096: GreyBeards YE2019 IT Industry Trends podcast

In this, our yearend industry wrap up episode, the GreyBeards discuss trends and technologdies impacting the IT industry in 2019 and what’s ahead for 2020. This year we have Matt and Keith on the podcast along with Ray. Just like last year, we start off with NVMeoF.

NVMeoF unleashed

This year just about every major storage vendor announced new systems that either have support for NVMeoF or currently offer NVMeoF on their storage systems. Most offer FC based NVMeoF but a few offer NVMeoF/Ethernet, fewer still offer both.

All of the NVMeoF/Ethernet seem to be using RoCE or iWARP. Unclear if one is more often used that the other, so for now both continue to be used in the market. Some storage vendors are offering NVMeoF as an internal fabric to access storage while still using iSCSI or FC/SCSI to access the data. This works better than SAS but won’t provide all the performance you can get from end-to-end NVMeoF.

NVMeoF is all about increasing IOPS and reducing response times. That and getting ready for SCM SSDs. In the mean time the SSD industry has introduced some very attractive NVMe (NAND) SSDs that in NVMeoF storage system can increase IOPS and reduce latencies.

We talked last year about NVMeoF standards finally stabilizing and this year the rollout across enterprise storage systems is testament to that.

SCM hits the enterprise

Most of us attended an Intel Data Center Event earlier this past yea,r where Optane DC PM was introduced. Optane DC PM is the memory version of Optane SCM (3DX Crosspoint) technology. Intel offers two distinct modes of accessing Optane DC PM as memory: 1) App Direct mode, where data in Optane DC PM persists across power cycles but requires one to use a special AP; and 2) Memory mode where Optane DC PM is cleared during a power cycle, (see our RayOnStorage post Need memory, Intel’s Optane DC PM…).

Vendors seem to be using Optane both memory and SCM technology differently. Pure is using Optane SSDs plugged into their FlashArray as sort of a read cache for customer IO. They suggest for well behaved applications this can reduce IO response times considerably.

Dell EMC introduced SCM as a storage tier and are using their automated storage tiering to move the hottest data to SCM. Oracle’s latest Exadata appliance uses Optane DC PM as both a read and write caching layer.

It won’t be long before every enterprise vendor offers SCM drives in their storage systems with a few offering Optane DC PM as in memory caching technology.

Of course, the big news for Optane DC PM is its use in memory databases, specifically SAP HANA. HANA can take advantage of the (6) TB of memory to to handle larger databases. Keith mentioned that even Microsoft SQL server can take advantage of the additional memory to provide faster responses to queries.

Keith also mentioned that there are some systems out there that can be configured to share Optane memory (or storage). When SAP or other databases use this solution they are able to amortize the cost of the technology over more use cases.

Of course, Optane DC PM are only available on the lastest generation Intel processors. None of us have heard anything from AMD (or Micron) on providing a second source for support of Optane DC PM (or the memory technology itself). Presumably most customers would want a second source for Optane DC PM processor support (as well as the technology)

Cloud enterprise storage hits mainstream

The other thing we saw more of this year is enterprise vendors offering versions of storage in public cloud environments. NetApp was an early proponent of doing this.

We saw at Pure that they have a new Cloud Block Store witch is a re-architected version of FlashArray//X storage using AWS hardware and networking services. We were very impressed with what they have accomplished and it was the subject of more than one late night discussion. Listen to the Keith & Ray show at Pure//Accelerate2019 podcast to learn more.

Matt mentioned Nimble’s cloud volume storage which is cloud adjacent. Most enterprise vendors offer something similar today. They differentiate on how easy it is to configure, use and where (which regions) it’s available in.

NetApp has arguably been at this the longest and has the deepest offerings available from cloud adjacent file and block storage, to offering native enterprise file services for all public cloud environments, to supplying a suite of dedicated data services to surround all of their storage technology operating in public clouds and on premises.

While Dell EMC may have missed the turn to the cloud, they are quickly trying to catch up. Keith mentioned Faction, a Dell partner that offers cloud storage services using VMware with VMC. With Faction and vSAN customers have access to software defined storage that uses cloud hardware to support data services.

