50: Greybeards wrap up Flash Memory Summit with Jim Handy, Director at Objective Analysis

In this episode we talk with Jim Handy (@thessdguy), Director at Objective Analysis,  a semiconductor market research organization. Jim is an old friend and was on last year to discuss Flash Memory Summit (FMS) 2016. Jim, Howard and I all attended FMS 2017 last week  in Santa Clara and Jim and Howard were presenters at the show.

NVMe & NVMeF to the front

Although, unfortunately the show floor was closed due to fire, there were plenty of sessions and talks about NVMe and NVMeF (NVMe over fabric). Howard believes NVMe & NVMeF seems to be being adopted much quicker than anyone had expected. It’s already evident inside storage systems like Pure’s new FlashArray//X, Kamanario and E8 storage, which is already shipping block storage with NVMe and NVMeF.

Last year PCIe expanders and switches seemed like the wave of the future but ever since then, NVMe and NVMeF has taken off. Historically, there’s been a reluctance to add capacity shelves to storage systems because of the complexity of (FC and SAS) cable connections. But with NVMeF, RoCE and RDMA, it’s now just an (40GbE or 100GbE) Ethernet connection away, considerably easier and less error prone.

3D NAND take off

Both Samsung and Micron are talking up their 64 layer 3D NAND and the rest of the industry following. The NAND shortage has led to fewer price reductions, but eventually when process yields turn up, the shortage will collapse and pricing reductions should return en masse.

The reason that vertical, 3D is taking over from planar (2D) NAND is that planar NAND can’t’ be sharing much more and 15nm is going to be the place it stays at for a long time to come. So the only way to increase capacity/chip and reduce $/Gb, is up.

But as with any new process technology, 3D NAND is having yield problems. But whenever the last yield issue is solved, which seems close,  we should see pricing drop precipitously and much more plentiful (3D) NAND storage.

One thing that has made increasing 3D NAND capacity that much easier is string stacking. Jim describes string stacking as creating a unit, of say 32 layers, which you can fabricate as one piece  and then layer ontop of this an insulating layer. Now you can start again, stacking another 32 layer block ontop and just add another insulating layer.

The problem with more than 32-48 layers is that you have to (dig) create  holes (connecting) between all the layers which have to be (atomically) very straight and coated with special materials. Anyone who has dug a hole knows that the deeper you go, the harder it is to make the hole walls straight. With current technology, 32 layers seem just about as far as they can go.

3DX and similar technologies

There’s been quite a lot of talk the last couple of years about 3D XPoint (3DX) and what it  means for the storage and server industry. Intel has released Octane client SSDs but there’s no enterprise class 3DX SSDs as of yet.

The problem is similar to 3D NAND above, current yields suck.  There’s a chicken and egg problem with any new chip technologies. You need volumes to get the yield up and you need yields up to generate the volumes you need. And volumes with good yields generate profits to re-invest in the cycle for next technology.

Intel can afford to subsidize (lose money) 3DX technology until they get the yields up, knowing full well that when they do, it will become highly profitable.

The key is to price the new technology somewhere between levels in the storage hierarchy, for 3DX that means between NAND and DRAM. This does mean that 3DX will be more of between memory and SSD tier than a replacement for for either DRAM or SSDs.

The recent emergence of NVDIMMs have provided the industry a platform (based on NAND and DRAM) where they can create the software and other OS changes needed to support this mid tier as a memory level. So that when 3DX comes along as a new memory tier they will be ready

NAND shortages, industry globalization & game theory

Jim has an interesting take on how and when the NAND shortage will collapse.

It’s a cyclical problem seen before in DRAM and it’s a question of investment. When there’s an oversupply of a chip technology (like NAND), suppliers cut investments or rather don’t grow investments as fast as they were. Ultimately this leads to a shortage and which then leads to  over investment to catch up with demand.  When this starts to produce chips the capacity bottleneck will collapse and prices will come down hard.

Jim believes that as 3D NAND suppliers start driving yields up and $/Gb down, 2D NAND fabs will turn to DRAM or other electronic circuitry whichwill lead to a price drop there as well.

Jim mentioned game theory is the way the Fab industry has globalized over time. As emerging countries build fabs, they must seek partners to provide the technology to produce product. They offer these companies guaranteed supplies of low priced product for years to help get the fabs online. Once, this period is over the fabs never return to home base.

This approach has led to Japan taking over DRAM & other chip production, then Korea, then Taiwan and now China. It will move again. I suppose this is one reason IBM got out of the chip fab business.

