It’s 2017, let’s review Thick vs Thin Provisioning

For a long time, it has been widely considered that thick provisioning is required to achieve maximum storage performance and for many years this was a good rule of thumb.

Before we get into details, what are Thick and Thin provisioning?

Thick provisioning is where storage allocated to a LUN, NFS mount or Virtual Disk (such as a VMDK in ESXi, VHDX in Hyper-V or vDisk in AHV) is zeroed out and/or fully reserved regardless of how much capacity is actually used.

Thick provisioning avoids a storage subsystem from having to zero out a block before writing new data which is one of the reasons higher performance could be achieved on many storage platforms.

Thin provisioning on the other hand is where storage allocated to a LUN or Virtual Disk is zeroed as data is written and allows physical capacity to be overcommitted.

The advantages of Thick provisioning included easier capacity management, or simply put a “What you see is what you get” as well as maximum performance on most platforms. But by maximum performance, even on older storage platforms the advantage was rarely significant as people would claim.

VMware conducted a Performance Study of VMware vStorage Thin Provisioning back in the ESXi 4.0 days (~2009) which I will briefly summarise.

On page 6 of the performance study the following graph shows the different in performance between Thin and Thick VMDKs during zeroing and post-zeroing.

As you can see the performance is almost identical.

The disadvantages though were and remain significant to this day which include an inability to overcommit storage, meaning physical free space has to be maintained at multiple layers such as RAID group, LUN, Virtual Disk layers, leading to inefficiency.

The advantages of Thin provisioning include the ability to overcommit storage which results in more flexibility when sizing LUNs & Virtual Disks and less wasted space. The only real downsides were potentially increased capacity management complexity and lower performance.

I have previously written two example architectural decisions regarding using “Thin on Thin“, meaning thin provisioned virtual disks on a thin provisioned LUN or NFS mount as well as “Thin on Thick” meaning thin provisioned virtual disks on a thick provisioned LUN or NFS mount. These two examples cover off many of the traditional pros and cons between thick and think, so I won’t repeat myself here.

I never wrote an example design decision for Thick on Thick, but this was common practice when provisioning storage was time consuming, difficult and involved lengthly delays to engage subject matter experts.

In early 2015, I wrote a two part blog series where I explained it’s not as simple as you might think to calculate usable capacity where I compared SAN/NAS verses Nutanix. In part 1, I highlight that the LUN Provisioning Type is one area which can greatly impact the usable capacity of a traditional storage platform.

But fast forward into the era of hyper-converged platforms like Nutanix and some modern storage arrays and the major downsides of thin provisioning, being complexity of capacity management and reduced performance have not only been reduced, but at least in the case of Nutanix, have been eliminated all together.

Let’s address Capacity management w/ Nutanix:

Storage utilisation only needs to be monitored in ONE place, the storage summary which lives on the home screen of the Nutanix HTML 5 UI.


No matter how many nodes in your cluster, number of containers (which translate to datastores in a VMware environment), virtual machines & virtual disks or physical servers connecting via ABS, this is the only place you need to monitor capacity.

There are no RAID groups, Disk Groups, Aggregates, LUNs etc where capacity needs to be managed. All nodes in a cluster contributed to the capacity of the cluster and even when one or more virtual machines use more capacity than a the node they run on, Nutanix Acropolis Distributed Storage Fabric (ADSF) takes care of it.

So issue #1, Capacity management, is solved. Now it’s onto the issue of performance.

Thin Provisioning Performance w/ Nutanix:

When running ESXi, Nutanix runs NFS datastores and supports thick provisioning via the VAAI-NAS Space reservation primitive as discussed in this post. This allows the creation of thick provisioned (Eager Zero or Lazy Zero Thick) VMDKs when traditionally NFS datastores did not support it.

However this was only required for Oracle RAC and VMware Fault Tolerance and was not a performance requirement.

However from a performance perspective, Thin provisioning actually outperforms thick on intelligent storage such as Nutanix. In the specific case of Nutanix, random write I/O is serviced by the fastest tier available (e.g.: SSD) and via the operations log (OPLOG) which takes the random writes commits them to persistent media, and then coalesces them into sequential IO to then commit to SSD before tiering it off to lower cost storage in the case of hybrid nodes.

This means the write penalty for overwriting or zeroing blocks before writing new I/O is eliminated.

