Hi.
So in this talk, we'd like to take you on a journey across the environmental materiality
of digital services.
So the speakers in front of you, here's David.
My name is Benoit.
We are contributors to an NGO called Boavista that we'll present briefly later.
We also are colleagues in a small company called Hublot working on ICT and environmental
impacts.
Regarding Boavista, so the NGO we work for and this is the work of this NGO we present
to you today.
This is an NGO based in France that gathers more than 250 members now, private companies,
public organizations, universities, researchers, freelancers and so on.
And the goal of the organization is to provide public and open methods, data, tools and knowledge
about environmental impacts of ICT and its assessment.
And of course we try to provide a useful open source, open data and open science stuff.
Thank you Benoit.
So today's objective will be to see how can we get from digital service to its environmental
materiality.
Environmental materiality is another way of seeing its environmental impact and it includes
not only its carbon emission but also all of the other pollution and its usage of renewable
and non-renewable resources.
To do this we need to follow a process which is called environmental accounting.
And at Boavista we have chosen to do it with an open source approach.
What is very difficult when you're doing accounting, environmental accounting in the context of ICT
is that you must take into account all the value chain of your digital service including
the end user equipment, network, data centers, so all of the infrastructure that your service is using.
But you also need to take into account another dimension which is the lifecycle phases.
So you don't want to only include the use phase impact of the use phase but also the
impact of manufacturing the equipment that your service is running on, transporting those
equipment to their place of usage using them and also the end of life of the equipment.
Today we won't be able to dig in all of the dimension so you'll see on the slide what we're going to focus
but Boavista is working on all of the dimension here.
It's still me. So why have we decided to do open source?
So we're out for them, I think everyone here is convinced that we should do all of the data and
development with an open source process. But when we talk about environmental accounting,
it's more specifically important to follow an open approach.
First, because we believe it's a democratic necessity.
Environmental figures are often used to justify political orientation.
For instance, the Green New Deal is full of environmental figures and we believe that
citizens should be able to criticize, audit and criticize the figures that are being used to
make political orientation. Also, environmental figures and environmental accounting are used
to label product and services. I think you might have seen some data centers who said that
they are greener than greener. But to say this, you need to rely on figures, environmental figures
and often those claims are not based on open approaches and figures, which is for us a problem
since consumers cannot audit and criticize the figure.
There is also a very more straightforward argument because today environmental accounting in the context
of ICT is very immature. So the data that we use, the data that we report are of very bad quality.
To illustrate this, we've done some work. We normalize the carbon impact of manufacturing
one inch of a lead panel, so lead screen, and this is the impact for manufacturing one inch,
the carbon footprint. And you see from the five data sources that you have here, we have
a magnitude of 10 between the lowest impact and the highest impact. We could think that HP has a way
better environmental friendly process than Dell, but this is not the case. At least we cannot,
this is not the justification for this difference. This difference is, there is this difference
because all of those providers are not using the same data sources, the same hypothesis,
and the same method. And because all of those are not open, we are not able to explain you why there is
those difference. So open source should be a way, if all of those figures were based on open source approaches,
we could try to normalize those impacts, compare the provider once they get another,
and explain why different providers have different impacts.
So let's first focus on the energy footprint. So I guess the energy footprint is the part of the
ICT footprint we mostly think about when we work in ICT. That's easier to get a grasp on it.
But as David said, it's still, when we look at energy in ICT, it's still only one part of the impact.
So it's really about the usage phase. It doesn't cover the rest, which is, which can be way, way greater impact
than just the usage phase. That's also true for data centers. In what I will present to you today,
most of the information are accurate for data centers. Some of them may be applied to end user
equipment, but we didn't include specific information on network equipment. So we are going to
include specific information on network equipment for technical reasons and also because it's hard to get data on that part.
So first, a little bit of context regarding data centers. I don't know if you've seen the latest figures from the
EA. EA is International Energy Agency, and it, let's say, it's a rather conservative organism so far
regarding ICT and their own impact figures. But their latest figures is quite enlightening because we can see that in 2022
we were around 400 terawatt hour of energy consumed by data centers, which is the double from what they previously said for 2020,
which is a bit strange. And also that their projection for 2026 or in two years says that it will double again.
So around 800 terawatt hours. Part of it is because of AI, but not only. You guessed it. So this is the context.
What we can say here at least is that we are really in hyper growth trend and not the opposites. That's not what we have seen in some
medias like data centers and energy consumption is flat. That's not the case.
Then what's the issue here actually? What do you want to look at? It's not just about the energy consumption, of course.
I think I won't teach anything to anyone in this room when I say that energy consumption means that we at some point consume
oil, gas, and coal or other energy sources. This will emit greenhouse gas emissions, of course.
But we will also consume water in the process. We will consume water if we take into account the cooling of the data center.
And we will consume minerals and metals and other resources. Not all the resources that we can account for are listed on the draw.
