NetApp & Next Generation Storage Technologies.
April 17, 2018 2 Comments There are some exciting technology developments taking place in the storage industry, some behind closed doors but some that are also publicly announced and already commercially available that most of you may already have come across.
Some of these are organic developments to build on existing technologies but some are inspired by megascalers like AWS, Azure, GCP and various other cloud platforms.
I’ve been lucky enough to be briefed on some of these when I was at SFD12 last year I the Silicon Valley, by SNIA – The Storage and Networking Industry Association that I’ve previously blogged about here.
This time around, I was part of the Storage Filed Day (SFD15) delegate panel that got a chance to visit NetApp at their HQ at Sunnyvale, CA to find out more about some of exciting new product offerings that are in NetApp’s roadmap, either in the works or starting to just come out, incorporating some of these new storage technologies.
This post aim to provide a summary of what I learnt there and my respective thoughts.
It is no secret that Flash media has changed the dynamics of the storage market over the last decade due to their inherent performance characteristics.
While the earliest incarnations of flash media were prohibitively expensive to be used in mass quantities, the invention of SSDs commoditised the use of flash media across the entire storage industry.
For example, most tier 1 workloads in the enterprises today are held on a SSD backed storage system where SSD disk drives form the whole or a key part of the storage media stack.
When you look at some of the key storage solutions in use today, there are 2 key, existing flash technologies that stand out, DRAM & SSD.
DRAM is the fastest possible flash storage media that is most easily accessible by the data processing compute subsystem while SSD’s fall in to next best place when it comes to speed of access and the level of performance (IOPS & bandwidth).
As such, most enterprise storage solutions in the world, be that the ones aimed at the customer data centers or on the megascaler’s cloud platforms utilise one or both of these flash media types to either accelerate (caching) or simply store tier 1 data sets.
It is important to note that, while the SSD’s benefitted from the overall higher performance and lower latency compared to mechanical drives due to the internal architecture of the SSD disks themselves (flash storage cells that don’t require spinning magnetic media), both the SSD drives and classic mechanical (spinning) drives are typically attached & accessed by the compute subsystem via the same SATA or the SaS interface subsystem with the same interface speed & latency.
Often the internal performance of an SSD was not fully realised to its maximum potential, especially in an aggregated scenario like that of an enterprise storage array, due to these interface controller access speed and latency limitations, as illustrated in the diagram below.
One of the more recent technology developments in the storage and compute industry, namely “Non-Volatile Memory Express” (NVMe) aims to address these SAS & SATA interface driven performance and the latency limitations through the introduction of new, high performance host controller interface that has been engineered from the ground up to be able to fully utilise flash storage drives.
This new NVMe storage architecture is designed to be future proof and would be compatible with various future disk drive technologies that are NAND based as well as non-NAND based storage media.
NVMe SSD drives connected via these NVMe interfaces will not only outperform traditional SSD drives attached via SAS or SATA, but most importantly will enable higher future capabilities such as being able to utilise Remote Direct Memory Address (RDMA) for super high storage performance extending the storage subsystem over a fabric of interconnected storage and compute nodes.
A good introduction to the NVMe technology and its benefits over SAS / SATA interfaces can be viewed here.
Another much talked about development on the same front is the subject of the Storage Class Memory (SCM) – Also known as Persistent Memory (PMEM).
SCM is an organic successor to the NAND technology based SSD drives that we see in mainstream use in flash accelerated as well as all flash storage arrays today.
At a theoretical level, SCM can come in 2 main types as shown in the above diagram (from a really great IBM research paper published in 2013).
M-Type SCM (Synchronous) = Incorporate non-volatile memory based storage in to the memory access subsystem (DDR) rather than SCSI block based storage subsystem through PCIe, achieving DRAM like throughput and latency benefits for persistent storage.
Typically take the form of NVDIMM (that is attached to the memory BUS, similar to traditional DRAM) which is the fastest and best performant thing, next to DRAM itself.
Uses memory card slots and appear to the system to use as a caching layer or as pooled memory (extended DRAM space) depending on the NVDIMM type (NVDIMMs come in 3 types, NVDIMM-N, NVDIMM-F and NVDIMM-P.
A good explanation available here).
S-Type SCM (Asynchronous) = Incorporate non-volatile memory based storage but attached via the PCIe connector to the storage subsystem.
While this is theoretically slower than the above, it’s still significantly faster than NAND based SSD drives that are in common use today, .
Including those attached via NVMe host controller interface
Intel and Samsung both have already launched S-type SCM drives, Intel with their 3D XPoint architecture and Samsung with Z-SSD respectively but current drive models available are aimed more at consumer / workstation rather than server workloads.
Server based implementations of similar SCM drives will likely arrive around 2019.
(Along with supported server based software included within operating systems such as Hypervisors – vSphere 7 anyone?).
The idea of the SCM is to address the latency and performance gap that exist in every computer system when it comes to memory and storage since the advent of X86 computing.
Typically, access latency for DRAM is around 60ns, and the next best option today, NVMe SSD drives will have a typical latency of around 20-200us and the SCM will fit in between these 2, at a typical latency between 60ns-20uS, depending on the type of the SCM, with a significantly high bandwidth that is incomparable to SSD drives.
It is important to note however that most ordinary workloads do not need this type of super latency sensitive, extremely high bandwidth storage performance, the next generation data technologies involving Artificial Intelligence techniques such as machine learning, real-time analytics that relies on processing extremely large swathes of data at super quick time, would absolutely benefit, and in most instance, necessitate the need for these next gen storage technologies to be fully effective.
NetApp’s NVMe & SCM vision.
NetApp was one of the first classic storage vendors who incorporate flash in to their storage systems, in an efficient manner to accelerate the workloads that is typically stored on spinning disks.
This started with the concept of NVRAM that was included in their flagship FAS storage solutions as an acceleration layer.
Then came the flash cache (PAM cards) which were flash media attached via the PCIe subsystem to act as a cashing layer for reads which was also popular.
Since the advent of all flash storage arrays, NetApp went another step by introducing all flash storage in to their portfolio through the likes of All Flash FAS platform that was engineered and tuned for all flash media as well as the EF series.
NetApp innovation and constant improvement process hasn’t stopped there.
During SFD15 event, we were treated to the next step of this technology evolution by NetApp when they discussed how they plan to incorporate the above mentioned NVMe and SCM storage technologies in to their storage portfolio, in order to provide next gen storage capabilities to serve next gen use cases such as AI, big data and real-time analytics.
Given below is a holistic roadmap plan of where NetApp see NVMe and SCM technologies fitting in to their roadmap, based on the characteristics, benefits and costs of each technology.
The planned use of NVMe is clearly in 2 different points of the host->storage array communication path.
