LAURENCE MORONEY: Welcome to the Googleplex.
This is an incredible place with lots of great stuff being
worked on every single day.
Before I worked here, I always wondered
what it would be like to come to the Googleplex,
meet up with a Googler, and have coffee with them
and just chat about what they do, how they do it,
and why they do it.
And today, we're going to do exactly that.
Hi.
And welcome to this episode of Coffee with a Googler.
Today, we're reporting actually from inside Google's Cloud
itself, or at least one of the data centers that powers it.
And I'm meeting with Greg Wilson.
He's a manager on the Developer Advocacy Team for the Google
Cloud Platform.
But he's not one of your typical pointy haired managers.
You've worked on lots of cool stuff.
And you're going to tell us all about it today.
GREG WILSON: You bet.
Yep, thanks for having me.
LAURENCE MORONEY: So tell us what is it that you do here?
GREG WILSON: So I manage a team of people, developer advocates,
for Google Cloud Platform.
There's about 18 of us total.
And our job is to go out into the world
and make sure people know all the cool things that we're
doing with cloud platform.
It's innovating very quickly-- announcements every other week.
And we try to get the word out there.
LAURENCE MORONEY: Now there's a lot of diversity
around cloud developers.
There are so many different types of developers.
And it must be really hard to have a core message
to reach all of them.
What are the opportunities to reach out?
GREG WILSON: Yeah, it is.
It's very unique for our team, specifically,
in Google is that we're dealing with a platform that
has a different meaning to a lot of different audiences.
So for example, no JS developers see cloud
in a specific way, certain parts of cloud
that meet their needs for apps.
Similar with Ruby, Java.
But even things like data scientists,
people that are looking at six billion rows of transit data
and they want to draw some intelligence out of that.
So we're trying to get them interested in it as well.
It's cool.
We have some amazing services around all of those things.
So it's not just that we talk to developers in one language.
We have to be able to speak in multiple types of languages
to multiple types of audiences.
LAURENCE MORONEY: So that's quite a challenge.
But you've got a big team, well equipped team for it.
GREG WILSON: It is.
And it's fun too.
Because you get to see a lot of interesting things
that people are doing when you're
providing the computing power, the CPUs,
to drive all this stuff.
You see some pretty amazing things.
LAURENCE MORONEY: Now, you mentioned
that you're constantly releasing new things.
And there's a constant drumbeat of great new technologies
coming out.
What kind of recent ones have you done?
GREG WILSON: Gosh, so many things going on.
The recent ones that we've been doing some activity around-- we
have 32 CPU VMs now.
LAURENCE MORONEY: Nice, nice.
GREG WILSON: Matter of fact, one of them
is 208 gigabytes of memory with 32 CPUs.
LAURENCE MORONEY: Virtual.
GREG WILSON: Yeah, that's the gadget guy inside of me just
loves that, having all this computing
power at my fingertips.
And it's one thing to think about a 32 CPU VM,
that you start thinking about that in terms of clusters.
I want to have 1,000 of those doing something.
It's mind boggling what you can do.
And it's exciting for us.
And we try to share that excitement
with the people we talk to.
And then around the same time, we also
introduced a new feature called local SSDs.
So it's extremely high I/O bandwidth drives
that are physically connected to your virtual machine.
LAURENCE MORONEY: Nice.
GREG WILSON: We're talking 170,000 sustained IOPS, which
if you know anything about disk drives and hardware,
that's a stunning number.
LAURENCE MORONEY: Right.
And I know you've been putting all this together
to try and come up with some scenarios
that you can show it off, that numbers of CPUs an IOPS
might not mean much to other folks.
But the other stuff that you've been building does.
So can you share that?
GREG WILSON: Yeah.
And that's one of the challenges of our team,
is that how do we let people know beyond the specs?
We can show them a lot of numbers
of what the stuff is about.
But until they can see the kind of things you can do with it,
it doesn't really make sense to them sometimes.
So yeah, we're always thinking about how can we show this off?
What type of demos can we build?
What kind of story can we build, more importantly?
For example, when the 32 CPU DMs launched,
we found some software called Prime C that
generates prime numbers, using some neat very simple
algorithms.
And we generated a trillion prime numbers in 17 minutes
on a 32 CPU machine.
LAURENCE MORONEY: A trillion in 17 minutes.
GREG WILSON: A trillion, yeah.
And it was funny.
I tweeted about in.
And the tweet was, I generated to trillion prime numbers.
Because I can.
Why not?
LAURENCE MORONEY: And you said it took 17 minutes.
GREG WILSON: 17 minutes for that.
The software, thankfully, supports multi-core.
So it was able to take advantage of those 32 CPUs.
