Since we shipped .NET Standard 2.0 about a year ago, we’ve shipped two updates to .NET Core 2.1 and are about to release .NET Core 2.2. It’s time to update the standard to include some of the new concepts as well as a number of small improvements that make your life easier across the various implementations of .NET.
I find it interesting, but predictable, that .NET Framework 4.8 will stay on .NET Standard 2.0. At this point, I would consider only .NET Core and Mono/Xamarin to be following the standard going forward.
OWASP illustrates that developers keep making the same mistakes over and over again, but what about more esoteric vulnerabilities?
In this session Barry will take you beyond SQL injection covering some of the code behind now fixed ASP.NET vulnerabilities. By the end of the session you should be poring through your own code looking for problems with dictionaries, compression, encryption and more
This is a session given by Asbjørn Ulsberg at Nordic APIs 2018 Platform Summit on October 24th, in Stockholm, Sweden.
In the new brave world of decoupled and autonomous microservices, there’s a lot of knowledge, best practices and attention given to APIs. But once you start integrating these APIs in a UI, it quickly becomes a monolith of highly coupled components that replicate a lot of the functionality provided in the underlying APIs.
As everyone probably knows and agrees to by now, monoliths are not a design goal. By making your UI compositional through hosted views and by moving some of the business logic from the client to the server through the use of hypermedia, you can achieve full vertical integrations that are horizontally decoupled in a microservice fashion all the way from the persistence layer and up to the user interface.
We’re excited to announce today the release of ML.NET 0.7 – the latest release of the cross-platform and open source machine learning framework for .NET developers (ML.NET 0.1 was released at //Build 2018). This release focuses on enabling better support for recommendation based ML tasks, enabling anomaly detection, enhancing the customizability of the machine learning pipelines, enabling using ML.NET in x86 apps, and more.