NVMe SSD drives : NVMe SSD drives in a storage array, attached via NVMe host controller interface in order to be able to fully utilise the latency and throughput potential of the SSD drives themselves by the storage processor (in the controllers).
This will provide additional performance characteristics to the existing arrays.
NVMe-OF : NVMe over fabric which is attached to the storage consumer nodes (Servers) via a ultra-low latency NVMe fabric.
NVMe-OF enable the use of RDMA capabilities to reduce the distance between the IO generator and the IO processor thereby significantly reducing the latency.
NVMe-OF therefore is widely touted to be the next big thing in storage industry and a number of specialists start-ups like Excelero have already come out to market with specialist solutions and you can find out more about it in my blog here.
An example of the NVMe-OF storage solution available from NetApp is the new NetApp EF570 all flash array.
This product is already shipping and more details can be found here or here.
This platform offers some phenomenal performance numbers at ultra-low latency, built around their trusted, mature, feature rich, yet simple EF storage platform which is also a bonus.
The planned (or experimented) use of SCM is in 2 specific areas of the storage stack, driven primarily by the costs of the media vs the need for acceleration.
Storage controller side caching: NetApp mentioned that some of the experiments they are working on with prototype solutions already built are looking at using SCM media on the storage controllers as a another tier to accelerate performance, in the same way PAM cards or Flash cache was used on the older FAS system.
This a relatively straight forward upgrade and would be specially effective in an all flash FAS solution with SSD drives in the back end where a traditional flash cache card based on NAND cells would be less effective.
Server (IO generator) side caching: This use case looks at using the SCM media on the host compute systems that generates the IO to act as a local cache, but most importantly, used in conjunction with the storage controllers rather than in isolation, performing tiering and snapshots from the host cache to a backend storage system like an All Flash FAS.
NetApp are experimenting on this front primarily using their recent acquisition of Plexistor and their proprietary software that performs the function of combining DRAM and SCM as a single address space that is byte addressable (via memory semantics which is much faster than scsi / NVMe addressable storage) and presenting that to the applications as a cache while also presenting the backend NetApp storage array such as an All Flash FAS as a persistent storage tier.
The applications achieve significantly lower latency and ultra-high throughput this way through caching the hot data using the Plexistor file system which incidentally bypasses the complex Linux IO stack (Comparison below).
The Plexistor tech is supposed to provide enterprise grade feature as a part of the same software stack though the specifics of what those enterprise grade features meant were lacking (Guessing the typical availability and management capabilities as natively available within OnTAP?).
Based on some of the initial performance benchmarks, the effect of this is significant, as can be seen below when compared to a normal My thoughts.
As an IT strategist and an Architect at heart with a specific interest in storage who can see super data (read “extremely large quantities of data”) processing becoming a common use case soon across most industries due to the introduction of big data, real-time analytics and the accompanying Machine Learning tech, I can see value in this strategy from NetApp.
Most importantly, they are looking at using these advanced technologies in harmony with some the proven, tried and tested data management platforms they already have in the likes of OnTAP software could be a big bonus.
The acquisition of Plexistor was a good move for NetApp and integrating their tech and having a shipping product would be super awesome if and when that happens but I would dare say the use cases would be somewhat limited prohibitive initially given the Linux dependency.
Others are taking note and the HCI vendor Nutanix’s acquisition of PernixData kind of hints Nutanix also having a similar strategy to that of Plexistor and NetApp.
While the organic growth of current product portfolio with capabilities through incorporating new tech such as NVMe is fairly straight forward and help NetApp stay relevant, it remains to be seen however how well acquisition driven integration such as that of Plexistor with SCM technologies to the NetApp platform would pan out to become a shipping product.
NetApp has historically had issues around the efficiency of this integration process which in the past has known to be slow but this time around, under the new CEO George Kurian who brought in a more agile software development methodology and therefore, a more frequent feature & update release cycle, things may well be different this time around.
The evidence seen during SFD15 pretty much suggest the same to me which is great.
Slide credit to NetApp.
Thanks NetApp, NetAppUnited, SFD15 #SFD15, AI, Analytics, Artificial Intelligence, Big data, EF570, Machine Learning, ML, NetApp, NetAppUnited, NVMe, NVMe-OF, PMEM, SCM Impact from Public Cloud on the storage industry – An insight from SNIA at #SFD12.
April 6, 2017 3 Comments As a part of the recently concluded Storage Field Day 12 (#SFD12), we traveled to one of the Intel campuses in San Jose to listen to the Intel Storage software team about future of storage from an Intel perspective (You can read all about here).
While this was great, just before that session, we were treated to another similarly interesting session by SNIA – The Storage Networking Industry Association and I wanted to brief everyone on what I learnt from them during that session which I thought was very relevant to everyone who has a vested interest in field of IT today.
The presenters were Michael Oros, Executive Director at SNIA along with Mark Carlson who co-chairs the SNIA technical council.
Introduction to SNIA.
SNIA is a non-profit organisation that was formed 20 years ago to deal with inter-operability challenges of network storage by various different tech vendors.
Today there are over 160 active member organisations (tech vendors) who work together behind closed doors to set standards and improve inter-operability of their often competing tech solutions out in the real world.
The alphabetical list of all SNIA members are available here and the list include key network and storage vendors such as Cisco, Broadcom, Brocade, Dell, Hitachi, HPe, IBM, Intel, Microsoft, NetApp, Samsung & VMware.
Effectively, anyone using any and most of the enterprise datacenter technologies have likely benefited from SNIA defined industry standards and inter-operability Some of the existing storage related initiatives SNIA are working on include the followings.
Hyperscaler (Public Cloud) Storage Platforms.
According to SNIA, Public cloud platforms, AKA Hyperscalers such as AWS, Azure, Facebook, Google, Alibaba…etc are now starting to make an impact on how disk drives are being designed and manufactured, given their large consumption of storage drives and therefore the vast buying power.
In order to understand the impact of this on the rest of the storage industry, lets clarify few key basic points first on these Hyperscaler cloud platforms first (for those didn’t know) Public Cloud providers DO NOT buy enterprise hardware components like the average enterprise customer They DO NOT buy enterprise storage systems (Sales people please read “no EMC, no NetApp, No HPe 3par…etc.”).
They DO NOT buy enterprise networking gear (Sales people please read “no Cisco switches, no Brocade switches, HPe switches…etc”.).
They DO NOT buy enterprise servers from server manufacturers (Sales people please read “no HPe/Dell/Cisco UCS servers…etc.).
They build most things in-house Often this include servers, network switches…etc.
They DO bulk buy disk drives direct from the disk manufacturers & uses home grown Software Defined Storage techniques to provision that storage.
Now if you think about it, large enterprise storage vendors like Dell and NetApp who normally bulk buy disk drives from manufacturers such as Samsung, Hitachi, Seagate…etc would have had a certain level of influence over how their drives are made given the economies of scale (bulk purchasing power) they had.
