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127: Annual year end wrap up podcast with Keith, Matt & Ray

[Ray’s sorry about his audio, it will be better next time he promises, The Eds] This was supposed to be the year where we killed off COVID for good. Alas, it was not to be and it’s going to be with us for some time to come. However, this didn’t stop that technical juggernaut we call the GreyBeards on Storage podcast.

Once again we got Keith, Matt and Ray together to discuss the past year’s top 3 technology trends that would most likely impact the year(s) ahead. Given our recent podcasts, Kubernetes (K8s) storage was top of the list. To this we add AI-MLops in the enterprise and continued our discussion from last year on how Covid & WFH are remaking the world, including offices, data centers and downtowns around the world. Listen to the podcast to learn more.

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K8s rulz

For some reason, we spent many of this year’s podcasts discussing K8s storage. TK8s was never meant to provide (storage) state AND as a result, any K8s data storage has had to be shoe horned in.

Moreover, why would any IT group even consider containerizing enterprise applications let alone deploy these onto K8s. The most common answers seem to be automatic scalability, cloud like automation and run-anywhere portability.

Keith chimed in with enterprise applications aren’t going anywhere and we were off. Just like the mainframe, client-server and OpenStack applications before them, enterprise apps will likely outlive most developers, continuing to run on their current platforms forever.

But any new apps will likely be born, live a long life and eventually fade away on the latest runtime environment. which is K8s.

Matt mentioned hybrid and multi-cloud as becoming the reason-d’etre for enterprise apps to migrate to containers and K8s. Further, enterprises have pressing need to move their apps to the hybrid- & multi-cloud model. AWS’s recent hiccups, notwithstanding, multi-cloud’s time has come.

Ray and Keith then discussed which is bigger, K8s container apps or enterprise “normal” (meaning virtualized/bare metal) apps. But it all comes down to how you define bigger that matters, Sheer numbers of unique applications – enterprise wins, Compute power devoted to running those apps – it’s a much more difficult race to cal/l. But even Keith had to agree that based on compute power containerized apps are inching ahead.

AI-MLops coming on strong

AI /MLops in the enterprise was up next. For me the most significant indicator for heightened interest in AI-ML was VMware announced native support for NVIDIA management and orchestration AI-MLops technologies.

Just like K8s before it and VMware’s move to Tanzu and it’s predecessors, their move to natively support NVIDIA AI tools signals that the enterprise is starting to seriously consider adding AI to their apps.

We think VMware’s crystal ball is based on

  • Cloud rolling out more and more AI and MLops technologies for enterprises to use. on their infrastructure
  • GPUs are becoming more and more pervasive in enterprise AND in cloud infrastructure
  • Data to drive training and inferencing is coming out of the woodwork like never before.

We had some discussion as to where AMD and Intel will end up in this AI trend.. Consensus is that there’s still space for CPU inferencing and “some” specialized training which is unlikely to go away. And of course AMD has their own GPUs and Intel is coming out with their own shortly.

COVID & WFH impacts the world (again)

And then there was COVID and WFH. COVID will be here for some time to come. As a result, WFH is not going away, at least not totally any time soon. And is just becoming another way to do business.

WFH works well for some things (like IT office work) and not so well for others (K-12 education). If the GreyBeards were into (non-crypto) investing, we’d be shorting office real estate. What could move into those millions of square feet (meters) of downtime office space is anyones guess. But just like the factories of old, cities and downtowns in particular can take anything and make it useable for other purposes.

That’s about it, 2021 was another “interesteing” year for infrastructure technology. It just goes to show you, “May you live in interesting times” is actually an old (Chinese) curse.

Keith Townsend, (@TheCTOadvisor)

Keith 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, and can be found on LinkedIN.

Matt Leib, (@MBLeib)

Matt Leib 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 and he’s on LinkedIN.

