>> Voiceover: Live from
Las Vegas, it's theCUBE,
covering Discover 2016, Las Vegas.
Brought to you by Hewlett
Packard Enterprise.
Now, here are your hosts,
John Furrier and Dave Vellante.
>> Okay, welcome back everyone.
We are here live in Las Vegas
for SiliconANGLE Media's theCUBE.
It's our flagship program,
we go out to the events to extract
the signal from the noise,
we're your exclusive coverage
of HP Enterprise, Discover 2016,
I'm John Furrier with my
co-host, Dave Vellante,
extracting the signals from the noise
with two great guests,
Dr. Tom Bradicich, VP and General Manager
of the servers and IoT systems,
and Eric Starkloff,
the EVP of Global Sales and Marketing
at National Instruments,
welcome back to theCUBE.
>> Thank you.
>> John: Welcome for the
first time Cube alumni,
welcome to theCUBE.
>> Thank you.
>> So we are seeing
a real interesting historic
announcement from HP,
because not only is
there an IoT announcement
this morning that you
are the architect of,
but the twist that you're taking with IoT,
is very cutting edge,
kind of like I just had Google IO,
and at these big
conferences they always have
some sort of sexy demo,
that's to kind of show
the customers the future,
like AI, or you know,
Oculus Rift goggles as the
future of their application,
but you actually don't have
something that's futuristic,
it's reality,
you have a new product,
around IoT, at the Edge,
Edgeline, the announcements
are all online.
Tom, but you guys did something different.
And Eric's here for a reason,
we'll get to that in a second,
but the announcement
represents a significant bet.
That you're making, and HP's making,
on the future of IoT.
Please share the vision,
and the importance of this event.
>> Well thank you,
and it's great to be
back here with you guys.
We've looked around and
we could not find anything
that existed today, if you will,
to satisfy the needs of this
industry and our customers.
So we had to create
not only a new product,
but a new product category.
A category of products
that didn't exist before,
and the new Edgeline1000,
and the Edgeline4000
are the first entrance
into this new product category.
Now, what's a new product category?
Well, whoever invented
the first automobile,
there was not a category of automobiles.
When the first automobile was invented,
it created a new product
category called automobiles,
and today everybody has a
new entry into that as well.
So we're creating a new product category,
called converged IoT systems.
Converged IoT systems are needed
to deliver the real-time insights,
real-time response,
and advance the business outcomes,
or the engineering outcomes,
or the scientific outcomes,
depending on the situation
of our customers.
They're needed to do that.
Now when you have a name, converged,
that means somewhat,
a synonym is integration,
what did we integrate?
Now, I want to tell you
the three major things we integrated,
one of which comes from Eric,
and the fine National Instruments company,
that makes this technology
that we actually put in,
to the single box.
And I can't wait to
tell you more about it,
but that's what we did,
a new product category,
not just two new products.
>> So, you guys are bringing
two industries together,
again, that's not only
just point technologies
or platforms, in tooling,
you're bringing disparate
kind of players together.
>> Yes.
>> But it's not just a partnership,
it's not like shaking hands
and doing a strategic partnership,
so there's real meat on the bone here.
Eric, talk about one, the importance
of this integration of
two industries, basically,
coming together,
converged category if
you will, or industry,
and what specifically is in
the box or in the technology.
>> Yeah, I think you hit it exactly right.
I mean, everyone talks
about the convergence of OT,
or operational technology,
and IT.
And we're actually doing it together.
I represent the OT side,
National Instruments is a global leader.
>> John: OT, it means,
just for the audience?
>> Operational Technology,
it's basically industrial equipment,
measurement equipment,
the thing that is connected
to the real world.
Taking data and controlling the thing
that is in the internet of things,
or the industrial internet
of things as we play.
And we've been doing internet of...
>> And IT is Information Technologies,
we know what that is, OT is...
>> I figured that one you knew,
OT is Operational Technology.
We've been doing IoT
before it was a buzzword.
Doing measurement and control systems
on industrial equipment.
