>> Announcer: Live, from San Francisco,
celebrating 10 years of high tech coverage,
It's theCUBE!
Covering VMworld 2019.
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Brought to you by VMware and it's ecosystem partners.
>> Hello everyone, welcome back to theCUBE's
live coverage here in San Francisco, California
for VMworld 2019, I'm John Furrier with Dave Vellante.
Dave, this is our 10th year, 10 years
covering VMworld, quite a run.
Got a great story, more stories coming, M and A's,
a lot of organic growth, lot of IPO's in the startup scene.
Our next two guests, Mike Adams, Senior Director
VMware, and Ziv Kalmanovich,
Product Line Manager VMware. >> Nice work.
>> John: Welcome to theCUBE, great to see you.
>> Yeah, it's great to see you too.
>> You guys got a lot of activity happening
around Bitfusion, a lot of news to share.
Exciting, I mean, the M and A story's been high
on VMware, we talk with Pat Gelsinger earlier,
continuing to fill in on the strategy.
>> Mike: Yeah, absolutely. >> Give us the update.
>> Yeah, I think the key thing for us,
is we really want to become a key player
in the AI ML space, and say that those workloads
should come on vSphere, and with this acquisition,
we think provides a great framework
for a lot of the hardware accelerated devices,
the best of use known of those is GPU's,
but we think there's four coming market
with FPGA's and also custom ASIC's.
So we're super excited about that.
>> For the folks that don't know much about the acquisition,
what was the motivation, what was the companies
core product, what was the interest?
>> Yeah, the company had a product called FlexDirect,
and that particular product was really focused
on taking similar concept that a lot of VMware-ites know,
which was, "Hey, in the compute space, we trying to take
"these isolated islands and pull them together."
Same type of thing here, you had these expensive devices
that people were buying, and they were isolated,
and now, if we could take a single server,
it's got a bunch of GPU's on it,
why don't we share it, right?
You see all these papers that come out
around machine learning and at the very end,
it says, "Geez, I'm amazed that these GPU's
"are so underutilized."
Even when we're actually using them.
It's kind of like buying a car,
and then using the radio only, right?
It just doesn't make sense.
>> You've got this trend of alternative processors
just sort of exploding all over the place.
I mean, obviously Nvidia it's sort of,
people know what's going on there,
but you've got ARM, now you've got the EDGE comin' in.
You know, Intel is still dominant in the server space,
but even storage devices today use different type,
not Intel processors in there, it's a combination
of ARM or sometimes GPU's as you say, FPGA's,
even though they're sort of a narrow use case,
you're seeing ASICs make a comeback,
so you got all this additional processing power goin' in,
So that's a tailwind for you guys,
and it's sort of the intersection of those two,
Maybe talk about some of the trends you see
in that regard, and how you're taking advantage of them.
>> Yeah, I mean it reminds me of many moons ago,
when we had new chips that were coming out,
and we said, "Geez this is a hardware flurry here.", right?
And now we're in a really similar spot.
Ziv and I see a lot of different types of devices
and acceleration devices, whether it's compute,
or network, or storage, and in this particular case,
right, we just see a hotbed of all these customer
that are seeing this same problem, right?
And we've got great partnerships with Intel
that you mentioned, Nvidia and many others,
and we just want to really leverage those for these devices,
because you look at vSphere and say, "Okay,
"traditional workloads, we've done those very very well."
But as we get into containers, Kubernetes,
machine learning and AI, we want these newer cloud native,
and newer work loads to come our way, and taking advantage
of these new capabilities really helps
accelerate that in a big way.
>> Can you explain more on the vSphere impact,
because you know, first of all, VMware community,
you get the feedback right away on Twitter
and a lot of things, but sometimes you got to dig in,
and find out what people are thinking,
and where there might think there could be future
opportunities or there could be some skepticism as well.
VSphere native, having AI on vSphere,
That's just mind blowing to me but like,
I can see a data processor kind of vibe going on here,
where data needs to be processed, that seems to be a trend,
what is going on with vSphere with this, is there,
what should customers know?
