85: GreyBeards talk NVMe NAS with Howard Marks, Technologist Extraordinary and Plenipotentiary, VAST Data Inc.

As most of you know, Howard Marks was a founding co-Host of the GreyBeards-On- Storage podcast and has since joined with VAST Data, an NVMe file and object storage vendor headquartered in NY with R&D out of Israel. We first met with VAST at StorageFieldDay18 (SFD18, video presentation). Howard announced his employment at that event. VAST was a bit circumspect at their SFD18 session but Howard seems to be more talkative, so on the podcast we learn a lot more about their solution.

VAST Data is essentially an NFS-S3 object store, scale out solution with both stateless, VAST Data storage servers and JBoF drive enclosures with Optane and NVMe QLC SSDs. Storage servers or JBoFs can be scaled independently. They don’t support tiering or DRAM caching of data but instead seem to use the Optane SSDs as a write buffer for the QLC SSDs.

At the SFD18 event their spokesperson said that they were going to kill off disk storage media. (Ed’s note: Disk shipments fell 18% y/y in 1Q 2019, with enterprise disk shipments at 11.5M units, desktop at 24.5M units and laptops at 37M units).

The hardware

The VAST Data storage servers are in a 2U/4 server configuration, that runs interface protocols (NFS & S3), data reduction (see below), data reformating/buffering etc. They are stateless servers with all the metadata and other control state maintained on JBoF Optane drives.

Each drive enclosure JBoF has 12 Optane SSDs and 44 U.2 QLC (no DRAM/no super cap) SSDs. This means there are no write buffers on the QLC SSDs that can lose data when power failures occur. The interface to the JBoF is NVMeoF, either RDMA-RoCE Ethernet or InfiniBand (customer selected). Their JBoFs have high availability, with dual fabric modules that support 2-100Gbps Ethernet/InfiniBand ports per module, 4 per JBoF.

Minimum starting capacity is 500TB and they claim support up to Exabytes. Although how much has actually been tested is an open question. They also support billions of objects/files.

Guaranteed better data reduction

They have a rather unique, multi-level, data reduction scheme. At the start, data is chunked in variable length chunks. They use heuristics to determine the chunk size that fits best. (Ed note, unclear which is first in this sequence below so presented in (our view of) logical order)

  • 1st level computes a similarity hash (56 bit not SHA1), which is used to determine a similarity level with any other currently stored data chunk in the system.
  • 2nd level uses a ZSTD compression algorithm. If a similarity is found, the new data chunk is compressed with the ZSTD compression algorithm and a reference dictionary used by the earlier, similar data chunk. If no existing chunk is similar to this one, the algorithm identifies a semi-unique reference dictionary that optimizes the compression of this data chunk. This semi-unique dictionary is stored as metadata.
  • 3rd level, If it turns out to be a complete duplicate data chunk, then the dedupe count for the original data chunk is incremented, a pointer is saved to the original unique data and the data discarded. If not a complete duplicate of other data, the system computes a delta from the closest “similar’ block and stores just the delta bytes, includes a pointer to the original similar block and increments a delta block counter.

So data is chunked, compressed with a optimized dictionary, be delta-diffed or deduped. All data reduction is done post data write (after the client is ACKed), and presumably, re-hydrated after being read from SSD media. VAST Data guarantees better data reduction for your stored data than any other storage solution.

New data protection

They also supply a unique Locally Decodable Erasure Coding with 4 parity (-like) blocks and anywhere from 36 (single enclosure leaving 4 spare u.2 SSDs) to 150 data blocks per stripe all of which support up to 4 device failures per stripe. 

The locally decodable erasure coding scheme allows for rebuilds without having to read all remaining data blocks in a stripe. In this scheme, once you read the 4 parity (-like) blocks, one has all the information calculated from up to ¾ of the remaining drives in the stripe, so the system only has to read the remaining ¼ drives in the stripe to reconstruct one, two, three, or four failing drives.  Given their data stripe width, this cuts down on the amount of data needing to be read considerably. Still with 150 data drives in a stripe, the system still has to read 38 drives worth of QLC SSD data to rebuild a data drive.

In addition to all the above, VAST Data also reblocks the data into much larger segments, (it writes 1MB segments to the QLC drives) and uses a heat map along with other heuristics to separate actively written data from less actively written data, thus reducing garbage collection, write amplification.

