StorPool, fast storage for fast times

At Storage Field Day 18 (SFD18) a couple of weeks ago, we heard from a new company, StorPool, that provides ultra fast software defined storage for MSPs and other cloud providers. You can watch the videos of their sessions here.

Didn’t know what to make of them at first, but when they started demoing their performance, we all woke up. They ran an all read and mixed read-write IO workload, that almost blew away any other proprietary/non-proprietary storage I’ve seen before.

[Updated 12Mar2019] What they were trying to achieve was to match the performance of an Windows Server 2019 Hyper V benchmark which hit 13.8 M IOPS using 12 nodes of 384GB DRAM, 1.5TB Optane DC persistent memory, 32TB (4X8TB) NVMe SSDs and Mellanox 25Gbps RDMA ethernet, with each VM running on the server that had the VHDX file stored.

Their demo showed 70:30 R:W random 4KB mixed workload and achieved 1M IOPS with a read latency of 140 microsec. and write latency of 100 microsec. (end to end at the VM level). [Updated 12Mar2019] They were able to match the performance of a published benchmark without the 1.5TB Optane memory, without the 25Gbps RDMA Ethernet and without having the VMs and its storage running on same nodes. They were able to show this performance running StorPool, KVM and CentOS 7 across 12 nodes running both VMs and storage services.

They also showed information on a pgbench benchmark, which I was not familiar with. The chart had response times on the horizontal axis and TPS performance on the vertical axis.

What’s even more amazing is that even with the great performance they still offer reasonable data services such as CoW snapshots, asynchronous replication (with changed block tracking), thin provisioning, end to end data integrity, and iSCSI support.

Their target market is mostly MSPs and large customers moving to the private cloud configurations. They mentioned deep support for OpenNebula, [updated 12Mar2019] OpenStack, OnApp and Kubernetes which means each virtual disk is a volume/LUN. They support VMware and Windows Server/Hyper-V through iSCSI.

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The fact that they have a proprietary protocol is not that great but if they can generate the IOPS and response times they showed here with snapshot, thin provisioning and asynch replication, I’m ok with it. [Updated 12Mar2019]The fact that they were able to match the performance of the more expensive system with standard Ethernet, no Optane memory and all VMs running remote made a significant impression on me.

Want to learn more, check out these other discussions on StorPool (and other SFD18 vendors):

SFD18 – as intense as it gets by Max Mortillaro (@DarkAvenger), and

Podcast #3 review the SFD18 presenters by Chris M. Evans (@ChrisMEvans) and Matt Leib (@MBLeib).

[Updated 12Mar2019 Boyan Krosnov sent me an email indicating that the post had made some mistakes in the post which were corrected via updates above. Editors ]

IT in space

Read an article last week about all the startup activity that’s taking place in space systems and infrastructure (see: As rocket companies proliferate … new tech emerges leading to a new space race). This is a consequence of cheap(er) launch systems from SpaceX, Blue Origin, Rocket Lab and others.

SpaceBelt, storage in space

One startup that caught my eye was SpaceBelt from Cloud Constellation Corporation, that’s planning to put PB (4X library of congress) of data storage in a constellation of LEO satellites.

The LEO storage pool will be populated by multiple nodes (satellites) with a set of geo-synchronous access points to the LEO storage pool. Customers use ground based secure terminals to talk with geosynchronous access satellites which communicate to the LEO storage nodes to access data.

Their main selling points appear to be data security and availability. The only way to access the data is through secured satellite downlinks/uplinks and then you only get to the geo-synchronous satellites. From there, those satellites access the LEO storage cloud directly. Customers can’t access the storage cloud without going through the geo-synchronous layer first and the secured terminals.

The problem with terrestrial data is that it is prone to security threats as well as natural disasters which take out a data center or a region. But with all your data residing in a space cloud, such concerns shouldn’t be a problem. (However, gaining access to your ground stations is a whole different story.

AWS and Lockheed-Martin supply new ground station service

The other company of interest is not a startup but a link up between Amazon and Lockheed Martin (see: Amazon-Lockheed Martin …) that supplies a new cloud based, satellite ground station as a service offering. The new service will use Lockheed Martin ground stations.

Currently, the service is limited to S-Band and attennas located in Denver, but plans are to expand to X-Band and locations throughout the world. The plan is to have ground stations located close to AWS data centers, so data center customers can have high speed, access to satellite data.

There are other startups in the ground station as a service space, but none with the resources of Amazon-Lockheed. All of this competition is just getting off the ground, but a few have been leasing idle ground station resources to customers. The AWS service already has a few big customers, like DigitalGlobe.