It's really very much a CPU intensive operation
where there's other things that also take advantage of memory.
And you can mix and match a lot of the things that we offer
and compute to do that.
LAURENCE MORONEY: Now, to rent a 32 CPU machine for 17 minutes-
how much would that cost?
GREG WILSON: Well thankfully, we have the per minute billing
on that.
I think the hourly rate for the 208 gig one is anywhere from
a buck, 65, to 2.10 an hour, or something.
It's really inexpensive considering
what you're getting.
And that's part of the Google scale.
I mean, we were able to pass on that scale in incredible cost
savings.
And so what that means for geeks like me
is that I can get my hands on some serious hardware
for the price of a cup of coffee.
I have a lot of fun in 17 minutes.
LAURENCE MORONEY: Yeah, that trillion prime numbers
must've been pennies at the rate you just mentioned.
It's incredible.
GREG WILSON: Yeah.
So what is that, 1/4 of 2 bucks?
So yeah, 50 cents.
LAURENCE MORONEY: How many universities, and stuff,
have to go and invest hundreds of thousands of dollars
in infrastructure when you can do it this way?
GREG WILSON: Yeah, exactly.
And that's the whole idea behind cloud.
And that's why there's so much excitement in cloud,
not just Google, but a lot of the other big names in cloud
doing the same thing.
It's a very exciting space, which is what drew me into it.
LAURENCE MORONEY: And you took this sort of next step
on pay day.
I've heard some of the stuff you've been doing for that.
GREG WILSON: Yeah.
So sort of a funny story-- one of the guys on my team,
Ray Tsang-- he and I were at South by Southwest
with some other folks from Google.
South by Southwest was a few weeks ago
in Austin, Texas-- fantastic event.
And we were literally hanging out at a bar, 11:00 p.m.
At night.
LAURENCE MORONEY: When all the best ideas happen.
GREG WILSON: When all the best ideas happen--
having a couple of drinks.
And someone mentioned that the following day was Pi Day.
And Ray and I were like, man, I wonder
if we could do something with Pi Day
like we did with the prime numbers.
And we said, well, first of all, we
got to have some software that can do it.
We have ours.
We can't go write software to generate digits of pi.
Plus, it's not trivial.
It's pretty advanced mathematics.
So we both have our phones out.
And we're Googling, is there any software available?
And sure enough, we found this thing called y-cruncher,
by a gentleman named Alexander Lee.
It supports multi-core.
It will allow you to generate digits
of pi up to an astronomical number of digits.
So it supported the operating system that we had.
It ran on Linux.
It was very CPU intensive and memory intensive,
a good story for our VMs.
So at 11:00 PM, we were facing a choice.
Do we do we run back to the hotel and sit in the lobby
and make this work?
Or do we sit here and continue drinking with their friends?
Because we're geeks first.
And we basically were in a cab in five minutes.
So we excitedly get into a cab.
We go back.
We spent several hours experimenting with it.
So we were able to do a billion just in minutes.
I mean, it was incredibly fast.
And we were looking at how do our VMs
work with this the best?
And well, a billion is not that impressive.
And so well, why don't we try 10 billion.
So we did 10 billion.
And that ran pretty fast as well.
But we still didn't feel like we really stretched things.
So they we tried 100 billion.
Well, the problem with 100 billion
is that it needs a lot more memory than the 208 gig.
So we needed to provide disk for swapping.
And as you know, disks are much, much slower than memory.
LAURENCE MORONEY: SSD is not bad, right?
GREG WILSON: Exactly.
And with local SSDs, which are these physically connected
devices to your VM, they're extremely fast.
So that's where the 170,000 IOPS comes into play.
So we thought hey, here's a great opportunity.
We're about 12:05 AM at this point.
So now we're playing around.
LAURENCE MORONEY: So it's only an hour in.
GREG WILSON: Oh yeah.
We're still just getting started.
So we provision out the local SSDs.
We fire up a VM with them connected.
And we play around with the parameters of the software.
And we had 1.5 terabytes of local SSD connected.
Because not only do you need it for the swap,
but the output file itself.
If you're going to generate 100 billion digits of pi,
that's 800 billion characters in a file somewhere.
So we actually dabbled with doing a trillion digits.
But it was going to take more time.
It was going to go beyond Pi Day.
LAURENCE MORONEY: You needed to go to bed.
GREG WILSON: And we were getting sleepy at this point.
So anyway, Ray's on one laptop.
I'm on the other.
We're experimenting with different parameters.
And we found the perfect mix.
And thankfully, this is right in Ray's wheel house.
So we made a great team on this.
And so about 3:00 AM, we kick off
what we think is going to be the job.
And we call it a night.