The podcast runs ~49 minutes but Jim is a very knowledgeable, chip industry expert and a great friend from multiple  events. Howard and I had fun talking with him again. Listen to the podcast to learn more.

Jim Handy, Director at Objective Analysis

Jim Handy of Objective Analysis has over 35 years in the electronics industry including 20 years as a leading semiconductor and SSD industry analyst. Early in his career he held marketing and design positions at leading semiconductor suppliers including Intel, National Semiconductor, and Infineon.

A frequent presenter at trade shows, Mr. Handy is known for his technical depth, accurate forecasts, widespread industry presence and volume of publication. He has written hundreds of market reports, articles for trade journals, and white papers, and is frequently interviewed and quoted in the electronics trade press and other media.  He posts blogs at www.TheMemoryGuy.com, and www.TheSSDguy.com

49: Greybeards talk open convergence with Brian Biles, CEO and Co-founder of Datrium

Sponsored By:

In this episode we talk with Brian Biles, CEO and Co-founder of Datrium. We last talked with Brian and Datrium in May of 2016 and at that time we called it deconstructed storage. These days, Datrium offers a converged infrastructure (C/I) solution, which they call “open convergence”.

Datrium C/I

Datrium’s C/I  solution stores persistent data off server onto data nodes and uses onboard flash for a local, host read-write IO cache. They also use host CPU resources to perform some other services such as compression, local deduplication and data services.

In contrast to hyper converged infrastructure solutions available on the market today, customer data is never split across host nodes. That is data residing on a host have only been created and accessed by that host.

Datrium uses on host SSD storage/flash as a fast access layer for data accessed by the host. As data is (re-)written, it’s compressed and locally deduplicated before being persisted (written) down to a data node.

A data node is a relatively light weight dual controller/HA storage solution with 12 high capacity disk drives. Data node storage is global to all hosts running Datrium storage services in the cluster. Besides acting as a permanent repository for data written by the cluster of hosts, it also performs global deduplication of data across all hosts.

The nice thing about their approach to CI is it’s easily scaleable — if you need more IO performance just add more hosts or more SSDs/flash to servers already connected in the cluster. And if a host fails it doesn’t impact cluster IO or data access for any other host.

Datrium originally came out supporting VMware virtualization and acts as an NFS datastore for VMDKs.

Recent enhancements

In July, Datrium released new support for RedHat and KVM virtualization alongside VMware vSphere. They also added Docker persistent volume support to Datrium. Now you can have mixed hypervisors KVM, VMware and Docker container environments, all accessing the same persistent storage.

KVM offered an opportunity to grow the user base and support Redhat enterprise accounts  Redhat is a popular software development environment in non-traditional data centers. Also, much of the public cloud is KVM based, which provides a great way to someday support Datrium storage services in public cloud environments.

One challenge with Docker support is that there are just a whole lot more Docker volumes then VMDKs in vSphere. So Datrium added sophisticated volume directory search capabilities and naming convention options for storage policy management. Customers can define a naming convention for application/container volumes and use these to define group storage policies, which will then apply to any volume that matches the naming convention. This is a lot easier than having to do policy management at a volume level with 100s, 1000s to 10,000s distinct volume IDs.

Docker is being used today to develop most cloud based applications. And many development organizations have adopted Docker containers for their development and application deployment environments. Many shops do development under Docker and production on vSphere. So now these shops can use Datrium to access development as well as production data.

More recently, Datrium also scaled the number of data nodes available in a cluster. Previously you could only have one data node using 12 drives or about 10TB raw storage of protected capacity which when deduped and compressed gave you an effective capacity of ~100TB. But with this latest release, Datrium now supports up to 10 data nodes in a cluster for a total of 1PB of effective capacity for your storage needs.

The podcast runs ~25 minutes. Brian is very knowledgeable about the storage industry, has been successful at many other data storage companies and is always a great guest to have on our show. Listen to the podcast to learn more.

Brian Biles, Datrium CEO & Co-founder

Prior to Datrium, Brian was Founder and VP of Product Mgmt. at EMC Backup Recovery Systems Division. Prior to that he was Founder, VP of Product Mgmt. and Business Development for Data Domain (acquired by EMC in 2009).

48: Greybeards talk object storage with Enrico Signoretti, Head of Product Strategy, OpenIO

In this episode we talk with Enrico Signoretti, Head of Product Strategy for OpenIO, a software defined, object storage startup out of Europe. Enrico is an old friend, having been a member of many Storage Field Day events (SFD) in the past which both Howard and I attended and we wanted to hear what he was up to nowadays.

