Tag Archives: EMC

The All-Flash Array (AFA) is Obsolete!

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Over the last few years, I’ve had numerous customers ask about how Nutanix can support bare metal workloads. Up until recently, I haven’t had an answer the customers have wanted to hear.

As a result, some customers have been stuck using their exisiting SAN or worse still being forced to go out and buy a new SAN.

As a result many customers who have wanted to use or have already deployed hyperconverged infrastructure (HCI) for all other workloads are stuck managing an all flash array silo to service some bare metal workloads.

In June at .NEXT 2016, Nutanix announced Acropolis Block Services (ABS) which now allows bare metal workloads to be serviced by new or existing Nutanix clusters.

ABSoverview

As Nutanix has both hybrid (SSD+SATA) and all-flash nodes, customers can chose the right node type/s for their workloads and present the storage externally for bare metal workloads while also supporting Virtual Machines and Acropolis File Services (AFS) and containers.

So why would anyone buy an all-flash array? Let’s discuss a few scenarios.

Scenario 1: Bare metal workloads

Firstly, what applications even need bare metal these days? This is an important question to ask yourself. Challenge the requirement for bare metal and see if the justifications are still valid and if so, has anything changed which would allow virtualization of the applications. But this is a topic for another post.

If a customer only needs new infrastructure for bare metal workloads, deploying Nutanix and ABS means they can start small and scale as required. This avoids one of the major pitfalls of having to size a monolithic centralised, dual controller storage array.

While some AFA vendors can/do allow for non-disruptive controller upgrades, it’s still not a very attractive proposition, nor is it quick or easy. and reduces resiliency during the process as one of two controllers are offline. Nutanix on the other hand performs one click rolling upgrades which mean the largest the cluster, the lower the impact of an upgrade as it is performed one node at a time without disruption and can also be done without risk of a subsequent failure taking storage offline.

If the environment will only ever be used for bare metal workloads, no problem. Acropolis Block Services offers all the advantages of an All Flash Array, with far superior flexibility, scalability and simplicity.

Advantages:

  1. Start small and scale granularly as required allowing customers to take advantage of newer CPU/RAM/Flash technologies more frequently
  2. Scale performance and capacity by adding node/s
  3. Scale capacity only with storage-only nodes (which come in all flash)
  4. Automatically scale multi-pathing as the cluster expands
  5. Solution can support future workloads including multiple hypervisors / VMs / file services & containers without creating a silo
  6. You can use Hybrid nodes to save cost while delivering All Flash performance for workloads which require it by using VM flash pinning which ensures all data is stored in flash and can be specified on a per disk basis.
  7. The same ability as an all flash array to only add compute nodes.

Disadvantages:

  1. Your all-flash array vendor reps will hound you.

Scenario 2: Mixed workloads inc VMs and bare metal

As with scenario 1, deploying Nutanix and ABS means customers can start small and scale as required. This again avoids the major pitfall of having to size a monolithic centralised, dual controller storage array and eliminates the need for separate environments.

Virtual machines can run on compute+storage nodes while bare metal workloads can have storage presented by all nodes within the cluster, including storage-only nodes. For those who are concerned about (potential but unlikely) noisy neighbour situations, specific nodes can also be specified while maintaining all the advantages of Nutanix one-click, non-disruptive upgrades.

Advantages:

  1. Start small and scale granularly as required allowing customers to take advantage of newer CPU/RAM/Flash technologies more frequently
  2. Scale performance and capacity by adding node/s
  3. Scale capacity only with storage-only nodes (which also come in all flash)
  4. Automatically scale multi-pathing for bare metal workloads as the cluster expands
  5. Solution can support future workloads including multiple Hypervisors / VMs / file services & containers without creating a silo.

Disadvantages:

  1. Your All-Flash array vendor reps will hound you.

What are the remaining advantages of using an all flash array?

In all seriousness, I can’t think of any but for fun let’s cover a few areas you can expect all-flash array vendors to argue.

Performance

Ah the age old appendage measuring contest. I have written about this topic many times, including in one of my most popular posts “Peak performances vs Real world performance“.

The fact is, every storage product has limits, even all-flash arrays and Nutanix. The major difference is that Nutanix limits are per cluster rather than per Dual Controller Pair, and Nutanix can continue to scale the number of nodes in a cluster and continue to increase performance. So if ultimate performance is actually required, Nutanix can continue to scale to meet any performance/capacity requirements.

In fact, with ABS the limit for performance is not even at the cluster layer as multiple clusters can provide storage to the same bare metal server/s while maintaining single pane of glass management through PRISM Central.

I recently completed some testing with where I demonstrated the performance advantage of storage only nodes for virtual machines as well as how storage-only nodes improve performance for bare metal servers using Acropolis Block Services which I will be publishing results for in the near future.