However now, Public cloud providers who also bulk buy, often quantities far bigger than those said storage vendors would have, also become hugely influential over how these drives are made, to the level that their influence is exceeding that of those legacy storage vendors.
This influence is growing such that they (Public Cloud providers) are now having a direct input towards the initial design of the said components (i.e disk drives…etc.) and how they are manufactured, simply due to the enormous bulk purchasing power as well as the ability they have to test drive performance at a scale that was not even possible by the drive manufacturers before, given their global data center footprint.
Expanding on the focus these guys have on Software Defined storage technologies to aggregate all these disparate disk drives found in their servers in the data center is inevitably leading to various architectural changes in how the disk drives are required to be made going forward.
For example, most legacy enterprise storage arrays would rely on the old RAID technology to rebuild data during drive failures and there are various background tasks implemented in the disk drive firmware such as ECC & IO re-try operations during failures which adds to the overall latency of the drive.
However with modern SDS technologies (in use within Public Cloud platforms as well as some new enterprise SDS vendors tech), there are multiple copies of data held on multiple drives automatically as a part of the Software Defined Architecture (i.e.
Erasure Coding) which means those specific background tasks on disk drives such as ECC, and re-try mechanism’s are no longer required.
For example, SNIA highlighted Eric Brewer, the VP of infrastructure of Google who talked about the key metrics for a modern disk drive to be, IOPS.
Lower tail latency (long tail of latencies on a drive, arguably caused due to various background tasks, typically causes a 2-10x slower response time from a disk in a RAID group which causes a disk & SSD based RAID stripes to experience at least a single slow drive 1.5%-2.2% of the time).
So in a nutshell, Public cloud platform providers are now mandating various storage standards that disk drive manufacturers have to factor in to their drive design such that the drives are engineered from ground up to work with Software Defined architecture in use at these cloud provider platforms.
What this means most native disk firmware operations are now made redundant and instead the drive manufacturer provides an API’s through which cloud platform provider’s own software logic will control those background operations themselves based on their software defined storage architecture.
Some of the key results of this approach includes following architectural designs for Public Cloud storage drives, Higher layer software handles data availability and is resilient to component failure so the drive firmware itself doesn’t have to.
Custom Data Center monitoring (telemetry), and management (configuration) software monitors the hardware and software health of the storage infrastructure so the drive firmware doesn’t have to The Data Center monitoring software may detect these slow drives and mark them as failed (ref Microsoft Azure) to eliminate the latency issue.
The Software Defined Storage then automatically finds new places to replicate the data and protection information that was on that drive.
Primary model has been Direct Attached Storage (DAS) with CPU (memory, I/O) sized to the servicing needs of however many drives of what type can fit in a rack’s tray (or two) – See the OCP Honey Badger.
With the advent of higher speed interfaces (PCI NVMe) SSDs are moving off of the motherboard onto an extended PCIe bus shared with multiple hosts and JBOF enclosure trays – See the OCP Lightning proposal.
Remove the drives ability to schedule advanced background operations such as Garbage collection, Scrubbing, Remapping, Cache flushes, continuous self tests…etc on its own and allow the host to affect the scheduling of these latency increasing drive maintenance operations when it sees fit – effectively remove the drive control plane and move it up to the control of the Public Cloud platform (SAS = SBC-4 background Operation Control, SATA = ACS-4 advanced background operaitons feature set, NVMe = Available through NVMe sets) Reduces unpredictable latency fluctuations & tail latency.
The result of all these means Public Cloud platform providers such as Microsoft, Google, Amazon are now also involved at setting industry standards through organisations such as SNIA, a task previously only done by hardware manufacturers.
An example is the DePop standard which is now approved at T13 which essentially defines a standard where the storage host will shrink the usable size of the drive by removing the poor performing (slow) physical elements such as drive sectors from the LBA address space rather than disk firmware.
The most interesting part is that the drive manufacturers are now required to replace the drives when enough usable space has shrunk to match the capacity of a full drive, without necessarily having the old drive back (i.e.
Public cloud providers only pay for usable capacity and any unusable capacity is replenished with new drives) which is a totally different operational and a commercial model to that of legacy storage vendors who consume drives from drive manufacturers.
Another concept that’s pioneered by the Public cloud providers is called Streams which maps lower level drive blocks with an upper level object such as a file that reside on it, in a way that all the blocks making the file object are stored contiguously.
This simplifies the effect of a TRIM or a SCSI UNMAP command (executed when the file is deleted from the file system) which reduces delete penalty and causes lowest amount of damage to SSD drives, extending their durability.
Future proposals from Public Cloud platforms.
SNIA also mentioned about future focus areas from these public cloud providers such as, Hyperscalers (Google, Microsoft Azure, Facebook, Amazon) are trying to get SSD vendors to expose more information about internal organization of the drives Goal to have 200 µs Read response and 99.9999% guarantee for NAND devices.
I/O Determinism means the host can control order of writes and reads to the device to get predictable response times – Window of reading – deterministic responses.
Window of writing and background – non-deterministic responses.
The birth of ODM – Original Design Manufacturers There is a new category of storage vendors called Original Design Manufacturer (ODM) direct who package up best in class commodity storage devices into racks according to the customer specifications and who operate at much lower margins.
They may leverage hardware/software designs from the Open Compute Project (OCP) or a similar effort in China called Scorpio, now under an organization called the Open Data Center Committee (ODCC), as well from as other available hardware/software designs.
SNIA also mentioned about few examples of some large global enterprise organisations such as a large bank taking the approach of using ODM’s to build a custom storage platform achieving over 50% cost savings over using traditional enterprise storage.
All of these Public Cloud platform introduced changes are set to collectively change the rest of the storage industry too and how they fundamentally operate which I believe would be good for the end customers.
Public cloud providers are often software vendors who approaches every solution with a software centric solution and typically, would have highly cost efficient architecture of using cheapest commodity hardware with underpinned by intelligent software.
This will likely re-shape the legacy storage industry too and we are already starting to see the early signs of this today through the sudden growth of enterprise focused Software Defined Storage vendors and legacy storage vendors struggling with their storage revenue.
All public cloud computing and storage platforms are a continuous evolution for the cost efficiency and each of their innovation in how storage is designed, built & consumed will trickle down to the enterprise data centers in some shape or form to increase overall efficiencies which surely is only a good thing, at least in my view.
And smart enterprise storage vendors that are software focused, will take note of such trends and adopt accordingly (i.e.
SNIA mentioned that NetApp for example, implemented the Stream commands on the front end of their arrays to increase the life of the SSD media), where as legacy storage / hardware vendors who are effectively still hugging their tin, will likely find the future survival more than challenging.
