>>  http://evilpiepirate.org/git/linux-bcache.git/tree/Documentation/bcache.txt

> 
> no, I was explicitly testing random I/O writes of 4k blocks, 
> no sequential writing. With a file of 1000 GB it does work, but
> if I use a 10000 GB file, it seems to fail. I would expect, that
> the size should not really matter here, at least until the cache
> is filled up.


When the SSD gets too slow it will get by-passed by bcache. The tunable is in 
the document. Though if memory serves it's a latency of 20ms for writes which 
is probably way too short since SSDs can easily take 1-5 seconds when they have 
to resort to heavy lifting.



What you should do is turn off RAID controller READ caching entirely. And turn 
OFF writeBACK-caching for the SSD-based LUN(s) at said controller that are 
being used as bcache caching devices.

It would be helpful is you elaborated as to the HBA and SSD drives you are 
using. BTW doing RAID across the SSDs being used for cache is rather pointless 
IMO. You're shortening their life, adding unnecessary write IOPs. It's a cache. 
It's supposed to fail. Bcache will(?) properly handle a busted SSD.

Cache is only useful for absorbing sudden spikes in IOPs or for highly 
localized and frequently re-used blocks. It's not intended to magically improve 
the underlying storage by 10-100x under a load that can't be sustained by said 
layer. Big $$$ SANs have lots of cache but at some point you will reach the 
saturation point and everything slows to HDD speed.

I also wouldn't futz with the EXT4 settings you had posted previously while 
doing  benchmark runs because I expect it gets in the way and makes performance 
worse than if the block stream was less chunky. Only once you have defined a 
realistic sustained workload and know how often and how fast journaled-to-SSD 
writes (bcache write-back) can reasonably be de-staged would I revisit those 
tuning parameters and see if there is any merit to them.

Personally I put NVRAM boards in my servers to be filesystem journals and MD 
mirror maps. They're incredibly cheap.
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