One thing we have learned, is that the appeal of cloud services is as much about the ecosystem that surrounds it, as the service offering itself. So having satellite ground stations as a service is good, but having these services, tied directly into other public cloud computing infrastructure, is much much better. Google, Microsoft, IBM are you listening?

Data centers in space

Why stop at storage? Wouldn’t it be better to support both storage and computation in space. That way access latencies wouldn’t be a concern. When terrestrial disasters occur, it’s not just data at risk. Ditto, for security threats.

Having whole data centers, would represent a whole new stratum of cloud computing. Also, now IT could implement space native applications.

If Microsoft can run a data center under the oceans, I see no reason they couldn’t do so in orbit. Especially when human flight returns to NASA/SpaceX. Just imagine admins and service techs as astronauts.

And yet, security and availability aren’t the only threats one has to deal with. What happens to the space cloud when war breaks out and satellite killers are set loose.

Yes, space infrastructure is not subject to terrestrial disasters or internet based security risks, but there are other problems besides those and war that exist such as solar storms and space debris clouds. .

In the end, it’s important to have multiple, non-overlapping risk profiles for your IT infrastructure. That is each IT deployment, may be subject to one set of risks but those sets are disjoint with another IT deployment option. IT in space, that is subject to solar storms, space debris, and satellite killers is a nice complement to terrestrial cloud data centers, subject to natural disasters, internet security risks, and other earth-based, man made disasters.

On the other hand, a large, solar storm like the 1859 one, could knock every data system on the world or in orbit, out. As for under the sea, it probably depends on how deep it was submerged!!

Photo Credit(s): Screen shots from SpaceBelt youtube video (c) SpaceBelt

Screens shot from AWS Ground Station as a Service sign up page (c) Amazon-Lockheed

Screen shots from Microsoft’s Under the sea news feature (c) Microsoft

Screaming IOP performance with StarWind’s new NVMeoF software & Optane SSDs

Was at SFD17 last week in San Jose and we heard from StarWind SAN (@starwindsan) and their latest NVMeoF storage system that they have been working on. Videos of their presentation are available here. Starwind is this amazing company from the Ukraine that have been developing software defined storage.

They have developed their own NVMe SPDK for Windows Server. Intel doesn’t currently offer SPDK for Windows today, so they developed their own. They also developed their own initiator (CentOS Linux) for NVMeoF. The target system was a multicore server running Windows Server with a single Optane SSD that they used to test their software.

Extreme IOP performance consumes cores

During their development activity they tested various configurations. At the start of their development they used a Windows Server with their NVMeoF target device driver. With this configuration and on a bare metal server, they found that they could max out the Optane SSD at 550K 4K random write IOPs at 0.6msec to a single Optane drive.

When they moved this code directly to run under a Hyper-V environment, they were able to come close to this performance at 518K 4K write IOPS at 0.6msec. However, this level of IO activity pegged 100% of 8 cores on their 40 core server.

More IOPs/core performance in user mode

Next they decided to optimize their driver code and move as much as possible into user space and out of kernel space, They continued to use Hyper-V. With this level off code, they were able to achieve the same performance as bare metal or ~551K 4K random write IOP performance at the 0.6msec RT and 2.26 GB/sec level. However, they were now able to perform only pegging 2 cores. They expect to release this initiator and target software in mid October 2018!

They converted this functionality to run under ESX/VMware and were able to see much the same 2 cores pegged, ~551K 4K random write IOPS at 0.6msec RT and 2.26 GB/sec. They will have the ESXi version of their target driver code available sometime later this year.

Their initiator was running CentOS on another server. When they decided to test how far they could push their initiator, they were able to drive 4 Optane SSDs at up to ~1.9M 4K random write IOP performance.

At SFD17, I asked what they could have done at 100 usec RT and Max said about 450K IOPs. This is still surprisingly good performance. With 4 Optane SSDs and consuming ~8 cores, you could achieve 1.8M IOPS and ~7.4GB/sec. Doubling the Optane SSDs one could achieve ~3.6M IOPS, with sufficient initiators and target cores with ~14.8GB/sec.

Optane based super computer?

ORNL Summit super computer, the current number one supercomputer in the world, has a sustained throughput of 2.5 TB/sec over 18.7K server nodes. You could do much the same with 337 CentOS initiator nodes, 337 Windows server nodes and ~1350 Optane SSDs.