The podcast is a long and runs over ~43 minutes. Howard has always been great to talk with and if anything, now being a vendor, has intensified this tendency. Listen to the podcast to learn more.

Howard Marks, Technologist Extraordinary and Plenipotentiary, VAST Data, Inc.

Howard Marks brings over forty years of experience as a technology architect for hire and Industry observer to his role as VAST Data’s Technologist Extraordinary and Plienopotentary. In this role, Howard demystifies VAST’s technologies for customers and customer requirements for VAST’s engineers.

Before joining VAST, Howard ran DeepStorage an industry test lab and analyst firm. An award-winning speaker, he has appeared at events on three continents including Comdex, Interop and VMworld.

Howard is the author of several books (all gratefully out of print) and hundreds of articles since Bill Machrone taught him journalism at PC Magazine in the 1980s.

Listeners may also remember that Howard was a founding co-Host of the Greybeards-on-Storage Podcast.


83: GreyBeards talk NVMeoF/TCP with Muli Ben-Yehuda, Co-founder & CTO and Kam Eshghi, VP Strategy & Bus. Dev., Lightbits Labs

This is the first time we’ve talked with Muli Ben-Yehuda (@Muliby), Co-founder & CTO and Kam Eshghi (@KamEshghi), VP of Strategy & Business Development, Lightbits Labs. Keith and I first saw them at Dell Tech World 2019, in Vegas as they are a Dell Ventures funded organization. The company has 70 (mostly engineering) employees and is based in Israel, with offices in NY and the Valley as well as elsewhere around the world. Kam was previously with (Dell) EMC DSSD and Muli’s spent years as a Master Inventor with IBM Research.

[This was Keith Townsend’s (@CTOAdvisor & The CTO Advisor), first time as a GreyBeard co-host and we had a great time with him on the show.]

I would have to say it was a far ranging discussion but focused on their software defined, NVMeoF/TCP storage. As you may recall we talked with Solarflare Communications last year who were also working on a NVMeoF/TCP, only in their case it was an accelerator board. After the recording, Muli said the hardware accelerator they have is their own design.

Why NVMeoF/TCP?

Most NVMeoF today, that uses Ethernet, requires RoCE or iWARP compatible NICs and switches. Lightbits Labs has long been active in the NVMeoF/RoCE-iWARP market place. Early on they noticed that enterprise and cloud service providers were reluctant to adopt NVMeoF technology because of the need to change out all their networking equipment to use it. This is what brought about their focus on NVMeoF/TCP.

The advantage of NVMeoF/TCP is that it can be run on any Ethernet NIC and switch available today. From Muli’s perspective, NVMeoF/TCP is going to become the next SAN of choice for the data center. They were active, early on, in the standards committee to push for NVMeoF/TCP adoption.

How does it work?

Their software defined solution runs LightOS® storage software, a Linux based package, and uses off the shelf, server hardware with persistent storage (Optane DC PM/SSDs, NV DIMMs, V-NAND, etc.). They use persistent memory for a FAST write buffer and a place where they can “mold” the written data into something that can be better written to backend NVMe SSDs.

One surprise about Lightbits solution is that it offers a decent set of data services. These include erasure coding, thin provisioning, wire-speed inline compression, QoS and wide striping. It seems like any of these can be disabled by a customers want. But they only add very little overhead. I think Muli mentioned one Lightbits customer with encrypted data that disabled compression.

Lightbits also offers a global FTL (flash translation layer), which means they control SSD addressing which maps data to physical/raw NAND locations at the storage system level. If done well, a global FTL can help improve flash endurance and may offer better write performance (through increased parallelism).

Lightbits claim to inline, wire speed data compression is premised on the use of more current CPUs with high (>=28) core counts in a storage server. If the storage server has older CPUs (<28 cores), they suggest you install their LightField™ hardware accelerator add in card. LightField offers a number of hardware based, performance accelerations in addition to compression speedups.

LightOS requires no host (client) software. Muli’s a long time Linux kernel contributor and indicated that the only thing LightOS needs is a current Linux Kernel (5.0 or later) which has the NVMeoF/TCP driver software (and persistent memory). Lightbits believes that it’s only a matter of time until other OSs also implement NVMeoF/TCP drivers.

Lightbits business considerations

Long term, Lightbits sees a need for compute-storage disaggregation in hyper scalar and enterprise cloud environments. Early on it was relatively easy to replicate servers with DAS storage but as NVMe SSDs came out the expense to do this throughout their >>1000 server environment starts to become exorbitant. If they only had an easy way to disaggregate their storage from compute and still enjoy all the performance advantages of DAS NVMe SSDS. With LightOS they can do that.

