SAVANNAH GOODMAN: Hi.
Thanks for joining our session, where
you will learn how to measure, report, and reduce
the carbon emissions of your Google Cloud applications.
My name is Savannah Goodman, and I'm a Technical Program Manager
on Google's Data Center Energy team, where I work on our 24/7
carbon-free energy program.
I'm joined today by my colleague, Steren.
STEREN GIANNINI: Hi.
I'm Steren Giannini.
I'm a Senior Product Manager at Google Cloud.
Thanks for joining us.
SAVANNAH GOODMAN: To start, I want
to talk about three key categories
of carbon emissions associated with running workloads
on Cloud.
The primary source of carbon emissions for computing
is from the electricity that's consumed by the data centers
powering those workloads.
Electricity is produced by the power plants that are operating
on a particular regional grid.
Those power plants could be a combination
of carbon-emitting fossil fuel generators,
such as coal or gas, and carbon-free generators,
such as wind or solar.
Different regional electric grids
have different makeups of power plants,
depending on the resources available within that region.
This means that carbon emissions from the grid
will vary, depending on the location
the electricity is being consumed.
Also, in order to meet the demand for electricity,
different power plants need to operate
at different times of the day.
This means that the grid emissions
can vary on an hourly basis.
For example, on a grid with abundant solar energy
during the day, the emissions of the grid
will be lower than at night, when the grid may
rely on natural gas generators.
Next, in the rare event of a power outage,
data centers will run on backup generators, which
typically rely on diesel fuels and, therefore, emit carbon.
Finally, there are emissions from activities
that are not directly related to powering the data centers.
For example, there are emissions from the manufacturing
and disposal of the hardware that's
put into the data centers.
There's also emissions from Google employees traveling
to and from the data centers in order
to support the construction or operations.
The scope of these upstream and downstream activities
is quite large.
But it's important to account for these indirect emissions
when thinking about the total carbon impact of a workload.
In order to eliminate our primary source
of direct emissions, Google has set a goal
to achieve 24/7 carbon-free electricity by 2030.
To specify what we mean by carbon-free,
we include energy produced by wind, solar, geothermal,
biomass, nuclear, hydropower, pump storage,
and battery discharge.
So for each region we operate in,
we measure the percentage of carbon-free energy consumed
in a particular location on an hourly basis.
In addition to the carbon-free energy that's already
supplied by the grid, Google invests
in renewable energy generation in each location we operate in.
Let's take a look at our data center in Iowa as an example.
The regional grid in Iowa has a carbon-free energy score
of 32%.
But Google has invested enough wind energy
to increase the average hourly score to over 90%.
As a customer, the regional CFE score
represents the average percentage of time
your applications deployed in that Cloud region
will be running on carbon-free energy.
Remember that Google Cloud is carbon-neutral,
meaning that Google purchases enough renewable energy
and carbon offsets on an annual basis
to neutralize the operational emissions associated
with your workloads.
Given that the difference in carbon emissions
heavily depends on the region, we
will be diving into how to consider carbon when
selecting your Cloud regions.
But first, I'll go over the different considerations
in addition to carbon when picking a region.
As a developer, you should consider
is there a data locality constraint,
meaning does this data or workload need
to be located in a certain region
due to a regulatory or legal constraint?
Next, what's the latency requirement?
Depending on the workload type, latency
may be higher or lower priority.
For example, production workloads serving user traffic
may require a much lower latency than a batch job.
What's the cost?
Different regions may have different prices, thus
impacting the operational cost.
Finally, as we know, each region can
have a significantly different carbon emissions profile.
So we need to consider this impact when selecting a region.
That is why we've published the carbon-free energy scores
for every region we operate in.
As you can see, the CFE score can vary greatly
between regions, even between some
that may be relatively close in proximity.
For example, you can see that if you move a workload from Salt
Lake City, which has a CFE score of 28%,
to Oregon, which has a CFE score of 90%,
you can significantly reduce its carbon emissions.
In fact, selecting a low region is
one of the most impactful choices
you can make to reduce your overall Cloud carbon
emissions footprint.
