1 Analysis of VDI Storage Performance During Bootstorm Introduction Virtual desktops are gaining popularity as a more cost effective and more easily serviceable solution. The most resource-dependent process for many virtual desktop pools is the bootstorm. Enterprises deploying a virtual desktop infrastructure (VDI) environment have a variety of choices when deciding what sort of storage to deploy for their VDI s. Solid State Storage is known to dramatically decrease boot times compared to hard disk drives (HDD), and may be a good storage choice for a pool of Virtual Machines (VMs). Demartek evaluated the performance of Internal HDD, Fibre Channel (FC) HDD, and Fibre Channel solid state drives (SSD) under bootstorm conditions and compared VM boot times, server load, and disk throughput performance metrics. In addition, Demartek compared results for different cache configurations and host bus adapter (HBA) queue depths. This evaluation was conducted in the Demartek lab in Colorado. Executive Summary and Key Findings Demartek evaluated the differences SSD and HDD storage had on bootstorm performance, and analyzed the effects of queue depth and cache configuration on that performance. For Fibre Channel SSDs we found that: Average VM boot time ranged from 2.3x to 4.2x faster than any HDD storage configuration tested. CPU usage ranged from 16% to 105% higher than any HDD storage configuration tested. Lower drive latency during the bootstorm enabled VM boots to be initiated 1.6x to 6.9x faster than any HDD storage configuration tested.
2 Page 2 of 26 For Internal HDDs we found that: Doubling the controller cache size from 512 MB to 1024 MB decreased average boot time by 18%. For Fibre Channel host bus adapters (HBAs) we found that: Increasing the HBA queue depth from 32 to 254 decreased HDD boot times by 33% and decreased SSD boot times by 18%. Increasing the HBA queue depth from 32 to 254 increased HDD CPU usage by 54% and increased SSD CPU usage by 6%. We recommend that enterprises consider SSDs for VDI storage. If HDDs must be used, a larger cache and increased HBA queue depth will greatly increase performance.
3 Test Configuration Analysis of VDI Storage Performance During Bootstorm Page 3 of Windows 7 VMs were set up in VMware vsphere 5.1 on the internal HDDs. Each VM had a startup script which recorded the time in a unique file and then transferred the file over to a server. These VMs were updated as of 5/14/13, and then cloned to storage on the FC SSD and FC HDD drives. Scripts accessing the ESXi console recorded the time and then sent commands to power on a VM. ESXTOP was used to record server load and disk I/O data. Script Delays When ESXi software sent commands to start all 90 VMs at the same time, the software gave errors when attempting to power on some of the VMs. Most of the errors were due to loading shared libraries. As a result, not all VMs would be issued the power-on command by ESXi software. Adding a slight delay to the VM power-on commands led to all VMs booting properly. Multiple attempts at delaying power-on commands were tried for each configuration until the minimum time required was found. This time varied for each storage
4 Page 4 of 26 configuration. This fact led to the conclusion that ESXi software libraries wait for a response from storage while powering-on VMs. Lower latency storage configurations made it possible for the ESXi software to handle more boot requests at the same time without denying requests. Caching Two different internal HDD configurations were tested, one with a 512MB cache RAID controller and one with a 1024MB cache RAID controller replacing the original RAID controller. The Fibre Channel HDD configuration included a 1744 MB data cache. During the first test it was configured for read-only caching, and during the second test it was configured for write-back caching as well. Write back caching is not recommended for usage unless there is a backup battery or data can afford to be lost. Queue Depth The initial tests using Fibre Channel storage used the default queue depth of 32 for the FC HBA. During the second round of tests, the queue depth was increased to 254. Data Collection Server load and disk I/O data was collected in intervals of 15 seconds using ESXTOP. Boot-related timestamps gathered by scripts were rounded to the same 15 second intervals for graph production.
5 Internal HDD Analysis of VDI Storage Performance During Bootstorm Page 5 of 26 We found that the Internal HDDs had a difficult time keeping up with demand. While doubling the read/write cache size from 512MB to 1024MB offered noticeable improvement, some users would have to wait over 8 minutes before their desktop booted. The server CPU was not over-taxed during the bootstorm, topping out at 41% CPU utilization while using the 1024MB cache. Taken to Issue Start Commands (mm:ss) Taken for a VM to Boot Minimum Maximum Average Maximum CPU Utilized Maximum IOPS 512MB Cache 1:59 00:53 09:40 04:30 37% 5, MB Cache 1:47 00:34 08:20 03:42 41% 5,842 The graphs below show the results averaged over three tests for each configuration. Processor peaked slightly higher for the larger cache, while IOPs and memory usage only varied slightly.
