#433 Processing data in parallel using Channels

Processing data in parallel using Channels

Thanks to the Task Asynchronous Programming model writing asynchronous code in .NET is usually straightforward. One feature that rarely gets its spot in the limelight is Channels.

Getting Started with C# and InfluxDB open source time series platform (sponsor)

If your data changes every minute, MySQL isn’t going to cut it. Learn how to level up your time-series data analysis with a time-series database. This article covers how to set up open-source InfluxDB using C#, reading and writing data, and how to handle updates. Read the guide.

A new wave of analyzers in .NET 8

Analyzers did become an integral part of the .NET ecosystem. Their main responsibility is to find potential code issues and warn you. Often times this comes even with potential fixes you can directly apply.

ASP.NET Core Response Caching

In this post we are going to take a quick look at the built in Response Caching feature in ASP.NET Core.

How to make the fastest .NET serializer

Serializer performance is based on both the “data format specification” and the “implementation in each language”. For example, while binary formats generally have an advantage over text formats (such as JSON), it is possible to have a JSON serializer that is faster than a binary serializer.

Detect and Remove Dead Code with Roslyn

Any large project will create lots of dead code (code that is not used by the application) overtime. How to identify these dead code and remove them are a challenge work to do.

Also, Eric Lippert (one of the most influential members of C# team) recently left Facebook. It doesn't look like he'd be coming back to Microsoft. But hopefully, he gets to write more! 🤞


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