Lightbits can be sold today through Dell, as a partner solution, which means that Dell can integrate, test and validate their servers with LightField accelerator card and deliver that package to your data center. I believe you still need to purchase and install their LightOS software yourself.

Lightbits charges for LightOS software on a per storage node basis, but they have different charges based on the maximum number of NVMe SSD slots available is in a server. There is no capacity charge. They also offer worldwide service and support for LightOS software and LightField hardware.

It’s all about performance

From a performance perspective, one Fortune 500 hyper-scalar benchmarked their storage solution against a DAS NVMe server and found it added about 30 µsec to the IO latency as compare to DAS NVMe SSDs. From their perspective, the added data services, better endurance, and disaggregated compute-storage environment provided by LightOS more than made up for the additional overhead.

Finally, I asked about whether multiple LightOS storage servers could be clustered together. Muli intervened, after stating some legal stuff, said they were working on the next generation LightOS and it will support clustered storage servers, local data replication as well as distributed (across storage servers) erasure coding.

The podcast is a long one and runs over ~47 minutes. There was a lot to talk about and Kam and Muli seem to know it all. It was interesting to hear the history of their pivot to TCP. They seem to have the right technology to address the market. Listen to the podcast to learn more.

Muli Ben-Yehuda, Co-founder and CTO, Lightbits Labs

Muli Ben-Yehuda is the CTO and Co-Founder of Lightbits Labs, where he leads technological developments.

Prior to founding Lightbits, he was chief scientist at Stratoscale and a researcher and Master Inventor at IBM Research.

He holds an M.Sc. in Computer Science (summa cum laude) from the Technion — Israel Institute of Technology and a B.A. (cum laude) from the Open University of Israel.

He is a long time Linux kernel contributor and his code and ideas are most likely included in an operating system or hypervisor running near you. He is also one of the authors of the NVMe/TCP standard and technology. 

Kam Eshghi, VP Strategy & Business Development, Lightbits Labs

Kam joined Lightbits Labs from Dell EMC and has over 20yrs of experience in strategic marketing and business development with startups and public companies.

Most recently as VP of strategic alliances at startup DSSD, Kam led business development with technology partners and developed DSSD’s partnership with EMC, leading to EMC’s acquisition of DSSD.

Previously as Sr. Director of Marketing & Business Development at IDT, Kam built their NVMe Controller business from scratch. Previous to that, Kam worked in data center storage, compute and networking markets at HP, Intel, and Crosslayer Networks. 

Kam is a U.C. Berkeley and MIT graduate with a BS and MS in Electrical Engineering and Computer Science and an MBA.

82: GreyBeards talk composable infrastructure with Sumit Puri, CEO & Co-founder, Liqid Inc.

This is the first time we’ve had Sumit Puri, CEO & GM Co-founder of Liqid on the show but both Greg and I have talked with Liqid in the past. Given that we talked with another composable infrastructure company (see our DriveScale podcast), we thought it would be nice to hear from their  competition.

We started with a brief discussion of the differences between them and DriveScale. Sumit mentioned that they were mainly focused on storage and not as much on the other components of composable infrastructure.

[This was Greg Schulz’s (@storageIO & StorageIO.com), first time as a GreyBeard co-host and we had some technical problems with his feed, sorry about that.]

Multi-fabric composable infrastructure

At Dell Tech World (DTW) 2019 last week, Liqid announced a new, multi-fabric composability solution. Originally, Liqid composable infrastructure only supported PCIe switching, but with their new announcement, they also now support Ethernet and InfiniBand infrastructure composability. In their multi-fabric solution, they offer JBoG(PUs) which can attach to Ethernet/InfiniBand as well as other compute accelerators such as FPGAs or AI specific compute engines.

For non-PCIe switch fabrics, Liqid adds an “HBA-like” board in the server side that converts PCIe protocols to Ethernet or InfiniBand and has another HBA-like board sitting in the JBoG.

As such, if you were a Media & Entertainment (M&E) shop, you could be doing 4K real time editing during the day, where GPUs were each assigned to a separate servers running editing apps and at night, move all those GPUs to a central server where they could now be used to do rendering or transcoding. All with the same GPU-sever hardware andusing Liqid to re-assign those GPUs, back and forth during day and night shifts.  