Also, the concept of ODM’s really interest me and I can see the use of ODM’s increasing further as more and more customers will wake up to the fact that they have been overpaying for their storage for the past 10-20 years in the data center due to the historically exclusive capabilities within the storage industry.
With more of a focus on a Software Defined approach, there are large cost savings to be had potentially through following the ODM approach, especially if you are an organisation of that size that would benefit from the substantial cost savings.
I would be glad to get your thoughts, through comments below If you are interested in the full SNIA session, a recording of the video stream us available here and I’d recommend you watch it, especially if you are in the storage industry.
Slide credit goes to SNIA and TFD.
SFD12, SNIA, Storage Field Day, Tech Field Day #SFD12, Cloud, Future, Hyperscaler, Latency, LTFS, NVM, NVMe, NVMe over fabric, ODM, Original Design Manufacturer, SFD, SNIA, storage, Tail, TWG Storage Futures With Intel Software From #SFD12.
March 18, 2017 5 Comments As a part of the recently concluded Storage Field Day 12 (#SFD12) , we traveled to one of the Intel campuses in San Jose to listen to the Intel Storage software team about future of storage from an Intel perspective.
This was a great session that was presented by Jonathan Stern (Intel Solutions Architect / @JonSternAtIntel) and Tony Luck (Principle Engineer) and this post is to summarise few things I’ve learnt during those sessions that I thought were quite interesting for everyone.
(prior to this session we also had a session from SNIA that was talking about future of storage industry standards but I think that deserves a dedicated post so I won’t mention those here – stay tuned for a SNIA event specific post soon!) First session from Intel was on the future of storage by Jonathan.
It’s probably fair to say Jonathan was by far the most engaging presenter out of all the SFD12 presenters and he covered somewhat of a deep dive on the Intel plans for storage, specifically on the software side of things and the main focus was around the Intel Storage Performance Development Kit (SPDK) which Intel seem to think is going to be a key part of the future of storage efficiency enhancements.
The second session with Tony was about Intel Resource Director Technology (addresses shared resource contention that happens inside an Intel processor in processor cache) which, in all honesty was not something most of us storage or infrastructure guys need to know in detail.
So my post below is more focused on Jonathan’s session only.
Future Of Storage.
As far as Intel is concerned, there are 3 key areas when it comes to the future of storage that need to be looked at carefully.
To put this in to some context, see the below revenue projections from Wikibon Server SAN research project 2015 comparing the revenue projections for Traditional Enterprise storage such as SAN, NAS, DAS (Read “EMC, Dell, NetApp, HPe”).
Enterprise server SAN storage (Read “Software Defined Storage OR Hyper-Converged with commodity hardware “).
Hyperscale server SAN (Read “Public cloud”).
It is a known fact within the storage industry that public cloud storage platforms underpinned by cheap, commodity hardware and intelligent software provide users with an easy to consume, easily available and most importantly non-CAPEX storage platform that most legacy storage vendors find hard to compete with.
As such, the net new growth in the global storage revenue as a whole from around 2012 has been predominantly within the public cloud (Hyperscaler) space while the rest of the storage market (non-public cloud enterprise storage) as a whole has somewhat stagnated.
This somewhat stagnated market was traditionally dominated by a few storage stalwarts such as EMC, NetApp, Dell, HPe…etc.
However the rise of the server based SAN solutions where commodity servers with local drives combined with intelligent software to make a virtual SAN / storage pool (SDS/HCI technologies) has made matters worse for these legacy storage vendors and such storage solutions are projected to eat further in to the traditional enterprise storage landscape within next 4 years.
This is already evident by the recent popularity & growth of such SDS/HCI solutions such as VMware VSAN, Nutanix, Scality, HedVig while at the same time, traditional storage vendors announcing reducing storage revenue.
So much so that even some of the legacy enterprise storage vendors like EMC & HPe have come up with their own SDS / HCI offerings (EMC Vipr, HPe StoreVirtual, annoucement around SolidFire based HCI solution…etc.) or partnered up with SDS/HCI vendors (EMC VxRail, VxRail…etc.) to hedge their bets against a loosing back drop of traditional enterprise storage.
If you study the forecast in to the future, around 2020-2022, it is estimated that the traditional enterprise storage market revenue & market share will be even further squeezed by even more rapid growth of the server based SAN solutions such as SDS and HCI solutions.
(Good luck to legacy storage folks) An estimate from EMC suggest that by 2020, all primary storage for production applications would sit on flash based drives, which precisely co-inside with the timelines in the above forecast where the growth of Enterprise server SAN storage is set to accelerate between 2019-2022.
According to Intel, one of the main reasons behind this forecasted increase of revenue (growth) on the enterprise server SAN solutions is estimated to be the developments of Non-Volatile Memory (NVMe) based technologies which makes it possible achieve very low latency through direct attached (read “locally attach”) NVMe drives along with clever & efficient software that are designed to harness this low latency.
In other words, drop of latency when it comes to drive access will make Enterprise server SAN solutions more appealing to customers who will look at Software Defined, Hyper-Converged storage solutions in favour of external, array based storage solutions in to the immediate future and legacy storage market will continue to shrink further and further.
I can relate to this prediction somewhat as I work for a channel partner of most of these legacy storage vendors and I too have seen first hand the drop of legacy storage revenue from our own customers which reasonably backs this theory.
With the increasing push for Hyper-Convergence with data locality, the latency becomes an important consideration.
As such, Intel’s (& the rest of the storage industry’s) main focus going in to the future is primarily around reducing the latency penalty applicable during a storage IO cycle, as much as possible.
The imminent release of this next gen storage media from Intel as a better alternative to NAND (which comes with inherent challenges such as tail latency issues which are difficult to get around) was mentioned without any specific details.