>> Well, I think that the first thing to clarify here,
is that often there is this question,
"Why would I run ML or AI workloads specifically on
"vSphere as a platform?"
But then customers do run ML AI workloads
on public clouds, and those layers are not that different
than vSphere, it's virtualization layer,
and they are running it in virtual machines.
So the whole idea of it, BitFusion specifically,
is that it actually, we can make it even more efficient
to run these workloads on top of vSphere.
Because the underlying infrastructure that you own,
actually you have, to accelerate these workloads.
Today, they are mostly GPU's obviously,
but in the future, as Mike also mentioned,
new ASICs are coming in and FPGA's are coming in.
We are going to make those as well, that's the plan,
using the BitFusion framework,
be more efficient to use and utilize.
>> I'm surprised that people are skeptical around
running machine learning on vSphere,
not skeptical, because, I mean it's great
for any time you have the opportunity to automate something,
or use software to make something go away that's not
either differentiate or undifferentiated.
I mean, so it makes sense, but I'm just tryin'
to figure out where, specifically, within vSphere
is it being targeted to use?
>> Where in vSphere? >> Yeah.
>> As in, well,
>> If I'm operating vSphere, and I'm a operator.
And I got dev's kickin' around the corner,
I got cloud, my whole hybrid climate,
Where does this fit in?
>> This fits into essentially,
anyplace where vSphere is running.
It doesn't matter if it would run on VMware cloud
or any other of our cloud partnerships,
or on the EDGE where vSphere runs,
this is a core capability of vSphere,
so it doesn't matter where physically your infrastructure is
we would be able to expose this technology.
The idea is also that, you mentioned the trends
in the ASICs as they're coming into the enterprise.
There's an architectural change that's also coming in,
and then the server perspective, is just,
the servers are actually getting more denser
in their acceleration infrastructure that they have in them.
So you're seeing four to eight GPU's in a single server.
Those are very powerful machines.
You can't just move all your workloads
onto a single machine.
Again, that brings us back to BitFusion
and this segregated model of accelerator use,
which is very similar by the way to
centralized storage use for example.
>> I think you guys are onto something really big here,
I think that hardware assists off load,
anything hardware assists on hardware off load,
is going to be a more of a bigger trend.
And we saw it happen big time in hyper converged,
just for storage and networking, but I think
as you move up the stack where Kubernetes is going to flourish.
>> Mike: Yeah, yeah.
>> I mean, imagine all the services that are being
turned on and turned off.
I mean may not even know when it gets turned of or off.
>> Absolutely, we've been doing off load for a while,
with things like arrays, right, trying to push processing
off to a big array that you've got there.
And then one other thing that you said,
that I think was really important is the audience, right?
If you look at AI and ML, we've traditionally haven't talked
to the data scientists or the machine learning folks.
And we need to get to the IT folks that are supporting
those workloads, saying it's similar to some other
workloads that were new, and saying,
"These are going to come your way,
"and so we need to be prepared,
"and you need to be able to leverage that."
>> So what's the pitch to those folks?
What are you guys saying to them, because it is a benefit
for devs and, 'cause dev ops is dev ops, right?
Everybody's got the ops down, okay, see that,
and there's some change happening, but a dev,
what's the pitch, how do you get their attention,
what's the value proposition?
>> Mike: Yeah, you want to take that?
>> Actually, that's the beauty of it.
It's exactly the same viable proposition that vSphere
and VMware, the VMwares tech provides to the developers,
and the only thing is that now we are letting the ops people
to actually provide this new infrastructure as well
in the same efficient manner.
So you are basically it's giving
the exact same value proposition.
>> What about the multi-cloud tie-in here?
We've heard a lot about multi-cloud,
and I think multi-cloud, in part anyway,
is being able to run any application and workload anywhere.
And one of the things about your technology,
is the ability to not have to rewrite the application
to take advantage of acceleration.
Does it fit into multi-cloud, and if so, how?
>> Yeah, when we made the BitFusion acquisition,
if you look at their story, they had
the any, any, any story as well, just like we do.
And so, you know, we made an announcement with Nvidia
and AWS and VMware, it's definitely possible
the technology that we have, to extend that even further.
