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Predicting Application Problems from the Database

Ed Pollack has a pattern for rooting out application problems based on database activity:

We can approach I/O file stats very similarly to how we handled row counts above: Regularly collect data, store it in a reporting table, and then run analytics against it as needed. Since these database metrics are reset when SQL Server services restart, we need to collect a bit more often. We’ll also want to collect often enough to be able to correlate changes to ongoing application activity. Hourly is typically an acceptable collection frequency, but your environment may lend itself to the more frequent or less frequent collection.

What’s nice is that you can get a long way with heuristics and domain knowledge, even before applying data science techniques.