>> Live from Las Vegas, it's the CUBE,
covering DELL Technologies World 2019,
brought to you by DELL Technologies
and its ecosystem partners.
>> Welcome back to DELL Technologies World 2019
here in Las Vegas, I'm Stu Miniman with my co-host,
Dave Valontay, talking multi-cloud,
talking about DELL Technologies
and all the pieces of the environment,
and we're going to drill in some
to some of the storage environment.
Happy to welcome back to the program, Sudhir Srinivasan,
who's the senior vice president and CTO
of the storage division of Dell EMC.
Sudhir, thanks to much for joining us.
>> Thanks for having me Stu.
>> Alright, so as I said, day one,
a lot of the vision, digital transformation, multi-cloud,
with Thottu Nadel up on stage, got a little bit about.
Today got back into the products.
Everything, you know, such a broad portfolio.
Everything from the Latitude business devices,
through of course many updates in the storage world.
Been diggin' in with a number of your team.
Give us a little flavor as to what you've been working on.
I know as a CTO you can't have a favorite family,
but some of the things
you and the team are really proud of to unveil.
>> Absolutely, thanks.
It's been a big day as well,
and I would say a big year for us.
So we've shown incredible growth in our business
in the last four quarters,
taking share every one of those four quarters,
so just a phenomenal year.
A lot of that has to do with
just the strength of the portfolio.
We've been investing a lot in innovation in the portfolio
so I think the biggest one today that I'm really proud of
is the Unity launch.
I think it's a longtime coming.
We've been working on it for quite a while.
The amount of performance that it's going to deliver,
while also delivering incredible storage efficiency,
data reduction, that's a huge boost.
But what we haven't spent a whole lot of time talking about
from a technology point of view as a geek.
What's cool about Unity XT
that you may not have heard a lot about,
is that it's actually using machine learning inside.
So last year we launched the PowerMax
that had machine learning inside
for making all these real time decisions.
We're taking that across the family,
and Unity XT uses machine learning
in order to actually deliver that data reduction
that we just talked about.
The five to one data reduction.
And why that's cool, is because we've had products
that do data reduction with brute force,
where they use a lot of memory.
You can't do that in a midrange product,
because it kicks you out of the cost profile.
So we use machine learning
to take advantage of a little amount of memory,
but to still not compromise on the data reduction.
>> Yeah, actually I had a conversation today
talking about PowerMax.
We made a big deal about what was happening internally
as well as what does that mean for the customers
and the decisions that they don't have to make.
You know, in our industry, we've talked about intelligence
and automation and storage for decades.
So yeah, on the mid range, what does that mean?
What will be different for customers
as they roll out the XT product line?
>> So I think it's simplicity.
It's just the ease of use.
We talk about zero touch, in this case
there's fewer knobs and dials.
You actually don't have to do a lot of tuning at all.
Out of the box it will serve
the majority if the use cases in the requirements.
You still have the option if you want to go in,
if you're sort of the black belt type
and you want to customize it to your own needs,
you can do that.
But that's sort of the journey we're on,
is we call this the autonomous or self driving storage
so a lot of people are talking about it.
We're actually doing it across the portfolio.
And it's actually coupled with two parts,
or coupled with another part.
There's intelligence in Unity XT and PowerMax,
but there's also intelligence in Cloud IQ,
which is our global brain in the cloud.
And we saw that on stage today as well,
where it's doing longterm analytics,
deeper learning across longer time horizons,
to help you manage the system without really much effort.
>> So a couple follow ups if I may
on the data reduction front,
sounds like that's a new innovation
you guys developed kind of from scratch.
Are you bringing it across the portfolio, or is it sort of,
obviously Unity XT today,
does the technology apply to other products potentially?
>> Absolutely does, and in fact,
that's something we're doing across the board
from last year to this year
is you've seen we've become one storage team,
and there's a lot of technology reuse
going on now inside the portfolio.
