JOE MASTERS EMISON: At BuildFax, we've
been using Google Compute Engine as part of our production
delivery system.
So taking our production servers and our database servers,
and putting them on Google Compute Engine,
and seeing how that met our needs.
And we've been very satisfied with the way
Google Compute Engine performs.
So one of the great things about Google Compute
Engine in our experience is that the performance
is really reliable.
So there's not a lot of variability in the performance
that we see.
So that means when a user makes a request,
no matter what time of day it is,
the response times are very similar.
At BuildFax, our customers are mainly insurance companies
and lenders.
And that means they require of a certain performance
characteristics for our web service.
So when they make a request to us,
we have to give them data within a certain amount of time,
or we can't collect money, or we may even have to pay penalties.
So for us, consistent performance
is really important.
And one of the things that's difficult about being
on the public cloud is consistent performance,
because these are shared resources.
And so one of the great things about using Google Compute
Engine is the real performance benefits and the consistency
of performance that we've seen on Google Compute Engine.
The specific use case that we have used on Google Compute
Engine is delivering data points to insurance companies
at the point of underwriting policies.
So that is you're a customer, you go in,
you want to get homeowner's insurance,
and a lot of information gets pulled back about your home
in order to price your policy.
So that's data that we have to deliver on a schedule
very quickly.
And so what we did with Google Compute Engine is
we put our delivery servers there,
we put our database servers there,
and then we ran endless benchmarks
against these servers to see what the performance
profile would be.
And what we saw was that we consistently
were getting results in less than four seconds and almost
no variability.
We were seeing something like a 0.02,
0.03 standard deviation in terms of delivery time.
So in other words, delivery most of the time
was happening between 0.37 and 0.43 seconds.
We see Google as a great provider
of computing resources.
So we absolutely can see our production pipeline
going onto Google Compute Engine and running.
And we can see all a lot of our big data requirements
and big data analysis that we do moving to Compute Engine.
A key advantage to us, and to me in particular of Google Compute
Engine, is that Google is one of the pioneers in this space.
I mean, they brought Bigtable, they brought MapReduce.
And at this point in time, it's been an internal Google
resource.
You know, separate companies haven't
had access to use Google's own resources
that they have pioneered.
And really everything else out there
is just copying or re-implementation
of what Google's had longer than anybody else.
And so the idea that we can have access to Google Compute
Engine, like Bigtable, and these tools
that Google has built for their own infrastructure
that we know scale out, that we know are highly resilient,
it's fabulous for us.
And so there's a lot of confidence
that I have when I'm using Google Compute Engine that I'm
using this fabulous resource that
is so battle-tested out there.
And it's excellent.
And in using Google Compute Engine, I have seen this.
I've used a lot of options out there for virtualized hardware.
And Google Compute Engine just worked.
Even though we were early on and we
were part of a trusted tester program,
the resources just worked.
Clearly, this works.
It's been there for a while.
It's just good stuff.
A company like BuildFax has never
had access to actually run on Google's hardware.
And now we can.
You know, I've used Google Compute Engine, and it works.
It's there.
I can tell that what they've built here
is something that is going to work for our business
and is going to be a spectacular entry here.
It's amazing to have Google enter a public cloud
space where anybody can run their own servers on Google's
infrastructure.
And it's not just about virtualized hardware,
about buying computing cycles.
It's about the whole infrastructure
that Google has behind this.
We know it works.
We know they've got tons of machines.
We know that they know how to manage them.
And they're managing every piece of them
from security, to the network layer,
to all of the data channels.
And it's just fast.
So we've been using RightScale now for almost three years.
And we've built a lot of server templates
that have all of our configurations in them.
And so when we went to use Google Compute Engine,
we just pointed those server templates at Google Compute
Engine, and it just worked.
BRIAN STANLEY: Across all of the tests,
the thing that stuck out the most
was the consistency of performance.
So we started running the tests over and over
on Google Compute Engine.
We got the same results every time,
which is something we've learned that you can't necessarily
take for granted particularly when you've
got a deployment in the cloud.