SAN Performance Best Practises

Troubleshooting Storage Performance

Properly assessing the workload requirements is key to good storage design. This process should be reviewed continuously as requirements change and the infrastructure expands – I/O characteristics are rarely static. In relation to performance a good storage design should account for growth in workload and throughput. In this post we will cover some of the potential areas affecting performance and look at common solutions.

Principle Areas Affecting SAN Performance

  • Failure, to correctly assess and understand the workload characteristics and requirements (IO, Bandwidth, IO Profiles – Random vs Sequential)
  • Subsystem bottlenecks such as choice of physical disks (whether you have enough back-end IOPs to support workloads).
    • Drive response times, this is defined as the time it takes for a disk to execute an I/O request.
      • Nearline (NL) provide less I/O performance than 10/15K SAS disks.
      • Response time = (queue length + 1) x the service time to complete task.
    • Slow array  response times might be caused by a number of issues some include:
      • SAN fabric fan-in ratios / increasing contention causing throughput bottlenecks.
      • Front-end cache saturation (memory storing I/Os before they are de-staged to the backend drives).
      • Heavy workloads
  • Large workload I/O sizes can saturate interfaces impacting performance.
    • To identify VM I/O sizes use the vscsiStats tool, Cormac Hogan explains it nicely.
  • Poor change control mechanisms and workload awareness (Beware of unnecessary operations being performed on the array. New SAN – “Wouldn’t it be cool if we run IOmeter @100% random ops to see what this thing can really do!” – not if its in production.
  • I/O path saturation, incorrectly configured path selection policies.
  • Poor choice of RAID configuration for the supporting workloads. There is a penalty for every write operation performed, this varies depending on RAID policy (see below). Note that RAID rebuilds can impact performance and depending on the size of the disk can take a long time to complete.
RAID I/O Penalty
1 2
5 4
6 6
10 2
RAID-DP (NetApp) 2

Fabric Switching, IP & FC Impact on Performance FC Fabric Check physical switches for:

  • CRC errors, indicating code violations within FC frames.
    • Potential causes are: Faulty SFP’s or damaged cables. The impact is additional CPU overhead caused by retransmissions.
  • Loss of Sync – indicative of multiple code violations (character corruption), due to incompatible speeds between initiators and targets (don’t forget your ISL’s).
    • Loss of Sync errors, can also be caused by faulty SFP’s or HBA’s.
  • Class 3 discards, no acknowledgement from the receiver, FC frames can be discarded due to port congestion (check ISL oversubscription).
  • Exchange completion times, An ‘exchange’ is made up of [frames] & [sequences]. Frames include information about source and destination ID’s, originating exchange and sequence ID’s. Often a true measure of performance in switched fabric environments is how long each exchange takes to complete (specifically reads/write operations). Its important to note that latency here, cascades up the stack ultimately impacting the application.
    •  Issues affecting exchange rates: HBA’s (check firmware), physical server, number of hops, disk speeds, interfaces, configuration issues, I/O transaction sizes (Ref I/O sizes : see Brocade doc on buffer credit management).
  • Check Fan-in/Fan-out ratios, ensure there is enough bandwidth available – see Class 3 discards (above).

IP Fabric

  • The switch should be able to process and forward a continuous stream of data at full 
wire speed (1 Gbps) on all ports simultaneously, also known as ‘non-blocking’.
  • Adequate port buffering, this is working space for inbound (ingress) and outbound (egress). There are two different modes: 1) Shared port buffering, 2) Dedicated port buffering. Shared port buffering dynamically allocates memory to to ports as needed, where dedicated port buffering has a fixed memory amount per port.
  • Best practise: Disable spanning tree on initiator and target ports. If you have to use STP enable rapid spanning tree to reduce the convergence time and set port to immediately forward frames.
  • Check switch vendor recommendations regarding flow control (preventing buffer overflow, reducing retransmissions).
  • Check switch vendor recommendations for storm control.
  • Stacking / Trunking, check ISL is not oversubscribed, be aware of backplane oversubscription.
  • Both IP and FC storage traffic can be susceptible to congestion, however when an iSCSI path is overloaded, the TCP/IP protocol drops packets and requires them to be resent. This is typically caused by oversubscription of paths or low port buffer.
  • Minimise the amount of hops between initiators and targets, traffic should not be routed and sit on the same subnet.

