SRIKANTH BELWADI: So something phenomenal
happened around this time last year.
About half of all web traffic was actually video.
It crossed the 50% mark when I was looking
at the stats of YouTube.
And about 300 million-- sorry, 300 hours of video
was uploaded every single minute.
300 hours every minute.
And Red Bull conducted the Stratos Jump,
and approximately eight million users
were watching that stream simultaneously, a single video.
And just last year, YouTube crossed
about one billion users-- active, unique users--
every single month.
This was a big shift that was happening.
And this was not just on the distribution and the content
delivery side.
It was looking at what's happening on the content
production side, as well.
So YouTube obviously delivers low resolution media
for end user devices.
AUDIENCE: [INAUDIBLE].
SRIKANTH BELWADI: Thank you.
But the content that's produced in the studio
is a very small part of that, that's
actually watched by users.
The high-res 4K uncompressed video.
Every studio produces approximately 20 terabytes
of video every day.
And this content needs to be probably stored for decades.
Actually, lifetime.
Probably centuries.
We cannot imagine Disney's "Snow White"
some footage being lost after 100 years.
It's just not possible.
This needs to be stored forever.
So it's not just the content that's produced,
but all the post-production that needs to happen on this.
Last year, I learned that "How to Train Your Dragon 2"
required about 75 million computers
to render all the frames with about 250 TB
of active disk space.
And probably more recent films require even more
compute power.
All of this could have been a very tractable problem--
huge amount of data, huge amount of processing--
if not for this graph.
If it was a uniform distribution of computers
over a period of about one year or so,
all the studios could have probably
gone ahead and built larger and larger data centers, whether
[INAUDIBLE] their business or not,
and still been able to solve for this problem.
Look at how the rendering hours was actually
used by one of the studios over a period of six months of movie
production, and this was how it looked.
This graph is a nightmare for anybody
who's planning for capacity or resources.
But it also makes a case for public cloud,
where you can get elastic resources,
where you can spin up hundreds or thousands of computes
as required and then spin them down.
But burstability, or this bursty nature of traffic,
is only part of the problem.
This industry is facing millions of media formats,
with all the codecs and standards and end user
devices that this content needs to be delivered to.
Hard release dates.
Irrespective of how much resources are required,
the producers have set the final release date as constant,
and get the resources as much as required.
Complex toolchains that changes all the time.
In fact, every production almost seems
like starting a new company.
And distributed workforce.
Last week I was in India, and there were so many colleges
and institutions where visual effects and animation degrees
and certificates were being offered.
There are tax incentives distributed in different parts
of the world.
So studios are no longer at one location.
And this workforce, which is distributed across the world,
is probably working on the same project and needs collaborate.
And somehow, we need to handle this enormous, enormous data.
And this challenge of data and processing
is not limited to one stage of the media lifecycle.
The challenge is across.
How do you ingest this huge amount of content
into storage to where the compute is,
with all the bandwidth and latency challenges
that we have?
How do you render all these frames with these huge compute
requirements?
And also, how do you get the software licenses that
are required, which have all been probably provisioned
for on-premises till now?
How do you transcode for this myriad device
formats that are there?
How do you archive this content?
And it's not just storing this content
for a long time at low cost.
How will you be able to retrieve this content as required,
and when you need it, in minutes?
And distributing to users who are worldwide.
So all these are the challenges that this industry faces.
And Google Cloud Platform is actually
investing substantial resources and infrastructure
to address these very problems.
And the essential cloud elements,
which probably we will talk through through the rest
of the sessions today is flexible compute.
How can you spin up, if you need, as required,
tens, hundreds, thousands of VMs,
and spin down when you don't need them?
And pay for exactly what you use?
Always available storage.
High performance block storage that you find on public cloud,
but also, can you get the same low cost of archival
but be able to retrieve it in a matter of minutes?
Global networking.
Goggle has around 70 plus edge locations and points
of presence across the world, and connected
through massive network, including submarine fibers,
and we are not telecom company.
And solutions for big data and analytics.
And it's not just the infrastructure investments
that are made.
Over the last year or so, [INAUDIBLE]
have launched about 100 plus features--
externally-facing, very important,
large, large features.
Some of them, for example, the more recent ones,
very relevant for the media industry,
and we will talk about this through the rest
of the sessions.
The Nearline storage, 32-core VMs,
integration with [INAUDIBLE].
We'll have a full session on that today.
HTTP load balancing and more.
But probably you don't need to know any of that.
And if there are just three words
that you are going to take away from all of today's sessions,
it would be these.
Our team, we are working very hard
to make sure that the media industry can
get a little bit of simplicity in their already complex life.
How can we simplify your workflows,
whether you're a small time developer, a freelancer who
needs probably a plug-in to their desktop host
applications, or a large, complex studio
and you have a hybrid model?
You have an existing data center,
but you need to burst to cloud.
How can we do all this in a safe and secure manner?
Google has hundreds of engineers, security engineers.
Many of them are PhDs.
That's their life-- working for you
to keep your data safe and secure.
These are the engineers who are trained to ward off
most sophisticated attacks, including
from nation-states for Google.
They're the ones who will be working on this for you guys.
And lastly, the economics.
The real promise of cloud, which was pay for exactly what you
used, not for the entire hour.
If you used it for a minute, pay for the minutes.
You don't have to make large commitments.
The pricing should be simple.
And if you use more, you should automatically
get a lower price without you having to commit anything.
So throughout the next four to six hours,
we'll try to address each of these elements
through multiple sessions.
And I hope you'll have a good time.
Google Cloud Platform currently powers multiple media
companies, from small studios, individual freelancers,
distributors like [INAUDIBLE], Framestore, and even YouTube,
by far the largest media distribution company out there.
And we believe what we're doing can help you, too.
With this, is let me call upon Todd Prives, who's
a Product Manager for Rendering at Google Cloud Platform.
Todd came from ZYNC.
And over the last six months, I've
learned so much from Todd that I don't now
feel that I'm new to this [INAUDIBLE] at all.
Todd?
[APPLAUSE]