So when we say we're making it real,
this Edgeline system actually incorporates
in National Instruments technology,
on an industry standard called PXI.
And it is a measurement
and control standard
that's ubiquitous in the industry,
and it's used to connect
to the real world,
to connect to sensors,
actuators,
to take in image data,
and temperature data
and all of those things,
to instrument the world,
and take in huge amounts of analog data,
and then apply the compute
power of an Edgeline system
onto that application.
>> We don't talk a lot about
analog data in the IT world.
>> Yeah.
>> Why is analog data so important,
I mean it's prevalent
obviously in your world.
Talk a little bit more about that.
>> It's the largest source
of data in the world,
as Tom says it's the oldest as well.
Analog, of course if you think about it,
the analog world is literally infinite.
And it's only limited by how
many things we want to measure,
and how fast we measure them.
And the trend in technology
is more measurement points and faster.
Let me give you a couple of examples
of the world we live in.
Our customers have
acquired over the years,
approximately 22 exabytes of data.
We don't deal with exabytes that often,
I'll give an analogy.
It's streaming high definition video,
continuously,
for a million years,
produces 22 exabytes of data.
Customers like CERN, that do
the Large Hadron Collider,
they're a customer of ours,
they take huge amounts of analog data.
Every time they do an experiment,
it's the equivalent of 14 million images,
photographs,
that they take per second.
They create 25 petabytes
of data each year.
The importance of this and
the importance of Edgeline,
and we'll get into this some,
is that when you have
that quantity of data,
you need to push processing,
and compute technology,
towards the edge.
For two main reasons.
One, is the quantity of data,
doesn't lend itself, or
takes up too much bandwidth,
to be streaming all of it back to central,
to cloud, or centralized
storage locations.
The other one that's very,
very important is latency.
In the applications that we serve,
you often need to make a
decision in microseconds.
And that means that the
processing needs to be done,
literally the speed of
light is a limiting factor,
the processing must be done on the edge,
at the thing itself.
>> So basically you need
a data center at the edge.
>> A great way to say it.
>> A great way to say it.
And this data, or big analog
data as we love to call it,
is things like particulates,
motion, acceleration, voltage, light,
sound, location,
such as GPS,
as well as many other things
like vibration and moisture.
That is the data that
is pent up in things.
In the internet of things.
And Eric's company National Instruments,
can extract that data,
digitize it, make it ones and zeroes,
and put it into the IT world
where we can compute it
and gain these insights and actions.
So we really have a seminal moment here.
We really have the OT
industry represented by Eric,
connecting with the IT industry,
in the same box,
literally in the same product in the box,
not just a partnership as you pointed out.
In fact it's quite a moment,
I think we should have a photo op here,
shaking hands,
two industries coming together.
>> So you talk about this
new product category.
What are the parameters
of a new product category?
You gave an example of
an automobile, okay,
but nobody had ever seen one before,
but now you're bringing together
sort of two worlds.
What defines the parameters
of a product category,
such that it warrants a new category?
>> Well, in general,
never been done before,
and accomplishes something
that's not been done before,
so that would be more general.
But very specifically,
this new product, EL1000 and EL4000,
creates a new product category
because this is an industry first.
Never before have we
taken data acquisition
and capture technology
from National Instruments,
and data control technology
from National Instruments,
put that in the same box as deep compute.
Deep x86 compute.
What do I mean by deep?
64 xeon cores.
As you said, a piece of the data center.
But that's not all we converged.
We took Enterprise Class
systems management,
something that HP has done
very well for many, many years.
We've taken the Hewlett
Packard Enterprise iLo
lights-out technology,
converged that as well.
In addition we put storage in there.
10s of terabytes of
storage can be at the edge.
So by this combination of things,
that did exist before,
the elements of course,
by that combination of things,
we've created this new product category.
>> And is there a data
store out there as well?
A database?
>> Oh yes, now since we have,
this is the profundity of what I said,
lies in the fact that because
we have so many cores,
so close to the acquisition of the data,
from National Instruments,
we can run virtually any application
that runs on an x86 server.
