>> Narrator: Live from Washington D.C. it's the Cube
covering .Next Conference, brought to you by Nutanix.
>> Welcome back to D.C., everybody, this is the Cube,
the leader in live tech coverage.
This is our special coverage and presentation
of Nutanix NextConf 2017.
This is the third U.S. conference that the Cube has done
of Nutanix .NEXT.
Nicolaus Radford is here as a Senior Vice President
of Engineering and the CTO at Houston Mechatronics,
wait till you hear what these guys do,
and Satyam Vaghani, who is the V.P. of technology
at Nutanix.
Gentlemen, welcome to The Cube.
>> Glad to be here.
>> How you doing?
>> Let's get right into it.
>> Yep.
>> We're talking IOT, we're talking edge, you guys do
some pretty interesting stuff.
Tell us about the company.
>> Well we're a robotics as a service company primarily,
but we do some intelligent automation
and intelligent drilling, in the IOT space,
so it's pretty exciting and dynamic area, actually, and...
Just imagine taking a bunch of different systems
that haven't typically talked together before,
and we've kind of glued them all together.
And one of the big oil field services companies
was attracted to our sort of thinking in this area,
and have taken some, given us some work, and you know,
we're taking and running with it.
>> Can you just explain what robotics as a service means?
>> Well usually, you know, you can kind of break this down
in a couple different ways, you know, there's a lot
of people out there that sell robots and it's kind of
a thin business, right?
You know, you might sell a robot and then the people you
sell it to use it and make a bunch of money off of it,
and then you're stuck trying to find a new customer
to sell a robot to.
But if you consume the robots, so to speak, that you build,
and then use them as a service, it's a much more
lucrative position to have.
And so we do technology systems development for partners,
and then we also operate that robot in the field for them.
So it's a good residual, pull-through revenue stream for us.
>> So, Satyam, the industrial technology world
and the information technology worlds
are coming crashing together.
>> Satyam: Absolutely.
>> IT and OT, Nutanix has been talking about the edge
more and more, I mean, if you're not talking about the edge,
you're not in the game, but give us an update
on your strategy with regard to the edge, and really,
your thinking about companies like Nick's.
>> I know, great question.
I guess I have so much to tell.
>> Host: Yeah.
>> Nick: Make it edgy.
>> Make it edgy.
>> Host: Start wherever you like.
>> But yeah, I guess we kind of, sort of,
naturally fell into it because we saw that the
future of computing might be more edgy, if you will,
than we think, as you know, right now we are spending a lot
of time and energy worrying about clouds,
you know, private cloud, public clouds,
how to consolidate them.
But then at the same time we are seeing that there are
so many of these sensors being deployed in the world,
just this year it's going to be roughly
eight and a half billion sensors, if you count consumer
and industrial RD together.
By 2020 it's going to be 20 billion sensors.
And so all the data that these sensors are going to
generate is going to be processed in real time,
closer to where the sensors cleared the data,
as opposed to slightly farther away, which is in the cloud.
Of course, the cloud remains relevant, as the cloud is
going to do much more longer term processing,
and the edge is going to do real time processing
on the data.
>> Host: Alright.
>> And so, in that sense, we saw that as a natural step two
of the hyperconvergence yearning, is if you think about
step one of hyperconvergences, the convergence of
computer storage and network resources inside a data center,
step two is the convergence of the edge and the cloud
into one fabric, one OS, if you will.
>> Yeah, I wonder if you could help us unpack that a little,
'cause we saw, kind of, public cloud pulled at the
data center for years and now the edge is pulling
at the cloud.
>> Satyam: Pulling it back out.
>> So the edge is different from the data center
so most people think of Nutanix, you know, I'm either
living in a data center or maybe some service provider,
so, you know, different form factor, I know there are some
announcements Nutanix made to kind of get to robo-cases.
Is that the same for the edge?
>> Yeah, different form factors, 'cause, you know,
some of this hardware needs to be regulized, you know,
it's on oil rigs, or drones, or military vehicles,
and so on, but also slightly different and evolving
storage stack because now the problem of deploying
applications at the edge is about deliverers having to
write code, and not having to worry about how the code
runs on the edge.
