I don’t have the test results at hand, but the problems weren’t so much that the host CPU usage was too high for a given workload, but that in CPU starvation conditions, the IOOPs dropped off dramatically. This may be tied to the specific hardware I was using (and the corresponding vendor drivers), but that was my experience
In my environment, the workload is alternately CPU and IO intensive and there is no good way to predict when each condition will occur. As with any system tied to market data, the only thing you can say for sure is that the work comes in bursts. On the application level there is logic to coalesce and drop work beyond the physical capacity so that latency is not sacrificed too much, but certain parts cannot be dropped.
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Really!? You’re seeing LESS *net* host CPU usage from storing your data on a SAN with SSDs than you are with NVMe disks, for the same I/O performance?
If so, that’s fascinating and useful data. Not many of us can mount that size test system, and being much more than casually involved with NVMe (cough), that would be an interesting data point.
Then again… maybe the way our database tables are constructed, once things are set there’s relatively little I/O? (note use of word *relative*)… hot data stays hot, for example…
There should be an interesting application for storage tiering here.
Sorry… but I’m sure we all like to play architect in somebody else’s sandbox occasionally. It’s the dilettante in us.
Peter
OSR
@OSRDrivers
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