What’s driving data growth

There seems to be no end for the need for storage to store data. The GreyBeards point to three trends driving data growth today.

  1. IoT seems to have no bounds. A recent RayOnStorage post Internet of Tires discussed how tire companies were tying their tires to the internet. And that’s just the start, pretty soon every artifact, every device, every manufactured item will have a number of sensors attached all of which will be creating massive amounts of data.
  2. AI ML DL has an insatiable appetite for data. IoT is being used largely to optimize products and services. But it’s DL, with a large dollop of data, that is behind much of that optmization.
  3. SaaS applications is a relatively new application approach that’s being rolled out to more arenas and as it’s online and user oriented, seems to generate lots of data.

Containers storage debate

We closed the podcast with a heavy debate on whether container applications have need for storage. Keith was adamant that containers by their very nature are stateless and that Kubernetes ability to stop and start container applications at will almost requires stateless operations.

Ray was a bit more theoretical on the topic and believed that most container applications today take advantage of some sort of database or other services to store state and that state is just another word for storage.

Keith mentioned encoding as a typical container app. Encoding containers can be fired up and taken down at will without hurting anything but throughput. Yes, but those encoder container apps must access some database or other state information to find out what work is left to do and as they complete their work they update this data as well as store their newly encoded segments. This all involves the use of state information.

In the end, I think we were talking about the same thing but using different terminology. Keith believes that persistent state information is needed and Ray says that this is just another word for (containers) storage. Matt said we probably need Nigel (@NigelPoulton) on the podcast to straighten us both out.

The podcast ran a bit long and could have run longer. Keith and Matt bring systems level perspective to what’s happening in the storage market. But they come at it from different sides. Ray seems to frame everything from a storage perspective. Diverse perspectives lead to a more fuller and interesting discussion. Listen to the podcast to learn more.


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Ray Lucchesi ( @RayLucchesi) is the host of GreyBeardsOnStorage and is President/Founder of Silverton Consulting, and a prominent blogger at RayOnStorage.com.

Keith Townsend (@CTOAdvisor) is a IT thought leader who has written articles for many industry publications, interviewed many industry heavyweights, worked with Silicon Valley startups, and engineered cloud infrastructure for large government organizations. Keith is the co-founder of The CTO Advisor, blogs at Virtualized Geek

Matt Leib (@MBLeib), one of our co-hosts, has been blogging in the storage space for over 10 years, with work experience both on the engineering and presales/product marketing. His blog is at Virtually Tied to My Desktop.


095: GreyBeards talk file sync&share with S. Azam Ali, VP Customer Success at CentreStack

We haven’t talked with a file synch and share vendor in a while now and Matt was interested in the technology. He had been talking with CentreStack, and found that they had been making some inroads in the enterprise. So we contacted S. Azam Ali, VP of Customer Success at CentreStack and asked if he wanted to talk about their product on our podcast.

File synch and share, is part collaboration tool, part productivity tool. With file synch & share many users share the same files, across many different environments and end point devices. It’s especially popular with road warriors that need access to the same files on the road that reside in corporate data centers. With this technology, files updated anywhere would be available to all.

Most file synch&share systems require you to use their storage. But CentreStack just provides synch and share access to NFS and SMB storage that’s already in the data center.

CentreStack doesn’t use VPNs to access data, many other vendor do. But with CentreStack, one just log’s into a website (with AD credentials) and they have immediate browser access to files.

CentreStack uses a gateway VM, that runs in the corporate data center, configured to share files/file directories/shares. We asked whether they were in the data path and Azam said no. However, the gateway does register for file system notifications (e.g. when files are updated, outside CentreStack, they get notified).

CentreStack does maintain meta-data on the files, directories, shares that are under it’s control. Presumably, once an admin sets it up, it goes out and access the file systems that have shared files and populates their meta-data for those files.

