C# Programming Language Articles

Code metrics have become a standard feature in modern development environments, yet their implementation and interpretation often leave much to be desired. While Visual Studio and .NET provide comprehensive code metrics analysis, the way these metrics are configured, presented, and (more critically) acted upon reveals a fundamental disconnect between measurement and meaningful improvement.

What code metrics actually measure, how to configure them properly, and (more importantly) why blindly following thresholds without understanding context is, frankly, a recipe for misguided refactoring efforts that waste your team’s time and actively damage your codebase.

Microsoft wants you to believe .NET 10 is boring. They’re right — and that’s the best news we’ve had in years.

.NET 10 is here, and for once, Microsoft didn’t oversell it. LTS support through 2028, JIT improvements that actually matter, and C# 14 features that won’t rewrite your architecture. Here’s what you need to know before migrating.

.NET’s yearly rhythm has become a symbol of stability — yet also a source of pressure. The release cycle paradox describes the tension between predictability and exhaustion: a release schedule that keeps the ecosystem healthy, but teams constantly catching up.

With .NET 10 on the horizon, developers must learn to navigate this rhythm rather than fight it.

It begins like many stories in software: a well-intentioned developer joining a project, determined to do things properly. You arrive at a codebase that has grown organically, perhaps even chaotically. You decide you will bring order. You set up unit testing, you configure continuous integration, you measure code coverage. You write dozens or hundreds of tests. Every public method is touched, every branch is at least executed. The dashboard lights up green. You feel, quite frankly, on top of things.

Then one day, production breaks under your watch

Let’s be honest: health checks are the broccoli of .NET projects. Everyone says they have them, but nobody’s excited to eat their greens. What starts as a humble SELECT 1 in a try/catch quickly explodes into a wild jungle of scripts, copy-pasted connection strings, and endpoints that only half the team remembers. Sure, it works—until it doesn’t. And when it breaks, it’s never at a good time.

While you’re busy optimizing database queries and adding cache layers, thousands of string searches per second are quietly eating your CPU budget. The problem isn’t visible in your APM dashboard because it’s distributed across every request. But it’s there. Compounding. Scaling linearly with load.

I discovered this the hard way when a log processing API started choking under production traffic. The bottleneck? String validation and sanitization. The fix? A .NET 8 feature that delivered a 5x performance improvement and let us shut down servers instead of adding them. And it’s gotten even better in .NET 9 and 10.