Because as soon as they have to worry about that,
the deliverers become operators, infrastructure operators,
and so this one will also have a slightly higher level of
application stack, you know, machine learning services,
or analytic services at the edge so that applications can
directly consume those high level services, as opposed to
the lower level, you know.
>> Which actually that's, it's really intriguing because
as part of our robotics as a service side of our business
we have a pipe inspection system that we're going to be
deploying in quantity, and so what you...
That's a type of edge device, right?
That's, I mean robots are really nothing more
than fancy data collection systems, right?
And so we put them out into the world to collect the data,
but then what do you do with that data?
How is it stored?
What sort of of post analytics are you doing on that data
to then feed forward back to the intelligence at the edge
so that they can make decisions better, right?
So when you have our robot that we call PEARL,
the pipe inspection robot, you'll actually see a demo of it
later, fingers crossed.
As it's traveling through the pipe
it's collecting all this data, right?
So but all of the runs prior to that, it's afforded all of
that knowledge on the decisions it's making
right then and there, right?
Because we've done all this back learning, if you will,
on what deformities look like, which increases the quality
of our inspections, and so then if you start looking at
a ubiquitous deployment of these type of assets,
where you might have 10, 20, 30 in the field,
that's a massive amount of data that you're collecting
right there, right where the sensor's being taken.
The processing of that data is determining
whether the robot stops and maybe observes
a little bit more, but then it's all being shipped back
at a later date to the cloud for further analytics,
then to feed forward in the next operation
to perform that better.
So it's this feedback process of learning between
the application that's actually happening in real time,
and the later-on analytics that will occur.
>> So let's stay on the data for a moment, because it is
all about the data.
Is it correct that much of the data in your world
is analog data that you're able to now
convert into digital, or ...?
>> Satyam: Yeah, so I mean.
>> Or are you already there?
>> At the end of the day you're trying to take
an analog measurement of some type, right?
We live in an analog world, and if I'm trying to measure
the thickness of a pipe I'm using a transducer.
>> Host: Yeah.
>> That by nature is typically an analog device.
I can then digitize that information, and that's how
I send it over in, you know, communication streams
and whatnot, and of course it's stored digitally, but at the
end of the day, you know, we're taking analog information,
doing data processing on that, looking at what it means
in the activity that we're trying to do:
measuring the thickness of a tube.
And then we ship the data back at a more convenient time
when we have more bandwidth back to the cloud for all of
the deep learning, deep type of analytics.
>> Nicolaus, could you kind of explain that,
kind of your stack or your flows.
>> Nick: I was hoping you were going to explain it to me.
>> Because, how did you get to Nutanix?
What goes into what public cloud?
What services are you using there? If, whatever you could
share would be kind of good to understand.
>> We're involved with Nutanix on our rig automation side.
And so we use their storage,
you know, we use their storage in the way
that they've created an excellent way of doing that.
And so that's primarily how we interface with them and one
of our big oil and gas partners is a huge client of theirs.
And so that's our primary relationship with them.
In fact I sent Rich a picture of a Nutanix box that we
just recently installed in our server room, and I was like,
giving the thumbs up, and I was like,
"Hey buddy!"You know.
>> Alright, and public cloud, you know,
do you have a specific one you're using?
Are you using many clouds?
>> Nick: No, no, no, no, I mean.
>> For the processing and data you say some of it goes
to the public cloud, though, it just...
>> Yeah, no, I mean, it's more under the local area.
>> Nick: I mean this is the stuff we're using intern...
I mean this is...
The security requirements that we have is...
>> Host: So your cloud isn't on PremCloud.
>> Yeah, exactly.
>> Okay. How much of the data, I mean,
I know it can't be precise but if you think about all
this real-time decision-making that you're doing,
how much of the data is actually going to go back
to the cloud?
I mean, this even rough percentage terms. I want opinions.
>> Well we'd like to send it all back, right?
>> Host: Hundred percent.
It's just what you don't send then and there, right?
There might be a little stream of it coming back off of,
let's say, our pipe inspection robot, but at some point,
though, you want to take that, download everything,
store backup, I mean it's and all the big data analytic
techniques and analyze it, I mean, you know.
>> So you expect you want to persist
the majority of the data, and you ultimately will not
do that at the edge.