So, and I'm not exaggerating,
thousands.
Thousands of databases.
Machine learning.
Manageability, insight,
visualization of data.
Data capture tools,
that all run on servers and workstations,
now run at the edge.
Again, that's never been done before,
in the sense that at the edge today,
are very weak processing.
Very weak, and you can't
just run an unmodified app,
at that level.
>> And in terms of the value chain,
National Instruments is a supplier
to this new product category?
Is that the right way to think about it?
>> An ingredient,
a solution ingredient but
just like we are, number one,
but we are both reselling
the product together.
>> Dave: Okay.
>> So we've jointly, collaboratively,
developed this together.
>> So it's engineers and
engineers getting together,
building the product.
>> Exactly.
His engineers, mine, we
worked extremely close,
and produced this beauty.
>> We had a conversation yesterday,
argument about the iPhone,
I was saying
hey, this was a game-changing
category, if you will,
because it was a computer
that had software
that could make phone calls.
Versus the other guys, who had a phone,
that could do text messages and do email.
With a browser.
>> Tom: With that converged product.
>> So this would be similar, if I may,
and you can correct me if I'm wrong,
I want you to correct me and clarify,
what you're saying is,
you guys essentially looked
at the edge differently,
saying let's build the data center,
at the edge, in theory or in concept here,
in a little concept,
but in theory,
the power of a data center,
that happens to do edge stuff.
>> Tom: That's right.
>> Is that accurate?
>> I think it's very accurate.
Let me make a point and let you respond.
>> Okay.
>> Neapolitan ice cream has three flavors.
Chocolate, vanilla, strawberry,
all in one box.
That's what we did with this Edgeline.
What's the value of that?
Well, you can carry it, you can store it,
you can serve it more conveniently,
with everything together.
You could have separate boxes,
of chocolate, vanilla, and strawberry,
that existed, right,
but coming together,
that convergence is key.
We did that with deep compute,
with data capture and control,
and then systems management
and Enterprise class device
and systems management.
And I'd like to explain
why this is a product.
Why would you use this product,
you know, as well.
Before I continue though,
I want to get to the seven
reasons why you would use this.
And we'll go fast.
But seven reasons why.
But would you like to add anything
about the definition of the conversion?
>> Yeah, I was going to just
give a little perspective,
from an OT and an industrial
OT kind of perspective.
This world has generally
lived in a silo away from IT.
>> Mm-hmm.
>> It's been proprietary
networking standards,
not been connected to the
rest of the enterprise.
That's the huge opportunity
when we talk about the IoT,
or the industrial IT,
is connecting that to the
rest of the enterprise.
Let me give you an example.
One of our customers is Duke Energy.
They've implemented an
online monitoring system
for all of their power generation plants.
They have 2,000 of our
devices called CompactRIO,
that connect to 30,000 sensors
across all of their generation plants,
getting real-time monitoring,
predictive analytics,
predictive failure,
and it needs to have
processing close to the edge,
that latency issue I mentioned?
They need to basically be
able to do deep processing
and potentially shut down a machine.
Immediately if it's an a
condition that warrants so.
The importance here is that
as those things are brought online,
into IT infrastructure,
the importance of deep compute,
and the importance of the
security and the capability
that HPE has,
becomes critical to our customers
in the industrial internet of things.
>> Well, I want to push back
and just kind of play devil's advocate,
and kind of poke holes in your thesis,
if I can.
>> Eric: Sure thing.
>> So you got the probes
and all the sensors
and all the analog stuff
that's been going on
for you know, years and years,
powering and instrumentation.
You've got the box.
So okay, I'm a customer.
I have other stuff I might put in there,
so I don't want to just
rely on just your two stuff.
Your technologies.
So how do you deal with the corner case
of I might have my own different devices,
it's connected through IT,
is that just a requirement on your end,
or is that...
How do you deal with
the multi-vendor thing?
>> It has to be an open standard.
