Tag: .NET

The C# nullability features introduced in C#8 help you minimize the likelihood of encountering that dreaded System.NullReferenceException. Nullability syntax and annotations give hints on whether a type can be nullable or not. Better static analysis is available to catch unhandled nulls while developing your code. What’s not to like? Introducing explicit nullability into an existing code base is quite an effort. There’s much more to it than just sprinkling some ? and ! throughout your code. It’s not a silver bullet either: you’ll still need to check non-nullable variables for null.

For close to two years now, I’ve had SpeakerTravel up & running. It’s a tool that helps conference organizers to book flights for speakers. You invite speakers, they pick their flight of choice (within a budget the organizer can specify), and the organizer can then approve and book the flight with a single click. In this post, I want to go a bit into the process of building this tool. Why I started it in the first place, how it works, a look at it from the business side, and maybe a follow-up post that covers any questions you may have after reading.

If you’re building workloads on Azure Functions, there’s a good chance you’ve looked at building custom bindings. Custom bindings can greatly reduce the boilerplate code you have to write in an Azure Function, so you can focus on the logic in your function instead. There are various examples of custom bindings out there, including several that I wrote while working on Indexing and searching NuGet.org with Azure Functions and Search. And then .NET 5 came, along with the new Azure Functions .NET Isolated Worker. Not a lot of documentation out there, and custom bindings don’t seem to work anymore…

In this post, let’s see how you can run a .NET Core / .NET 5 application as a service on Linux. We’ll use Systemd to integrate our application with the operating system and make it possible to start and stop our service, and get logs from it. To build my supply chain attack with .NET, I needed to host a DNS server to capture the hostnames sent to me. Let’s use that as an example!

For a couple of months now, I’ve been pondering about what tools are at your disposal in .NET to help build and execute a supply chain attack. My goal was to see what is available out there, and what we, as .NET developers, should be aware of. Prepare for a long read! Now, forget that short introduction, and let’s start anew…

Early December 2020, we released JetBrains Space. Along with it, we built a Kotlin SDK and a .NET SDK. In this post, I want to walk you through the process of building that .NET SDK. This is another half-book blog post, so I’ve included a table of contents for you to jump to the parts you may be interested in. I’ve tried my best to build up the story, so of course, reading this post in full is highly appreciated. Let’s start with the basics…

Chances are you keep a personal calendar, maybe a family calendar, and a work calendar. Working from home, it’s super important to keep these calendars more or less in sync. Colleagues book meetings because your work calendar shows you’re available, while in reality you’ve planned to do some errands or maybe pick up your kids from school.

Last week, I came across the following question: “Is there an async producer/consumer collection these days in .NET?” Why yes, there is! Using System.Threading.Channels, we can create producer/consumer pairs, and we can even chain them together in a pipeline. In this post, I will try to explain concurrency, producer/consumer, and System.Threading.Channels concepts using a practical example, to refresh our collective memories.

Yesterday, Aaron Stannard posted some awesome news for the .NET community: the introduction of Sdkbin. Sdkbin is targeted at solving the OSS sustainability problem by automating the majority of the sales, fulfillment, licensing, and accounting needed to sell libraries, frameworks, and support plans. It’s (roughly speaking) an App Store, delivered as a NuGet feed. This seems like a great idea, and most of all, one that is needed.

In this blog post, we’ll see how we can use Azurite, an open source Azure Storage API compatible server (emulator), in Docker, and how to run it from JetBrains Rider. We can use Azurite in Docker to keep Azure Storage data local to a solution, and, for example, have different blobs and queues for different Azure Functions projects. Ever since I started playing with Azure back in 2008, I’ve been using the Azure Storage Emulator to have a local storage emulator to develop with. It provides a local environment for testing applications that use Azure blob and/or queues.