8 Page 8 of 26 However, we found that bootstorms are a cache-friendly workload. Increasing cache size to 1024MB enabled the ESXi software to handle VM start requests faster, which lowered the number of VMs in queue and caused the queue to be completed faster. Boot times were reduced for all VMs by an average of 18%. VMs in Queue VMs in Queue MB Cache 1024 MB Cache
9 Page 9 of 26 Increasing cache size to 1024MB enabled the first VMs to complete boot sooner, giving this configuration a head start. In addition, there was a peak of 8 VMs completing boot in 15 seconds with the 1024MB cache, while the 512MB cache typically peaked at 6 VMs completing boot in 15 seconds. Boots were completed faster with the larger cache, cutting down on boot-time for all VMs. VMs Booted VMs Booted MB Cache 1024 MB Cache
10 Fibre Channel HDD Analysis of VDI Storage Performance During Bootstorm Page 10 of 26 The initial Fibre Channel HDD test with queue depth 32 and write through did not have near the same performance as the internal HDD configuration. However, enabling writeback caching and increasing queue-depth to 254 for the second set of tests improved performance dramatically, resulting in a 33% faster boot time on average than the queue depth 32 configuration. This more than brought the performance to levels on par with internal HDDs. Average boot times for the final tests were 9% faster than for the internal HDDs. Taken to Issue Start Commands (mm:ss) Taken for a VM to Boot Minimum Maximum Average Maximum CPU Utilized Maximum IOPS Queue Depth 32, 1744MB Read Cache Queue Depth 254, 1744MB Read/Write Cache 04:36 00:53 11:20 05:02 25% 3,278 01:38 00:41 06:42 03:22 38% 5,669 An analysis of read and write operations can help us determine the source of the bulk of the performance improvements. Writes per second increased from 354 to 497 when the caching was enabled and queue depth was increased to 254, a 40% improvement. Reads/sec increased from an average of 2246 to 3010 when queue depth increased to 254, a 34% improvement. Read caching was enabled for both tests, so the improvement in reads/sec is entirely due to the increase in queue depth. We can see that writes/sec increased by 6% more than reads/sec increased. We can conclude that the majority of the improvement in writes/sec was due to the increase in queue depth, with the additional increase in writes/sec being due to the write cache. As most of the performance improvement appears to be due to the increase in queue depth, the initial bottleneck appears to have been due to the HBA settings.
11 Page 11 of 26 The graphs below show results averaged over three tests for each configuration. IOPS 5,000 4,500 4,000 3,500 3,000 2,500 2,000 1,500 1, IOPS for Queue Depth 254 and 32 Queue Depth 254 Reads/sec Queue Depth 32 Reads/sec Queue Depth 254 Writes/sec Queue Depth 32 Writes/sec The graphs below indicate that faster storage drove the processor 54% harder and resulted in VMs completing boot sooner.
13 Page 13 of 26 IOPS 6,000 5,000 IOPS 4,000 3,000 2,000 1,000 0 Queue Depth 32 Read Cache Queue Depth 254 Read/Write Cache As mentioned previously, ESXi shared libraries wait for a response from storage while powering on VMs, requiring software power-on requests to be delayed to avoid ESXi errors. Below we can see that the reduced latency with queue depth 254 enabled the VM queue to be populated 64% faster, which enabled more VMs to boot at the same time and all VMs to boot faster.
14 Page 14 of 26 VMs in Queue VMs in Queue Queue Depth 32 Read Cache Queue Depth 254 Read/Write Cache
15 Page 15 of 26 The rate at which VMs were able to complete boot was faster for queue depth 254 than it was for queue depth 32, as evidenced by the slope of these lines. Again this shows that the bottleneck was mostly due to the HBA settings. VMs Booted VMs Booted Queue Depth 32 Read Cache Queue Depth 254 Read/Write Cache
16 Fibre Channel SSD Analysis of VDI Storage Performance During Bootstorm Page 16 of 26 Fibre Channel SSDs were tested with queue depths of 32 and 254. Increasing the queue depth enhanced performance, resulting in an 18% improvement in average boot time. The SSDs were the only drives to produce boot times across the board that would be acceptable to an end user, with the maximum boot time topping out at 2 minutes 17 seconds for the slower queue depth 32 configuration, and less than two minutes for the faster queue depth 254 configuration. Taken to Issue Start Commands (mm:ss) Taken for a VM to Boot Minimum Maximum Average Maximum CPU Utilized Maximum IOPS Queue Depth 32 1:01 00:35 02:17 01:28 48% 12,981 Queue Depth :40 00:16 01:57 01:12 50% 12,489 The graphs below show the results averaged over three tests for each configuration. IOPs and CPU vary only slightly between the two tests. CPU was driven only 6% harder on average and IOPS actually decreased by 3% when queue depth was increased to 254. A possible explanation for the decrease in IOPs could be the HBA taking some of the load away from the SSDs.