And there's two elements of open standard
in this product,
I'll let Tom come in on one,
but one of them is,
the actual IO standard,
that connects to the physical world,
we said it's something called PXI.
National Instruments is a major vendor
within this PXI market,
but it is an open standard,
there are 70 different vendors,
thousands of products,
so that part of it in connecting
to the physical world,
is built on an open standard,
and the rest of the platform is as well.
>> Indeed.
Can I go back to your
metaphor of the smartphone
that you held up?
There are times even today,
but it's getting less and less,
that people still carry around a camera.
Or a second phone.
Or a music player.
Or the Beats headphones, et cetera, right?
There's still time for that.
So to answer your question,
it's not a replacement for everything.
But very frankly, the vision is over time,
just like the smartphone,
and the app store,
more and more will get
converged into this platform.
So it's an introduction of a platform,
we've done the inaugural convergence
of the aforementioned
data capture, high compute,
management, storage,
and we'll continue to add more and more,
again, just like the smartphone analogy.
And there will still be
peripheral solutions around,
to address your point.
>> But your multi-vendor
strategy if I get this right,
doesn't prevent you,
doesn't foreclose the
customer's benefits in any way,
so they connect through IT,
they're connected into
the box and benefits.
You changed, they're just
not converged inside the box.
>> At this point.
But I'm getting calls regularly,
and you may too, Eric,
of other vendors saying, I want in.
I would like to relate that
conceptually to the app store.
Third party apps are being
produced all the time
that go onto this platform.
And it's pretty exciting.
>> And before you get to
your seven killer attributes,
what's the business model?
So you guys have jointly
engineered this product,
you're jointly selling
it through your channels,
>> Eric: Yes.
>> If you have a large
customer like GE for example,
who just sort of made
the public commitment
to HPE infrastructure.
How will you guys "split
the booty," so to speak?
(laughter)
>> Well we are actually,
as Tom said we are doing reselling,
we'll be reselling this
through our channel,
but I think one of the key things
is bringing together our mutual expertise.
Because when we talk about
convergence of OT and IT,
it's also bringing together
the engineering expertise
of our two companies.
We really understand acquiring
data from the real world,
controlling industrial systems.
HPE is the world leader in IT technology.
And so, we'll be working together
and mutually with customers
to bring those two perspectives together,
and we see huge opportunity in that.
>> Yeah, okay so it's engineering.
You guys are primarily a
channel company anyway, so.
>> Actually, I can make
it frankly real simple,
knowing that if we go back
to the Neapolitan ice cream,
and we reference National
Instruments as chocolate,
they have all the contact
with the chocolate vendor,
the chocolate customers if you will.
We have all the vanilla.
So we can go in and then
pull each other that way,
and then go in and pull this way, right?
So that's one way as this market develops.
And that's going to very
powerful because indeed,
the more we talk about when
it used to be separated,
before today,
the more we're expressing
that also separate customers.
That the other guy does not know.
And that's the key here
in this relationship.
>> So talk about the trend
we're hearing here at the show,
I mean it's been around
in IT for a long time.
But more now with the agility,
the DevOps and cloud and everything.
End to end management.
Because that seems to be the table stakes.
Do you address any of
that in the announcement,
is it part, does it fit right in?
>> Absolutely, because,
when we take, and we shift left,
this is one of our monikers,
we shift left.
The data center and the
cloud is on the right,
and we're shifting left the
data center class capabilities,
out to the edge.
That's why we call it shift left.
And we meet,
our partner National
Instruments is already there,
and an expert and a leader.
As we shift left,
we're also shifting with it,
the manageability capabilities
and the software that runs the management.
Whether it be infrastructure,
I mean I can do virtualization
at the edge now,
with a very popular
virtualization package,
I can do remote desktops
like the Citrix company,
the VMware company,
these technologies and databases
that come from our own Vertica database,
that come from PTC,
a great partner,
with again, operations technology.
Things that were running
already in the data center now,
get to run there.
>> So you bring the benefit to the IT guy,
out to the edge, to management,
and Eric, you get the benefit
of connecting into IT,
to bring that data benefits
into the business processes.