So things that we're doing in unstructured for example,
are we're looking at applying it
into other parts of the portfolio.
Data reduction's obviously one of the key ones.
It's the first example that people think of,
so we are definitely looking at that.
What I'd also say is from a technology point of view,
we're changing the way software's built.
We're not building it as
monolithic within micro code anymore.
It's containerized assets
that we can embed in different products.
>> And then in terms if the autonomous storage piece,
roll back five, ten years ago, tiering,
and you had a lot of knobs to turn,
and that was always featured as an advantage,
because people wanted to play with it.
What you're talking about today
is an environment that's much more complex,
and talk about more what autonomous storage is.
Is it hands off?
>> So that's a great question.
So we have this internal, almost a joke.
We call it, we're talking about self-driving cars.
Surely we can build a a self-driving storage system by now.
It's kind of a shame that we're not doing that,
but I would say it's four steps.
Just like you have four levels of autonomy
in self driving cars if you follow that,
level five I think is the ultimate, zero, fully autonomous,
and maybe we will never get there,
but similarly in storage, I break it up into four parts.
One is it's got to be application-aware
so you're not dealing with LUNs and file systems
and RAID groups anymore,
you're dealing with this is my application,
and that's how the human interacts with it.
That's easy, relatively easy.
Second element
>> It only took 50 years, okay, go ahead.
>> Touche.
The second element is sort of self-awareness.
Actually before that is policy-based.
Alright, so if you're driving a car,
you're not telling the car which route you want to take.
You want to say I want to take the fastest route,
or I want to take the scenic route, that's it.
And the car needs to figure out what that is.
So that's policy-based.
I want it optimized for latency, performance,
blah blah blah.
Third element is self-awareness,
which is the storage system needs to know
where it's operating in its comfort zone.
Is it close to the edge?
Is it going to drive off the cliff?
It is going to exit the lane, to use the car analogy.
It needs to know how far away it is from the car ahead.
That's also, that's the stuff that we're now releasing
with PowerMax and what we're doing in Unity.
That's where we're using learning
to figure out how to close to the operating edge
the system itself is.
And once you have that,
then you can start optimizing and self-healing.
>> And that's level four, and that's self-awareness.
So you've got decades of data,
are you able to leverage that data,
or is that not as much used, so you have to
>> Absolutely the case.
That's the key differentiator actually,
thanks for bringing it up,
because there's a lot of AI washing going on, right.
Everybody says there's that AI,
but AI's one thing you can't just develop overnight.
So we have used all of the decades of dial home data.
We've been working on machine learning technologies
for the last five years I would say, at least.
So those models are being trained with the dial home data,
and Cloud IQ is doing that on a daily basis now.
>> Why now in 2019, Sudhir, is it,
are we at the point where this has become reality?
Is it compute power?
Is it the amount of data?
Just better algorithms?
>> It's two things.
You nailed it, those two things.
It's first and foremost compute power,
but also I think the algorithms,
they're much more sophisticated now,
and it's real well understood,
on what algorithms to use for what types of problems.
I think 30 years ago there was like, uber intelligence,
that was a very ambitious goal.
I would say even today that's not a reality.
Why we're succeeding,
is we're applying it to very focused problems.
Just like in the rest of the industry,
we're applying it to focused problems that we can solve,
and then broadening our aperture.
>> And to be clear, this is metadata,
it's not customer data that you're utilizing
obviously across the portfolio.
>> That's right.
We're looking at things like how much CPU it's using,
how much memory it's using,
how is the latency varying over time,
how far away it is from its service level, things like that.
>> So just another advantage of being old.
>> So we talked about that's metadata,
but one of the things we talk about,
is when you talk about digital transformation,
it's customers become data-driven.
So we've covered this, it's the 10th year
we've been at this show.
In the early days it was storage,
and oh my gosh, my growth of data,
and I can't take care of it.