And so, you know, the only thing I know
with users going forward, is they're going to have
more than one cloud, and so we just need
to prepare for that and make sure that it works,
and it works well across the board.
And a common layer, when you look at our
multi-cloud strategy, is vSphere is going to be
at each of those layers, so if this ties in as vSphere,
it should be pretty easy to make it work
in each of those environments.
>> What was the announcement you made?
Can you just share that with us?
>> Well, the big one was being able to use
Nvidia in the context of cloud and AWS, so those GPU
capabilities, and bring it to the service as we do on-prem.
And so that was a big piece, and then we also,
obviously, in making that announcement, talking about,
hey, you know, this is a critical area for us,
because not only are we doing this,
but we're also saying that BitFusion will
help enhance this, because we think Nvidia and BitFusion
work very well together as well.
>> And is that a product, a service,
a go-to-market initiative?
>> In the case of the cloud and AWS, it would be offered
as part of the service, so when you consume the compute,
you know, you want a GPU, it'll be there for you,
to help run that workload in the cloud.
>> Dave: And that's available when?
>> That's an Nvidia and AWS kind of question,
when they are making that infrastructure available,
it's essentially going to be another instance-type
that VMware cloud and AWS will offer.
>> Dave: Right, okay, yeah.
>> Be announced it at a tech preview.
>> Yeah, right.
>> What are some of the things that people should know about?
Because, again, in the pattern I'm seeing here
at VMworld is, as you move up the stack,
with Kubernetes being that abstraction layer
that Gelsinger is promoting heavily, and rightfully so we're
big fans of Kubernetes, we were there from the beginning,
Is that you're going to have this purpose-built
native capability, so that you guys have got
this native vibe going on, native to hype vSphere.
Native to ESX, native, I mean, what is that actually mean,
native, like Kubernetes is native on,
what does it native mean?
Explain to the audience what that actually means.
>> Yeah, I'll start it, I'm sure you can elaborate.
>> Yeah, I can talk about it for another 30 minutes,
if you want, but I'll let Mike first.
>> I mean, what does that mean, true native, native.
>> Yeah, the idea for us was, you know,
use Kubernetes in really two ways, you know.
Most of the time, when we've been talkin' about
Kubernetes and containers, it's running that
on top of vSphere, right?
Well, what happens if you could take the DNA of that,
and put it actually inside of vSphere, right?
So not only you could run these clusters and native pods,
but you could also leverage some of the value.
And one of the things that Kubernetes does really well,
is it handles workloads really well.
So if we take an example where we have 145 VM's,
and they make up your app, right?
Normally you'd have to go to each one
of those, and figure out, "Okay,
"let's make some changes, some tweaks."
And now what I can do, is I can treat all of those
as one workload, and I can move them, I can do
really interesting things with that, and that's the power,
one of the powers that you have with Kubernetes.
>> And that's where the differentiation is.
(mumbles) anything to add there Ziv?
>> Yeah, exactly, I mean, you are essentially getting,
there are a lot of benefits to customers,
value that the customer is getting today from vSphere,
generically speaking, and our long time customers
are familiar with those value propositions.
And what we are seeing is that when you are getting
something as a native capability, is that essentially
ties into all the other capabilities that you already
know very well, and you will be able to get those,
sometimes on top or with conjunction
with these technologies. >> So what is that
going to enable now, let's talk about the enablement piece.
>> So, let's go back all the way, if you go all the way
back to BitFusion for example.
If you enable it as a native technology,
then if you are running containers or VM's on vSphere,
natively, they can consume the BitFusion technology.
If you have Kubernetes, it can orchestrate, natively,
the VM's and containers that are using the BitFusion
technologies and accelerators, so this is the whole thing,
>> John: It's more efficient from a platform standpoint.
>> And it's easier to manage as well,
because you don't have to install a bunch of stuff
one on top of each other, because it's native,
it's part of the infrastructure.
>> So a lot of the hassles go away
that people might know of.
>> That's right, bake it in.
And you're going to have two guests tomorrow
that are going to go deep into it with you.