OpenIO open source SDS

It turns out that OpenIO is an open source object storage project that’s been around since 2008 and has recently (2015) been re-launched as a new storage startup. The open source, community version is still available and OpenIO has links to downloads to try it out. There’s even one for a Raspberry PI (Raspbian 8, I believe) on their website.

As everyone should recall object storage is meant for multi-PB data storage environments. Objects are assigned an ID and are stored in containers or buckets. Object storage has a flat hierarchy unlike file systems that have a multi-tiered hierarchy.

Currently, OpenIO is in a number of customer sites running 15-20PB storage environments. OpenIO supports AWS S3 compatible protocol and OpenStack Swift object storage API.

OpenIO is based on open source but customer service and usability are built into the product they license to end customers  on a usable capacity basis. Minimum license is for 100TB and can go into the multiPB range. There doesn’t appear to be any charge for enhancements of additional features or additional cluster nodes.

The original code was developed for a big email service provider and supported a massive user community. So it was originally developed for small objects, with fast access and many cluster nodes. Nowadays, it can also support very large objects as well.

OpenIO functionality

Each disk device in the OpenIO cluster is a dedicated service. By setting it up this way,  load balancing across the cluster can be at the disk level. Load balancing in OpenIO, is also a dynamic operation. That is, every time a object is created all node’s current capacity is used to determine the node with the least used capacity, which is then allocated to hold that object. This way there’s no static allocation of object IDs to nodes.

Data protection in OpenIO supports erasure coding as well as mirroring (replication{. This can be set by policy and can vary depending on object size. For example, if an object is say under 100MB it can be replicated 3 times but if it’s over 100MB it uses erasure coding.

OpenIO supports hybrid tiering today. This means that an object can move from OpenIO residency to public cloud (AWS S3 or BackBlaze B2) residency over time if the customer wishes. In a future release they will support replication to public cloud as well as tiering.  Many larger customers don’t use tiering because of the expense. Enrico says S3 is cheap as long as you don’t access the data.

OpenIO provides compression of objects. Although many object storage customers already compress and encrypt their data so may not use this. For those customers who don’t, compression can often double the amount of effective storage.

Metadata is just another service in the OpenIO cluster. This means it can be assigned to a number of nodes or all nodes on a configuration basis. OpenIO keeps their metadata on SSDs, which are replicated for data protection rather than in memory. This allows OpenIO to have a light weight footprint. They call their solution “serverless” but what I take from that is that it doesn’t use a lot of server resources to run.

OpenIO offers a number of adjunct services besides pure object storage such as video transcoding or streaming that can be invoked automatically on objects.

They also offer stretched clusters where an OpenIO cluster exists across multiple locations. Objects can have dispersal-like erasure coding for multi-site environments so that if one site goes down you still have access to the data. But Enrico said you have to have a minimum of 3 sites for this.

Enrico mentioned one media & entertainment customer stored only one version of a video in the object storage but when requested in another format automatically transcoded it in realtime. They kept this newly transcoded version in a CDN for future availability, until it aged out.

There seems to be a lot of policy and procedural flexibility available with OpenIO but that may just be an artifact of running in Linux.

They currently support RedHat, Ubuntu and CentOS. They also have a Docker container in Beta test for persistent objects, which is expected to ship later this year.

OpenIO hardware requirements

OpenIO has minimal hardware requirements for cluster nodes. The only thing I saw on their website was the need for at least 2GB of RAM on each node.  And metadata services seem to require SSDs on multiple nodes.

As discussed above, OpenIO has a uniquely light weight footprint (which is why it can run on Raspberry PI) and only seems to need about 500MB of DRAM and 1 core to run effectively.

OpenIO supports heterogeneous nodes. That is nodes can have different numbers and types of disks/SSDs on them, different processor, memory configurations and OSs. We talked about the possibility of having a node go down or disks going down and operating without them for a month, at the end of which admins could go through and fix them/replacing them as needed. Enrico also mentioned it was very easy to add and decommission nodes.

OpenIO supports a nano-node, which is just an (ARM) CPU, ram and a disk drive. Sort of like Seagate Kinetic and other vendor Open Ethernet drive solutions. These drives have a lightweight processor with small memory running Linux accessing an attached disk drive.

Also, OpenIO nodes can offer different services. Some cluster nodes can offer metadata and object storage services and others only object storage services. This seems configurable on a server basis. There’s probably some minimum number of metadata and object services required in a cluster. Enrico mentioned three nodes as a minimum cluster.