Even before the multi-fabric option Liqid supported composing NVMe SSDS and servers. So with a 1U server which in the package may support 4 SSDS, with Liqid you could assign 24-48 or whatever number made the most sense  to that 1U server for a specialized IO intensive activity. When that activity/app was done, you could then allocate those NVMe SSDs to other servers to support other apps.

Why compose infrastructure

The promise of composability is no more isolated/siloed/dedicated hardware in your environment. Resources like SSDs, GPUS, FPGAs and really servers can be torn apart and put back together without sending out a service technician and waiting for hours while they power down your system and move hardware around. I asked Sumit how long it took to re-configure (compose) hardware into a new congfiguration and he said it was a matter of 20 seconds.

Sumit was at an NVIDIA show recently and said that Liqid could non-disruptively swap out GPUs. For this you would just isolate the GPU from any server and then go over to the JBoG and take the GPU out of the cabinet.

How does it work

Sumit mentioned that they have support for Optane SSDs to be used as DRAM memory (not Optane DC PM) using IMDT (Intel Memory Drive Technology). In this way you can extend your DRAM up to 6TB for a server. And with Liqid it could be concentrated on one server one minute and then spread across dozens the next.

I asked Sumit about the overhead of the fabrics that can be used with Liqid. He said that the PCIe switching may add on the order of 100 nanoseconds and the Ethernet/InfiniBand networks on the order of 10-15 microseconds or roughly 2 orders of magnitude difference in overhead between the two fabrics.

Sumit made a point of saying that Liqid is a software company. Liqid software runs on switch hardware (currently Mellanox Ethernet/InfiniBand switches) or their PCIe switches.

But given their solution can require HBAs, JBoGs and potentially PCIe switches there’s at least some hardware involved. But for Ethernet and InfiniBand their software runs in the Mellanox switch gear. Liqid control software has a CLI, GUI and supports an API.

Liqid supports any style of GPU (NVIDIA, AMD or ?). And as far as they were concerned, anything that could be plugged into a PCIe bus was fair game to be disaggregated and become composable.

Solutions using Liqid

Their solution is available from a number of vendors. And at last week’s, DTW 2019 Liqid announced a new OEM partnership with Dell EMC. So now, you can purchase composable infrastructure, directly from Dell. Liqid’s route to market is through their partner ecosystem and Dell EMC is only the latest.

Sumit mentioned a number of packaged solutions and one that sticks in my mind was a an AI appliance pod solution (sold by Dell), that uses Liqid to compose an training data ingestion environment at one time, a data cleaning/engineering environment at another time, a AI deep learning/model training environment at another time, and then an scaleable inferencing engine after that. Something that can conceivably do it all, an almost all in one AI appliance.

Sumit said that these types of solutions would be delivered in 1/4, 1/2, or full racks and with multi-fabric could span racks of data center infrastructure. The customer ultimately gets to configure these systems with whatever hardware they want to deploy, JBoGs, JBoFs, JBoFPGAs, JBoAIengines, etc.

The podcast runs ~42 minutes. Sumit was very knowledgeable data center infrastructure and how composability could solve many of the problems of today. Some composability use cases he mentioned could apply to just about any data center. Ray and Sumit had a good conversation about the technology. Both Greg and I felt Liqid’s technology represented the next step in data center infrastructure evolution. Listen to the podcast to learn more.

Sumit Perl, CEO & Co-founder, Liqid, Inc.

Sumit Puri is CEO and Co-founder at Liqid. An industry veteran with over 20 years of experience, Sumit has been focused on defining the technology roadmaps for key industry leaders including Avago, SandForce, LSI, and Toshiba.

Sumit has a long history with bringing successful products to market with numerous teams and large-scale organizations.

80: Greybeards talk composable infrastructure with Tom Lyon, Co-Founder/Chief Scientist and Brian Pawlowski, CTO, DriveScale

We haven’t talked with Tom Lyon (@aka_pugs) or Brian Pawlowski before on our show but both Howard and I know Brian from his prior employers. Tom and Brian work for DriveScale, a composable infrastructure software supplier.

There’s been a lot of press lately on NVMeoF and the GreyBeards thought it would be good time to hear from another way to supply DAS like performance and functionality. Tom and Brian have been around long enough to qualify as greybeards in their own right.

The GreyBeards have heard of composable infrastructure before but this was based on PCIe switching hardware and limited to a rack or less of hardware. DriveScale is working with large enterprises and their data center’s full of hardware.