In fact if you configure thick provisioned virtual disks, as the zeros (or whitespace) is being written by the hypervisor, the Nutanix storage fabric acknowledges every I/O and discards the zeros in favour of storing metadata and simply reserving the capacity. In simple terms, this just means Nutanix has to acknowledge a whole bunch of nothing and the thick provisioning is achieve with a simple reservation as opposed to zeroing out many GBs or TBs of storage.

This means thick provisioning is actually lower performance than thin provisioning on Nutanix.

With modern, intelligent storage, there is limited if any benefits to using thick provisioning, the only example I can think of is to artificially inflate the deduplication ratio as thick provisioned virtual disks tend to have a lot of zeros all of which dedupe. I wrote an article titled: “Deduplication ratios – What should be included in the reported ratio?” which covers off this point in detail but in short, don’t create unnessasary data (in this case, zeros) just to inflate your dedupe ratio, it just wastes storage controller resources and achieves no additional benefits.

The following is a comprehensive list of the real world advantages of using thick provisioning on Nutanix.

This space is intentionally left blank


For the best efficiency and performance when deploying virtual machines or storage for physical servers via ABS on Nutanix, use thin provisioning!

How to successfully Virtualize MS Exchange – Part 16 – Virtual Disk Provisioning Types

Once you have made the decision on storage platform, and assuming you have chosen to use VMFS or NFS datastores, the next decision is how should my VMDKs be provisioned?

The VMware Exchange 2013 Best Practice Guide does not make mention of disk provisioning options nor does it make any recommendations, however you’re in luck as we will cover all the options along with pros and cons here.

For Exchange 2010, Microsoft state in Understanding Exchange 2010 Virtualization:

Virtual disks that dynamically expand aren’t supported by Exchange.

Virtual disks that use differencing or delta mechanisms (such as Hyper-V’s differencing VHDs or snapshots) aren’t supported.

However I have been unable to find confirmation if this has changed or not for Exchange 2013 in the Exchange 2013 storage configuration options document which does state Thin provisioning for Storage spaces is supported but it does not state that any other form of thin provisioning is or is not supported.

While technically not supported in 2010, there is plenty of experts who understand and recommend thin provisioning including MCM and MVP for Exchange Dustin Smith who in this video talks about some of the considerations and benefits of thin Provisioning for Exchange 2010.

Now on to the topic at hand:

When creating a Virtual Machine, VMDK/s can be provisioned in one of three ways, these are:

1. Thick Provisioned Lazy Zeroed
2. Thick Provisioned Eager Zeroed
3. Thin Provisioned

Starting with Thick Provisioned Lazy Zeroed this means that the VMDK is thick provisioned but only zeroed in a just in time fashion.

The advantages of Thick Provisioned Lazy Zeroed VMDKs include:

1. Faster VM creation time than Eager Zeroed Thick (Minimal if the storage supports VAAI Write Same primitive) 
2. The entire VMDKs capacity is reserved making capacity planning easier than Thin Provisioning

The disadvantages of Thick Provisioned Lazy Zeroed VMDKs include:

1. Slower provisioning that Thin Provisioning (although the different is generally minimal)
2. The entire VMDKs capacity is reserved and unavailable for use by other virtual machines.

With Thick Provisioned Eager Zeroed (EZT) the VMDK is thick provisioned and all blocked zeroed at the time of creation. Eager Zeroed Thick VMDKs are supported on all VMFS datastores and on NFS datastores which support the VAAI-NAS Reserve Space primitive.

The advantages of EZT VMDKs these days are really minimal but include:

1.  Supporting Oracle RAC and VMware Fault Tolerance (neither being applicable to Exchange)
2. Increased performance verses Lazy and Thin Provisioned VMDKs (but more on this topic later).

However there are a number of downsides to this method which include:

1. Slower VM creation times. The time depends on the size of the VMDK/s being created and the speed of your storage as every Gb needs to be zeroed, just like performing a Full (not quick) format on your physical server.

Note: Storage array’s who support VAAI with the “Write Same” primitive can offload the zeroing to the storage array to reduce the load on the ESXi host and speed up provisioning time dramatically.

2. Increased potential for wasted capacity on a datastore.

3. Free space within VMDKs cannot be shared with other VMs which requires every VMDK have some (generally >10% is recommended) free space per VMDK to ensure the VM does not run out of space.

Lastly there is  Thin Provision which means the VMDK only takes up the amount of space that data is written too and before each write the block must be zeroed.