Data Reduction

Nutanix has had support for deduplication, compression for a long time and introduced Erasure Coding (EC-X) mid 2015. Each of these technologies are supported when using Acropolis Block Services (ABS).

As a result, when comparing data reduction with all-flash array vendors, while the implementation of these data reduction technologies varies between vendors, they all achieves similar data reduction ratios when applied to the same dataset.

Beware of some vendors who include things like backups in their deduplication or data reduction ratios, this is very misleading and most vendors have the same capabilities. For more information on this see: Deduplication ratios – What should be included in the reported ratio?

Cost

Here we should think about what are the age old problems are with centralized shared storage (like AFAs)? Things like choosing the right controllers and the fact when you add more capacity to the storage, you’re not (or at least rarely) scaling the controller/s at the same time come to mind immediately.

With Nutanix and Acropolis Block Services you can start your All Flash solution with three nodes which means a low capital expenditure (CAPEX) and then scale either linearly (with the same node types) or non-linearly (with mixed types or storage only nodes) as you need to without having to rip and replace (e.g.: SAN controller head swaps).

Starting small and scaling as required also allows you to take advantage of newer technologies such as newer Intel chipsets and NVMe/3D XPoint to get better value for your money.

Starting small and scaling as required also minimizes – if not eliminates – the risk of oversizing and avoids unnecessary operational expenses (OPEX) such as rack space, power, cooling. This also reduces supporting infrastructure requirements such as networking.

Summary:

As shown below, the Nutanix Acropolis Distributed Storage Fabric (ADSF) can support almost any workload from VDI to mixed server workloads, file, block , big data, business critical applications such as SAP / Oracle / Exchange / SQL and bare metal workloads without creating silos with point solutions.

NutanixSingleFabricAllWorkloads

In addition to supporting all these workloads, Nutanix ADSF scalability both from a capacity/performance and resiliency perspective ensures customers can start small and scale when required to meet their exact business needs without the guesswork.

With these capabilities, the All-Flash array is obsolete.

I encourage everyone to share (constructively) your thoughts in the comments section.

Note: You must sign in to comment using WordPress, Facebook, LinkedIn or Twitter as Anonymous comments will not be approved,

Related Articles:

  1. Things to consider when choosing infrastructure.

  2. Scale out performance testing with Nutanix Storage Only Nodes

  3. What’s .NEXT 2016 – Acropolis Block Services (ABS)

  4. Scale out performance testing of bare metal workloads on Acropolis Block Services (Coming soon)

  5. What’s .NEXT 2016 – Any node can be storage only

  6. What’s .NEXT 2016 – All Flash Everywhere!

PART 2 – Problems with RAID and Object Based Storage for data protection

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Following on from Part 1, this post will discuss hyper-converged Distributed File Systems (i.e,: Nutanix) and compare with traditional SAN/NAS RAID and  hyper-converged solutions using Object storage for data protection.

The below diagram shows a 4 node hyper-converged solution using a Distributed File System with the same 4 x 4TB SATA drives with data protection using replication with 2 copies. (Nutanix calls this Resiliency Factor 2)

HyperconvergedDFSNormal

The first difference you may have noticed, is the data is much more granular than the Hyper-Converged Object store example in Part 1.

The second less obvious difference is the replicated copies of the data (i.e.: The data with Purple letters) on node 1 do not reside on a single other node, but are distributed throughout the cluster.

Now lets look at a drive failure example:

Here we see Node 1 has lost a Drive hosting 8 granular pieces of data 1MB in size each.

HyperconvergedDFSRecovery

Now the Distributed File System detects that the data represented by A,B,C,D,E,I,M,P has only a single copy within the cluster and starts the restoration process.

Lets walk through each step although these steps are completed concurrently.

1. Data “A” is replicated from Node 2 to Node 3
2. Data “B” is replicated from Node 2 to Node 4
3. Data “C” is replicated from Node 3 to Node 2
4. Data “D” is replicated from Node 4 to Node 2
5. Data “E” is replicated from Node 2 to Node 4
6. Data “I” is replicated from Node 3 to Node 2
7. Data “M” is replicated from Node 4 to Node 3
8. Data “P” is replicated from Node 4 to Node 3

Now the cluster has restored resiliency.

So what was the impact on each node?readwriteiorecovery

The above table shows a simplified representation of the workload of restoring resiliency to the cluster. As we can see, the workload (being 8 granular pieces of data being replicated) was distributed across the nodes very evenly.

Next lets look at the advantages of a Hyper-Converged Solution with a Distributed File System (which Nutanix uses).