18 Page 18 of 26 IOPS 14,000 12,000 10,000 8,000 6,000 4,000 2,000 0 IOPS Queue Depth 32 Queue Depth 254 Most of the performance increase may be attributed to the VM Queue populating slightly faster, with the time taken to put all VMs into the queue reducing by 24%.We can see the results of this in the graph below where there are more VMs in queue at the beginning of the test, which gives the queue depth 254 configuration a head start.
19 Page 19 of 26 VMs in Queue VMs in Queue Queue Depth 32 Queue Depth 254 A graph of VMs completing boot shows again how the queue depth 254 configuration gets a head start. The time before the first VM completes boot is shorter when the queue depth is increased to 254, but the slope of both lines for queue depth 254 and queue depth 32 are the same once the boots are started, suggesting that the advantage was again that the first boots were completed faster, giving a head start when the queue depth was increased.
21 Summary and Conclusion Analysis of VDI Storage Performance During Bootstorm Page 21 of 26 The data in the graphs below was taken from the queue depth 254 Fibre Channel SSDs, the queue depth 254 Fibre Channel HDDs with write-back, and the 1024MB cache internal HDDs, as these were the optimal configurations for each storage type. The SSDs completed boot much faster than their HDD counterparts. VMs in Queue VMs in Queue Fibre Channel SSD Fibre Channel HDD Internal HDD
22 Page 22 of 26 Memory 80% 70% 60% 50% 40% 30% 20% 10% 0% % Memory Fibre Channel SSD Fibre Channel HDD Internal HDD SSDs dramatically outperformed the HDDs in a bootstorm, regardless of configuration. This appears to be due to their low latency. Latency for HDDs increased as more VMs were added to the queue, but latency for solid state drives stayed low the entire time. As the ESXi libraries waited for responses from storage, lower latency SSDs were able to increase ESXi library availability, enabling more VMs to start their boot sequences.
24 Page 24 of 26 In addition, solid state drives had the throughput necessary to efficiently handle storage requests from the starting VMs. IOPS 14,000 12,000 10,000 8,000 6,000 4,000 2,000 0 IOPS Fibre Channel SSD Fibre Channel HDD Internal HDD However, SSDs drive CPU harder, and may not be an option if processor availability is limited.
25 Page 25 of 26 Processor 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% % Processor Fibre Channel SSD Fibre Channel HDD Internal HDD HDDs can improve performance by using caching and increasing queue-depth, but do not compete with solid state drive performance. SSDs are recommended for all bootstorm configurations. Should SSDs not be cost effective, HDDs do have acceptable boot times for the first VMs that are started, before the VM queue gets built up. Data indicates boot times stayed below two minutes for the first VMs booted in HDD optimal configurations. HDDs, whether internal or via Fibre Channel, may be acceptable for environments where bootstorms will only consist of 20 VMs or less. It is also possible that more HDD VMs could have booted in under two minutes had the server not been taking new boot requests while attempting to process storage requests from the already booting VMs, possibly delaying their storage requests. Special care must be paid to caching configuration and queue depth when deploying HDDs to achieve optimal performance.
26 Appendix Evaluation Environment The tests were conducted in the Demartek lab in Colorado. Storage Internal HDD Analysis of VDI Storage Performance During Bootstorm Page 26 of 26 15x 15K GB HDD (1.98TB RAID 0 LUN used). External HDD (via Fibre Channel) 12x 15K 300GB HDD, 2x 8Gb interfaces (2.5TB RAID 0 LUN used). External SSD (via Fibre Channel) 24x 100GB SSD, 2x 8Gb interfaces (2.04TB RAID 0 LUN used). Server Dell PowerEdge R820 4x Intel Xeon E5-4650, 2.70 GHz, 256 GB RAM ESXi Dell PERC H710P adapter, 1024MB cache 1 Dell PERC H710 adapter, 512MB cache 1 Brocade Gb Fibre Channel HBA (used 1 interface) Virtual Machines 1 CPU, 2 MB Memory, 20 GB OS drive (thin provisioned) Windows 7 Ultimate SP1, with current updates as of 5/14/13. The most current version of this report is available at on the Demartek website. Demartek is a trademark of Demartek, LLC. All other trademarks are the property of their respective owners.
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