This data is available on our Cloud website, GitHub,
and as a BigQuery public data set.
Now I'll hand it off to Steren, who
will tell you more specifically about the data we've published
and the other ways we've incorporated it
into our products.
STEREN GIANNINI: Our first step to help customers pick a Google
Cloud region based on carbon was to publish carbon information
on every Google Cloud region on the Cloud website.
So on this page, you can find a table with--
for every Google Cloud region, its average
Google carbon-free energy percentage as well as
its average annual grid carbon intensity.
As you can see, some regions get a small, low CO2 label.
This is given when the region meets a certain criteria
of high carbon-free energy percentage or low grid carbon
intensity.
Our next step was to add all of the other Google Cloud
documentation in the Locations Notes pages, those same labels.
So here, we are on the Cloud Storage documentation.
And you can see for every region where
Cloud Storage is available, we call out
if this region is low-carbon.
We went even further by adding, in context of the Cloud
Console, the same information.
So here, we are in Cloud Run, and users
have to pick a region when they create a service.
Well, as you can see, right in context of the Region Selector,
we added the same low CO2 information, helping you,
at a glance, know which regions have the lowest carbon impact.
And lastly, as Savannah said, because picking a region
is more than just considering carbon,
you have to consider carbon, price, latency, we've
built this very simple tool that allows
you to enter what you care about,
and it returns you the best region based on your inputs.
So let's say, for example, that you are
running a daily background job.
In that case, you probably don't care about latency.
And let's assume that you care as much about price
as you care about carbon.
In that case, we recommend you to use our Iowa data center.
But now let's assume that you are in France,
and you really care about latency.
But you also care very much about carbon.
In that case, we would recommend europe-north1.
And in case you really want to optimize for price, too,
then you see how the selection and the recommendation
actually changes.
So we hope that providing this simple tool that
is based on open data we published,
the carbon data I presented earlier,
the public prices of Google Cloud,
and the approximation of the distances,
we can help you pick a region based
on what you care about, and notably, carbon information.
Before rolling out these changes,
we wanted to measure their impact.
So we rolled out an A/B testing experiment
to measure if displaying carbon information in the Cloud
Console Region pickers would influence consumers' behavior.
After running it for enough time,
we got those significant results.
Among all users, 19% of them were
more likely to select a low carbon region when
they were exposed to the "Low CO2" indicator in the Region
Picker.
And among new Google Cloud users, more than 50% of them
were more likely to select the low carbon regions.
Those users are users who did not yet
have picked a region for their architecture.
So we've explored how we are sharing regional carbon
information.
Now let me introduce you to Google Cloud Carbon Footprint.
So customers reach us to help them meet their sustainability
goals.
Many of them are needing insights
into the carbon footprint of their cloud usage.
And if we think about it, the cloud is like a black box.
Many of our customers have done the estimates
that were lacking some critical data to come up
with carbon footprint numbers.
With Google Cloud Carbon Footprint,
we help you report on your gross carbon emission of your Google
Cloud usage, and we help you reduce your company's carbon
footprint.
Let's see it in action.
Let me introduce you to Google Cloud Carbon Footprint.
Here, I am in the Google Cloud Console.
From the left navigation, I scroll down under Tools,
and I select Carbon Footprint.
Here, I can see the carbon footprint
coming from the electricity used by GCP resources
for the selected billing account.
This dashboard is accessible to anyone from the Cloud Console
who has access to the billing account.
Let's take a closer look.
At the top, we have a recap of the footprint.
On the left, the carbon footprint for the last year.
In the middle, the carbon footprint
for the current month, compared to the previous month.
And on the right, a reminder that Google
is investing in enough renewable and carbon offsets
to neutralize all of its global operations.
Below, we have four charts breaking down
the same information of our different dimensions.
The first one is showing the carbon footprint
over time, broken down by month.
So this chart would be quite useful to see
how you are trending, and if you are successful at reducing
your carbon footprint.
To the right, we have the carbon footprint
for the last month broken down by Google Cloud projects.
Below, we have the same data, but this time,
broken down by Google Cloud product.