Lastly, if your switches have the capability use performance counters to identify times of peak workloads, you may be able to cross reference this information with other latency alarms setup across your datacentre (See VMware LogInsight).

Calculating functional IOPs of the array

This is important as it will give you a good idea of the performance capabilities taking into account the RAID write penalty.

First we need to understand the Raw IOPs of the array, this is calculated as drive unit IOPs x n (total amount of drives in the array).

Second we need understand the I/O cross section – Read% vs Write%. This information can be obtained from your SAN management tools or looking at throughput for reads & writes.

Formula: Total Reads (KBps) + Total Writes (KBps) = Total Throughput in KBps

340,000KBps  + 100,000KBps  = 440,000 KBps 340,000 / 440,000 = 77.27 % Read 100,000 / 440,000 = 22.72 % Write

We can then use the this information to determine the functional IOPs of the array, this value is key in assessing whether or not the SAN is up to the job.

Functional IOPs = (Raw IOPs x Read%) + ((Raw IOPs x Write%) / RAID Write Penalty) 

Calculating Throughput Requirements

MBps = (Peak VM Workload IOPS * KB per IO) /1024 (use the VMware vscsiStats tool to output workload IO sizes)

MBps = (2000 * 8) /1024 = 15.625MBps

In the above example where the I/O workload requirement is 2000 IOPS, we would need 16MBps (128 Mbp/s @ 8KB per IO) of throughput to satisfy that requirement.

Note: esxtop can be used to determine SAN performance problems impacting hosts. Here are a couple of latency counters that should be monitored closely:

Value  Description
CMDS/s This is the total amount of commands per second and includes IOPS (Input/Output Operations Per Second) and other SCSI commands such as SCSI reservations, locks, vendor string requests, unit attention commands etc. being sent to or coming from the device or virtual machine being monitored. In most cases CMDS/s = IOPS unless there are a lot of metadata operations (such as SCSI reservations)
DAVG/cmd This is the average response time in milliseconds per command being sent to the deviceWarning threshold = 25High numbers (greater than 15-20ms) represent a slow or over worked array.
KAVG/cmd This is the amount of time the command spends in the Vmkernel.Warning threshold = 2 High numbers (greater than 2ms) represent either an overworked array or an overworked host.
GAVG/cmd This is the response time as it is perceived by the guest operating system. This number is calculated with the formula: DAVG + KAVG = GAVGWarning threshold = 2

Calculating I/O Size and I/O Profile : Random vs Sequential

See VMware vscsiStats tool / Dtrace for linux, SQLIO Windows.

ESX host monitoring

Have a look at the following VMware KB – Using esxtop to identify storage performance issues for ESX / ESXi (multiple versions) (1008205)

Virtual Machine Monitoring

  • Setup latency alarms within VMware vCentre to monitor virtual machine total disk latency.
    • The default is 75ms however, this should be adjusted depending on your KPI’s (<=25ms).

Host SCSI Latency

  • To reduce latency on the host, ensure that the sum of active commands from all virtual machines does not consistently exceed the LUN queue depth.
  • Either increase the LUN queue depth or move virtual machines to another LUN.
    • Observe vendor best practices for adjusting queue length on HBAs.
  • Work with the storage teams to ensure that each LUN is comprised of multiple physical disks.
  • To reduce latency on the array, reduce the maximum number of outstanding I/O commands to the shared LUN.
    • Distribute workloads across datastores.
    • Reduce VM to datastore ratios / reduce logical contention.
  • The maximum number of outstanding I/O commands that the array is capable of handling varies by array configuration, see my post on storage design considerations: Link

SCSI Reservations A SCSI reservation is a lock operation on the LUN preventing I/O from other operations. Consistent lock operations add latency measured in milliseconds.

  • Operations performed which can create locking metadata:
    • Creating a VMFS datastore
    • Expanding a VMFS datastore onto additional extents
    • Powering on a virtual machine
    • Acquiring a lock on a file
    • Creating or deleting a file
    • Creating a template
    • Deploying a virtual machine from a template
    • Creating a new virtual machine
    • Migrating a virtual machine with vMotion
    • Growing a file, for example, a snapshot file or a thin provisioned virtual disk
    • For the zeroed thick type of virtual disk the reservation is required only when zeroing the blocks.

In vSphere 4.x VMware released VAAI – VMware API for Array Integration, these primitives included an ATS – Atomic Test & Set which reduces locking.