CentreStack works with any NFS and SMB file system as well as NAS servers that support these two. It’s unclear whether customers can have more than one gateway server in their data center supporting synch and share but Azam did say that it wasn’t unusual for customers with multi-data centers to have a gateway in each, to support synch&share requirements for each data center.

They use client software on end point devices, which presents the shared files as an external drive (to Mac), presumably a cloud drive for Windows PCs and similar services (in an App) for other systems (IOS, Android phones, iPad, etc.). We believe Azam said Linux was coming soon.

The client software can be configured in cache mode or offline mode:

  • Cache mode – the admin can configure how much space to use on the endpoint device and the software will cache the most recently used files in that space for faster access
  • Offline mode – the software moves all files that the endpoint login can access, to the device.

In cache mode, when users open a file (not in the most recently used cache), there will be some delay as the system retrieves data from the internet and copies it to the endpoint device. Unclear what the delay might be but it’s probably a function of internet speed and load on the gateway, with possibly some overhead for the NFS/SMB/NAS system to supply the data. If there’s not enough space to hold the file, the oldest non-open file is erased from the cache.

In both modes, Centrestack supports cross domain locking. That is, if one client has a file open (for update), all other systems/endpoints may only access the file in read-only mode. After the file is closed. the file can then be opened for update by other users.

When CentreStack clients are used to update files, the data is stored back in the original file systems with versioning. This way if the data is corrupted, admins can easily return back to a known good copy version.

CentreStack also offers a cloud backup and DR service. Gateway admins can request that synch&share files be backed up to cloud storage (AWS S3, Azure Blob and Wasabi). When CentreStack backups file data to the cloud, it also includes metadata information about the files so they can be re-constituted anywhere.

A CentreStack cloud gateway VM can be activated in the cloud to supply access to backed up files. Unclear whether the CentreStack cloud backup has to be restored to block or file storage first or if it just accesses the data on cloud storage directly. But one customers using CentreStack cloud DR would need to run client software in their applications accessing these files.

Wasabi seemed an odd solution to have on their list of supported cloud storage providers, but Azam said for their market, the economics of Wasabi storage were hard to ignore. See our previous podcast with David Friend, Co-Founder& CEO, Wasabi, to learn more about Wasabi.

CentreStack is licensed on a per user basis, not storage capacity bucking industry trends. But they don’t actually own the storage so it makes sense. For CentreStack cloud backup, customers also have to supply the cloud storage.

They also offer a 30 day free trial on their website with unlimited users. We assume this uses CentreStacks cloud gateway and customers bring their own cloud storage to support it.

The podcast runs about 35 minutes. Azam was a bit more marketing than we are used to, but he warmed up once we started asking questions. Listen to the podcast to learn more.

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S. Azam Ali, VP of Customer Success, CentreStack

S. Azam Ali, is VP of Customer Success at CentreStack and is an executive with extensive experience in managing global teams including sales, support and consulting services.

Azam’s channel experience includes on-boarding new partners including creation of marketing and training collateral for the partners. Azam is an executive with a passion for customer success and establishing long term relationships and partnerships.

Azam is also an advisor to startups as well as established technology companies.

094: GreyBeards talk shedding light on data with Scott Baker, Dir. Content & Data Intelligence at Hitachi Vantara

Sponsored By:

At Hitachi NEXT 2019 Conference, last month, there was a lot of talk about new data services from Hitachi. Keith and I thought it would be a good time to sit down and talk with Scott Baker (@Kraken-Scuba), Director of Content and Data Intelligence, at Hitachi Vantara about what’s going on with data operations these days and how customers are shedding more light on their data.

Information supply chain

Something Scott said in his opening remarks caught my attention when he mentioned customer information supply chains. The information supply chain is similar to manufacturing supply chains, but it’s all about data. Just like manufacturing supply chains where parts and services come from anywhere and are used to create products/services for customers,

information supply chains are about the data used in their organization operations. Information supply chain data is A) being sourced from many places (or applications); B) being added to by supply chain processing (or other applications); and C) ultimately used by the organization to supply a product/service to customers.