But there are 16 environmental criteria that we take into account in Boa Vista tools.
So what do you have in your position to work on your own energy consumption of your services?
So we have talked during the day in this room about paraffin power top. There are other options as well.
Of course there are physical measurement devices. So smart PDUs, ID rack or ID low administration cards if you have them on your server.
What matters in general? This is one way. The other way is software evaluation. So those are the options that I've listed on the top.
All of them are open source solutions. If you are, let's say in a bare metal server context, you might choose power API, paraff, power top,
SkaFound. If you are in, let's say more in a development phase of software, you could use power Jula. If you are in a Kubernetes context,
Kepler or SkaFound may help you. And if you are in a machine learning context, code carbon could be of good help.
And these are some examples. What's behind the scene is actually interfaces that have been mentioned previously in the day.
So NVIDIA, SMI for getting the energy consumption of GPUs, RapeL for Intel or AMD, X86 CPUs.
And the third approach is modeling. So we could classify this as measurement. This is more about modelization.
And some of those tools also use modeling, then don't necessarily use only measurement with those interfaces.
And the Bois API is also part of it because it does modelize energy consumption and answers about what's the carbon composition of the electricity.
What, if I take the words from the previous presentation.
But when we say that we have to precise something is that both hardware and software measurement tools have their limits.
If you take the wider purple and pink squares, they represent what perimeter, a physical device will be able to measure.
So the whole machine actually, but you won't be able to zoom on what's the footprint of a software or a given component.
On the other side, if you look at the yellow and green screens, not so green, but the smaller squares here, we see this is the perimeter that RapeL is able to measure.
So a CPU, if there is an integrated GPU memory can be measured for GPUs, SMIs.
In some cases you may have a broader perimeter in RapeL, but this is for recent machines only.
So we have an issue here because we are in a trade-off between completeness of the evaluation and precision and the ability to zoom in on the footprint of one software, for example.
And so how could we fix that situation?
In Bovista we are launching a project called EnerGista, which is basically a collaborative science.
This is a collaborative database that we open and we propose voluntary organizations, individuals to share with an open source agent energy data and data about the hardware of the machine that has been measured.
Which will help us to do statistics and then at some point produce better models that will help us improve software evaluation for power evaluation.
Thank you Benoit.
So from the beginning of the presentation we've told you that the use phase and the energy consumption is not the only thing that should take into account when you want to account for the materiality of your service.
And this is where the life cycle approach comes in.
So a life cycle approach will try to take into account all of the phase of the life cycle of your service, but also all the impacts, well, most of the impacts of your criteria.
So not only carbon footprint, but depletion of minerals and usage of water, for instance.
We're going to focus here on how can you identify the environmental impact of manufacturing a server.
So it will be mostly in this area.
But at Bovista we try to have a comprehensive approach by identifying the impact of all the phase from all the value chain.
So this is a very, very partial and simplified model on how can you get the environmental materiality of a server for a specific service.
So the first step that we do when we do environmental accounting is we try to identify what is the technical infrastructure that hosts the service.
And this is often the most difficult part, because for instance if you take a function as a service that runs on AWS, it's very hard to know what is the specific consumption of resources and what is the technical material that your function is running on.
But we need this data to know and to understand what specific component is used and what is the impact of those components that we should allocate to the service.
So this is sometimes like archaeology when we need to dig and try to make some hypotheses to know how do we get from a service to its technical layer.
But once we have the technical layer, we need to go to the raw material, because this is where the impact comes from.
So we try to map all the processes that needs to be completed to assemble and build a manufacturer server.
In a simplified way, we could say that a server is an assembly of plastic for the casing and packet and components.
So CPU, RAM, Graphic Card Card and so on.
And a component has many processes, but the most impactful process is the packing process.
When you pack the dye, it's part of the components that is engraved where you have the semiconductors.
And for this, you need to have metal.
And for having the dye, you need to engrave a silicaweather.
And so as you can see, the process of engraving consumes a lot of water.
And also you need metals to, of course, produce a silicaweather.
Across all of these processes, there is the use of energy, which also will use raw material, which will cause the pollution and resource depletions.
So of course, you don't want, each time you want to assess a service, we are not going to draw this map and go until the usage of coal, oil and so on.
So what we do is we factorize the processes and we make them easier to access through the different tools we are building at Boavista.
One main tool that we have is Boavista API, which is an API that can make a translation between the ICT world with IT people and the environmental impact.
So you give to the API a technical configuration.
It can describe a digital service, an equipment, a component.
And the API will give you back environmental impact, not only on global warming, so not only on the carbon footprint.
But for instance, on other impacts that has primary energy that you should know if you know a little bit about energy and abiotic depletion potential, which is a criteria that assess the removal of non-renewable resources.
So this includes minerals and fossil resources.
Around the API, we built, so our architecture is in microservices, so the API is a central microservice.
But we have other tools, such as Cloud Scanner, which will scan an AWS account and try to assess with the API the impact of the AWS account.
