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Home/ Questions/Q 704629
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Editorial Team
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Editorial Team
Asked: May 14, 20262026-05-14T03:57:46+00:00 2026-05-14T03:57:46+00:00

I am developing large data collecting ASP.Net/Windows service application-pair that uses Microsoft SQL Server

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I am developing large data collecting ASP.Net/Windows service application-pair that uses Microsoft SQL Server 2005 through LINQ2Sql.
Performance is always the issue.

Currently the application is divided into multiple larger processing parts, each logging the duration of their work. This is not detailed and does not help us with anything. It would be nice to have some database tables that contain statistics that the application itself collected from its own behavior.

What logging tips and data structures do you recommend to spot the parts that cause performance problems?

Edit:
Mostly I am looking for parts of the application that can cripple the whole system when excessively used. There are peaks during the day when some parts of the application are under heavy load. Some advanced logging would help me isolate the parts that need more attention and optimizing.

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  1. Editorial Team
    Editorial Team
    2026-05-14T03:57:47+00:00Added an answer on May 14, 2026 at 3:57 am

    Don’t use logging for this, use Performance Counters instead. The runtime impact of performance counters is minor and you can simple have them always on. To collect and monitor the performance, you can rely on the existing performance counters infrastructure (perfmon.exe, logman.exe, relog.exe etc).

    I personally use XML and XSLT to generate the counters. I can then decorate all my code with performance counters tracking functions being run, average call duration time, number of executions, rate of executions per second and so on and so forth. Good choice of counters will give an immediate, accurate, performance picture much faster than logging can. While logging can give more insight on certain event paths (ie. order of events that lead to certain state), logging can seldom be ‘always on’ as the impact on performance is significant, not only on performance but most importantly on concurrency as most existing logging infrastructures add contention.

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