Category Archives: Storage

Dare2Compare Part 1 : HPE/Simplivity’s 10:1 data reduction HyperGuarantee Explained

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HPE have been relentless with their #HPEDare2Compare twitter campaign focused on the market leading Nutanix Enterprise Cloud platform and I for one have had a good laugh from it. But since existing and prospective customers have been asking for clarification I thought I would do a series of posts addressing each claim.

In part of this series, I will respond to the claim (below) that Nutanix can’t guarantee at least a 10:1 data efficiency ratio.

HPEDare2CompareTweetLol

Firstly let’s think about what is being claimed by HPE/SVT.

If you’re a potential customer, it would be fair for you to assume that if you have 100TB on your current SAN/NAS and you purchase HPE/SVT, you would only need to buy 10TB plus some room growth or to tolerate failures.

But this couldn’t be further from the truth. In fact, if you have 100TB today, you’ll likely need to purchase a similar capacity of HPE/SVT as most platform, even older/legacy ones have some data efficiency already, so what HPE/SVT is offering with deduplication and compression is nothing new or unique.

Let’s go over what the “HyperGuarantee” states and why it’s not worth the paper it’s written on.

HyperEfficientLol

It sounds pretty good, but two things caught my eye. The first is “relative to comparable traditional solutions” which excludes any modern storage which has this functionality (such as Nutanix) and the words “across storage and backup combined”.

Let’s read the fine print about “across storage and backup combined”.

HyperEfficientMoreLol

Hold on, I thought we were talking about a data reduction guarantee but the fine print is talking about a caveat requiring we configure HPE/Simplivity “backups”?

The first issue is if you use an enterprise backup solution such as Commvault, or SMB plays such as Veeam? The guarantee is void and with good reason as you will (HPE)discover shortly. 😉

Let’s do the math on how HPE/SVT can guarantee 10:1 without giving customers ANY real data efficiency compared to even legacy solutions such as Netapp or EMC VNX type platforms.

  1. Let’s use a single 1 TB VM as a simple example.
  2. Take 30 snapshots (1 per day for 30 days) and count each snapshot as if it was a full “backup” to disk.
  3. Data stored now equals 31TB  (1 TB + 30 TB)
  4. Actual Size on Disk is only ~1TB (This is because snapshots don’t create any copies of the data)
  5. Claimed Data Efficiency is 31:1
  6. Effective Capacity Savings = 96.8% (1TB / 31TB = 0.032) which is rigged to be >90% every time

So the guarantee is satisfied by default, for every customer and without actually providing data efficiency for your actual data!

I have worked with numerous platforms over the years, and the same result could be guaranteed by Netapp, Dell/EMC, Nutanix and many more. In my opinion the reason these vendors don’t have a guarantee is because this capability has long been table stakes.

Let’s take a look at a screenshot of the HPE/SVT interface (below).

SimplyshittyScreenshot

Source of image us an official SVT case study which can be found at: https://www.simplivity.com/case-study-coughlan-companies/

It shows an efficiency of 896:1 which again sounds great, but behind the smoke and mirrors it’s about as misleading as you can get.

Firstly the total “VM data” is 9.9TB

The “local backups” which are actually just pointer based copies (not backups at all) reports 3.2PB.

Note: To artificially inflate the report “deduplication” ratio, simply schedule more frequent metadata copies (what HPE/SVT incorrectly refer to as “backups”) and the ratio will increase.

The “remote backups” funnily enough are 0.0Kb which means the solution actually has no backups.

The real data reduction ratio can be easily calculated by taking the VM data of 9.9TB and dividing that by the “Used” capacity of 3.7TB which equates to 2.67:1 which can be broken down to be 2:1 compression as shown in the GUI with a <1.5:1 deduplication ratio.

In short, the 10:1 data efficiency HyperGuarantee is not worth the paper it’s written on, especially if you’re using a 3rd party backup product. If you choose to use the HPE/SVT built in pointer based option with or without replication, you will see the guaranteed efficiency ratio but don’t be fooled into thinking this is something unique to HPE/SVT as most other vendors including Nutanix have the same if not better functionality.

Remember, other vendors including Nutanix do not report metadata copies as “backups” or “data reduction” because its not.

So ask your HPE/SVT rep: “How much deduplication and compression is guaranteed WITHOUT using their pointer based “backups”. The answer is NONE!

For more information read this article which has been endorsed by multiple vendors on what should be included in data reduction ratios.

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Expanding Capacity on a Nutanix environment – Design Decisions

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I recently saw an article about design decisions around expanding capacity for a HCI platform which went through the various considerations and made some recommendations on how to proceed in different situations.

While reading the article, it really made me think how much simpler this process is with Nutanix and how these types of areas are commonly overlooked when choosing a platform.