This would assumes that Starwind’s initiator and target NVMeoF systems can scale but they’ve already shown they can do 1.8M IOPS across 4 Optane SSDs on a single initiator server. Aand I assume a single target server with 4 Optane SSDs and at least 8 cores to service the IO. Multiplying this by 4 or 400 shouldn’t be much of a concern except for the increasing networking bandwidth.

Of course, with Starwind’s Virtual SAN, there’s no data management, no data protection and probably very little in the way of logical volume management. And the ORNL Summit supercomputer is accessing data as files in a massive file system. The StarWind Virtual SAN is a block device.

But if I wanted to rule the supercomputing world, in a somewhat smallish data center, I might be tempted to put together 400 of StarWind NVMeoF target storage nodes with 4 Optane SSDs each. And convert their initiator code to work on IBM Spectrum Scale nodes and let her rip.

Comments?

Photonic or Optical FPGAs on the horizon

Read an article this past week (Toward an optical FPGA – programable silicon photonics circuits) on a new technology that could underpin optical  FPGAs. The technology is based on implantable wave guides and uses silicon on insulator technology which is compatible with current chip fabrication.

How does the Optical FPGA work

Their Optical FPGA is based on an eraseable direct coupler (DC) built using GE (Germanium) ion implantation. A DC is used when two optical waveguides are placed close enough together such that optical energy (photons) on one wave guide is switched over to the other, nearby wave guide.

As can be seen in the figure, the red (eraseable, implantable) and blue (conventional) wave guides are fabricated on the FPGA. The red wave guide performs the function of DC between the two conventional wave guides. The diagram shows both a single stage and a dual stage DC.

By using imlantable (eraseable) DCs, one can change the path of a photonic circuit by just erasing the implantable wave guide(s).

The GE ion implantable wave guides are erased by passing a laser over it and thus annealing (melting) it.

Once erased, the implantable wave guide DC no longer works. The chart on the left of the figure above shows how long the implantable wave guide needs to be to work. As shown above once erased to be shorter than 4-5µm, it no longer acts as a DC.

It’s not clear how one directs the laser to the proper place on the Optical FPGA to anneal the implantable wave guide but that’s a question of servos and mirrors.

Previous attempts at optical FPGAs, required applying continuing voltage to maintain the switched photonics circuits. Once voltage was withdrawn the photonics reverted back to original configuration.

But once an implantable wave guide is erased (annealed) in their approach, the changes to the Optical FPGA are permanent.

FPGAs today

Electronic FPGAs have never gone out of favor with customers doing hardware innovation. By supplying Optical FPGAs, the techniques in the paper would allow for much more photonics innovation as well.

Optics are primarily used in communications and storage (CD-DVDs) today. But quantum computing could potentially use photonics and there’s been talk of a 100% optical computer for a long time. As more and more photonics circuitry comes online, the need for an optical FPGA grows. The fact that it’s able to be grown on today’s fab lines makes it even more appealing.

But an FPGA is more than just directional control over (electronic or photonic) energy. One needs to have other circuitry in place on the FPGA for it to do work.

For example, if this were an electronic FPGA, gates, adders, muxes, etc. would all be somewhere on the FPGA

However, once having placed additional optical componentry on the FPGA, photonic directional control would be the glue that makes the Optical FPGA programmable.

Comments?

Photo Credit(s): All photos from Toward an optical FPGA – programable silicon photonics circuits paper

 

Skyrmion and chiral bobber solitons for racetrack storage

Read an article this week in Science Daily (Magnetic skyrmions: Not the only one of their class; …) about new magnetic structures that could lend themselves to creating a new type of moving, non-volatile storage.  (There’s more information in the press release and the Nature paper [DOI: 10.1038/s41565-018-0093-3], behind a paywall).

Skyrmions and chiral bobbers are both considered magnetic solitons, types of magnetic structures only 10’s of nm wide, that can move around, in sort of a race track configuration.

Delay line memories

Early in computing history, there was a type of memory called a delay line memory which used various mechanisms (mercury, magneto-resistence, capacitors, etc.) arranged along a circular line such as a wire, and had moving pulses of memory that raced around it. .

One problem with delay line memory was that it was accessed sequentially rather than core which could be accessed randomly. When using delay lines to change a bit, one had to wait until the bit came under the read/write head . It usually took microseconds for a bit to rotate around the memory line and delay line memories had a capacity of a few thousand bits 256-512 bytes per line,  in today’s vernacular.

Delay lines predate computers and had been used for decades to delay any electronic or acoustic signal before retransmission.

A new racetrack

Solitons are being investigated to be used in a new form of delay line memory, called racetrack memory. Skyrmions had been discovered a while ago but the existence of chiral bobbers was only theoretical until researchers discovered them in their lab.