And so the next morning, we excitedly
logged back into the terminal.
And it had finished.
And it ran at about 5.3 hours and generated
100 billion digits.
LAURENCE MORONEY: 100 billion in five hours, wow.
GREG WILSON: So then we did a fun tweet.
In celebration of pi day, Ray and I
generated 100 billion digits of pi.
And we put it out there.
And this is getting back to the developer advocacy job.
We're trying to generate some buzz
and show people the cool things you
can do with this technology and this platform.
And the tweet did really well.
I mean, it took off.
It caught in some of the excitement of Pi Day.
[INAUDIBLE] was tweeting about Pi Day.
We were really hoping he would catch our tweet.
And a few people actually pointed him to it.
But he's probably got other things on his mind.
LAURENCE MORONEY: He's probably watching our show now.
GREG WILSON: Yeah, I'm sure he will.
So he missed his opportunity.
The next Pi Day will be his makeup.
So that was a fun day.
We got a good amount of buzz out of that.
We high fived.
Because that was developer advocacy success.
LAURENCE MORONEY: It's a big win, right?
GREG WILSON: So now we want to take it to the next level
and try to break some records on speed.
On the site that has y-cruncher, there
are documented records of how long it takes to do these.
We actually broke a couple of records with what we're doing.
But we don't want to publish those yet.
Because we want to go for a bigger record.
So we want to do a trillion digits next.
That's very feasible.
But the world record for pi is 13.3 trillion.
The current record was done on a workstation
with nearly 300 terabytes of drives attached to it for swap.
And it ran for 208 days.
But that's a workstation with a bunch of drives.
I've got Google data centers at my fingertips.
I should be able to beat that, right?
So it's more challenging than you might think.
So we're going to be working on that.
So hopefully, we'll be talking a few months about how we now
hold the world record.
LAURENCE MORONEY: We'll be celebrating
you breaking the record.
GREG WILSON: We'll see what happens.
LAURENCE MORONEY: And when you did the 100 billion
for five hours, again, just thinking in terms of cost--
because it's just the two of you on your laptops terminalling
into a cloud server somehow.
And compared to having the dedicated hardware for it,
the cost must've been a lot lower.
GREG WILSON: Oh, yeah.
It was cheaper than the two drinks
we were drinking when we left the bar.
For the Pi Day specifically, the local SSDs,
we only charged for the storage for the drives themselves.
You don't get charged for the bandwidth.
Because they're physically connected.
And then the virtual machine is the pricing per minute.
LAURENCE MORONEY: You have it for five hours.
GREG WILSON: Right, so you're looking--
I mean-- no more than $15, probably little
less than 15 bucks.
LAURENCE MORONEY: So it wasn't even particularly expensive
drinks?
GREG WILSON: No, it wasn't.
And that's the beauty of this.
And we're having fun with this.
There's not a lot of practical use
to this other than some buzz.
But you think about a lot of the research that's going on
and a lot of the computing power that's needed.
And especially when you start thinking beyond a single VM,
and you think, that times 1,000 or 10,000 VMs in a cluster,
you can really start doing some game changing things.
LAURENCE MORONEY: Absolutely.
Sounds cool.
GREG WILSON: Now for folks who are watching the show who
might want to start dabbling in this
and maybe calculate some other numbers,
how would they get started?
What's a good place?
GREG WILSON: Best starting place is just go to cloud.google.com.
We actually have a trial that you can sign up for.
You get $300 for a couple of months of playing
around, $300 for 60 days.
You can have a lot of fun with $300,
I mean, just based on what we just talked about.
LAURENCE MORONEY: That's 20 times your pi calculations.
GREG WILSON: Yeah, you could do a lot of digits of pi.
Hopefully, you would do something
more exciting than that.
So you can't missed the free trial button.
It's everywhere.
And there is documentation.
I mean, we've only touched on virtual machines.
We're starting to do a lot of exciting stuff
around containers with a container engine,
BigQuery, the very large data analysis that we mentioned
earlier, Kubernetes project.
There are so many amazing things going on in cloud
that I think people would be surprised what we're doing.
LAURENCE MORONEY: Cool.
And it's all summarized on cloud.google.com.
GREG WILSON: It is, yep, everything you can find.
LAURENCE MORONEY: Thanks, Greg.
That was so cool-- lots of great stories.
GREG WILSON: Thanks.
I appreciate you having me.
LAURENCE MORONEY: Well thanks everybody
for watching this episode of Coffee with a Googler.
For more great videos on Google Developer topics,
and on Google Cloud and everything else that we do,
take a look at the Google Developers channel
and subscribe to us.
If any questions for me or if you
have any questions for Greg, please leave them
in the comments below.
And thanks so much.