Ray Lucchesi, (@RayLucchesi)

Ray is the host and co-founder of GreyBeardsOnStorage and is President/Founder of Silverton Consulting, and a prominent (AI/storage/systems technology) blogger at RayOnStorage.com. Signup for SCI’s free, monthly industry e-newsletter here, published continuously since 2007. Ray can also be found on LinkedIn

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113: GreyBeards talk storage for next gen. workloads with Liran Zvibel, Co-Founder & CEO WekaIO

Sponsored By:

I’ve known Liran Zvibel, Co-founder and CEO of Weka IO for many years now and it’s the second time he’s been on our show, (see: Episode 56: GreyBeards talk high performance file storage...). In those days, WekaIO was just coming out and hitting the world with this extremely high-performing, scale out unstructured data solution. Well since then, they’ve just gotten better.

Keith and I had a great time talking with Liran again. Liran has deep knowledge about unstructured data and how enterprises use it these days. WekaIO’s story, over the last two years has gone beyond great performance to real world, hybrid cloud offerings e as well as going after the cloud native app’s (read Kubernetes [K8S]) persistent storage. Listen to the podcast to learn more.

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We started with a history lesson on WekaIO. Back in those days (which persists today, I might add) there were many IO workloads that required companies to purchase different solutions for different work. For example, they needed DAS or SAN for performance, NAS for ease of access and object for scale. WekaIO came out with an answer to all these problems in a single, scaleable storage system. That is, they performed IO as fast as DAS or SAN block, had all the ease of access of NAS, and could scale as much as object.

However, the real culprit holding the world back was “NFS”. At the outset NFS was designed (back in the 1990s) with the then current networking speeds available (10-100Mbps), which performed just fine at those speeds. But when 10-100GbE came out in the 2000’s, NFS’s metadata overhead was too chatty to support wire speeds. Thus, any storage that depended on NFS protocols couldn’t supply (small) files fast enough for modern applications.

This is why WekaIO has moved to not only support NFS and SMB but also POSIX and NVIDIA® GPUDirect® Storage interfaces. By offering POSIX, WekaIO is able to plug into standard Linux and Windows server systems and provide excellent small file performance. Of course applications that demand small file performance today are mostly data analytics and AI/ML/DL workloads.

Consequently., NVIDIA came out with their GPUDirect Storage protocol to address getting small file (data) into GPUs faster. With GPUDirect, storage systems can RDMA data directly from storage to GPU memory and vice versa, with no OS intervention (other than to set up the transfer). If you happen to have a small file, high performing storage system attached to your fabric that supports GPUDirect , like WekaIO, you can significantly speed up your AI/ML/DL workloads.

Next we started talking K8S storage. WekaIO usestheir POSIX interface in their CSI plugin to support K8S container persistent storage. Again, supplying high performance for small files seems to be tailor made for K8S container applications that exist today and will for the foreseeable future.

Enter the cloud. Almong other things, WekaIO is a AWS primary storage vendor. It also offers snap to cloud. And with both of these in tandem, it’s just become a lot easier to move and access your unstructured data in the cloud. Liran mentioned that WekaIO primary storage in AWS operates across AZ’s. This means it can be configured to support better availability than EBS.

Large BioPharma companies are using WekaIO in AWS to store and process field data and research data, so that this work can be done around the world. Some companies have run out of compute in a single AZ (unbelievable I know but it’s COVID). By offering multi-AZ support unstructured data access with WekaIO, these companies can spread their compute across AZ’s and region and still access their data. And when their products are ready for gov’t certification, having all this data in the cloud, can make provide an easy way to have gov’t access this same data.

Liran Zvibel, Co-founder and CEO WekaIO

As Co-Founder and CEO, Mr. Liran Zvibel guides long term vision and strategy at WekaIO. Prior to creating the opportunity at WekaIO, he ran engineering at social startup and Fortune 100 organizations including Fusic, where he managed product definition, design, and development for a portfolio of rich social media applications.

Liran also held principal architectural responsibilities for the hardware platform, clustering infrastructure and overall systems integration for XIV Storage System, acquired by IBM in 2007.

Mr. Zvibel holds a BSc.in Mathematics and Computer Science from Tel Aviv University.