>> Exactly.
And as the industrial
internet of things scales
to billions of machines
that have monitoring,
and online monitoring capability,
that's critical.
Right, it has to be manageable.
You have to be able to
have these IT capabilities
in order to manage such
a diverse set of assets.
>> Well, the big data group
can basically validate that,
and the whole big data thesis is,
moving data where it needs to be,
and having data about
physical analog stuff,
assets,
can come in and surface more insight.
>> Exactly. The biggest data of all.
>> And vice versa.
>> Yup.
>> All right, we've got to
get to the significant seven,
we only have a few minutes left.
>> All right. Oh yeah.
>> Hit us.
>> Yeah, yeah.
And we're cliffhanging here on that one.
But let me go through them real quick.
So the question is,
why wouldn't I just, you know,
rudimentary collect the data,
do some rudimentary analytics,
send it all up to the cloud.
In fact you hear that today a lot, pop-up.
Censored cloud, censored cloud.
Who doesn't have a cloud today?
Every time you turn around,
somebody's got a cloud,
please send me all your data.
We do that, and we do that well.
We have Helion,
we have the Microsoft Azure IoT cloud,
we do that well.
But my point is, there's
a world out there.
And it can be as high as 40
to 50 percent of the market,
IDC is quoted as suggesting 40 percent
of the data collected at the edge,
by for example National Instruments,
will be processed at the edge.
Not sent,
necessarily back to the
data center or cloud, okay.
With that background,
there are seven reasons
to not send all the data,
back to the cloud.
That doesn't mean you
can't or you shouldn't,
it just means you don't have to.
There are seven reasons
to compute at the edge.
With an Edgeline system.
Ready?
>> Dave: Ready.
>> We're going to go fast.
And there'll be a test on this, so.
>> I'm writing it down.
>> Number one is latency, Eric
already talked about that.
How fast do you want your turnaround time?
How fast would you like to know
your asset's going to catch on fire?
How fast would you like to know
when the future autonomous car,
that there's a little
girl playing in the road,
as opposed to a plastic bag
being blown against the road,
and are you going to rely on the latency
of going all the way
to the cloud and back,
which by the way may be dropped,
it's not only slow,
but you ever try to make
a phone call recently,
and it not work, right?
So you get that point.
So that's latency one.
You need to time to
incite, time to response.
Number one of seven, I'll go real quick.
Number two of seven is bandwidth.
If you're going to send
all this big analog data,
the oldest, the fastest,
and the biggest of all big data,
all back, you need tremendous bandwidth.
And sometimes it doesn't exist,
or, as some of our
mutual customers tell us,
it exists but I don't want to use it all
for edge data coming back.
That's two of seven.
Three of seven is cost.
If you're going to use the bandwidth,
you've got to pay for it.
Even if you have money
to pay for it,
you might not want to,
so again that's three, let's go to four.
(coughs)
Excuse me.
Number four of seven is threats.
If you're going to send
all the data across sites,
you have threats.
It doesn't mean we can't
handle the threats,
in fact we have the best
security in the industry,
with our Aruba security,
ClearPass,
we have ArcSight, we have Volt.
We have several things.
But the point is, again,
it just exposes it to more threats.
I've had customers say,
we don't want it exposed.
Anyway, that's four.
Let's move on to five,
is duplication.
If you're going to collect all the data,
and then send it all back,
you're going to duplicate at the edge,
you're going to duplicate not all things,
but some things, both.
All right, so duplication.
And here we're coming up to number six.
Number six is corruption.
Not hostile corruption,
but just package dropped.
Data gets corrupt.
The longer you have it in motion,
e.g. back to the cloud, right,
the longer it is as well.
So you have corruption, you can avoid.
And number three, I'm sorry, number seven,
here we go with number seven.
Not to send all the data back,
is what we call policies and compliance,
geo-fencing,
I've had a customer say,
I am not allowed to send all
the data to these data centers
or to my data scientists,
because I can't leave country borders.
I can't go over the ocean, as well.