The podcast runs ~42 minutes but Enrico is a very knowledgeable, industry expert and a great friend from multiple SFD/TFD events. Howard and I had fun talking with him again. Listen to the podcast to learn more.

Enrico Signoretti, Head of Product Strategy at OpenIO.

In his role as head of product strategy, Enrico is responsible for the planning design and execution of OpenIO product strategy. With the support of his team, he develops product roadmaps from the planning stages to development to ensure their market fit.

Enrico promotes OpenIO products and represent the company and its products at several industry events, conferences and association meetings across different geographies. He actively participates in the company’s sales effort with key accounts as well as by exploring opportunities for developing new partnerships and innovative channel activities.

Prior to joining OpenIO, Enrico worked as an independent IT analyst, blogger and advisor for six years, serving clients among primary storage vendors, startups and end users in Europe and the US.

Enrico is constantly keeping an eye on how the market evolves and continuously looking for new ideas and innovative solutions.

Enrico is also a great sailor and an unsuccessful fisherman.

47: Greybeards talk Storage as a Service with Lazarus Vekiarides, CTO & Co-Founder ClearSky Data

Sponsored By:

In this episode, we talk with ClearSky Data’s Lazarus Vekiarides, CTO and Co-founder,  who we have talked with before (see our podcast from October 2015). ClearSky Data provides a storage-as-a-service offering that uses an on-premises appliance plus point of presence (PoP) storage in the local metro area to hold customer data and offloads this data to cloud storage. In addition to the on-premises storage-as-a-service they offer access to customer data from an in-cloud virtual appliance. ClearSky provides the whole storage service, including gigabit metro Ethernet connections from the customer to the POP for simple capacity based charge every month.

How does it work

Their Edge (on premises) appliance supports 24 SSDs and can scale up to 4 appliances. Soon a single appliance will be able to hold up to 32TB of data.  It’s intended to hold a data center’s entire working set for one week of activity. So essentially it’s a big caching appliance for the local data center

For ClearSky Data the lone source of truth for customer data lies in the PoP. The PoP is connected to metro wide fibre that is available in a number of large metropolitan areas. Laz says they have measured sub 500 µsec round trip response time between their PoP equipment and Edge appliance. The PoP provides the backing store for the Edge appliance. Data written to the edge appliance(s) are written through to the PoP storage. This data and it’s metadata (<1% of LUN size) is flushed to cloud storage which holds the data indefinitely.

DR through the PoP

If customers have multiple data centers within the same metro area (100Km) then they can have a single “logical” array that accesses the same data, say a cluster file system across the two data centers. The PoP will take care of copying the metadata to the secondary edge device and will invalidate any data sitting in the secondary device which is no longer valid. In this way customers can have a Recovery Point Objective (RPO)=0 seconds. That is any data written to the primary data center is automatically available to the secondary data center as long as the PoP survives.

But even if you wanted to fail over to a different metro area the PoP data is offloaded to the cloud continuously so while you wouldn’t attain an RPO=0 seconds, it could be awfully short, on the order of a couple of seconds.

Recent enhancements

ClearSky Data has recently enhanced their storage as a service to provide policy management over snapshots. That is you can establish policies as to how often to take LUN snapshots and how long to retain them in the cloud.

Also, ClearSky Data has added VMware functionality via plugins that allow their storage to know which VMs are writing data or are being backed up to their appliance. And this is included in the metadata written for a LUN which is offloaded to the cloud. Someday soon when you can have vSphere running bare metal in a public cloud service, you will be able to run the Cloud Edge (cloud software version of their Edge appliance) and restore the data from your data center directly to the cloud and have an iSCSI LUN available to EC2 running VMware providing complete Cloud DR for a data center.

We talked a bit about our favorite topic, NVMe storage and Laz sees a potential for it to help their Edge appliances but at the moment fault-tolerence/high availability is not there. And as they are primary storage for data centers HA is a critical capability.

Pricing and availability

Their product is priced as a service in $0.nn/GB/Month and if you do a 36 month cost analysis they feel they would come out cheaper than hybrid storage. They currently have PoP’s in Boston, NyNy, Northern Virginia, Dallas, and California. Laz says they believe there’s 15 major metropolitan areas across the USA they have targeted for service.  What nothing in Europe or Asia? We would imagine this is merely a question of the number of customers, amount of data and metro infrastructure.