But after the product/service is supplied the similarity between manufacturing and information supply chains breaks down. With the information supply chain, data is effectively indestructible, is infinitely re-useable and can live forever. Who throws data away anymore?

The problem most organizations have with information supply chains is once the product/service is supplied, data is often put away never to be seen again or as Scott puts it, goes dark.

This is where Hitachi Content intelligence (HCI) comes in. HCI is designed to take (unstructured or structured) data and analyze it (using natural language and other processing tools) to surround it with information and other metadata, so that it can become more visible and useful to the organization for the life of its existence.

Customers can also use HCI to extract and blend data streams together, automating the creation of an information rich, data repository. The data repository can readily be searched to re-discover or uncover attributes about the data not visible before.

Scott also mentioned the Hitachi Pentaho Platform which can be used to make real time decision from structured data. Pentaho information can also be fed into HCI to provide more intelligence for your structured data.

But HCI can also be used to analyze other database data as well. For instance, database blob and text elements can be fed to and analyzed by HCI. HCI analysis can include natural language processing and other functionality to tag the data by adding key:value information, all of which can be supplied back to the database or Pentaho to add further value to structured data.

Customers can also use HCI to read and transform database tables into XML files. XML files can be stored in object stores as objects or in file systems. XML data could easily be textually indexed and be searched by various tools to better understand the structured data information

We also talked about Hadoop data that can be offloaded to Hitachi Content Platform (HCP) object storage with a stub left behind. Once data is in HCP, HCI can be triggered to index and add more metadata, which can then later be used to decide when to move data back to Hadoop for further analysis.

Finally, Keith mentioned that he just got back from KubeCon and there was an increasing cry for data being used with containerized applications. Scott mentioned HCP for Cloud Scale, the newest member of the HCP object store family, focused on scale out capabilities to provide highly consistent, object storage performance for customers that need it. Customers running containerized workloads use scale-out capabilities to respond to user demand and now they have on premises object storage that can scale with them, as needs change.

The podcast ran ~24 minutes. Scott was very knowledgeable about data workflows, pipelines and the need for better discovery tools. We had a great time discussing information supply chains and how Hitachi can help customers optimize their data pipelines. Listen to the podcast to learn more.

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Scott Baker, Director of Content and Data Intelligence at Hitachi Vantara

Scott Baker is, and has been, an active member of the information technology, data analytics, data management, and data protection disciplines for longer than he is willing to admit.

In his present role at Hitachi, Scott is the Senior Director of the Content and Data Intelligence organization focused on Hitachi’s Digital Transformation, Data Management, Data Governance, Data Mobility, Data Protection and Data Analytics solutions which includes Hitachi Content Platform (HCP), HCP Anywhere, HCP Gateway, Hitachi Content Intelligence, and Hitachi Data Protection Solutions.

Scott is a VMware Certified Professional, recognized as a subject matter expert, industry speaker, and author. Scott has been a panelist on topics related to storage, cloud, information governance, data security, infrastructure standardization, and social media topics. His educational background includes an MBA, Master’s & Bachelor’s in Computer Science.

When he’s not working, Scott is an avid scuba diver, underwater photographer, and PADI Scuba Instructor. He has a passion for public speaking, whiteboarding, teaching, and traveling the world.

93: GreyBeards talk HPC storage with Larry Jones, Dir. Storage Prod. Mngmt. and Mark Wiertalla, Dir. Storage Prod. Mkt., at Cray, an HPE Enterprise Company

Supercomputing Conference 2019 (SC19) is coming to Denver next week and in anticipation of that show, we thought it would be a good to talk with some HPC storage group. We contacted HPE and given their recent acquisition of Cray, they offered up Larry and Mark to talk about their new ClusterStor E1000 storage system.

There are a number of components that go into Cray supercomputers and besides the ClusterStor, Larry and Mark mentioned their new SlingShot cluster interconnect which is Ethernet based with significant enhancements to congestion handling. But the call focused on ClusterStor.