You'll ultimately have to get it back up to the cloud.
>> Yeah, absolutely, yeah. That's the way we see it.
>> Host: You're going to use the Chevy truck...
>> Nick: Unless you have a different opinion.
>> Use the Chevy truck access method to get it there or what?
Go ahead, please.
>> I have a different opinion, kind of sort of similar
principal but a different opinion which is, you know,
in terms of volume, a very small fraction of the data
is going to make it to the cloud.
But in terms of intelligence, you know, almost hundred
percent of the intelligence is going to make it,
but it is how the edge participates in
reducing the volume of the data.
And just again to give you numbers, you know,
in the year 2020 it's projected, and this is I think
the Cisco Global Cloud Index, they project that
roughly 600 zetabytes of data is going to be
created on the edge.
And the public and private cloud combined in that year
is going to roughly witness 15 zetabytes of data.
And so the question is where did the rest of it go?
And I think my answer is, if you look at, for example,
a smart building, or a robot inspection, that kind of
scenario, the robot's taking pictures or video streams,
which is ridiculously rich data, and changing it into
time series, database of whether some anomaly was detected
or not, you know, look at a smart airport example.
We're going to take a lot of surveillance data and change
it into whether a person of interest was detected or not,
or did you see a white van that you're looking for?
And so really the information, the volume of information
goes down but the refinement goes up.
Is, you know, the cloud really is interested to know,
because, presumably in the smart airport example,
you have somebody sitting at a dashboard monitoring
all California airports looking for a person of interest,
and all they are worried about is whether somebody
showed up or not, and so it's the metadata that shows up,
as opposed to the raw data.
>> So the needles go back.
>> Satyam: Needles go back, exactly.
That's a good way to put it.
Not the haystack.
>> Yeah, Nicolaus, one of the things we look at IOTs,
it's really created a much larger, I mean,
orders of magnitude more surface area for security attacks.
Is that something that concerns you, your clients,
you know, how can security fit in?
>> It concerns our clients very much so.
Absolutely, in fact, one of the first questions out of
everybody's mouth is,
"How are you going to handle security?"
So it's paramount and very important.
Absolutely.
>> Alright, Satyam, how are you going to solve that?
>> Satyam: The running joke is Blockchain, and you know,
people stop asking questions as soon as you say Blockchain.
But no, it's an unbelievable problem.
In fact, something that probably we haven't, you know,
kind of solved in generations.
We are struggling with cloud security, with cyber security,
and now we are talking about a number of devices that's
going to be three orders of magnitude more than the
number of servers that run in the cloud today.
>> What about, one of the things we haven't talked about
is connectivity.
How do you connect the edge?
Is it just all wireless?
>> Yeah, I mean, the ubiquity of the wireless networking
systems are very high right now, I mean it's all...
>> Host: How's the quality?
>> Ah, you know, good.
>> Host: It's like wireless.
>> It's like wireless.
>> Host: But is it a headwind?
>> No it's actually, it's, you know, one of the issues that
we're having with honestly, our pipe inspection
demonstration today is just being flooded.
There's 4,000 people in the main hall, right?
And so there's all this wireless activity and sometimes,
you know, our pipe inspection robot doesn't know who it
should be quite listening to, and I mean, you know, you
go to a concert, and you look like you might head to a
Metallica concert here and there.
>> I do.
>> And, you know, sometimes you can't even send a text
because there's just so many people and trying to connect
and it's a big deal and so...
>> Host: So it's a challenge for you.
>> Nick: Absolutely it's a challenge.
>> Excellent.
>> I've seen some vendors, they are deploying
special networks, right?
They are deploying low bandwidth networks.
Verizon's doing it I think, AT&T is doing it.
>> Host: Yeah, okay, no pineapples.
>> No pineapples hopefully
>> That's like the most recent silicon valley episode, right?
>> Alright gentlemen, listen, thanks very much.
I really appreciate you coming on the Cube.
>> Satyam: Thanks for having us.
>> Great story and news cases, it's always a pleasure.
>> Nick: Thanks
>> [Second Interviewer] Good luck with the demo.
>> Alright, keep right there everybody we'll be back with
our next guests.
This is the Cube, we're live from Nutanix NextConf.
Be right back.
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