[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.

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 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.

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 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 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 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