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Automated Machine Learning (AutoML) is a field of study and technology aimed at automating the end-to-end process of designing and building machine learning models. I explore the basics and key concepts of AutoML using Amazon's SageMaker Autopilot.

Recently Amazon OpenSearch Serverless was announced that allows the use of the same service but will automatically scale and where you pay for the resources consumed, this is split over the cost of Compute and cost of Storage.

Infrastructure as Code (IaC) is an important part of Cloud Infrastructure, by utilizing flexible cloud resources, preferably serverless, then it opens up the possibility of a pipeline to create a full Developer environment per Branch, and then destroy it again after the Pull Request is merged.

Machine Learning can be intimidating and unapproachable, but with AWS you have access to many services where no ML experience is required. With these you can analyse images, text, video, perform translation and more.

PhantomJS is a tool that should be considered for this regression checking, with only simple simple scripting it can be put into your Continuous Integration system and you have a way of catching regression early and before it goes for QA.

If you have a need to unit test a helper method which does a call to Action then you will hit an issue due to how HtmlHelper is not mockable and the call to Action will end up going through many layers and actually calling an action.