I’m sure that was a reference to the Intel 3D XPoint drives (Only just this week announced officially by Intel http://www.intel.com/content/www/us/en/solid-state-drives/optane-solid-state-drives-dc-p4800x-series.html) and based on the published stats, the projected drive latencies are in the region of < 10μs (sequential IO) and < 200μs (random IO) which is super impressive compared to today’s ordinary NVMe SSD drives that are NAND based. This however presents a concern as the current storage software stack that process the IO through the CPU via costly context switching also need to be optimised in order to truly benefit from this massive drop in drive latency. In other words, the level of dependency on the CPU for IO processing need to be removed or minimised through clever software optimisation (CPU has long been the main IO bottleneck due to how MSI-X interrupts are handled by the CPU during IO operations for example). Without this, the software induced latency would be much higher than the drive media latency during an IO processing cycle which will contribute to an overall higher latency still. (My friend & fellow #SFD12 delegate Glenn Dekhayser described this in his blog as “the media we’re working with now has become so responsive and performant that the storage doesn’t want to wait for the CPU anymore!” which is very true). Furthermore, Storage Performance Development Kit (SPDK). Some companies such as Excelero are also addressing this CPU dependency of the IO processing software stack by using NVMe drives and clever software to offload processing from CPU to NVMe drives through technologies such as RDDA (Refer to the post I did on how Excelero is getting around this CPU dependency by reprogramming the MSI-X interrupts to not go to the CPU). SPDK is Intel’s answer to this problem and where as Excelero’s RDDA architecture primarily avoid CPU dependency by bypassing CPU for IOs, Intel SPDK minimizes the impact on CPU & Memory bus cycles during IO processing by using the user-mode for storage applications rather than the kernel mode, thereby removing the need for costly context switching and the related interrupt handling overhead. According to http://www.spdk.io/, “The bedrock of the SPDK is a user space, polled mode, asynchronous, lockless NVMe driver that provides highly parallel access to an SSD from a user space application.” With SPDK, Intel claims that you can reach up to around 3.6million IOPS per single Xeon CPU core before it ran out of PCI lane bandwidth which is pretty impressive. Below is a IO performance benchmark based on a simple test of CentOS Linux kernel IO performance (Running across 2 x Xeon E5-2965 2.10 GHz CPUs each with 18 cores + 1-8 x Intel P3700 NVMe SSD drives) Vs SPDK with a single dedicated 2.10 GHz core allocated out of the 2 x Xeon E5-2965 for IO. You can clearly see the significantly better IO performance with SPDK, which, despite having just a single core, due to the lack of context switching and the related overhead, .
Is linearly scaling the IO throughput in line with the number of NVMe SSD drives
(In addition to these testing, Jonathan also mentioned that they’ve done another test with Supermicro off the shelf HW and with SPDK & 2 dedicated cores for IO, they were able to get 5.6 million IOPS before running out of PCI bandwidth which was impressive) SPDK Applications & My Thoughts.
SPDK is an end-to-end reference storage architecture & a set of drivers (C libraries & executables) to be used by OEMs and ISV’s when integrating disk hardware.
According to Intel’s SPDK introduction page, the goal of the SPDK is to highlight the outstanding efficiency and performance enabled by using Intel’s networking, processing and storage technologies together.
SPDK is available freely as an open source product that is available to download through GitHub.
It also provide NVMeF (NVMe Over Fabric) and iSCSI servers to be built using the SPDK architecture, on top of the user space drivers that are even capable of servicing disks over the network.
Now this can potentially revolutionise how the storage industry build their next generation storage platforms. Consider for example any SDS or even a legacy SAN manufacturer using this architecture to optimise the CPU on their next generation All Flash storage array? (Take NetApp All Flash FAS platform for example, they are known to have a ton of software based data management services available within OnTAP that are currently competing for CPU cycles with IO and often have to scale down data management tasks during heavy IO processing. With Intel DPDK architecture for example, OnTAP can free up more CPU cycles to be used by more data management services and even double up on various other additional services too without any impact on critical disk IO.
I mean its all hypothetical of course as I’m just thinking out loud here.
Of course it would require NetApp to run OnTAP on Intel CPUs and Intel NVMe drives…etc but it’s doable & makes sense right.
I mean imagine the day where you can run “reallocate -p” during peak IO times without grinding the whole SAN to a halt? :-).
I’m probably exaggerating its potential here but the point here though is that SDPK driven IO efficiencies can apply same to all storage array manufacturers (especially all flash arrays) where they can potentially start creating some super efficient, ultra low latency, NVMe drive based storage arrays and also include a ton of data management services that would have been previously too taxing on CPU (think inline de dupe, inline compression, inline encryption, everything inline…etc.) that’s on 24×7 by default, not just during off peak times due to zero impact on disk IO.
Another great place to apply SPDK is within virtualisation for VM IO efficiency.
Using SPDK with QEMU as follows has resulted in some good IO performance to VM’s I mean imagine for example, a VMware VSAN driver that was built using the Intel DPDK architecture running inside the user space using a dedicated CPU core that will perform all IO and what would be the possible IO performance.
VMware currently performs IO virtualisation in kernel right now but imagine if SPDK was used and IO virtualisation for VSAN was changed to SW based, running inside the user-space, would it be worth the performance gain and reduced latency.
(I did ask the question and Intel confirmed there are no joint engineering currently taking place on this front between 2 companies).
What about other VSA based HCI solutions, especially take someone like Nutanix Acropolis where Nutanix can happily re-write the IO virtualisation to happen within user-space using SPDK for superior IO performance.
Intel & Alibaba cloud case study where the use of SPDK was benchmarked has given the below IOPS and latency improvements NVMe over Fabric is also supported with SPDK and some use cases were discussed, specifically relating to virtualisation where VM’s tend of move between hosts and a unified NVMe-oF API that talk to local and remote NVMe drives being available now (some part of the SPDK stack becoming available in Q2 FY17) Using the SPDK seems quite beneficial for existing NAND media based NVMe storage, but most importantly for newer generation non-NAND media to bring the total overall latency down.
However that does mean changing the architecture significantly to process IO in user-mode as opposed to kernel-mode which I presume is how almost all storage systems, Software Defined or otherwise work and I am unsure whether changing them to be user-mode with SPDK is going to be a straight forward process.
It would be good to see some joint engineering or other storage vendors evaluating the use of SPDK though to see if the said latency & IO improvements are realistic in complex storage solution systems.
I like the fact that Intel has made the SPDK OpenSource to encourage others to freely utilise (& contribute back to) the framework too but I guess what I’m not sure about is whether its tied to Intel NVMe drives & Intel processors.
If anyone wants to watch the recorded video of our session from # SFD12 the links are as follows Jonathan’s session on SPDK.
Tony’s session on RDT.
#SFD12 #TechFieldDay @IntelStorage Intel, SFD12, Storage Field Day, Tech Field Day #SFD12, 3D XPoint, Acropolis, Development, Excelero, Intel, Interrupt, Jonathan, Kit, MSX-I, NetApp, Nutanix, NVMe, NVMeF, NVMesh, Performance, RDDA, SPDK, Stern, storage, TDF, , .
VSAN Excelero – The Latest Software Defined Storage Startup
March 15, 2017 5 Comments As a part of the recently concluded Storage Field Day 12 (#SFD12), I had the privilege to sit in front of the engineering & the CxO team of the silicon valley’s newest (and should I say one of hottest) storage start up, Excelero, to find out more about their solution offering on the launch day itself of the company.
This post is to summarise what I’ve learnt, and my honest thoughts on what I saw and heard about their solution.
Apologies about the length of the post – Excelero has some really cool tech and I wanted to provide my thoughts in detail, in a proper context.
???? Enterprise Storage Market.
So lets start with a bit of context first.
If you look at the total storage market as a whole, it has been growing due to the vast and vast amounts of the data being generated from everything we do (consumer as well as enterprise activities).