Composable infrastructure has many definitions but the one DriveScale probably prefers is that it manages resource pools of servers and storage, that can be combined, per request, to create any mix of servers and DAS storage needed by an application running in a data center. DriveScale is targeting organizations that have from 1K to 10K servers with from 10K to 100K disk drives/SSDs.

Composable infrastructure for large enterprises

DriveScale provides large data centers the flexibility to better support workloads and applications that change over time. That is, these customers may, at one moment, be doing big data analytics on PBs of data using Hadoop, and the next, MongoDB or other advanced solution to further process the data generated by Hadoop.

In these environments, having standard servers with embedded DAS infrastructure may be overkill and will cost too much. For example., because one has no way to reconfigure (1000) server’s storage for each application that comes along, without exerting lots of person-power, enterprises typically over provision storage for those servers, which leads to higher expense.

But if one had some software that could configure 1 logical server or a 10,000 logical servers, with the computational resources, DAS disk/SSDs, or NVMe SSDs needed to support a specific application, then enterprises could reduce their server and storage expense while at the same time provide applications with all the necessary hardware resources.

When that application completes, all those hardware resources could be returned back to their respective pools and used to support the next application to be run. It’s probably not that useful when an enterprise only runs one application at a time, but when you have 3 or more running at any instant, then composable infrastructure can reduce hardware expenses considerably.

DriveScale composable infrastructure

DriveScale is a software solution that manages three types of resources: servers, disk drives, and SSDs over high speed Ethernet networking. SAS disk drives and SAS SSDs are managed in an EBoD/EBoF (Ethernet (iSCSI to SAS) bridge box) and NVMe SSDs are managed using JBoFs and NVMeoF/RoCE.

DriveScale uses standard (RDMA enabled) Ethernet networking to compose servers and storage to provide DAS like/NVMe like levels of response times.

DriveScale’s composer orchestrator self-discovers all hardware resources in a data center that it can manage. It uses an API to compose logical servers from server, disk and SSD resources under its control available, throughout the data center.

Using Ethernet switching any storage resource (SAS disk, SAS SSD or NVMe SSD) can be connected to any server operating in the data center and be used to run any application.

There’s a lot more to DriveScale software. They don’t sell hardware. but have a number of system integrators (like Dell) that sell their own hardware and supply DriveScale software to run a data center.

The podcast runs ~44 minutes. The GreyBeards could have talked with Tom and Brian for hours and Brian’s very funny. They were extremely knowledgeable and have been around the IT industry almost since the beginning of time. They certainly changed the definition of composable infrastructure for both of us, which is hard to do. Listen to the podcast to learn more. .

Tom Lyon, Co-Founder and Chief Scientist

Tom Lyon is a computing systems architect, a serial entrepreneur and a kernel hacker.

Prior to founding DriveScale, Tom was founder and Chief Scientist of Nuova Systems, a start-up that led a new architectural approach to systems and networking. Nuova was acquired in 2008 by Cisco, whose highly successful UCS servers and Nexus switches are based on Nuova’s technology.

He was also founder and CTO of two other technology companies. Netillion, Inc. was an early promoter of memory-over-network technology. At Ipsilon Networks, Tom invented IP Switching. Ipsilon was acquired by Nokia and provided the IP routing technology for many mobile network backbones.

As employee #8 at Sun Microsystems, Tom was there from the beginning, where he contributed to the UNIX kernel, created the SunLink product family, and was one of the NFS and SPARC architects. He started his Silicon Valley career at Amdahl Corp., where he was a software architect responsible for creating Amdahl’s UNIX for mainframes technology.

Brian Pawlowski, CTO

Brian Pawlowski is a distinguished technologist, with more than 35 years of experience in building technologies and leading teams in high-growth environments at global technology companies such as Sun Microsystems, NetApp and Pure Storage.

Before joining DriveScale as CTO, Brian served as vice president and chief architect at Pure Storage, where he focused on improving the user experience for the all-flash storage platform provider’s rapidly growing customer base. He also was CTO at storage pioneer NetApp, which he joined as employee #18.

Brian began his career as a software engineer for a number of well-known technology companies. Early in his days as a technologist, he worked at Sun, where he drove the technical analysis and discussion on alternate file systems technologies. Brian has also served on the board of trustees for the Anita Borg Institute for Women and Technology as well as a member of the board at the Linux Foundation.