What is ClusterStor

ClusterStor, is a Lustre file system hardwareappliance. Lustre has always been popular with the HPC crowd as it offered high bandwidth file services. But Lustre often took a team of (PhD) scientists to configure, deploy and run properly because of all the parameters that had to be setup for optimum performance.

Cray’s ClusterStor was designed to make configuring, deploying and running Lustre a lot simpler with a GUI and system defaults that provided an optimal running environment. But if customers still want access to all Lustre features and functionality, all the Lustre parameters can still be tweaked to personalize it.

What sort of appliance

The ClusterStore team has created a Lustre storage appliance using two systems, a 2U-24 NVMe SSD system and a 4U-106 disk drive system. Both systems use PCIe Gen 4 buses which offer 2X the bandwidth of Gen 3 and NVMe Gen 4 SSDs. Each ClusterStore E1000 appliance comes with 2 servers for HA and the storage behind it.

Larry said the 2U NVMe Gen 4 appliance offers 80GB/sec of read and 60GB/sec of write data bandwidth. And a full rack of these, could support ~2.5TB/sec of data bandwidth. One TB/sec seems like an awful lot to the GreyBeards, 2.5TB/sec, out of this world.

We asked if it supported InfiniBAND interconnects? Yes, they said it supports the latest generation of InfiniBAND but it also offers Cray’s own (SlingShot) Ethernet interconnect, unusual for HPC environments. And as in any Lustre parallel file system, servers accessing storage use Lustre client software.

ClusterStor Data Services

But on the backend, where normally one would see only LDISKFS for backend storage, ClusterStor also offers ZFS. Larry and Mark said that LDISKFS is faster but ZFS offers more functionality like snapshots and data compression.

Many of the Top 100 & Top 500 supercomputing environments are starting to deploy ML DL (machine learning-deep learning) workloads along with their normal HPC activities. But whereas HPC work has historically depended on bandwidth to read, write and move large files around, ML DL deals with small files and needs high IOPS. ClusterStor was designed to satisfy both high bandwidth and high IOPS workloads.

In previous HPC Lustre flash solutions, customers had to deal with the complexity of where to place data, such as on flash or on disk. But with net ClusterStor E1000, the system can do all this for you. That is it will move data from disk to flash when it sees an advantage to doing so and move it back again when that advantage is gone. But, just as with Lustre configuration parameters above, customers can still pre-stage data to flash.

The other challenge for HPC environments is extreme size. Cray and others are starting to see requirements for Exascale (exabyte, 10**18) byte) storage systems. In fact, Cray has a couple of ClusterStor E1000 configurations of 400PB or more already, As these systems age they may indeed grow to exceed an exabyte.

With an exabyte of data, systems need to support billions of files/inodes and better metadata services and indexing. ClusterStor offers optimized inode indexing and search to enable HPC users to quickly find the data they are looking for. Further, ClusterStor offers, data at rest encryption and supports virtual file systems, for multi-tenancy.

With a ZFS backend, ClusterStor can supply data compression and snapshots. Cray has tested ZFS compression on HPC scientific ( mostly already application compressed) data and still see ~30% reduction is storage footprint. At an exabyte of storage 30% can be a significant cost reduction

The podcast ran long, ~46 minutes. Larry and Mark had a good knowledge of the HPC storage space and were easy to talk with. Matt’s an old ZFS hand, so wanted to take even more about ZFS. I had a good time discussing ClusterStor and Lustre features/functionalit and how the HPC workloads are changing. Listen to the podcast to learn more. [The podcast was recorded on November 6th, not the 5th as mentioned in the lead in, Ed.]

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Larry Jones, Director Storage Product Management

Larry Jones is a director of storage product management for Cray, a Hewlett Packard Enterprise company.

Jones previously held senior product management roles at Seagate, DDN and Panasas.

Mark Wiertalla, Director Storage Product Marketing

Mark Wiertalla is a product marketing director for Cray, a Hewlett Packard Enterprise company.

Prior to Cray, Wiertalla held product manager roles at EMC and SGI.