  • For compatibility, check the VMware HCL/SAN Vendor –

From the hosts the following commands can be used to check the internal status ESX4.x

# esxcfg-scsidevs -l | egrep &amp;quot;Display Name:|VAAI Status:&amp;quot;


# esxcli storage core device vaai status get

Note: You may need to install the binaries on the ESX host, if these have not been included. The binaries come in the form of VIBs, a reboot of the host will be required after installation.

VAAI changes are logged in the VMKernel logs at /var/log/vmkernel (for ESXi 5.0 vmkernel.log) or /var/log/messages).

VMware also provide a great KB for troubleshooting SCSI reversions conflicts on VMware Infrastructure VMware KB: 1005009 VMware KB enabling and troubleshooting VAAI : KB 1021976

Possible Solutions

Correctly plan and identify the workload characteristics and requirements:

  • Analyse total throughput, identify I/O profiles (read versus write percentages), I/O types (sequential vs random) and particularly I/O size.
  • Understand the workload characteristics, In most cases database workloads are inherently more I/O intensive than say the same number of web servers.
  • To reduce contention and latency, avoid oversubscribing by:
    • Spreading workloads across different LUNs (use VMware SDRS to automate balance workload across datastores).
    • Identify front-end bottlenecks, balance I/O to different storage processors and storage processor ports.
    • Use different FC or Ethernet paths.
    • Use multiple ESXi storage HBAs and HBA Ports.
    • Set appropriate pathing policies based on storage vendor best practises.
    • Sometimes poor storage performance can be attributed to bad host and VM management, check VM disk alignment, identify if VM’s are swapping consistently to your SAN , attributing to unnecessary I/O across your storage fabric, use local server-side storage to home VM SWAP if possible.
      • In the case of the latter reduce memory overcommit or increase physical RAM/Hosts.
  • Set appropriate queue depth values on HBA adapters, follow vendor recommendations. Observe impact to consolidation ratios specifically the number of VMs in a VMFS datastore. Setting queue depths too high can have a negative impact on performance (very large queue depths 64+, tend to just mask issues and are indicative of a larger performance problem).
  • Distributing workloads with a large number of transactions per second, you can also reduce latency by reducing the number of hops in the storage path.
  • Increase I/O front-end ports if possible (some SAN devices support the installation of additional HBA cards).
  • Check if target and initiator ports have negotiated correctly (check port properties on SAN fabric switches).
  • For NFS/iSCSI – Use, good quality switches and preferably dedicated stacks (1GbE – Dell PowerConnect 6200’s, Cisco 3750’s), if you are using 10GbE use NIOC to prevent other I/O operations from impacting your storage I/O.
  • Not directly related to performance but ensure proper L2 isolation between iSCSI traffic and general network traffic.
  • Calculate I/O cost to support the workload, factoring RAID write penalty.
    • Increase the number of drives to meet requirements.
  • Upgrade controller/SP cache, however in the event cache is saturated you will be reliant on back-end performance of the underlying drives, front-end cache is not a fix for poor back-end storage design.
    • To prevent noisy neighbours using all available front-end cache look at array side tools to create I/O polices for different workloads, prioritise those that are business critical.
    • VMware Storage IO Control (SIOC) can be used when latency impacts VM workloads by prioritising IO (only invoked during periods of contention).
  • Investigate potential use of SSD’s to absorb intensive I/O operations (Server side cache may also help – See PernixData FVP for VMs).
  • Investigate sub-lun tiering mechanisms to move hot blocks of data to drives with faster performance characteristics and less used blocks to slower storage (EMC FAST, HP 3PAR AO).
  • Use array multipathing policies, either native or thirdparty such as EMC powerpath. These policies can help by distributing I/O across all available storage paths in a more effective manner.
  • I/O Analyzer (VMware fling) can measure storage performance in a virtual environment and to help diagnose storage performance concerns. I/O Analyzer, supplied as an easy-to-deploy virtual appliance.
  • VMware Log Insight can aggregate and perform deep analysis of system logs identifying trends in many metrics in a fully customisable package. This is particularly useful when investigating storage related problems.

Recommended Reading

VMware KB / Troubleshooting Storage Performance Issues with VMware Products

Brocade FOS Admin Guide / Buffer Credit Management 

VMware Blog / Troubleshooting Storage Performance Queues

IBM Redbooks / Storage Area Networking

VMware vSphere Storage Design Considerations

In my previous post I looked at the calculations required to determine the minimum number of hosts needed to satisfy the compute design. This was achieved through an assessment of the current state analysis, identifying average peak CPU and memory consumption.

