Category Archives: Storage

Calculating Actual Usable capacity? It’s not as simple as you might think! – Part 2 Nutanix

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In Part 1, the example provided showed usable capacity for a SAN/NAS using a combination of RAID 10, RAID 5 and RAID 6 along with the various sizing considerations resulted in 35.68TB usable capacity or approx 1/3rd of the RAW 100TB.

In Part 2 we will discuss the misconception that Nutanix (a Hyper-converged platform) provides lower effective usable capacity compared to SAN or NAS solutions.

At a high level, Nutanix uses Replication Factor 2 (RF2) which has the same overhead as RAID 1 so straight away a lot of people jump to the conclusion that the usable capacity is less that a traditional SAN/NAS because *insert your favourite RAID level here* has less overhead.

Let’s say we have a Nutanix cluster with 100TB Raw storage using the most common node type, the NX3050.

Now let’s address the same points as we did in Part 1 for the SAN/NAS example:

So starting with the same 100TB RAW as we did for the SAN/NAS example and see where things end up on Nutanix.

1. Deducting hot spare drives

Nutanix does not use hot spare drives, data is balanced across all drives in the “Storage Pool”. To cater for failure, it is recommended to size for N+1 for Resiliency Factor 2 (RF2) deployments. If we we’re using NX3050 nodes (the most popular Nutanix node) then the overhead of N+1 would be ~4.8TB RAW.

100TB – N+1 Node (4.8TB RAW) = 95.2TB

2. RAID Overhead

Nutanix doesn’t use RAID, but the Replication Factor 2 has an overhead is 50% (the same as RAID10).

95.2TB – 50% (RF2) = 47.6TB remaining

3. Free Space on the platform required to ensure performance

For Nutanix all write I/O goes to either the Extent Storage or Oplog, both of which are housed on the SSD tier. All random writes are serviced by the Oplog until it reaches 95% capacity at which point the oplog is bypassed.

As such, performance remains high until 95% capacity. Therefore only 5% free capacity is required to ensure high performance.

47.6TB – 5% (Free space for performance) = 45.2TB

FYI: Nutanix Performance and Engineering team members including myself typically conduct benchmarks at greater than 90% cluster capacity.

4. Free space per LUN

Nutanix does not use LUNs. Nutanix presents containers to the hypervisor. All containers are thin provisioned and all containers can use all available space in the storage pool. Meaning free space only needs to be managed at the Storage Pool layer, not at each individual container.

As we have already taken into account the 5% free space there is no need to take another 5% of space therefore we remain at 45.2TB usable.

5. Free space per VMDK

As with physical servers and SAN/NAS environments, we don’t want our VMs drives running out of capacity, as a result it is common to size VMDKs well above what is strictly required to make capacity management (operational tasks) easier.

As mentioned in Part 1, I typically see architects recommending upwards of 10-20% free space per VMDK over and above what is required to account for unexpected growth, OS patching etc. This makes perfect sense for the same reason as we have free space per LUN because if space runs out for a VM, it’s another bad day for I.T.

For this example, I will assume the same 10% free space per VMDK as I did for SAN/NAS example, the difference with Nutanix is performance remains the same regardless of the VMDK being Thick or Thin provisioned, so with every VM Thin Provisioned, no capacity is required to be reserved for free space within VMDK files as it would be for traditional environments requiring Eager Zero Thick VMDKs for performance..

So we’re still at 45.2TB usable.

Now where are we at?

So far, the first 5 points are fairly easy to calculate.

Next we will look at various factors which further reduce usable capacity for SAN/NAS and see how they apply to Nutanix.

6. Silos for Performance

Nutanix does not require nor recommend silos being created for performance reasons. All VMs can reside in a single container therefore no capacity is unusable as a result of performance requirements.

As no silos are required for maximum performance, we are still at 45.2TB usable.

7. Silos of (or Fragmented) Usable Capacity

Nutanix does not configure usable capacity to containers, a container can use all the available storage in the underlying Storage Pool. Where multiple containers are provisioned, each container can see the total capacity of the storage pool while providing logical separation of the VMs within the containers. This avoids the issue of fragmented free capacity.

The diagram below shows 5 containers hosted by an example Nutanix cluster (Storage Pool) with 100TB total capacity, each container has a capacity of 100TB and 25TB free space in alignment with the underlying storage pool.

NutanixFreeSpace

In this case, when creating a new VM, or adding or expanding VMDKs for existing VMs, it does not matter which container we place the VM, as long as it is less than the 25TB available in the pool, it makes no difference to capacity.

This removes the requirement for complex capacity management, or using Storage DRS and Storage vMotion.

So we’re still at 45.2TB usable.

Other factors which reduce usable capacity?