92: Ray talks AI with Mike McNamara, Sr. Manager, AI Solution Mkt., NetApp

Sponsored By: NetApp

NetApp’s been working in the AI DL (deep learning) space for a long time now and announced their partnership with NVIDIA DGX systems, back in August of 2018. At NetApp Insight, this week they were showing off their new NVIDIA DGX systems reference architectures. These architectures use NetApp AFF A800 storage (for more info on AI DL, checkout Ray’s Learning Machine (deep) Learning posts – part 1, – part 2 and – part3).

Besides the ONTAP AI systems, NetApp also offers

  • FlexPod AI solution based on their partnership with Cisco using UCS C480 ML M5 rack servers which include 8 NVIDA Tesla V100 GPUs and also features NetApp AFF A800 storage for use in core AI DL.
  • NetApp HCI has two configurations with 2- or 3-NVIDIA GPUs that come in 1U or 2U rack servers and run VMware vSphere or RedHad OpenStack/OpenShift software hypervisors suitable for edge or core AI DL.
  • E-series reference architecture that uses the BeeGFS parallel file system and offers InfiniBAND data access for HPC or core AI DL.

On the conference floor, NetApp showed AI DL demos for automotive, financial services, Public Sector and healthcare verticals. They also had a facial recognition application running that could estimate your age and emotional state (I didn’t try it, but Mike said they were hedging the model so it predicted a lower age).

Mike said one healthcare solution was focused on radiological image scans, to identify pathologies from x-Ray, MRI, or CAT scan images. Mike mentioned there was a lot of radiological technologists burn-out due to the volume of work caused by the medical imaging explosion over the last decade or so. Mike said image analysis is something that h AI DL can perform very effectively and doing so would improve the accuracy and reduce the volume of work being done by technologists.

He also mentioned another healthcare application that uses an AI DL app to count TB cells in blood samples and estimate the extent of TB infections. Historically, this has been time consuming, error prone and hard to do in the field. The app uses a microscope with a smart phone and can be deployed and run anywhere in the world.

Mike mentioned a genomics AI DL application that examined DNA sequences and tried to determine its functionality. He also mentioned a retail AI DL facial recognition application that would help women “see” what they would look like with different makeup on.

There was a lot of discussion on NetApp Cloud services at the show, such as Cloud Volume Services and Azure NetApp File (ANF). Both of these could easily be used to implement an AI DL application or be part of an edge to core to cloud data flow for an AI DL application deployment using NetApp Data Fabric.

NetApp also announced a new, all flash StorageGRID appliance that was targeted at heavy IO intensive uses of object store like AI DL model training and data analytics.

Finally, Mike mentioned NetApp’s ecosystem of partners working in the AI space to help customers deploy AI DL algorithms in their industries. Some of these include:

  1. Flexential, Try and Buy AI so that customers could bring them in to supply AI DL expertise to generate an AI DL application using customer data and deploy it on customer cloud or on prem infrastructure .
  2. Core Scientific, AI-as-a-Service, so that customers could purchase a service to implement an AI DL application using customer data and running on Core Scientific infrastructure..
  3. Scale Matrix, Mobile data center AI, so that customers could create an AI DL application and run it on Scale Matrix infrastructure that was transported to wherever the customer wanted it to be run.

We recorded the podcast on the show floor, in a glass booth, so there’s some background noise (sorry about that, but can’t be helped). The podcast is ~27 minutes. Mike is a long time friend and NetApp product expert, recently working in AI DL solutions at NetApp. When I saw Mike at Insight, I just had to ask him about what NetApp’s been doing in the AI DL space. Listen to the podcast to learn more.

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Mike McNamara, Senior Manager AI Solution Marketing, NetApp

With over 25 years of data management product and solution marketing experience, Mike’s background includes roles of increasing responsibility at NetApp (10+ years), Adaptec, EMC and Digital Equipment Corporation. 

In addition to his past role as marketing chairperson for the Fibre Channel Industry Association, he was a member of the Ethernet Technology Summit Conference Advisory Board, a member of the Ethernet Alliance, and a regular contributor to industry journals, and a frequent speaker at events.