And we have also a pedagogical front end, which is called DataVista, which is based on the API, but it's just a nice layer on top of the API for people who doesn't want to manipulate API.
So for instance, here is a way to assess the impact of a server.
And you see you can configure a server.
For instance, let's say that I have one CPU.
Demo effect, where it's just, okay, I put an L.
I can also change the location where I use a server.
So this will chase the carbon footprint of the electricity where the server is running.
So I invite you to play with this tool and see a little bit what is the main cause of the impact, both from the manufacturer and the use face.
And also the manufacturer impact, you can have it by component.
So it's also interesting to see which component is most impactful.
There is also other features, which are also in the API.
You can assess the impact of your cloud usage, for instance, or of end user devices, but we haven't introduced those during the talk.
Yeah.
The API is you can scan the QR code and this will get you to the repository of the BoaVista API.
We wanted to open up this talk.
So we've begun by talking about energy.
Then we took a broader approach with the life cycle approach, life cycle assessment approach.
And we wanted to open up with an even more systemic approach, which I call systemic footprint, but it could be also called a consequential approach.
Yeah.
From the beginning of the presentation, we'll talk, we've talked about the direct impact of digital service.
So it means the impact of the value chain of the service.
But maybe sometimes the most impactful part of digital service, it's not just direct footprint, but it is the indirect externalities, environmental externalities that is brought by the fact of deploying your service.
Your service, you're doing your service for some usages and you need to be careful on why your service is used and how your service is used, because this might be, this service might be used to make environmental harm.
So when you want to understand what is the consequences of launching your service, you need to take another approach, which is a causal approach, and trying to map the different causes and consequences that are, that follow the introduction of your software.
For instance, if you take a cloud provider, cloud are known to be often more mutualized and more optimized in time of energy, energy usage and carbon footprint.
But since we have consumed, since cloud is very easily accessed, we are consuming way more compute resources than we did before.
So this is what we call the rebound effect.
And this is something that we can get from a basic life cycle analysis.
We need to have a more systemic approach to, to understand all of those social transformation that is brought by ICT.
And I think we're done in.
Thank you for your attention.
We have some minutes left for questions.
Yes, it was very interesting.
But so the problem is that everybody must know this kind of thing for in collaboration to climate, environment and so on.
And because there is no studies of Greenpeace about this kind of thing, about energy provider.
Yes, in Belgium, but so this kind of thing is very difficult of because so I know that the three said what is French?
I don't know in English.
So I'm a Amazon Web Service.
Yes, so and this, this kind of thing is very, very, very important to their data centers, how it's take off energy, its, its harm effect on the river or something like that.
So, so all this kind of thing for the construction of, of a computer and so on.
I would like to have that is an, an, an Greenpeace barometers of this kind of thing everywhere.
So because it's very important for our future.
So also when dissipate energy in a river, a separation of energy and so on.
So your remark is about awareness, I think.
So there, there, I think there is no report from Greenpeace, but there is a report from WWF at least.
And I think the, the main purpose of Boa Vista and the tools that we're building is not efficiency, but it's more making people aware of those problems and taking action because I think, and I think we can, we can talk for both of us.
We think that having more IT people engage is one way to, to fight against those, this, this, the impact of IT.
Hello, thank you very much for this.
When you were presenting the server impact thing, I have a technical question.
There was a discussion about jewels and primary energy as opposed to something that we might use like kilowatt hours, which is quite common.
Could you maybe talk a little bit about why you chose that rather than a figure that we see used in lots of other places?
Because that is something that I found a little bit difficult to understand when I first looked at it.
So primary energy versus secondary energy.
If you could explain some of that and explain the decision to choose one versus what hours, for example, instead of jewels.
Yeah.
You want to answer?
Why do we express primary energy in jewels?
Yeah, what I can say, but I don't know if it's an accurate answer, but in practical terms, jewels are very used for very precise measurement purposes.
Most of the time when we talk about big figures, we are more about what hours, kilowatt hours, megawatt hours and so on.
What's its power?
So it's not expressed on a timeframe.
That has been said in a previous talk.
I don't know if it clarifies or...
Yeah.
Oh, okay.
Actually, I understand the confusion.
Primary energy is an impact criteria.
Secondary energy is a flow.
So it's not considered a final impact.
We use...
If you see here, let's say, we can model the secondary energy, the power usage here, in what?
And we use it to compute the usage impacts for the difference impact criteria.
Primary energy is how do you deplete earth from primary energy?
Does it?
Maybe you're time for one.
Maybe you can do both.
So the question is, because of some countries now don't want any more of the rubbish servers from our countries,
did the data centers change the policy in terms of management, for example, for the storage system?
At Google, they used to break the hardware into small pieces, not even recycling them at all.
And where there are changes recently for the spare parts management?
Because of the fact that countries don't want to make the recycling any more offshore countries.
Actually, that's a very complicated talk.