8. LUN Provisioning Type

In many cases, especially when talking about high performance applications, storage vendors recommend using Thick Provisioned LUNs and as mentioned in Part 1, It’s anyone’s guess how much space is wasted as a result.

But with Nutanix, all containers are Thin Provisioned so no capacity is wasted on Thick Provisioning and performance is optimal

9. Wasted Capacity from using SSDs as Cache

Nutanix does not use SSDs as Cache! The SSD’s form part of the Extent Store which is for persistent data storage. The OpLog which is also on SSD is also persistent and not a “cache”. As such, no capacity is being reduced as a result of caching.

10. Snapshot Reserves

Nutanix does not use reserve capacity for snapshots. Snapshots simply use available capacity in the storage pool. If you don’t use snapshots, no space is wasted, if you do use snapshots, then the delta changes are stored. Simple as that.

Summary:

From the 100TB RAW factoring in what is a realistic Nutanix configuration including N+1 to tolerate a node failure and support the cluster being able to fully self heal the effective usable capacity is 45.2TB which is just under 50% of 100TB RAW.

This is a very simple configuration to manage from both a performance and capacity perspective, and one which is easily calculated and repeatable.

If the Resiliency Factor was 3 (which IMO is rarely if ever required) across the entire environment (which again would be extremely unusual as VMs which require RF3 can be configured in an RF3 container) then the usable capacity would be ~30TB which is only sightly below the SAN/NAS example and RF3 delivers higher resiliency.

In reality, >95% of workloads should be deployed on RF2, with a very small number of VMs possibly using RF3. In reality RF2 is extremely resilient and self healing so IMO RF3 is rarely required.

So in conclusion, Nutanix usable capacity is ~50% of RAW capacity, the difference between Nutanix and traditional SAN/NAS is you actually can use almost all the “usable” capacity and maintain optimal performance with little/no complexity.

Nutanix also has data reduction technologies such as Compression and De-duplication, along with intelligent cloning to increase the effective capacity of the storage pool.

While I believe Nutanix’ usable capacity today is excellent especially when considering how resilient RF2 is and comparing usable capacity to many products on the market, Nutanix has the advantage of not being constrained by legacy technologies such as RAID, so I’ll leave you with a little teaser:

Usable capacity will be improving significantly in upcoming releases of Nutanix Operating System. 🙂

Calculating Actual Usable capacity? It’s not as simple as you might think! – Part 1 SAN/NAS

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Calculating the usable capacity for your next SAN/NAS is easy. Work out the number of drives you have, what RAID config your going to use and your done, right?!

Wrong! There are numerous factors which come into play to understand the ACTUAL or TRUE usable capacity of a SAN/NAS solution.

So let’s take an example of a traditional SAN/NAS using RAID and work out how much space we can actually use.

Note this is a simplified and generic example, which will vary from vendor to vendor.

Let’s say a SAN/NAS has 100 x 1TB drives (Note: The type of drive is not important for this example) and has the requirement to support mixed workloads such as MS SQL , MS Exchange and general server workloads.

As per vendor best practices, RAID 10 is used to maximize IOPS for SQL / Oracle and other storage intensive applications, RAID 5 is used for things like MS Exchange and RAID 6 (or DP) is used for general server workloads.

The vendor also recommends one hot spare drive per 2 disk shelves to ensure when drives fail, there are sufficient hot spares available.

So let’s start with 100TB RAW and see where things end up.

1. Deducting hot spare drives

So assuming 14 drives per shelf, that’s 7 drives (or 7TB RAW) dedicated to hot spares.

100TB – 7TB = 93TB

2. RAID Overhead

Let’s assume 20% of our workloads require RAID 10, so 20 drives are used. RAID 10 has a usable capacity of 50% so 20TB – 50% = 10TB

Next let’s say 40% of our workloads use RAID 5, so 40 drives broken up into 5 x RAID 5s each with 8 drives in a 7+1 Parity configuration. Therefore with 5 x RAID 5s volumes we loose 5 drives (5TB RAW) worth of capacity.

The final 40% of our workloads use RAID6 (or DP), so 40 drives broken up into 5 x RAID 6s each with 8 drives in a 6+2 Parity configuration therefore with 5 x RAID 6s we loose 10 drives (10TB RAW) worth of capacity.

93TB – 10TB (RAID 10) – 5TB (RAID5) – 10TB (RAID6) = 68TB remaining

3. Free Space on the platform required to ensure performance

For most traditional storage solutions, the vendors recommend ensuring a specific percentage of free space to ensure performance remains consistent.

For some vendors this is 20% and others say around 30%.

For this example, I will assume best case scenario of 20%.