Let’s start with a few basics:

The Nutanix Acropolis Distributed Storage Fabric (ADSF) is made up of all the drives (SSD/SAS/SATA etc) in all nodes in the cluster. Data is written locally where the VM performing the write resides and replica’s are distributed based on numerous factors throughout the cluster. i.e.: No Pairing, HA pairs, preferred nodes etc.

In the event of a drive failure, regardless of what drive (SSD,SAS,SATA) fails, only that drive is impacted, not a disk group or RAID pack.

This is key as it limited the impact of the failure.

It is importaint to note, ADSF does not store large objects nor does the file system require tuning to stripe data across multiple drives/nodes. ADSF by default distributes the data (at a 1MB granularity) in the most efficient manner throughout the cluster while maintaining the hottest data locally to ensure the lowest overheads and highest performance read I/O.

Let’s go through a few scenarios, which apply to both All Flash and Hybrid environments.

  1. Expanding capacityWhen adding a node or nodes to an existing cluster, without moving any VMs, changing any configuration or making any design decisions, ADSF will proactively send replicas from write I/O to all nodes within the cluster, therefore improving performance while reactively performing disk balancing where a significant imbalance exists within a cluster.

    This might sound odd but with other HCI products new nodes are not used unless you change the stripe configuration or create new objects e.g.: VMDKs which means you can have lots of spare capacity in your cluster, but still experience an out of space condition.

    This is a great example of why ADSF has a major advantage especially when considering environments with large IO and/or capacity requirements.

    The node addition process only requires the administrator to enter the IP addresses and its basically a one click, capacity is available immediately and there is no mass movement of data. There is also no need to move data off and recreate disk groups or similar as these legacy concepts & complexities do not exist in ADSF.

    Nutanix is also the only platform to allow expanding of capacity via Storage Only nodes and supports VMs which have larger capacity requirements than a single node can provide. Both are supported out of the box with zero configuration required.

    Interestingly, adding storage only nodes also increases performance, resiliency for the entire cluster as well as the management stack including PRISM.

  2. Impact & implications to data reduction of adding new nodesWith ADSF, there are no considerations or implications. Data reduction is truely global throughout the cluster and regardless of hypervisor or if you’re adding Compute+Storage or Storage Only nodes, the benefits particularly of deduplication continue to benefit the environment.

    The net effect of adding more nodes is better performance, higher resiliency, faster rebuilds from drive/node failures and again with global deduplication, a higher chance of duplicate data being found and not stored unnecessarily on physical storage resulting in a better deduplication ratio.

    No matter what size node/s are added & no matter what Hypervisor, the benefits from data reduction features such as deduplication and compression work at a global level.

    What about Erasure Coding? Nutanix EC-X creates the most efficient stripe based on the cluster size, so if you start with a small 4 node cluster your stripe would be 2+1 and if you expand the cluster to 5 nodes, the stripe will automatically become 3+1 and if you expand further to 6 nodes or more, the stripe will become 4+1 which is currently the largest stripe supported.

  3. Drive FailuresIn the event of a drive failure (SSD/SAS or SATA) as mentioned earlier, only that drive is impacted. Therefore to restore resiliency, only the data on that drive needs to be repaired as opposed to something like an entire disk group being marked as offline.

    It’s crazy to think a single commodity drive failure in a HCI product could bring down an entire group of drives, causing a significant impact to the environment.

    With Nutanix, a rebuild is performed in a distributed manner throughout all nodes in the cluster, so the larger the cluster, the lower the per node impact and the faster the configured resiliency factor is restored to a fully resilient state.

At this point you’re probably asking, Are there any decisions to make?

When adding any node, compute+storage or storage only, ensure you consider what the impact of a failure of that node will be.

For example, if you add one 15TB storage only node to a cluster of nodes which are only 2TB usable, then you would need to ensure 15TB of available space to allow the cluster to fully self heal from the loss of the 15TB node. As such, I recommend ensuring your N+1 (or N+2) node/s are equal to the size of the largest node in the cluster from both a capacity, performance and CPU/RAM perspective.

So if your biggest node is an NX-8150 with 44c / 512GB RAM and 20TB usable, you should have an N+1 node of the same size to cover the worst case failure scenario of an NX-8150 failing OR have the equivalent available resources available within the cluster.

By following this one, simple rule, your cluster will always be able to fully self heal in the event of a failure and VMs will failover and be able to perform at comparable levels to before the failure.

Simple as that! No RAID, Disk group, deduplication, compression, failure, or rebuild considerations to worry about.

Summary:

The above are just a few examples of the advantages the Nutanix ADSF provides compared to other HCI products. The operational and architectural complexity of other products can lead to additional risk, inefficient use of infrastructure, misconfiguration and ultimately an environment which does not deliver the business outcome it was originally design to.

