A .NET Core tool for real-time performance monitoring of applications, from single processes to microservices, via a web dashboard.
PerformanceMonitor is a .NET Core tool that enables developers to monitor application performance in real time through a web dashboard. It collects metrics like CPU usage, memory consumption, HTTP requests, and garbage collection via an installable class library, providing insights for both simple applications and complex microservices architectures. The tool helps identify performance bottlenecks and optimize resource usage across .NET-supported platforms.
.NET Core developers and teams building applications ranging from single-process apps to distributed microservices who need detailed performance insights. It is particularly useful for those managing multi-service environments and requiring cohesive monitoring across processes.
Developers choose PerformanceMonitor for its seamless integration, real-time visualization, and ability to group multiple processes under a single application view. Unlike generic monitoring tools, it is tailored for .NET ecosystems, offering customizable metrics and microservice-aware tracking without requiring complex setup.
.NET Core Application Performance Monitor
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Runs on all .NET-supported platforms and monitors any application type, from console to web apps, as stated in the README's Key Features.
Allows grouping distinct processes or microservices under a single logical application for cohesive performance analysis, enabling easy tracking of complex architectures.
Web application displays live-updating graphs for CPU and memory usage, providing immediate insights without manual refresh, as shown in the visualization section.
Supports customizable sampling and transmission rates, plus selective tracking of metrics like exceptions and GC events via simple API calls.
Requires Visual Studio to run the performance monitor, limiting cross-platform development and teams using alternative IDEs.
Uses a SQL database on Docker for data storage, adding infrastructure complexity and deployment steps compared to lightweight embedded solutions.
Only CPU and memory graphs update live; other tables for events like exceptions require page refresh, reducing interactivity for non-core metrics.