The advantages of Thin Provisioning VMDKs include:

1. You can create larger VMDKs with no space utilization penalty making capacity planning and growth easier.
2. Reduce wasted or unused space on the storage
3. Allows for disk space to be overcommitted ensuring maximum utilization and flexibility.
4. Free space in VMDKs is not wasted on the datastore reducing capacity requirements compared to Eager and Lazy Zeroed VMDKs.
5. The impact of SCSI reservations (VMFS datastores ONLY) causing performance issues (increased latency) when thin provisioned virtual machines (VMDKs) grow is no longer an issue as the VAAI Atomic Test & Set (ATS) primitive alleviates the issue of SCSI reservations.
6. Thin provisioned VMs reduce the overhead for Storage vMotion , Cloning and Snapshot activities. Eg: For Storage vMotion it eliminates the requirement for Storage vMotion (or the array when offloaded by VAAI XCOPY Primitive) to relocate “White space”. Note: Storage vMotion should rarely if ever be required for Exchange VMs.
7. Thin provisioning leaves maximum available free space on the physical spindles which should improve performance of the storage subsystem as a whole.

The disadvantages of thin provisioning include:

1. Increased risk of running out of space on a datastore or underlying storage array.
2. Additional write penalty of zeroing a block before writing to it. (again more on performance later in this post).
3. Increased importance of monitoring storage capacity utilization.
4. Not supported for Exchange 2010. Note: However there is no technical inhibitor for using Thin Provisioning but supported options are obviously preferable.

All in all, @FrankDenneman (VCDX #29) sums it up perfectly with his article Thin or thick disks? – it’s about management not performance. I would also suggest considering all other workloads in the environment, not just Exchange when making decisions about Thin Provisioning as it can be very beneficial and a huge cost saving (especially CAPEX) when purchasing new equipment.

Which brings us to our next topic, Thin Vs Thick Provisioning Performance!

There have been many recommendations not to use Thin Provisioning due to the performance impact of Zeroing a block before writing to it. This recommendation has been around for a long time, and like the VMDK on NFS debate appears to have strong options on both sides.

Now for the facts!

From a performance perspective most people are surprised to learn there is no significant performance advantage to using Thick Provisioned (Eager or Lazy Zeroed) VMDKs compared to Thin Provisioned disks.

In addition to that, with the reduction of I/O from Exchange 2007 to 2010 being around 50%, and from 2010 to 2013 another 50% reduction in I/O, Exchange is no longer the huge storage I/O heavy monster it once was.

VMware conducted a Performance Study of VMware vStorage Thin Provisioning back in the ESXi 4.0 days (~2009) which I will briefly summarize.

On page 6 of the performance study the following graph shows the different in performance between Thin and Thick VMDKs during zeroing and post-zeroing.

As you can see the performance is almost identical.


The next chart shows also from Page 6 is a comparison of throughput between thin and thick VMDKs. Again we see the difference is insignificant.


As a result of there being no significant performance impact of using Thin Provisioning, Performance should no longer be considered an objection to using Thin Provisioning!

I recommend taking advantage of the flexibility of using Thin Provisioning and creating larger Thin Provisioned VMDKs which can help simplify capacity management from a VM/OS and application perspective as well as making growth easier for Exchange as mailbox sizes increase over time.


When using thin provisioning always ensure you have your alerting properly set-up with early warning on your vSphere environment AND underlying storage to advise when storage capacity of a datastore or underlying LUN/NFS mount or storage is running low so this can be remediated.

In an upcoming post I will discuss the underlying storage, including provisioning type for LUNs and NFS mounts (i.e.: Thin on Thick / Thin on Thin / Thick on Thick and Thick on Thin).

Recommendations for VMDK provisioning:

1. Check with your storage vendor and unless they have solid justification for not using Thin Provisioning OR you have an operational constraint preventing it, use Thin Provisioned VMDKs. (The pros outweigh the cons in my opinion)
2. When using Thin Provisioning create larger VMDKs to simplify capacity management at the VM and OS/Application layer.
3. When using Thick or Thin provisioning, ensure you test performance using Jetstress and LoadGen with the same provisioning type.
4. Ensure alerting is configured and working to monitor capacity utilization especially when using thin provisioned VMDKs.

Back to the Index of How to successfully Virtualize MS Exchange.

More Information on VMDK and Datastore provisioning options:

1. Example Architectural Decision – Datastore (LUN) and Virtual Disk Provisioning (Thin on Thin)

2. Example Architectural Decision – Datastore (LUN) and Virtual Disk Provisioning (Thin on Thick)

Back to the Index of How to successfully Virtualize MS Exchange.

Deduplication ratios – What should be included in the reported ratio?