This growth in storage requirements I believe will likely accelerate even faster in the future as we are going to be generating even more data and most of such data are likely going to end up on megascaler’s cloud storage platforms (public cloud).
Due to this impact from Public cloud platforms such as AWS, Azure, Google cloud…etc.
that suck up most of those storage requirements, the traditional enterprise storage market (where customers typically used to own their own storage) has been very competitive and is perceived to be going through a bit of a downward trend.
This has prompted a number of consolidation activities across the storage tech industry and the obvious elephant in the room is the Dell acquisition of EMC while similar other events include HPe’s recent acquisition of Nimble storage and Dell killing off its DSSD array plans etc. So, specially in this supposedly dwindling enterprise storage market (non cloud), the continuous innovation is critical for these enterprise storage vendors in order to compete with Public cloud storage platforms and demand a larger portion of this dwindling, enterprise storage pie.
This constant innovation, often software & hardware lead rather than just hardware lead, gives them the ability to provide their customers with faster, larger storage solutions and most importantly a differentiated storage solution offering, together with added data management technologies to meet various 21st century business requirements.
Now, as someone that work in an organisation that partners with almost all of these storage tech companies (legacy and start-ups), I know fairly well that almost every single one of the storage tech vendors are prioritising the use of NVMe flash drives (in its various form factors) as a key focus area for innovation (in most cases, .
NVMe in itself is their only option without any surrounding innovation which is poor)
This was also evident during the #SDF12 event I attended as almost all the storage vendors that presented to us touted NVMe based flashed drives as their key future road map items.
Even SNIA – The body for defining standards in the Storage and Networking industry themselves included a number of new NVMe focused standards as being in their immediate and future focus areas. (separate blog post to cover SNIA presentation content from #SDF12 – Stay tuned!).
Talking about NVMe in particular
the forecast on the NVMe technology roadmap going in to the future looks somewhat like below (image credit to www.nvmexpress.org) where the future is all focused around NVMe over fabric technologies that can integrate multiple NVMe drives across various different hosts via a high bandwidth NVMe fabric (read “low latency, high bandwidth network”).
Introduction to Excelero.
Excelero is a brand new, Israel tech startup, that was founded in 2014 in Tel Aviv that has a base in Silicon valley, that just came out of stealth on the 8th of March 2017. Despite only just coming out of stealth, as you can see they have some impressive list of high end customers on the list already.
Their offering is primarily a SDS solution with some real innovation in the form of an efficient (& patented) software stack, engineered to exploit latest development in the storage hardware technologies such as NVMe drives, NVMe over Fabric (NVMesh) and RDMA technology all working in harmony to boost NVMesh performance, unlike any other storage vendor that I know of (At this point in time). They have built a patented software stack focused around RDDA (Remote Direct Data Access which is similar to RDMA in how it operates – more details below) which by passes CPU (& memory to a level) on the storage controllers / nodes / servers when it comes to storage IO processing, .
Such that it requires zero CPU power on the storage node to serve IO
If you are a storage person, you’d know the biggest problem is / has been in the storage industry for scaling performance up is the CPU power on the storage nodes / controllers, especially when you use NAND technologies such as SSD and this is why if you look at every All Flash Array, you’ll see a ton of CPU cores operating at a very high frequency in every controller node.
Excelero is conveniently getting around this issue by de-coupling storage management & data and most importantly, using RDDA technology to bypass storage server CPU for disk IO (which is now offloaded to a dedicated RDMA capable network card (RoCE / RNIC) such as Mellanox Connectrix-3/4/5 card).
In a nutshell (and this is for the sales people that reads this) – Excelero is a scale out, innovative, Software Defined Storage solution that is unlike any other in the market right now.
They use next generation storage & networking hardware technologies to provide a low cost, extremely low latency, extremely high bandwidth storage solution for specific enterprise use cases that demands such a solutions. Excelero claims that they can produce 100 million IOPS along with some obscene bandwidth throughputs with little to no CPU capacity on the server side (storage nodes) and I believe them, especially after having seen a scaled down demo in action.
I would say they are probably one of the best if not the best solution of its kind available in the market right now and that is my honest view.
Please read on the understand why.
Typical use cases Excelero initially aims to address are any enterprise business requirements looking for a high bandwidth, ultra low latency, block protocol storage solution.
Some of the typical examples are as follows.
Advanced warning: If you are a SALES GUY, FORGET THIS SECTION!.
I’m certain it aint gonna work for you.
Honestly, don’t waste your time.
Just skip this section and read the next section ????.
If you are a techie however, do carry on.
It is important first of all to understand some key concepts used within the Excelero solution and their architectural overview.
The NVMesh server SAN Architecture that Excelero has built is a key part of the Excelero software stack & given below is a high level overview.
NVMesh is the technology using which Excelero aggregates various remote NVMe drives in to a single pool of drives that are accessible by all participating storage nodes over the NVMe fabric network, but most importantly as local drives (with local drive characteristics such as latency) NVMesh design goals: Performance, Scalability, Integration, Flexibility, Efficiency, Ease of use.
Components involved Control path Centralised management for provisioning, management & all control activities.
(All intelligence reside at this layer).
Runs as a Node.js application on top of MongoDB.
Pools drives, provisions volumes and monitor.
Transforms drives from raw storage into a pool.
Also includes topology manager which Runs on all the nodes as a distributed service.
Implements the cluster management and HA.
Performs volume lifecycle management.
Uses Multi-RAFT protocols avoid split brain and RAIN data protection across a large node cluster.
Communicates with the target software that runs on the storage nodes.
Rest-full API for integration with automation and external orchestration platforms such as Mesos (Kubernetes support is on the road map).
Docker support with a persistent storage plugin available.
Data path Kernel module that manages drives and act as a storage server for clients.
Provide true convergence which removes target module from the data path (CPU) such that storage nodes can run applications and other data services on the server nodes without CPU conflict / Impact (node that this is a new definition to hyper-converged compared to other HCI vendors such as VMware / Nutanix …etc.).
Point to point communication with other storage nodes, management & clients.
NVMesh client Intelligent client block driver (Linux) where client side storage services are implemented.
Kernel module that presents logical volumes via the above block driver API.
No need for iSCSI or FC as the Excelero solution is not using SCSI protocol for communication.
Hardware components Standard X86 servers with NVMe drives (more details on HW below) & RNIC cards.
Next generation switches.
Software components (Excelero Intellectual Property)
Note that the current version of NVMesh (1.1) is supported on Linux only and lacks any specific data services such as de-duplication & compression etc but these services are included in the roadmap.
Based on what was disclosed to us, some these future improvements include QoS capabilities, Additional drive media support, additional Hardware architecture support, Non-Linux OS support, Additional deployment methods, reduced power configurations as well as integration with Software Defined Networking solutions which sounds very promising as a total solution as was very good to hear.