Previously, the thought was that one would encode digital data with only skyrmions and spaces. But the discovery of chiral bobbers and the fact that they can co-exist with skyrmions, means that chiral bobbers and skyrmions can be used together in a racetrack fashion to record digital data.  And the fact that both can move or migrate through a material makes them ideal for racetrack storage.

Unclear whether chiral bobbers and skyrmions only have two states or more but the more the merrier for storage. I am assuming that bit density or reliability is increased by having chiral bobbers in the chain rather than spaces.

Unlike disk devices with both rotating media and moving read-write heads, the motion of skyrmion-chiral bobber racetrack storage is controlled by a very weak pulse of current and requires no moving/mechanical parts prone to wear/tear. Moreover, as a solid state devices, racetrack memory is not sensitive to induced/organic vibration or shock,  So, theoretically these devices should have higher reliability than disk devices.

There was no information comparing the new racetrack memory reliability to NAND or 3D Crosspoint/PCM SSDs, but there may be some advantage here as well. I suppose one would need to understand how to miniaturize the read-erase-write head to the right form factor for nm racetracks to understand how it compares.

And I didn’t see anything describing how long it takes to rotate through bits on a skyrmion-chiral bobber racetrack. Of course, this would depend on the number of bits on a racetrack, but some indication of how long it takes one bit to move, one postition on the racetrack would be helpful to see what its rotational latency might be.

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At the moment, reading and writing skyrmions and the newly discovered chiral bobbers takes a lot of advanced equipment and is only done in major labs. As such, I don’t see a skyrmion-chiral bobber racetrack storage device arriving on my desktop anytime soon. But the fact that there’s a long way to go before, we run out of magnetic storage options, even if it is on a chip rather than magnetic media,  is comforting to know. Even if we don’t ever come up with an economical way to produce it.

I wonder if you could synchronize rotational timing across a number of racetrack devices, at least that way you could be reading/erasing/writing a whole byte, word, double word etc, at a time, rather than a single bit.

Comments?

Photo Credit(s): From Experimental observation of chiral magnetic bobbers in B20 Type FeGe paper

From Experimental observation of chiral magnetic bobbers in B20 Type FeGe paper

From Timeline of computer history Magnetoresistive delay lines

From Experimental observation of chiral magnetic bobbers in B20 Type FeGe paper

Hitachi Vantara HCP, hits it out of the park #datacenternext

We talked with Hitachi Vantara this past week at a special Tech Field Day extra event (see videos here). This was an all day affair and was a broad discussion of Hitachi’s infrastructure portfolio.

There was much of interest in the days session but one in particular caught my eye and that was the session on Hitachi Vantara’s Content Platform (HCP).

Hitachi has a number of offerings surrounding their content platform, including:

  • HCP, on premises object store:
  • HCP Anywhere, enterprise file synch and share using HCP,
  • HCP Content Intelligence, compliance and content search for HCP object storage, and
  • HCP Data Ingestor, file gateway to HCP object storage.

I already knew about these  offerings but had no idea how successful HCP has been over the years. inng to Hitachi Vantara, HCP has over 4000 installations worldwide with over 2000 customers and is currently the number 1 on premises, object storage solution in the world.

For instance, HCP is installed in 4 out of the 5 largest banks, insurance companies, and TelCos worldwide. HCP Anywhere has over a million users with over 15K in Hitachi alone.  Hitachi Vantara has some customers using HCP installations that support 4000-5000 object ingests/sec.

HCP software supports geographically disbursed erasure coding, data compression, deduplication, and encryption of customer object data.

HCP development team has transitioned to using micro services/container based applications and have developed their Foundry Framework to make this easier. I believe the intent is to ultimately redevelop all HCP solutions using Foundry.

Hitachi mentioned a couple of customers:

  • US Government National Archives which uses HCP behind Pentaho to preserve presidential data and metadata for 100 years, and uses all open APIs to do so
  • UK Rabo Bank which uses HCP to support compliance monitoring across a number of data feeds
  • US  Ground Support which uses Pentaho, HCP, HCP Content Intelligence and HCP Anywhere  to support geospatial search to ascertain boats at sea and what they are doing/shipping.

There’s a lot more to HCP and Hitachi Vantara than summarized here and I would suggest viewing the TFD videos and check out the link above for more information.

Comments?

Want to learn more, see these other TFD bloggers posts:

Hitachi is reshaping its IT division by Andrew Mauro (@Andrew_Mauro)