I saw the below picture posted on Twitter, and there has been some discussion around the de-duplication ratio (shown below as an an amazing 28.4:1) and what this should and should not include.

03-Jan-15 12-39-25 PMA

In the above case, this ratio includes VM snapshots or what some people in my opinion incorrectly refer to as “backups” (But that’s a topic for another post). In other storage solutions, things like savings from intelligent cloning may also be included.

First l’d like to briefly explain what de-duplication means to me.

I think the below diagram really sums it up well. If 12 pieces of data exist (ie: Have been written or are in the process of being written in the case of in-line de-duplication) to the storage layer, de-duplication (in-line or post process) removes the duplicate data and uses pointers to direct duplicates back to a single copy rather than storing duplicates.


The above image is courtesy of

In the above example, the original data has 12 blocks which have been de-duplicated down to 4 blocks.

With this in mind, what should be included in the de-duplication ratio?

The following are some ways to reduce data consumption which in my opinion add value to a storage solution:

1. De-duplication (In-line or post process)
2. Intelligent cloning i.e.: Things like VAAI-NAS Fast File Clone, VCAI, FlexClone etc
3. Point in time snapshot recovery points. (As they are not backups until stored elsewhere)

Obviously, if data that exists or is being written to a storage system and its de-duplicated in-line or post process, this data reduction should be included in the ratio. I’d be more than a little surprised if anyone disagreed on this point.

The one exception to this is where VMDKs are Eager Zeroed Thick (EZT) and de-duplication is simply removing 0’s which in my opinion is simply putting additional load on the storage controllers and over inflating the de-duplication ratio when thin provisioning can be used.

For storage solutions de-duplicating zeros from EZT VMDKs, these capacity savings should be called out as a separate line item. (Discussed later in this post).

What about Intelligent cloning? Well the whole point of intelligent cloning is not to write or have the storage controllers process duplicate data in the first place. So based on this, VMs which are intelligently cloned are not deduped as duplicate data is never written or processed.

As such its my opinion Intelligent cloning savings should not be included in the de-duplication ratio.

Next lets talk “point in time snapshot recovery points“.

The below image shows the VM before a snapshot (a.) has blocks A,B,C & D.

Then after a snapshot without modifications, the VM has the same blocks A,B,C & D.

Then finally, when the VM makes modifications to or deletes data after the snapshot, we see the A,B,C & D remain in tact thanks to the snapshot but then we have a deleted item (B) then modified data (D+) along with net new data E1 & E2.


Image courtesy of

So savings from snapshots are also not “de-duplicating” data, they are simply preventing new data being written, much like intelligent cloning.

As with Intelligent cloning savings, my opinion is savings from snapshots should not be included in the de-duplication ratio.


In my opinion, the de-duplication ratio reported by a storage solution should only include data which has been written to disk (post process), or was in the process of being written to disk (in-line) that has been de-duplicated.

But wait there’s more!

While I don’t think capacity savings from Intelligent cloning and snapshots should be listed in the de-duplication ratio, I think these features are valuable and the benefits of these technologies should be reported.

I would suggest a separate ratio be reported, for example, Data Reduction.

The Data reduction ratio could report something like the following where all capacity savings are broken out to show where the savings come from:

1) Savings from Deduplication: 2.5:1 (250GB)
2) Savings from Compression: 3:1 (300GB)
3) Savings from Intelligent Cloning: 20:1 (2TB)
4) Savings from Thin Provisioning: 50:1 (5TB)
5) Savings from Point in time Snapshots: 30:1 (3TB)
6) Savings from removal of zeros in EZT VMDKs: 100:1 (10TB)

Then the Total data reduction could be listed e.g.: 60.5:1 (20.7TB)

For storage solutions, the effective capacity of each storage tiers (Memory/SSD/HDD) for example could also be reported as a result of the data reduction savings.

This would allow customers to compare Vendor X with Vendor Y’s deduplication or compression benefits, or compare a solution which can intelligently clone with one that cannot.


The value of deduplication, point in time snapshots and intelligent cloning in my mind are not in question, and I would welcome a discussion with anyone who disagrees.

I’d hate to see a customer buy product “X” because it was advertised to have a 28.4:1 dedupe ratio and then find they only get 2:1 because they don’t for example take 4 hourly snapshots of every VM in the environment.

The point here is to educate the market on what capacity savings are achieved and how so customers can compare apples with applies when making purchasing decisions for datacenter infrastructure.

As always, feedback is welcomed.

*Now I’m off to check what Nutanix reports as de-duplication savings. :)