A summary of the tools can be found here: VMware vSphere Compute Design … The same tools can be used to determine the VM/Physical server I/O profile, capacity and throughput requirements we need to design and scale an appropriate storage solution.

Getting your storage design right is crucial. A poorly designed SAN can negatively impact the vSphere Infrastructure. Storage like – networking and the compute layer are corner stone areas, that require careful planning and investment. Failures here may impact project delivery, budget, performance, damaging user and stakeholder experience.

This post will look at some of the principles around VMware storage design in general.

Key Decision Points & Considerations

  • Plan for failure, a good storage design should take into account the impact of failure, for example:
    • Site failure (DR), your SAN array may support block level replication, if you don’t have this capability (due to cost or features) look at network/host level replication offered in vSphere 5.1 or other replication tools. Disaster recovery is not just about ensuring you can backup and restore data its about ensuring business continuity.
    • Identify bandwidth replication requirements / what is the rate of change ? (this impacts whether or not you can perform synchronous or a-synchronous replication).
    • Failure of individual components (review this end to end) fabric interconnects, switches, storage processors, drive shelves, host HBA, power etc… the key point here is to find ways for mitigating any risks from an infrastructure point of view.
  • Size and plan according to workload peaks (example factors: backups, month-end reporting)
  • Array availability requirements, n+1, n+2 etc… at minimum your solution should withstand the failure of at least one node (n+1), however be aware of the impact if a storage processor is down for maintenance. During periods of maintenance availability requirements might not be satisfied.
  • Scale the design for current and future IOPs and capacity requirements, total storage capacity is the sum of all current storage usage plus projected growth, IOPs provides the performance the array needs to support the workloads.
  • Do you plan to use advanced technologies such as – deduplication, sub-lun tiering, caching?
    • How will this impact the design, observe SIOC & array vendor best practises regarding the use of sub-lun tiering.
  • Number and speed of drives needed (FC/SAS, SATA/NL, SSD), this has an impact on performance, capacity, availability and budget etc..
Drive Type Unit IOP/s
SSD(SLC) 6,000 +
SSD(MLC) 1,000 +
15K RPM 175-200
10K RPM 125-150
7.2K RPM 50-75
  • Storage Protocol Choices – (FC/FCoE, iSCSI, NFS), the decision is driven by throughput and existing requirements and constraints.
  • Whether service processors will run in an Active-Active, Active-Passive configuration
    • This impacts host path selection policies, whether I/O requests can be balanced across all available paths.
    • Impacts performance, I/O is balanced on a per LUN basis only – having additional ‘Active’ controllers to service requests can improve performance in conjunction with multi-pathing policies..
  • Check array support for the VMware VAAI primitives (VAAI, VAAI-NFS, VASA and by extension Storage I/O control).
    • This offers performance improvements (hardware offloading – hardware assisted copy, locking, block zeroing).
  • Will you thin provision at the LUN or VM level?
    • Thin provisioning has its benefits, but increases the management overhead. Common use case for environments that require ‘x’ amount of space but don’t use all the space allocated.
    • The impact of out of space conditions on VAAI-supported arrays causes VM’s to stun. VM’s can be resumed if VMFS datastore space is increased or reclaimed, alternatively if VM swap files are stored on same datastore power off non-critical VM’s (virtual machine swap files are by default stored in the base VM folder, this can be changed in certain instances e.g : reduce replication bandwidth). Powering off the VM removes the .vswp file (the .vswp file equals memory granted to the VM less any reservations).
    • The common cause for out of space conditions are attributed to poor or non-existent capacity monitoring. This can also be caused by snapshots that have grown out of control.
    • Thin on thin is not recommended, due to operational overhead required to monitor both vmfs datastores and backing LUNs.
  • Set appropriate queue depth values on HBA adapters (use with caution), follow vendor recommendations. Observe impact to consolidation ratios specifically the number of VMs in a VMFS datastore. Setting queue depths too high can have a negative impact on performance.
  • For business critical applications you may want to limit virtual machine disk files to one or two virtual disks per VMFS datastore.
    • Observe the ESXi LUN Maximums (currently 256)
    • In situations where you have multiple VM virtual disks per VMFS datastore, you may want to use Storage I/O control (requires enterprise plus licensing). SIOC is triggered during periods of contention, VMs on datastores use an I/O queue slot relative to the VM’s share values, this ensures that high-priority VMs receive greater throughput than lower-priority ones.
  • Quantify RAID requirement based on availability, capacity & performance requirements (IMO scope for throughput/IOPs first capacity second)
    • Caveat: There is little or no use case for RAID 0.
  • I/O size can have an adverse effect on IOPs, meaning a larger the I/O size the fewer the amount of IOPs the drive can generate.
  • I/O size (KB) multiplied by IOPs = throughput requirement, the larger the I/O size the more it impacts IOPs.
    • A higher number of IOPs might be due to a small I/O size (low throughput) whereas a larger I/O size might equate to a lower number of IOPs, but would be a higher amount of throughput. Understanding throughput requirements is crucial as this may dictate protocol & bandwidth requirements (iSCSI 1Gb/iSCSI 10Gb /FC etc…)
  • Ensure that host HBA cards use are same lane PCIe slots, a lane is composed of two differential signaling pairs: one pair for receiving data, the other for transmitting, its not recommended placing one card in a x4 slot and another x16 slot.
  • Design choices need to be validated against the requirements and constraints, as well as understanding the impact those decisions have on the design. For example, what if through your analysis you have determined that iSCSI is suitable protocol choice. Be aware of the impact to network components – a common strategy is to map this design choice against the infrastructure qualities (availability, manageability, performance, recoverability and security). Do you intend to use software initiators, dependent hardware initiators or independent hardware initiators? Each of these decisions impacts your design. i.e If you intend to use independent hardware initiators, how does this impact iSCSI security?, Do you have enough PCIe ports available in your hosts? Do you plan to use separate iSCSI switches or existing network switches?, Does the existing switches support large payloads sizes above 1500 bytes?, Do you have enough ports?, How will you secure the storage network ? (i.e.: with L2 non-routed VLANs), Will the switches be redundant? Is there available rack space/power etc…
  • Finally, document everything!