68TB – 20% (Free space for performance) = 54.4TB

4. Free space per LUN

Vendors typically recommend having between 10-20% free space per LUN to account for unexpected growth, VM level snapshots etc. This makes perfect sense as if a LUN runs out of space, its a bad day for the I.T dept.

For this example, I will assume only 10% free space per LUN but it could easily be 20% further reducing usable capacity.

54.4TB – 10% (Free space per LUN) = 48.96TB

5. Free space per VMDK

As with physical servers, we don’t want our VMs drives running out of capacity, as a result it is common to size VMDKs well above what is strictly required to make capacity management (operational tasks) easier.

I typically see architects recommending upwards of 10-20% free space per VMDK over and above what is required to account for unexpected growth, OS patching etc. This makes perfect sense for the same reason as we have free space per LUN because if space runs out for a VM, it’s another bad day for I.T.

For this example, I will assume only 10% free space per VMDK.

48.96TB – 10% (Free space per VMDK) = 44.064TB

Now where are we at?

So far, the first 5 points are fairly easy to calculate and if you agree or not with the specific examples or percentage deductions, I’d suggest few would disagree these are factors which reduce usable disk space for traditional SAN/NAS deployments.

Next we will look at various factors which further reduce usable capacity. Each of these factors will vary from customer to customer, which further complicates the sizing exersize and results in lower usable capacity than what you may believe.

6. Silos for Performance

In this example, we have assumed only 20% of our drives are configured for high I/O with RAID 10, but in many cases the drives required for performance could be a much higher percentage.

Now to get the IOPS required for these storage intensive applications, its common to see the capacity utilization of the LUNs be much lower than the usable capacity because the storage is IOPS constrained, not capacity.

This leads to Silos of drives with low utilization, where the remaining capacity cannot (or at least should not) be shared with other VMs as this would likely impact the performance of the IO intensive VMs.

So for example, if our RAID 10 LUNs have 50% free space (which I personally have found to be common) then we’re effectively wasting 5TB (50% of the RAID 10s 10TB usable).

44.064TB – 10% (Wasted Capacity for Performance Silos) = 39.65TB

7. Silos of (or Fragmented) Usable Capacity

In this example, we have assumed 40% of our drives are configured for RAID 5 and the remaining 40% for RAID 6 (DP) to suit the different workloads in this environment, as a result we have 2 “Silos” of usable capacity.

In this post I have described 5 x 8 drive RAID 5s and 5 x 8 Drive RAID 6 volumes. The below diagram is an example of what an environment in this configuration may have with regards to free space per LUN.

LUNsFreeSpace

So we can see the average free space per LUN is 20%, but it varies from one LUN having only 5% free space and another having 35%.

In this case, when creating a new VM, or adding or expanding VMDKs for existing VMs, we have a situation where we will need to be careful about where we place a new VMDK from a capacity perspective but keeping in mind performance as well.

Now not all VMs or VMDKs are the same size, so if a new VMDK needs to be 500GB even though the environment may have well in excess of 500GB available, the fact that the free space is fragmented across multiple LUNs means we cannot create the new VMDK without first migrating VMs across the LUNs.

Now Storage DRS can do a reasonable job of this, but that takes time and impacts performance (during the Storage vMotion) and depending on the size of the VMs in the environment may not always be able to solve the issue.

Best case scenario, in my experience is at least 10% of capacity is wasted simply because of the fact the drives are carved up into RAID groups and VMs don’t fit within the inflexible LUNs.

39.65TB – 10% (Wasted Capacity due to de-fragmented free space) = 35.68TB

Usable space so far from 100TB RAW is only 35.68TB or approx 1/3rd!

Other factors which reduce usable capacity?

8. LUN Provisioning Type

In many cases, especially when talking about high performance applications, storage vendors recommend using Thick Provisioned LUNs.

As a result limited or no overcommitment can be achieved which reduces the usable capacity due to the thick provisioning.

It’s anyone’s guess how much space is wasted as a result.

Summary:

From the 100TB RAW factoring in what I believe to be realistic configuration of RAID, the impact of free space requirements, thick provisioning and capacity fragmentation we end up with only 35.68TB usable capacity or approx 1/3rd of the RAW.

Now most vendors provide some form of data reduction such as compression/de-duplication, others recommend some thin provisioning and these may increase the effective capacity, but this example shows its not as simple as you think to size for SAN/NAS storage and the overhead of RAID is only one of the many factors which impact the effective usable capacity.

In Part 2, I will run through a similar example for Nutanix usable capacity.

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

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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.

deduplication_diagram

The above image is courtesy of www.enterprisestorageguide.com.

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.

Feature-Snapshots-Full

Image courtesy of www.softnas.com.

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.

Summary

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.

Conclusion: 

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. 🙂