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Task parallelism is the process of running tasks in parallel. Task parallelism divides tasks and allocates those tasks to separate threads for processing. It is based on unstructured parallelism. It means the parallel work unit may start and finish in places scattered according to the the executing of the program.
Have you ever found yourself refactoring your code and making the same or similar changes in multiple locations? Maybe you thought about making a regular expression so you could search and replace, but the effort to do that was too great? Eventually you probably resigned yourself to the time-intensive, error prone task of going through the code manually.
There’s an incredible built-in mechanism in Windows called Performance Counters that allows you to follow a whole lot of useful metrics. It’s easy to use, comes free, and perhaps not used as much as it deserves.
In this blog entry and some future ones I will be showing off functionalities that our new GC perf infrastructure provides. Andy and I have been working on it (he did all the work; I merely played the consultant role). We will be open sourcing it soon and I wanted to give you some examples of using it and you can add these to your repertoire of perf analysis techniques when it’s available.
In our application, daily, we are using Application Insights to report all requests to and from us so we could monitor the actual status of a system. Thanks to that we are sure that our clients wouldn’t experience unpleasantness because of not working or slowly working application. To look at the body of each request and response, we store them in a separate Log database. As long as the application growth, we have more and more users and regions to handle we thought it would be easier for us to have everything in one place. So we planned to involve everything in ApplicationInsights.
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