Resource Allocation

  • How will the resources, capacity, drive class characteristics (IOPs) be distributed amongst all the workloads?
    • VM-to-Datastore allocation, Application/Infrastructure life cycles – (Production, Test, Dev).
    • See use cases for SIOC: Link
  • Prioritise critical applications on faster class of drives offering better performance / higher availability.
  • It’s generally accepted to distribute intensive workloads across datastores, for example grouping several SQL servers on the same datastore can lead to contention and impact performance.
    • Use SDRS – SDRS can load balancing I/O among datastores within a datastore clusters.
  • Adhere to customer/business PCI-DSS compliance requirements (for example: logically separate datastores/storage domains). VCDX133 – Rene Van Den Bedem: has written a great post on how compliance requirements map to vSphere design decisions: Link.
  • VM/Application availability requirements, ie MS Clustering (do you plan to use RDM’s, if so physical or virtual operating mode?)
    • Beware of the impact of each mode (see my blog post on MS Clustering Design Guidelines).
  • Create single partitions with single VMFS partitions per LUN.
    • Creating multiple VMFS partitions per LUN increases SCSI reservations (impacting VM & virtual disk performance). For every partition created per LUN you increase the chance of metadata locks – this all adds up to increased latency.
  • Factors that determine optimal datastore size:
    • Max tolerable downtime (MTD), RPO-RTO, DR requirements.
  • How will restores be performed?
    • Will you be using disk or tape to perform VM restores?
      • What is the performance of your restore device? understanding this impacts you’re RTO & maximum tolerable downtime.
      • Tape drive transfer rates at 2: 1 compression – : LTO 2 = 173GB/hr, LTO 3 = 432GB/hr, LTO4 = 846GB/hr, LTO5 = 1TB/hr, LTO6 = 1.44TB/hr
  • Calculating VM storage consumption = (VM Disk(s) Size + 100MB Log files) + (.VSWP size – Reservations) + (25% Growth).

Storage Protocol Decisions

iSCSI, NFS, FC, FCoE – Have a look at Cormac Hogans : Storage Protocol Comparisons. Link

vSphere VAAI Storage Primitives – here to help!

