This article was initially published by Jonathan Davies in June, 2015:
"How many VMs can coexist within a single LUN?"
An important consideration when planning a deployment of VMs on XenServer is around the sizing of your storage repositories (SRs). The question above is one I often hear. Is the performance acceptable if you have more than a handful of VMs in a single SR? And will some VMs perform well while others suffer?
In the past, XenServer's SRs didn't always scale too well, so it was not always advisable to cram too many VMs into a single LUN. But all that changed in XenServer 6.2, allowing excellent scalability up to very large numbers of VMs. And the subsequent 6.5 release made things even better.
The following graph shows the total throughput enjoyed by varying numbers of VMs doing I/O to their VDIs in parallel, where all VDIs are in a single SR.
In XenServer 6.1 (blue line), a single VM would experience modest 240 MB/s. But, counter-intuitively, adding more VMs to the same SR would cause the total to fall, reaching a low point around 20 VMs achieving a total of only 30 MB/s – an average of only 1.5 MB/s each!
On the other hand, in XenServer 6.5 (red line), a single VM achieves 600 MB/s, and it only requires three or four VMs to max out the LUN's capabilities at 820 MB/s. Crucially, adding further VMs no longer causes the total throughput to fall, but remains constant at the maximum rate.
And how well distributed was the available throughput? Even with 100 VMs, the available throughput was spread very evenly -- on XenServer 6.5 with 100 VMs in a LUN, the highest average throughput achieved by a single VM was only 2% greater than the lowest. The following graph shows how consistently the available throughput is distributed amongst the VMs in each case:
• Host: Dell R720 (2 x Xeon E5-2620 v2 @ 2.1 GHz, 64 GB RAM)
• SR: Hardware HBA using Fibre Channel to a single LUN on a Pure Storage 420 SAN
• VMs: Debian 6.0 32-bit
• I/O pattern in each VM: 4 MB sequential reads (O_DIRECT, queue-depth 1, single thread). The graph above has a similar shape for smaller block sizes and for writes.
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