>> Oh, great. >> So we're excited.
>> So, we're hearing a lot, obviously, about Kubernetes
at this event, but most of the audience
are not developers.
So how can you use the, sort of BitFusion mojo,
to attract developers for some of these new workloads
that are coming to the marketplace?
>> Yeah, I mean, it's all about acquiring new audiences.
In our case of BitFusion, it's more the data scientists.
In the case of the Kubernetes,
it's more around the developer.
But I think, let's use the Kubernetes example
as a good one, and what we announced with Project Pacific,
Basically, the way it looks, the technology looks to them,
it'll look like the Kubernetes API,
with a little bit of vSphere goodness.
And from the operator perspective, the people that we know,
the 20,000 that are here, it looks to them
like vSphere with some Kubernetes goodness.
So that's the right mix, is you've got to get it
so it looks exact, and smells and feels,
just like what they're used to.
And I think that that's a key aspect.
And then for the data scientist with
>> BitFusion. >> BitFusion,
we really need to say, "Okay, you want to run these workloads,
"but geez, you're paying really a lot of money
"for these expensive, isolated devices.
"And you could get more value by kind of grouping them up,
"and making sure that they're used, kind of,
"in aggregate, right?"
>> So there's more leverage on the data science side,
so if I'm say, hiring someone, (mumbles)
I have more to work with, with BitFusion.
>> Exactly, essentially, it's the same story.
They don't need to change their applications,
their frameworks, their models.
They use the same CUDA interface, which is the
GPU interface for the GPU compute.
>> So let's talk about data, so data scientists, you know,
they always complain that most of their time
is spent wrangling data, that's their, you know, bugaboo,
and then there's a collaboration between data scientists
and developers, which probably doesn't happen enough.
What are you seeing in terms of the trends,
from the data science role,
and can you help solve some of those problems?
>> Well, what we are out to solve, is really
access to the infrastructure for them.
Easy access to the infrastructure
and their software stack, and the way to get there,
is to make the data engineers, that serve
these data scientists and application administrators,
that serve these data scientists, to get easy access
to the infrastructure they need to provide the software.
And that's where vSphere eventually comes in.
So it's not necessarily a direct relationship
with the end users, it's more enabling
the entire organization that actually serves
these end users and let them use as much
infrastructure as they can, as fast as possible.
>> And you're partners in that end user organization,
yeah, that's the buffer.
>> Guys, last question, share what's the plans are,
what's next, what's your goals for the next
six to 12 months, obviously you got the acquisition
under your belt, native in vSphere,
lot of other cool things, I mean, obviously.
>> I could tell you about customers,
and maybe you can talk about product.
From a customer perspective, you know,
we want to engage in proof of concepts.
So we want to bring them in, let them test out the software.
It already works with vSphere, so I'll be running
with multiple proof of concepts across the globe.
>> John: Any use case, or are there use case, or what's.
>> Yeah, I mean, it's pretty simple at the moment.
It seems to be most people that are using GPU's
around ML, we have a great demo down on the floor,
that shows people tryin' to run Inception three
or Resident 50, and then how can we actually help
those VM's that are running that.
So that's going to be my focus for the next six to 12 months.
>> All right, you hear it.
You got some use cases, come over here
and bring 'em up to Mike.
Ziv, product? >> And for the product
perspective, I mean, obviously we acquired
BitFusion in an early stage.
The technology works well.
It works well enough to be productized.
However, VMware and vSphere has very high
enterprise software standards, in terms of security,
and management, and governance, all this capabilities,
so that's going to be our focus for the next, you know,
even almost a year, to make sure that we bring it up
to a level where we can confidently provide it
and sell it as a product to our customer.
>> Yeah, you got an engineering high bar there.
>> Ziv: Yep. >> Mike: Absolutely.
>> Awesome, guys, thanks so much for comin' in theCUBE,
appreciate the update. >> Ziv: Thank you very much.
>> VMworld coverage, breakin' it down, 2019,
this is theCUBE, I'm John Furrier, Dave Vellante,
thanks for watching, be back with more,
after this short break.
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