The podcast runs ~24 minutes. Laz has been in the storage industry across a number of companies and has been with a few startups as well. Laz is very knowledgeable about storage, cloud, and metro networking, a good friend and is always a pleasure to talk with.  Listen to the podcast to learn more.

Lazarus Vekiarides, CTO & Co-Founder ClearSky Data

For over 20 years Laz Vekiarides has served in key technical and leadership roles delivering breakthrough technologies to market. Most recently, he served as the Executive Director of Software Engineering for Dell’s EqualLogic Storage Engineering group, where he led the development of numerous storage innovations and established the EqualLogic product line as a leader in host OS and hypervisor integration.

Laz joined Dell from EqualLogic, which was acquired in early 2008, where he was a member of the core leadership team – playing a key role in the company’s early success as a Senior Engineering Manager and Architect for the PS Series SAN arrays and host tools. Prior to EqualLogic, Laz held senior engineering and management positions at several companies including 3COM and Banyan Systems.

An occasional blogger, Laz frequently speaks at industry conferences, particularly in the areas of virtualization and data storage. He holds several storage technology patents, as well as a BSEE from Northeastern University, and an MSCS from the Worcester Polytechnic Institute.

46: Greybeards discuss Dell EMC World2017 happenings on vBrownBag

In this episode Howard and I were both at Dell EMC World2017 this past month and Alastair Cooke (@DemitasseNZ) asked us to do a talk at the show for the vBrownBag group (Youtube video here). The GreyBeards asked for a copy of the audio for this podcast.

Sorry about the background noise, but we recorded live at the show, with a huge teleprompter in the background that was re-broadcasting keynotes/interviews from the show.

At the show

Howard was at Dell EMC World2017 on a media pass and I was at the show on an industry analyst pass. There were parts of the show that he saw, that I didn’t and vice versa, but all keynotes and major industry outreach were available to both of us.

As always the Dell EMC team put on a great show, and kudos have to go to their AR and PR teams for having both of us there and creating a great event. There were lots of news at the show and both of us were impressed by how well Dell EMC have come together, in such a short time.

In addition, there were a number of Dell partners at the show. Howard met  Datadobi on the show floor who have a file migration tool that walks a filesystem tree and migrates files as well as reports on files it can’t. And we both saw Datrium (who we talked with last year).

Servers and other news

We both liked Dell’s new 14th generation server. But Howard objected to the lack of technical specs on it. Apparently, Intel won’t let specs be published until they announce their new CPU chipsets, sometime later this year. On the other hand, there were a few server specs discussed. For example, I was impressed the new servers would support many more NVMe cards. Howard liked the new server support for NV-DIMMs, mainly for the potential latency reduction that could provide software defined storage.

That led us on a tangent discussion about whether there is a place for non-software defined storage anymore.  Howard mentioned the downside of HCI/software defined storage on upgrading server (DIMM, PCIe card) hardware.

However, appliance hardware seems to be getting easier to upgrade. The new Unity AFA storage can be upgraded, non-disruptively from the low end to high end appliance by just swapping out controller hardware canisters.

Howard was also interested in Dell EMC’s new CloudFlex purchasing model for HCI solutions. This supplies an almost cloud-like purchasing option for customers. Where for a one year commitment,  you pay as you go (no money down, just monthly payments) rather than an up front capital purchase. After the year’s commitment expires you can send the hardware back to Dell EMC and stop paying.

We talked about Tier 0 storage. EMC DSSD was an early attempt to provide Tier 0 but came with lots of special purpose hardware. When commodity hardware and software emerged last year with NVMe SSD speed, DSSD was no longer viable at the premium pricing needed for all that hardware and was shut down. Howard and I discussed how doing special hardware requires one to be much faster (10-100X) than commodity hardware solutions to succeed and the gap has to be continued.

The other big storage news was the new VMAX 950F AFA and its performance numbers. Dell EMC said the new VMAX could do 6.7M IOPS of RRH (random read hit) and had a 350µsec response time. Howard noted that Dell EMC didn’t say at what IO load they achieved the 350µsec response time. I told him it almost didn’t matter, even if it was a single IO at that response time, it was significant.

The podcast runs about 40 minutes. It’s just Howard and I talking about what we saw/heard at the show and the occasional, tangental topic.  Listen to the podcast to learn more.


Howard Marks, DeepStorage

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

Ray Lucchesi, Silverton Consulting

Ray Lucchesi is the President and Founder of Silverton Consulting, a prominent blogger at RayOnStorage Blog, and can be found on twitter @RayLucchesi.