-RDDA (Remote Direct Data Access)-.
RDDA is the patented secret sauce that Excelero has developed which is the other most important part of their solution stack.
It works hand in hand with the NVMesh software stack (described above) and its primary purpose is to avoid the use of CPU on the storage nodes, when processing client IO.
They key points to note about the RDDA technology is Developed a while ago by Excelero to fill a gap that was in the market.
(A new replacement for this is coming soon).
No CPU utilisation on the target side – This is achieved through the RDDA technology which bypasses the target side CPU.
RDDA only works with NVMe & is highly optimised for NVMe & remote NVMe access (so if you use non NVMe drives, which is also possible, there are no RDDA capabilities).
However if used in converged mode (centralised storage), RDDA is not used so target side CPU will have an impact.
Now I’m not an expert of how a typical NVMe read / write would occur and all the typical sub-protocol level steps that are involved.
But from what I gathered based on their architect’s description, given below are the high level steps involved in Excelero’s RDDA technology when it comes to local and remote NVMe writes and reads.
I’ve included this in order to explain at a high level how this technology differs to others and why the CPU is no longer necessary on the target side.
Pre-requisite knowledge: If you are unfamiliar with certain NVMe operations & techniques such as submission queue, completion queue.
Doorbell.etc which are typically used in a NVMe I/O operation
refer to this article for a basic understanding of it first before reading the below in order to make better sense.
The below image is from that article Now that you supposedly understand the NVMe commend process, lets have a look at Excelero’s high level implementation of RDDA (based on my understanding – Actual process may slightly differ or have many more steps / validations…etc.) Each client side read or a write will always result in a single RDMA write that is sent from the client side directly in to the destination storage node.
There are 3 pieces of this NVMe write that occur on the storage node
Local write (if to a local NVMe disk) or a remote write (if reading or writing to a remote NVMe drive) to the NVMe drive’s submission queue.
This include any data to be written if that’s a write operation where write data is put in to the local or remote memory and is referenced within this write in the submission queue.
Also writes in to the RNIC’s queue (memory) a message (memory buffer called a “Bounce buffer” which is made to point to the completion queue of the NVMe drive) to be sent back to the client (imagine a sort of a pre-paid envelop).
This is effectively a pre-prepared message to be sent back to client (to be used if it’s a read request).
Ring the doorbell on the NVMe drive (to start executing) after which the NVMe drive on the storage node will start acting to execute the IO operation.
(Note that so far, there were no CPU operations on the storage node as no storage side SW has been used).
If it’s a read op, it will then fill the bounce buffer that was pre-prepared in the step 2 above with the data that is read from the NVMe disk.
If it’s a write op, it will write the data that was put in to memory (above) to the disk.
Once the above NVMe operation is complete, it will generate 2 things Small completion (less important part).
Most important part is that it then generate a MSI-X interrupt.
Typically speaking, MSI-X interrupts are targeted at the CPU which is why during IO cycles, the CPU utilisation on the storage controllers go up.
Unlike in a typical MSI-X interrupt’s case, with Excelero RDDA, the MSI-X interrupt is pre-programmed to not go to the CPU but instead, go ring the doorbell of the NVMe NIC.
Upon this doorbell, the NVMe NIC will then send the pre-prepared Bounce buffer (step 2 above) which was pointing at the completion queue of the NVMe drive read data if that was a read operation, or if that was a write op, it would send the completion queue details along with some other data back to the client via the NVMe fabric, involving “ZERO” CPU on the storage node.
This bit is the Excelero’s patented technology that allows them to NOT use any CPU on the storage server side during any IO operation no matter how big the IOPS / bandwidth is.
You’ll see from this high level operation flow that during the whole IO process, no server side CPU was ever required & all the IO processing were carried our by the RNIC’s and the NVMe drives, and the traffic transported across the NVMe fabric (network). Note however that on client side, CPU is used as normal (similar to any other client accessing storage).
Also note that there is no concept of caching to memory when it comes to write IO (no nvram) and therefore the acknowledgement is only sent back to the client once the data is written to the NVMe drive.
The current RNICs used within the Excelero solution are Mellanox (to be specific, Mellanox Connectrix-3/4/5) but they’ve mentioned that it could also work on Q-Logic RNIC cards too.
Excelero also indicated that they are already working with another large networking vendors for additional RNIC card support, though didn’t mention exactly who that is (Cisco or Broadcom??) -RAIN Architecture-.
Excelero uses a concept of RAIN (similar to RAID) when it comes to provisioning volumes and providing high availability.
Key details are as follows.
A logical volume is a RAIN data protected volume which consist of one or more partial drives.
high performance volume may include a number of drives but only a part of each drive’s capacities may be used).
The key differentiator here is that as opposed to RAID which is across local disks, RAIN is across disks from multiple host (similar to network RAID).
Current version of the solution support RAIN10 (imagine RAID 10 over the NW but this time over NVMe fabric).
Erasure coding would be available soon.
Excelero solution is supported as both Local Storage in Application server mode (similar to Hyper-Converged but without a hypervisor) as well as converged (centralised storage) mode and each method will have certain limitations (such as RDDA not being applicable in a converged deployment).
You can supposedly deploy them in mixed mode too though I don’t quite remember who that works.
Excelero boasts some obscene performance levels to produce 100 million IOPS with little to no CPU capacity on the storage nodes which totally seems believable.
It is important to understand that Excelero doesn’t necessarily promise to deliver more IO / bandwidth than a NVMe disk manufacturer claims possible from a raw NVMe disk, but they ensure that the maximum possible capability can be extracted from a NVMe drive with NAND storage when used with their solution.
In order to do that, Excelero NVMesh & RDDA technologies combine to present remote NVMe drives as local drives which makes a significant difference to the latency that is possible with no CPU penalty on server side.
No other storage vendor can provide such capability as far as I know (Perhaps, except for HPe’s prototype “Machine project” that is supposedly looking at the use of Photonics to reduce the distance between processors and persistent local and remote memory which is used as storage.
However this is not a shipping product and its doubtful whether it would ever ship, and if does, its likely going to cost an obscenely high amount, compared to low cost option available with Excelero) In order to see whats possible, we were treated to a live demo of their platform running on a bunch of Supermicro commodity server hardware with lower scale Intel Xeon CPU’s and a mix of Intel and Samsung NVMe drives interlinked with Mellanox ConnectX-5 100Gbs Ethernet RoCE adaptors and a Dell Z9100-ON network switch.
Its fair to say, the demo results blew our socks off!!.
And we did have some storage industry stalwarts in our delegate panel at #SFD12 who’s been there in the storage industry since its enterprise inception and every one of those guys (and myself) were grinning from the left year to the right, when watching this demo and the stats that came out (that’s a “GOOD” thing in case it wasn’t clear :-)).
