My name is Frank Shepherd I'd like to
take a few minutes today to talk to you
about Intelligent Infrastructure and the
role it plays in helping I.T. teams shift
from operations to innovation. One of the
things that we hear consistently when we
speak with our customers is that the
operational burden- the responsibilities
to keep users connected to keep
applications running to keep security
under control those things are
growing every year meaning that there's
less time to spend on innovation, 
collaboration with lines of business.
And it's unfortunate because innovation of course is the lifeblood of any
organization. It drives competitiveness
and hopefully revenue as well.
I want to take just a minute to talk about the concept of operational burden in terms
of something that we're all familiar
with- let's take just a simple road trip.
If we're in a car 25 years ago and we
have a map on our lap and we're driving
across the country the car does nothing:
it won't turn on its own, it won't stop
and start on its own- the driver is
responsible for all the operations. If we
get a you know late 90s and we get into
a GPS unit, it makes it easier- we don't
have to read the map, it will narrate
directions to us, it will navigate for us.
It takes some of the burden off-- the car
still doesn't really contribute to the
driving experience though. Cut to the
late 2000s and now things like Waze come
online and so we've got machine learning
in the cloud taking telemetry from all
of the users who are using Waze and now
providing optimized routing. So again
the experience begins to get even better
for the user; the car still not doing a
whole lot though in this case. We can
then cut to five years after that
somewhere in you know the last five
years we see Lane Assist or active
collision avoidance, active cruise
control...things that are that are obeying
laws: stay between the lines don't crash
into the bumper of the car in front of
you-- those sort of simple rules are
starting to actually make their way into
most cars into many cars today and it
has a
even more dramatic impact on the
feel- the operational burden of the
driver. So the car is now actually
starting to do some things on behalf of
the drivers taking some of that load off
of them.
But at this level where you
actually put machine learning inside of
the vehicle itself, it becomes
something of an appliance. So you take
Tesla and- local and state laws
notwithstanding- the car knows to change
lanes when they're slower traffic in
front of you, knows to take the exit, it
knows to turn left on Main Street. So for
all intents and purposes the
operational burden is now shifted
dramatically in favor of the
automobile and away from the user. Now
we're talking about taking significant
amount of cognitive load and operational
burden off of the driver, freeing them up
to do higher-order things on their drive
across the country. So let's apply this
to I.T.- let's take it back into
I.T. So if we take our regular old stack
of hardware, it requires care and feeding,
it requires hand holding and we've got
to keep an eye on it, we've got to make
sure it's running optimally. There are
lots of monitoring platforms out there- 
Splunk is huge and it's incredibly
effective- it takes some of that burden
off of I.T. It eases the operational
burden a little bit, but the the hardware
is not necessarily doing anything at
this point.
AI Ops is a huge buzzword right now and
so if we have machine learning platforms
that are applied to our hardware they
can still further relieve operations of
that operational burden. It's tightly
coupled with what we could call 
rules-based automation where the hardware
begins to obey rules. We can set
thresholds, we can set boundary
conditions and say, "If this is happening
then do this" it's much akin to "if the cars
in front of you are breaking, then slow
down." But then there's this missing
inflection point- now how do you get to
that inflection point that's much like
the Tesla of the data center. So to bake ML into the
hardware itself- to create an appliance
that has intelligence in it...that is
where the operational burden shifts
dramatically in favor of the hardware
itself and off of the staff, freeing them
up to do higher-order things. This is
where innovation can come back in. So as
a category, we would refer to this as
something like "Infrastructure
Intelligence." It's really helpful.
You've got ML up in the cloud, 
digesting tons and tons of data.
You've got rules-based automation here and there making tweaks to the
environment: it's not unhelpful...it's not
optimal though. And so to move into
something that the industry would refer
to as "Intelligent Infrastructure" we're
talking about the hardware with the
machine learning baked in so that the
telemetry, the visibility, the learning
models, and the adaptability, the
responsiveness, the remediation of those
conditions can all happen local to the
platform it matters on most. So if this
is a storage platform, you're looking at
the things we store: virtual machines,
databases. You can then see patterns of
behavior on a virtual machine, a database, an application level. And then
you can respond to those applications
and databases and virtual machines in
real time, dynamically and adjust very
gracefully to changing conditions. So if
we say this is the state of I.T. today we
have all this operational burden and
very little innovation. The introduction
of Intelligent Infrastructure is really
the key to flipping and creating an
inflection point where innovation can
now take a front seat and be the lion's
share of where I.T. teams are spending
their time, relieving them of a lot of
that operational burden and freeing them
up to drive revenue, drive innovation, and
drive competitive advantage for their
organizations. If you'd like to learn
more about how the Tintri VMstore
plays this role and all the things that
it offsets from an operational burden
standpoint, we'd love to have that
conversation with you. We're also happy
to put you in touch with any of our
customers who can probably tell that
story even better than we can- 
tell you they can give you real-world
examples of exactly what kind of a
difference the VMstore
hs made in their environment. We look
forward to talking to you. Thank you