Now again,
all these seven,
create a market for us,
so we can solve these seven,
or at least significantly
ameliorate the issues
by computing at the edge
with the Edgeline systems.
>> Great.
Eric, I want to get your
final thoughts here,
and as we wind down the segment.
You're from the ops
side, ops technologies,
this is your world,
it's not new to you, this edge stuff,
it's been there,
been there, done that,
it is IoT for you, right?
So you've seen the
evolution of your industry.
For the folks that are in IT,
that HP is going to be approaching
with this new category,
and this new shift left,
what does it mean?
Share your color behind,
and reasoning and reality check,
on the viability.
>> Sure.
>> And relevance.
>> Yeah, I think that there
are some significant things
that are driving this change.
The rise of software capability,
connecting these previously siloed,
unconnected assets to
the rest of the world,
is a fundamental shift.
And the cost point of
acquisition technology
has come down the point
where we literally have a better,
more compelling economic case to be made,
for the online monitoring of more and more
machine-type data.
That example I gave of Duke Energy?
Ten years ago they
evaluated online monitoring,
and it wasn't economical,
to implement that type of a system.
Today it is,
and it's actually very, very
compelling to their business,
in terms of scheduled downtime,
maintenance cost,
it's a compelling value proposition.
And the final one is
as we deliver more analytics
capability to the edge,
I believe that's going to create
opportunity that we don't even really,
completely envision yet.
And this deep computing,
that the Edgeline systems have,
is going to enable us to do
an analysis at the edge,
that we've previously never done.
And I think that's going to
create whole new opportunities.
>> So based on your expert opinion,
talk to the IT guys watching,
viability, and ability to do this,
what's the...
Because some people are a little nervous,
will the parachute open?
I mean, it's a huge
endeavor for an IT company
to instrument the edge of their business,
it's the cutting,
bleeding edge, literally.
What's the viability, the outcome,
is it possible?
>> It's here now.
It is here now, I mean this
announcement kind of codifies it
in a new product category,
but it's here now,
and it's inevitable.
>> Final word, your thoughts.
>> Tom: I agree.
>> Proud papa, you're
like a proud papa now,
you got your baby out there.
>> It's great. But the more I tell you
how wonderful the EL1000, EL4000 is,
it's like my mother calling me handsome.
Therefore I want to point
the audience to Flowserve.
F-L-O-W,
S-E-R-V-E.
They're one of our
customers using Edgeline,
and National Instruments equipment,
so you can find that video online as well.
They'll tell us about
really the value here,
and it's really powerful
to hear from a customer.
>> John: And availability is...
>> Right now we have EL1000s and EL4000s
in the hands of our customers,
doing evaluations,
at the end of the summer...
>> John: Pre-announcement,
not general availability.
>> Right, general availability is not yet,
but we'll have that at
the end of the summer,
and we can do limited
availability as we call it,
depending on the demand,
and how we roll it out, so.
>> How big the customer base is,
in relevance to the...
Now, is this the old boon shot box,
just a quick final question.
>> Tom: It is not, no.
>> Really?
>> We are leveraging
some high-performance,
low-power technology,
that Intel has just announced,
I'd like to shout out to that partner.
They just announced and launched...
Diane Bryant did her keynote
to launch the new xeon,
E3, low-power high-performance xeon,
and it was streamed,
her keynote,
on the Edgeline compute engine.
That's actually going into the Edgeline,
that compute blade is
going into the Edgeline.
She streamed with it,
we're pretty excited about that as well.
>> Tom and Eric,
thanks so much for sharing the big news,
and of course congratulations,
new category.
>> Thank you.
>> Let's see how this plays
out, we'll be watching,
got to get the draft picks in
for this new sports
league, we're calling it,
like IoT, the edge,
of course we're theCUBE,
we're living at the edge,
all the time, we're at
the edge of HPE Discovery.
Have one more day tomorrow,
but again, three days of coverage.
You're watching theCUBE,
I'm John Furrier with Dave Vellante,
we'll be right back.
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