  1. Highly granular distribution using 1MB extents not large Objects.
  2. The work required to restore resiliency after one drive (or node) failure was distributed across all drives and nodes in the Cluster leveraging all drives/nodes capability. (i.e.: Not constrained to the <100 IOPS of a single drive)
  3. The restoration rebuild is a low impact activity as the workload is distributed across the cluster and not dependant on source/destination pair of drives or nodes
  4. The rebuild has a low impact on the virtual machines running on the distributed file system and consistent performance is maintained.
  5. The larger the cluster the quicker and lower impact the rebuild is as the workload is distributed across a higher number of drives/nodes for the same size (Gb) worth of restoration.
  6. With Nutanix SSDs are used not only for Read/Write cache but as a persistent storage tier, meaning the recovering data will be written to SSD and where the data being recovered is not in cache (Memory or SSD tiers) it is still possible the data will be in the persistent SSD tier which will dramatically improve the performance of the recovery.

Summary:

As discussed in Part 1, Traditional RAID used by SAN/NAS and Hyper-converged solutions using Object based storage both suffer similar issues when recovering from drive or node failure.

Where as Nutanix Hyper-converged solution using the Nutanix Distributed File System (NDFS) can restore resiliency following a drive or node failure faster and with lower impact thanks to its highly granular and distributed architecture, meaning more consistent performance for virtual machines.

Scaling problems with traditional shared storage

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At VMware vForum Sydney this week I presented “Taking vSphere to the next level with converged infrastructure”.

Firstly, I wanted to thank everyone who attended the session, it was a great turnout and during the Q&A there were a ton of great questions.

One part of the presentation I got a lot of feedback on was when I spoke about Performance and Scaling and how this is a major issue with traditional shared storage.

So for those who couldn’t attend the session, I decided to create this post.

So lets start with a traditional environment with two VMware ESXi hosts, connected via FC or IP to a Storage array. In this example the storage controllers have a combined capability of 100K IOPS.

50kIOPS

As we have two (2) ESXi hosts, if we divide the performance capabilities of the storage controllers between the two hosts we get 50K IOPS per node.

This is an example of what I have typically seen in customer sites, and day 1, and performance normally meets the customers requirements.

As environments tend to grow over time, the most common thing to expand is the compute layer, so the below shows what happens when a third ESXi host is added to the cluster, and connected to the SAN.

33KIOPS

The 100K IOPS is now divided by 3, and each ESXi host now has 33K IOPS.

This isn’t really what customers expect when they add additional servers to an environment, but in reality, the storage performance is further divided between ESXi hosts and results in less IOPS per host in the best case scenario. Worst case scenario is the additional workloads on the third host create contention, and each host may have even less IOPS available to it.

But wait, there’s more!

What happens when we add a forth host? We further reduce the storage performance per ESXi host to 25K IOPS as shown below, which is HALF the original performance.

25KIOPS

At this stage, the customers performance is generally significantly impacted, and there is no easy or cost effective resolution to the problem.

….. and when we add a fifth host? We continue to reduce the storage performance per ESXi host to 20K IOPS which is less than half its original performance.

20KIOPS

So at this stage, some of you may be thinking, “yeah yeah, but I would also scale my storage by adding disk shelves.”

So lets add a disk shelf and see what happens.

20KIOPSAddDiskShelf

We still only have 100K IOPS capable storage controllers, so we don’t get any additional IOPS to our ESXi hosts, the result of adding the additional disk shelf is REDUCED performance per GB!

Make sure when your looking at implementing, upgrading or replacing your storage solution that it can actually scale both performance (IOPS/throughput) AND capacity in a linear fashion,otherwise your environment will to some extent be impacted by what I have explained above. The only ways to avoid the above is to oversize your storage day 1, but even if you do this, over time your environment will appear to become slower (and your CAPEX will be very high).

Also, consider the scaling increments, as a solutions ability to scale should not require you to replace controllers or disks, or have a maximum number of controllers in the cluster. it also should scale in both small, medium and large increments depending on the requirements of the customer.

This is why I believe scale out shared nothing architecture will be the architecture of the future and it has already been proven by the likes of Google, Facebook and Twitter, and now brought to market by Nutanix.

Traditional storage, no matter how intelligent does not scale linearly or granularly enough. This results in complexity in architecture of storage solutions for environments which grow over time and lead to customers spending more money up front when the investment may not be realised for 2-5 years.

I’d prefer to be able to Start small with as little as 3 nodes, and scale one node at a time (regardless of node model ie: NX1000 , NX3000 , NX6000) to meet my customers requirements and never have to replace hardware just to get more performance or capacity.

Here is a summary of the Nutanix scaling capabilities, where you can scale Compute heavy, storage heavy or a mix of both as required.

ScaingSolution