Sizing infrastructure based on vendor Data Reduction assumptions – Part 2

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In part 1, we discussed how data reduction ratios can, and do, vary significantly between customers and datasets and that making assumptions on data reduction ratios, even when vendors provide guarantees, does not protect you from potentially serious problems if the data reduction ratios are not achieved.

In Part 2 we will go through an example of how misleading data reduction guarantees can be.

One HCI manufacturer provides a guarantee promising 10:1 which sounds too good to be true, and that’s because it, quite frankly, isn’t true. The guarantee includes a significant caveat for the 10:1 data reduction:

The savings/efficiency are based on the assumption that you configure a backup policy to take at least one <redacted> backup per day of every virtual machine on every<redacted> system in a given VMware Datacenter with those backups retained for 30 days.

I have a number of issues with this limitation including:

  1. The use of the word “backup” referring directly/indirectly to data reduction (savings)
  2. The use of the word “backup” when referring to metadata copies within the same system
  3. No actual deduplication or compression is required to achieve the 10:1 data reduction because metadata copies (or what the vendor incorrectly calls “backups”) are counted towards deduplication.

It is important to note, I am not aware of any other vendor who makes the claim that metadata copies ( Snapshots / Point in time copies / Recovery points etc.) are deduplication. They simply are not.

I have previously written about what should be counted in deduplication ratios, and I encourage you to review this post and share your thoughts as it is still a hot topic and one where customers are being oversold/mislead regularly in my experience.

Now let’s do the math on my claim that no actual deduplication or compression is required to achieve the 10:1 ratio.

Let’s use a single 1 TB VM as a simple example. Note: The size doesn’t matter for the calculation.

Take 1 “backup” (even though we all know this is not a backup!!) per day for 30 days and count each copy as if it was a full backup to disk, Data logically stored now equals 31TB  (1 TB + 30 TB).

The actual Size on disk is only a tiny amount of metadata higher than the original 1TB as the metadata copies pointers don’t create any copies of the data which is another reason it’s not a backup.

Then because these metadata copies are counted as deduplication, the vendor reports a data efficiency of 31:1 in its GUI.

Therefore, Effective Capacity Savings = 96.8% (1TB / 31TB = 0.032) which is rigged to be >90% every time.

So the only significant capacity savings which are guaranteed come from “backups” not actual reduction of the customer’s data from capacity saving technologies.

As every modern storage platform I can think of has the capability to create metadata based point in time recovery points, this is not a new or even a unique feature.

So back to our topic, if you’re sizing your infrastructure based on the assumption of the 10:1 data efficiency, you are in for rude shock.

Dig a little deeper into the “guarantee” and we find the following:

It’s the ratio of storage capacity that would have been used on a comparable traditional storage solution to the physical storage that is actually used in the <redacted> hyperconverged infrastructure.  ‘Comparable traditional solutions’ are storage systems that provide VM-level synchronous replication for storage and backup and do not include any deduplication or compression capability.

So if you, for example, had a 5 year old NetApp FAS, and had deduplication and/or compression enabled, the guarantee only applies if you turned those features off, allowed the data to be rehydrated and then compared the results with this vendor’s data reduction ratio.

So to summarize, this “guarantee” lacks integrity because of how misleading it is. It  is worthless to any customer using any form of enterprise storage platform probably in the last 5 –  10 years as the capacity savings from metadata based copies are, and have been, table stakes for many, many years from multiple vendors.

So what guarantee does that vendor provide for actual compression and deduplication of the customers data? The answer is NONE as its all metadata copies or what I like to call “Smoke and Mirrors”.

Summary:

“No one will question your integrity if your integrity is not questionable.” In this case the guarantee and people promoting it have questionable integrity especially when many customers may not be aware of the difference between metadata copies and actual copies of data, and critically when it comes to backups. Many customers don’t (and shouldn’t have too) know the intricacies of data reduction, they just want an outcome and 10:1 data efficiency (saving) sounds to any reasonable person as they need 10x less than I have now… which is clearly not the case with this vendors guarantee or product.

Apart from a few exceptions which will not be applicable for most customers, 10:1 data reduction is way outside the ballpark of what is realistically achievable without using questionable measurement tactics such as counting metadata copies / snapshots / recovery points etc.

In my opinion the delta in the data reduction ratio between all major vendors in the storage industry for the same dataset, is not a significant factor when making a decision on a platform. This is because there are countless other substantially more critical factors to consider. When the topic of data reduction comes up in meetings I go out of my way to ensure the customer understands this and has covered off the other areas like availability, resiliency, recoverability, manageability, security and so on before I, quite frankly waste their time talking about table stakes capability like data reduction.

I encourage all customers to demand nothing less of vendors than honestly and integrity and in the event a vendor promises you something, hold them accountable to deliver the outcome they promised.