When 4 x Intel 400GB NVMe drives from 4 different hosts were used in a single storage pool and performed a random read operation with 4K IO’s, the stats we saw were around 4.9 million IOPS @ 25GB/s bandwidth and less than or around 200µs of latency (consistently) – This was somewhat previously unseen.
When the write test was shown (on the same disk pool across 4 servers) with 4K writes, the results were around 2.4 million IOPS @ < 200µs latency. We were also shown the CPU stats during the IO operations where the CPU utilisation on each storage node was hovering around 0.84% throughout the entire demo to prove the RDDA technology clearly bypasses the server side CPU which was super impressive. These IOPS & latency figures were more than good numbers and while I couldn’t verify this, Excelero team mentioned to us that the server configs used for this demo only cost them $13,000 each which, if true, is a massive cost saving that is potentially available for all future Excelero customers here. With RDDA, IO performance is now offloaded from the storage node CPU to the RNIC & the Ethernet fabric and while their saturation points are much higher than in a traditional architecture that relies on host CPU, the capabilities of the fabric the RNIC cards are now likely going to be the performance bottleneck in the future so if someone’s architecting a solution using Excelero, it would be pretty important to make the appropriate design choices on the fabric and the RNIC cards to make the solution future proof. Solution Licensing & Costs. We didn’t discuss much around the costs and we were not privy to list pricing, however its very likely that that the licensing & costs would be, Flexible pricing, and likely going to cost similar to that of a matching All Flash Array but Excelero would provide around 20-30% more performance. Can be licensed per NVMe drive or per server (Not penalised for capacity of the drive which is good) Hyper-Converged: Storage nodes where the storage is brought local to application servers (no hypervisor involved). Centralized (Converged): Separate price for storage nodes and client nodes. Customer Case Studies. Despite being a fresh start-up, they have some impressive customers already on board such as NASA, PayPal, Dell, Micron, Broadcom, HPe, Intel and most importantly they are an integral part of the LinkedIn’s Open19 project (New open standard for servers, storage & networking – I will produce a separate article on Open 19 in the future and much line the OCP project, its going to help define the datacenter of tomorrow). In the case of the NASA’s deployment of Excelero, we were made to understand that the solution is capable of doing around 140GB/s write throughput across 128 servers which is astonishing. Some popular customer case studies that are publicly referenceble are as follows My Thoughts. Put simply, I like their solution offering….. A lot…!. – No wait… that’s an understatement. I absolutely love their solution offering and the level of innovation they seem to have put in to it. For certain workloads that are pure performance centric and cares less about advanced data services, I think Excelero solution would be the one to beat, at least in the short term in the industry. As of right now, if you look at all hardware and software defined storage solutions that are generally available to purchase in the market, in my view, Excelero has a unique offering when it comes to its target market. Some of those uniqueness comes from the below points They have the only virtual SAN (SDS) solution that will harness shared NVMe (NVMe over fabric) in the market today. Unified NVMe which enables sharing storage across a network but still accessed at local speeds and latencies.
No CPU impact for storage IO on the storage node
Flexible architecture that provide hyper-converged as well as converged (disaggregated) architectures.
There are a ton of SDS solutions out there in the market, some from the legacy storage vendors such as Cisco, HPe, EMC as well as dedicated SDS vendor start-ups (that are no longer start-ups such as Nutanix, VMware vSAN, HedVig…etc.) and typically most of these solutions will look at using industry standard disk drives with industry standard server hardware (X86) plus, their own storage software stack on top, typically as a dedicated (read “centralised”) storage node or as a hyper-converged offering (read “de-centralised”). Excelero is no different from an architectural perspective to most of these SDS vendors.
However due to its additional unique capabilities such as RDDA & NVMesh
their SDS solution stack is likely going to be very attractive for most high end, ultra low latency storage requirements where no other SDS or a even a purpose build All Flash Array will no longer be able to compete anymore.
This is precisely Excelero’s initial target market and I would presume they would do very well within that segment, provided that they get their marketing message right.
However given the current lack of advanced data services, it is unlikely that they’d replace more mature, HCI or SDS offerings that are much richer in advanced data services such as VMware VSAN, Nutanix as well as All Flash Array offerings from the likes of NetApp (All Flash FAS or SolidFire), HPe 3Par All Flash, EMC XtremIO, when it comes to more common purpose mixed use cases, such as virtualisation platforms or VDI.
Having said that, you can argue that Excelero’s offering is a version 1 product right now and future versions will add these missing advanced data services which will make it equally competitive or even better.
Due to the lack of CPU dependency on storage IO processing
Excelero can afford to overload it’s storage nodes with so many advanced data services, all run inline and always on without any impact on any IO performance which is a big headache other All Flash Storage Array or SDS vendors cannot avoid.
So in theory, Excelero’s storage platform in time could be even superior than it is today.
At present, Excelero has 2 Go To Market (GTM) routes.
The obvious one is direct to customers in order to address their key use case (ultra low latency, high IOPS / Throughput use cases).
The other route to market is working with OEM manufacturers.
While Excelero will continue to enhance their core offering available under 1st GTM route above, I can see many other OEM vendors such as the legacy storage vendors wanting to license Excelero’s patented technology such as RDDA in order to be used in their own storage systems and this could well be quite popular revenue stream for Excelero.
In my view, having an awesome technology doesn’t necessarily ensure the survival of a tech start up and this 2nd GTM route may well be the obvious starting point for them, though then they are potentially limiting the technical advantage they have on the GTM 1.
Either way, they have an awesome, credible and based on current customers, a popular storage technology and I sincerely hope the business leaders within the company will make the strategically best decisions on how to monetize this exciting technology they have.
Given the lack of similar technology from other vendors at the moment, Excelero may have a slight advantage but the competition is unlikely to sit and wait as they too will likely work on similar but different architectures.
Intel have already hinted to us during our session at #SFD12 that there may well be a newer replacement to NAND based drives coming out soon from Intel and pretty soon, NVMesh & RDDA could well be a thing of the past before you know it so I hope my friends in Excelero act fast.
Finally, a group photo of the Excelero team that presented to us along with the #SFD12 delegates panel ???? Additional Reading.
If you are keen to explorer further in to Excelero and their solutions, the obvious place to start is their web site but if you would like to watch the recording of the presentation they gave to #SFD12 team, its available here.
If you have any questions or thoughts, please feel free to submit a comment below Slide credit goes to Excelero and Tech Field Day Thanks #SDF12 #Excelero.
Excelero, Storage Field Day, Tech Field Day #SFD12, ConnectX-3, ConnectX-4, ConnectX-5, Day, Excelero, Fabric, Field, Mellanox, MEMf, NVMe, NVMe over fabric, NVMesh, Qlogic, RDDA, RDMA, RoCE, storage, TDF, Tech.