Brian studied computer science at Arizona State University, physics at the University of Texas at Austin, as well as physics at MIT.

78: GreyBeards YE2018 IT industry wrap-up podcast

In this, our yearend industry wrap up episode, we discuss trends and technology impacting the IT industry in 2018 and what we can see ahead for 2019 and first up is NVMeoF

NVMeoF has matured

In the prior years, NVMeoF was coming from startups, but last year it’s major vendors like IBM FlashSystem, Dell EMC PowerMAX and NetApp AFF releasing new NVMeoF storage systems. Pure Storage was arguably earliest with their NVMeoF JBOF.

Dell EMC, IBM and NetApp were not far behind this curve and no doubt see it as an easy way to reduce response time without having to rip and replace enterprise fabric infrastructure.

In addition, NVMeoFstandards have finally started to stabilize. With the gang of startups, standards weren’t as much of an issue as they were more than willing to lead, ahead of standards. But major storage vendors prefer to follow behind standards committees.

As another example, VMware showed off an NVMeoF JBOF for vSAN. A JBoF like this improves vSAN storage efficiency for small clusters. Howard described how this works but with vSAN having direct access to shared storage, it can reduce data and server protection requirements for storage. Especially, when dealing with small clusters of servers becoming more popular these days to host application clusters.

The other thing about NVMeoF storage is that NVMe SSDs have also become very popular. We are seeing them come out in everyone’s servers and storage systems. Servers (and storage systems) hosting 24 NVMe SSDs is just not that unusual anymore. For the price of a PCIe switch, one can have blazingly fast, direct access to a TBs of NVMe SSD storage.

HCI reaches critical mass

HCI has also moved out of the shadows. We recently heard news thet HCI is outselling CI. Howard and I attribute this to the advances made in VMware’s vSAN 6.2 and the appliance-ification of HCI. That and we suppose NVMe SSDs (see above).

HCI makes an awful lot of sense for application clusters that VMware is touting these days. CI was easy but an HCI appliance cluster is much, simpler to deploy and manage

For VMware HCI, vSAN Ready Nodes are available from just about any server vendor in existence. With ready nodes, VARs and distributors can offer an HCI appliance in the channel, just like the majors. Yes, it’s not the same as a vendor supplied appliance, doesn’t have the same level of software or service integration, but it’s enough.

[If you want to learn more, Howard’s is doing a series of deep dive webinars/classes on HCI as part of his friend’s Ivan’s ipSpace.net. The 1st 2hr session was recorded 11 December, part 2 goes live 22 January, and the final installment on 5 February. The 1st session is available on demand to subscribers. Sign up here]

Computional storage finally makes sense

Howard and I 1st saw computational storage at FMS18 and we did a podcast with Scott Shadley of NGD systems. Computational storage is an SSD with spare ARM cores and DRAM that can be used to run any storage intensive, Linux application or Docker container.

Because it’s running in the SSD, it has (even faster than NVMe) lightening fast access to all the data on the SSD. Indeed, And the with 10s to 1000s of computational storage SSDs in a rack, each with multiple ARM cores, means you can have many 1000s of cores available to perform your data intensive processing. Almost like GPUs only for IO access to storage (SPUs?).

We tried this at one vendor in the 90s, executing some database and backup services outboard but it never took off. Then in the last couple of years (Dell) EMC had some VM services that you could run on their midrange systems. But that didn’t seem to take off either.

The computational storage we’ve seen all run Linux. And with todays data intensive applications coming from everywhere these days, and all the spare processing power in SSDs, it might finally make sense.

Futures

Finally, we turned to what we see coming in 2019. Howard was at an Intel Analyst event where they discussed Optane DIMMs. Our last podcast of 2018 was with Brian Bulkowski of Aerospike who discussed what Optane DIMMs will mean for high performance database systems and just about any memory intensive server application. For example, affordable, 6TB memory servers will be coming out shortly. What you can do with 6TB of memory is another question….

Howard Marks, Founder and Chief Scientist, DeepStorage

Howard Marks is the Founder and Chief Scientist of DeepStorage, a prominent blogger at Deep Storage Blog and can be found on twitter @DeepStorageNet.

Raymond Lucchesi, Founder and President, Silverton Consulting

Ray Lucchesi is the President and Founder of Silverton Consulting, a prominent blogger at RayOnStorage.com, and can be found on twitter @RayLucchesi. Signup for SCI’s free, monthly e-newsletter here.