  • Provides hardware offload capabilities
    • Full Copy (hosts don’t need to read everything they write), this significantly improves storage vMotion, VM Cloning, template creation.
      • Reduces unnecessary I/O on switches and front-end ports.
  • Block Zeroing, (Write Same $) = faster disk creation times (use case eager-zeroed thick virtual disks).
    • This also reduces the time it takes to create FT enabled VMs.
    • Recommended for high performance workloads.
  • Hardware Assisted Locking, (AT & S) – Excessive SCSI reservations by a host can cause performance degradation on other hosts that are accessing the same VMFS datastore.
    • AT&S improves scalability and access efficiency by avoiding SCSI reservation issues.
  • In addition SCSI/ T10 UNMAP, can reclaim dead-space by informing the storage array when a previously used blocks are longer needed.

Workload I/O Profiles

  • Differing I/O profiles can impact storage design, for example using an IOPs requirements of 20,000 IOPs / RAID 5 with 15K FC/SAS drives (approximately 180 IOPS each).
    • A Read-heavy workload, 90/10 (reads vs writes) could be satisfied with 149 drives.
    • A balanced workload 50/50 (read vs writes) would require 286 drives.
    • A write-heavy workload 10/90 (reads vs writes) would require 423 drives.
  • Remember I/O size correlates to throughput
    • Throughput = Functional Workload IOPs x I/O Size, using an an I/O Size of 8K
    • Functional Workload IOPs (2000 x 8K = 20MB/s) x Number of workloads on host = VM:Host consolidation ratio.
      • To convert MB/s to Megabits per second (iSCSI/NFS) multiply by 8.
      • 20MB/s x 8 = 160 Mbp/s (Note: iSCIS/NFS –  a single network card at full duplex can provide around 800Mbs, so in this scenario the workload requirement is satisfied but only on a single adapter).

Calculating the required number IOPs to satisfy the workload requirements

Use active or passive monitoring tools such as VMware Capacity planner (available to VMware partners only).If you are not a VMware partner check with your VAR(reseller) if they can perhaps help. There are also third-party tools available such as platespin power recon, perfmon, Quest, etc.. Which provide ways of capturing IO statistics.

Key points for assessment:
1. Determine the average peak IOPs per workload (VMware Capacity Planner, Windows Perfmon, iostat).
2. Determine the I/O profile– Reads versus Writes. Check the array or Perfmon/IOStat x number of workloads.
3. Determine throughput requirements, Read Mbps versus Write Mbps. Reads (KB/s) + Writes (KB/s) = Total maximum throughput.
4. Determine RAID type based on availability, capacity & performance requirements (as mentioned before scope for performance first).

As an example the following values will be used to run through a couple of sums –

Number of workloads 100
Average Peak IOPs 59
% Read 74
% Write 26
RAID – Write Penalty 2

IO Profile = (Total Unit Workload IOPS × % READ) + ((Total Unit Workload IOPS × % WRITE) × RAID Penalty)

(59 x 75%) + ((59 x 26%) x 2)
(44.25) + ((15.34) x 2)
44.25 + 30.68 = 74.93 (IOPs Required)
Rounded up to 75 IOPs

Therefore, 75 IOPs per VM x Number of VMs you want to virtualise = Total IOPs required

75 IOPs x 100 VMs = 7500 IOPs (note: you may want to add 25% growth depending on customer requirements)
75 IOPs x 125 VMs = 9375 IOPs (with 25% VM growth) – This is the amount of IOPs the Storage Array needs to support.

Calculate the number of drives needed to satisfy the IO requirements
Example values:

IOPs Required 20,000
Read rate KBps 270,000
Write rate KBps 80,000
Total throughput 440,000

Determining read/write percentages

Total throughput = Reads + Writes
270,000 KBps + 80,000 KBps = 350,000 KBps
Total Read% = 270,000 / 350,000 = 77.14
Total Write% = 80,000 / 350,000 = 22.85

Using the derived read/write values we can determine the amount of drives needed to support required workloads.

Number of drives required = ((Total Read IOPs + (Total Write IOPS x RAID Penalty)) / Disk Speed IOPs)

Total IOPS Required = 20,000
Read : 77.14% of 20,000 IOPS = 15428
Write: 22.85% of 20,000 IOPS = 4570

RAID-5, write penalty of 4
Total Number of disks required = ((15428 + (4570 x 4)) /175) = 193 Disks

RAID-1, write penalty of 2
Total Number of disks required = ((15428 + (4570 x 2))/175) = 141 Disks

I hope you found the information useful – Any questions or if you feel some of the information needs clarification let me know.

Recommended Reading

VMware vSphere Storage Guide ESXi 5.5