility, repeatability, resiliency and robustness.
The idea begins in 2015 when the Linux Foundation formed the Cloud-Native Computing Foundation. The idea was to collect the tools and processes that are often employed to develop cloud-based software.
However, the result was a collection of best practices which extend well beyond the realms of the cloud. This post introduces the essential components: DevOps, continuous delivery, microservices and containers.
The terms “Cloud” or “Cloud Services” have become so laden with buzz that they would be happy to compete with Apollo 11 or Toy Story. But the hype often hides the most important aspects that you need to know. Like how it works, or what you can do with it. This is the first of several introductory pieces that focus on the very basics of modern applications.