Big data was the bit flip
of turn that from a challenge
to I should be able to turn that into an opportunity,
and the next wave of AI is
I should be able to monetize that, run my business,
and the data's one of the most valuable things they have.
Bring us inside, you know,
how that shift in thinking in data
is impacting storage architectures
and how you work with customers.
>> That's awesome, great question.
So data capital is the big thing,
you've heard that today as well.
We are definitely sort of going beyond
thinking of ourselves as a storage division
to a data division,
and unlocking the data capital.
I'd say it's several elements.
One is building the best storage
for data applications, especially AI and MLs.
So I think our unstructured products
clearly are leading the charge in this.
We've got the machine learning solution with Isolon.
It's a perfect fit for that kind of application,
that's here and now already.
Using GPU technologies in conjunction
with our scale out architectures are critical.
But going beyond, we're looking at
does it make sense for some of these
data crunching applications
to be closer to the storage layer.
Thinking similar to what hyper converse has done
for general compute.
Is that a thing that would really
unlock the data capital?
We think that's a lot of potential.
>> And I'm glad you brought that up because you know,
the storage geeks talk about NVME, NVME over fabric,
and storage class memory.
Explain how that fits into
what you were just talking about,
and not just the next major wave
of a tool inside the infrastructure.
>> So storage, NVME and NVME over fabric
was part one of a two-part story as you know.
That allowed us to get that super low latency
high speed connection from the application to the data,
but the data devices themselves
were still, I mean flash is great compared to HDD,
but we're talking single micro second,
or sub micro second applications
that meet that kind of latency.
And that's where storage class memory comes in.
Right, so we're finally getting to that point
where the storage devices
are operating in that ten microsecond range
which will start to really get us to,
where if we can get those things co-located, close by,
it unlocks a lot of things.
And the beauty of NVME over fabric
is that it can give you the sense of being close by
without actually physically being close by.
So you can still be disaggregated,
and that opens up a whole lot of architectural options.
>> Can I ask a follow up questions on storage class memory.
The skeptics would say it's just way too expensive
and you're not going to get the volume of flash
that you get with these.
What do you think?
>> That's what they said
with flash too, didn't they?
>> No
>> Flash went into all the consumer devices,
and that met the scale to bring the price down.
>> Maybe before iPhones they said that,
but iPhone was the catalyst.
So is there a consumer analog for storage class memory?
>> I don't think it would be a consumer analog,
I think that's fair,
but I think there will be volume to drive it down.
However I'll say it's a fair point.
I think the actual magic lies in combining
super fast, perhaps expensive storage class memory,
with cheaper flash storage.
And so you almost have a hybrid solution again.
So the old hybrid becomes the hybrids back in fashion,
even with solid state.
>> The storage pyramid lives.
>> Exactly, we think that's going to be the killer combination.
>> Alright, so Sudhir, can't let you go without,
give us a little bit of a look for.
We talked about where we are,
we talked about some of the journeys that were there,
so it's our 10th year here at the show.
When we come back for year 11,
how do you foresee the industry maturing and moving forward?
>> I think for year 11,
the big things we're going to see is cloud.
Two things, I would say one is cloud,
and the other is software defined.
I think those are two
that are goona be big news next year.
And we're seeing some sneak previews of that this year
with the cloud announcements we made.
You'll see a lot more of that next year
from the storage side,
both as being part of the Dell Technologies Cloud Platform,
but also cloud-enabling our storage arrays
across all public clouds.
And then the second part is software-defined.
I think that's really the next wave, right.
So as I said, we are on a long journey internally,
we've already been on it,
where we're transforming our internal storage assets
to be more software-centric,
and you'll start to see some of that.
>> Alright, well Sudhir, really appreciate you helping us
geek out and dig into a lot of the pieces here
at Dell Technologies World 2019.
>> Thank you.
>> Alright, for Dave Elante, I'm Stu Miniman.
This is the end of two days of wall to wall coverage.
We're comin' back for one more,
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