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nyserit
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ESXi 4.0 RAID5 Datastore configuration.

I was wondering what the recommended way to configure a RAID5 Array with approximately 5TB DAS available, for an ESXi 4 host that will have a couple Windows 2003 VMs, a couple Windows XP VMs, and a few Linux VMs. Would breaking the array into many smaller virtual disks for each VM or a couple larger virtual disks for VMs to share be the best approach?

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J1mbo
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Not really, as they're all om the same underlying spindle set. It's quite a dangerous configuration if extents are on different disk sets, as failure of any one will wipe the lot!

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AndreTheGiant
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You need to create more virtual disk smaller than 2TB - 512B (the disk size limit of ESX).

On the community you can found diffent post about LUN sizing...

but in you case all virtual disks will be on the same physical disks...

so you can use also big (for example 1 TB) trunk size.

Andre

Andrew | http://about.me/amauro | http://vinfrastructure.it/ | @Andrea_Mauro
J1mbo
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To add, as it's presumably on a single underlying array, multiple just-user-2TB RAID-5 LUNs could be created. Then create a datastore with each LUN being added as an extent, so that the entire volume is available as a flat address space.

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nyserit
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Thanks for the replies.

So, I have 3 virtual disks at ~1.5TB each, I can add one as a datastore and two as extents? Is there any downside to added others as an extent?

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J1mbo
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Not really, as they're all om the same underlying spindle set. It's quite a dangerous configuration if extents are on different disk sets, as failure of any one will wipe the lot!

Please award points to any useful answer.

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AndreTheGiant
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Usual extent are a bad idea cause if you loose the first datastore you loose all.

But in your case physical disks are the same for all virtual disks, so you can use extent with no particular problem. Or also use multiple datastore Smiley Happy

Andre

Andrew | http://about.me/amauro | http://vinfrastructure.it/ | @Andrea_Mauro
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nyserit
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I have configured it with 1 datastore and 2 extents, and now have a 4.51TB datastore to use, which is exactly what I was looking for. Thank you both very much!

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