And finally, we have the carbon footprint for the last month,
broken down by Google Cloud regions.
So this is a curated dashboard of the carbon footprint data
that we computed for the given billing account.
But you might need some customization
of this dashboard, or you might want
to drill down into the data.
This is why we provide this Export mechanism.
By simply clicking Export at the top right,
you will be able to schedule a BigQuery export of the carbon
footprint data.
So I scheduled it before.
Here, I am in BigQuery.
And as you can see, this is the table
that we export in the selected project.
So the table has the same dimensions.
The month, the billing account, the project, the services,
the locations.
The carbon footprints.
And you can see--
you can explore it using SQL queries.
And you can see how you could build any query you want,
grouping by any dimension you want,
to create your own reporting.
This is very easy to save this data into a spreadsheet.
So I did so just before.
And here, you see the exact same data,
this time in Google Sheets, where, again, you
can very easily create charts or custom computations based
on the carbon footprint data that we computed
for your billing account.
So we are very excited to introduce this to you
today, the self-service carbon footprint of your Google Cloud
usage, right inside the Cloud Console, available to anyone.
Let me deep-dive into the methodology
that we use to compute this per-customer carbon footprint.
It can be broken down in three steps.
The first one is a Google-wide internal carbon apportionment.
We take three inputs for that one.
First, the measured energy consumption
of Google Cloud data centers, taking into account
the power usage effectiveness.
Then, the actual resource usage of
dedicated or shared resources for every internal accounting
group.
And lastly, the carbon intensity of the region where
the data center is located.
This gives us, for all of Google, the carbon
footprint per hour, region, and internal accounting group.
The next step is to look at this data
through the lens of Google Cloud.
So we filter the previous data on Google Cloud accounting
groups, and we bring in Google Cloud billing data
in order to calculate the carbon footprint per day, Google Cloud
region, and Google Cloud skew.
The third step is to compute the per-customer carbon footprint.
So we blend the previous data with actual customer usage
to compute the carbon footprint per day, region, Google Cloud
service, Google Cloud project, and of course, customer.
Finally, we aggregate this data on a monthly basis,
and we display it on the Google Cloud Console Dashboard,
or we export it into BigQuery.
We have been sharing the private preview of Google Cloud carbon
footprint to a few early testers.
They shared with us feedback, like Hervé Dumas,
who is Sustainability IT Director at L'Oreal.
He tells us, the capability to measure and understand
the environmental footprint of our public cloud usage
is among the key axes of our sustainable tech roadmap.
With Google Cloud Carbon Footprint,
we are now able to directly follow
the impact of our sustainable infrastructure approach
and architecture principles.
Now back to you, Savannah, for a recap.
SAVANNAH GOODMAN: To conclude, we're
going to summarize what you can do to reduce your carbon
footprint.
Consider carbon in your decisions.
First, make sure to pick a cleaner region
for your new applications.
If you are going to run an application over time,
running in the region with the highest CFE score
will emit the lowest carbon emissions.
Second, run batch jobs on the cleanest option.
Batch workloads often have the benefit of planning.
So you should be able to pick the region with the highest
CFE available to you.
Finally, set an organizational policy for clean regions.
You can restrict the location of your resources
to a particular Google Cloud region,
or subset a region using organizational policy
constraints.
STEREN GIANNINI: And lastly, we want
you to remember that Google Cloud gives you
all the tools to optimize your region selection.
For example, by publishing region carbon data
on the Google Cloud website, by providing a Region picking
tool, and by displaying, in context of the Cloud Console
and Cloud Documentation, those small "Low CO2" indicators.
But we also want you to remember that Google Cloud gives you
the tools to report on your gross carbon emissions.
Today, we have announced Google Cloud Carbon Footprint
to help you understand and reduce your cloud carbon
footprint linked to your cloud usage.
We are hoping it will be very helpful to you.
Thanks for joining us.
Savannah?
SAVANNAH GOODMAN: Thanks, Steren.
And thank you for joining our session
on cloud carbon emissions.
We hope you enjoy the rest of Cloud Next.