Roundup #52: .NET Core and systemd, System.Threading.Channels, screencastR, Configuration Pitfalls

Here are the things that caught my eye recently in .NET.  I’d love to hear what you found most interesting this week.  Let me know in the comments or on Twitter.

.NET Core and systemd

In preview7 a new package was added to the Microsoft.Extensions set of packages that enables integration with systemd. For the Windows focused, systemd allows similar functionality to Windows Services, there is a post on how to do what we discuss here for Windows Services in this post. This work was contributed by Tom Deseyn from Red Hat. In this post we will create a .NET Core app that runs as a systemd service. The integration makes systemd aware when the application has started/is stopping, and configures logs to be sent in a way that journald (the logging system of systemd) understands log priorities.

Link: https://devblogs.microsoft.com/dotnet/net-core-and-systemd/

An Introduction to System.Threading.Channels

I’ve recently begun making use of a relatively new (well, it’s a little over a year old at the time of writing) feature called “Channels”. The current version number is 4.5.0 (with a 4.6.0 preview also available as pre-release) which makes it sound like it’s been around for a lot longer, but in fact, 4.5.0 was the first stable release of this package!

In this post, I want to provide a short introduction to this feature, which I will hopefully build upon in later posts with some real-world scenarios explaining how and where I have successfully applied it.

Link: https://www.stevejgordon.co.uk/an-introduction-to-system-threading-channels

screencastR – Simple screen sharing app using SignalR streaming

In this article, we will see how to create simple screen sharing app using signalR streaming. SignalR supports both server to client and client to server streaming. In my previous article , I have done server to client streaming with ChannelReader and ChannelWriter for streaming support. This may look very complex to implement asynchronous streaming just like writing the asynchronous method without async and await keyword. IAsyncEnumerable is the latest addition to .Net Core 3.0 and C# 8 feature for asynchronous streaming. It is now super easy to implement asynchronous streaming with few lines of clean code. In this example, we will use client to server streaming to stream the desktop content to all the connected remote client viewers using signalR stream with the support of IAsyncEnumerable API.

Link: https://jeevasubburaj.com/2019/08/13/screencastr-simple-screensharing-app-using-signalr-streaming/

Avoiding ASP.Net Core Configuration Pitfalls With Array Values

ASP.NET Core continues to improve on the legacy of the .NET Framework. Our team is impressed with its performance and excited about future possibilities, but change is seldom a smooth transition. In this post, I’ll explain a pitfall you may run into using the newest configuration model in .NET Core and options to mitigate the issue.

Link: https://rimdev.io/avoiding-aspnet-core-configuration-pitfalls-with-array-values/

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Custom Metrics to AWS CloudWatch from ASP.NET Core

CloudWatch Custom Metrics

I was playing around with AWS CloudWatch and was curious to send custom metrics from ASP.NET Core. Specifically the execution time of an HTTP request.

AWS SDK

I created a simple middleware that starts a StopWatch before calling the next middleware in the pipeline. When it returns, stop the StopWatch and send the data to CloudWatch.

First is to add the relevant NuGet packages.

Configuration

If you’ve never used the AWS SDK/Packages, I recommend checking out my post on Configuring AWS SDK in ASP.NET Core. It goes over creating a named profile to store your AWS credentials and using appSettings or Environment variables to pass them through to ASP.NET Core.

Middleware

Next is to create a simple middleware using the SDK. The middleware is having the IAmazonCloudwatch injected into the constructor. In the Startup’s ConfigureServices is where this is configured.

We’re simply calling the PutMetricDataAsync with a list of one MetricDatum. It contains the metric name, value, unit, timestamp, and dimensions.

Startup

As mentioned, in order to use the AWS SDK and the IAmazonCloudWatch in the middleware, you can use the AddDefaultAWSOptions and AddAWSService<IAmazonCloudWatch> to ConfigureServices to register the appropriate types.

Results

If you look in CloudWatch, you can now see the new custom metrics we’ve published.

Next

Before you start using this in a production environment, there are a couple of glaring issues.

First, sending the metrics to AWS, although incredibly fast should be handled outside of the actual HTTP request. this can be done completely asynchronously from the actual request. There is no point in delaying the HTTP response to the client. To solve this, we’ll add a queue and do it in a background service.

Secondly, some of the cost associated with CloudWatch is based on the number of API calls. This is why there is a List<MetricDatum> in the PutMetricDataRequest. It allows you to send/batch multiple metrics together to limit the number of API calls.

This is a better solution is to collect PutMetricDataRequest separately and send them in batch in a background service.

More on that coming soon.

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Roundup #51: .NET Core 3.0 launches at .NET Conf, .NET Standard adoption, Nullable Reference Types, Cake on Linux, Logging in ASPNET Core

Here are the things that caught my eye recently in .NET.  I’d love to hear what you found most interesting this week.  Let me know in the comments or on Twitter.

.NET Core 3.0 launches at .NET Conf

.NET Conf is a FREE, 3 day virtual developer event co-organized by the .NET community and Microsoft. This year .NET Core 3.0 will launch at .NET Conf 2019! Come celebrate and learn about the new release. You won’t want to miss this one.

Link: https://www.dotnetconf.net/

Update on .NET Standard adoption

It’s about two years ago that I announced .NET Standard 2.0. Since then we’ve been working hard to increase the set of .NET Standard-based libraries for .NET. This includes many of the BCL components, such as the Windows Compatibility Pack, but also other popular libraries, such as the JSON.NET, the Azure SDK, or the AWS SDK. In this blog post, I’ll share some thoughts and numbers about the .NET ecosystem and .NET Standard.

Link: https://devblogs.microsoft.com/dotnet/update-on-net-standard-adoption/

Try out Nullable Reference Types

With the release of .NET Core 3.0 Preview 7, C# 8.0 is considered “feature complete”. That means that the biggest feature of them all, Nullable Reference Types, is also locked down behavior-wise for the .NET Core release. It will continue to improve after C# 8.0, but it is now considered stable with the rest of C# 8.0.

Link: https://devblogs.microsoft.com/dotnet/try-out-nullable-reference-types/

How to build with Cake on Linux using Cake.CoreCLR or the Cake global tool

In this post I show two ways to use the Cake build system to build .NET Core projects on Linux: using the Cake.CoreCLR library, or the Cake.Tool .NET Core global tool.

Link: https://andrewlock.net/how-to-build-with-cake-on-linux-using-cake-coreclr-or-the-cake-global-tool/

Logging, Metrics and Events in ASP NET Core – Martin Thwaites

Providing decent monitoring of your applications has always been considered the boring part of development, with tons of boilerplate code, and making upfront decisions around how it will be done, or retrofit afterwards. However, with dotnet core, things have changed, it’s never been easier to implement effective visibility into how your application is performing in production.

In this session I will cover the fundamental differences between Metrics and Logs, and Events and look at where one is useful over the other.

We’ll look at some of the things Microsoft has done in dotnet core to make logging easier, and some of the third-party libraries and tools that aim to make it easier to navigate.

We’ll cover tools like Serilog and Log4Net, along with AppMetrics for capturing application information. We’ll then take a quick look at Grafana, and see how we can make some sense of that information. Finally, we’ll look at Honeycomb.io and how they’re providing actionable insights for distributed systems using events, enabling testing in production.

Link: https://www.youtube.com/watch?v=Fvu2DJU-dFg

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