While metrics help identify the occurence of anomalous behavior, they offer little visibility into what went wrong. Why does my application have anomalous behavior? For known limitations with dotnet-counters, look at the open issues on GitHub.
In the example below, we see the CPU utilization and working set memory of our application jump up when we point a load generator at our web application.įor detailed instructions on how to use this tool, look at the dotnet-counters readme.
NET global tool by running the following commandĭotnet tool install -global dotnet-counters -version 1.0.3-preview5.19251.2 In 3.0-preview5, we are introducing a new command-line tool for observing metrics emitted by.
Unfortunately, the lack of a tool like Performance Monitor (perfmon) made it difficult to consume these metrics in real time. Additionally, unlike perf counters, they are also usable in low privilege environments (like xcopy deployments). NET Core via the EventCounter API.ĮventCounters offer an improvement over Windows perf counters as these are now usable on all OSes where. Instead, we had introduced a new way of emitting metrics in. Metrics (or time-series) data allow you to observe the state of your system at a high-level. Metrics are a representation of data measures over intervals of time. These are just some of the classes of problem you can pro-actively identify with metrics. Other times, certain problematic code paths may result in a spike in CPU utilization. Often times an application can slowly start leaking memory and eventually result in an out of memory exception.
These runtime features help you answer some common diagnostic questions you may have: NET runtime that make it easier to diagnose and solve performance problems. NET Core 3.0, we are introducing a suite of tools that utilize new features in the.
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