GreenOps with Greenpixie

Environment Variables

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Host Chris Adams sits down with James Hall, Head of GreenOps at Greenpixie, to explore the evolving discipline of GreenOps—applying operational practices to reduce the environmental impact of cloud computing. They discuss how Greenpixie helps organizations make informed sustainability decisions using certified carbon data, the challenges of scaling cloud carbon measurement, and why transparency and relevance are just as crucial as accuracy. They also discuss using financial cost as a proxy for carbon, the need for standardization through initiatives like FOCUS, and growing interest in water usage metrics.

Learn more about our people:

Chris Adams: LinkedIn | GitHub | Website
James Hall: LinkedIn
Greenpixie: Website

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News:

Resources:

Cloud Carbon Footprint [00:46]
Greenops - Wikipedia [02:18]
Software Carbon Intensity (SCI) Specification [05:12]
GHG Protocol [05:20]
Energy Scores for AI Models | Hugging Face [44:30]
What is GreenOps - Newsletter | Greenpixie [44:42]
Making Cloud Sustainability Actionable with FinOps
Fueling Sustainability Goals at Mastercard in Every Stage of FinOps

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TRANSCRIPT BELOW:

James Hall: We want get the carbon data in front of the right people so they can put climate impact as part of the decision making process. Because ultimately, data in and of itself is a catalyst for change.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello and welcome to Environment Variables where we explore the developing world of sustainable software development. We kicked off this podcast more than two years ago with a discussion about cloud carbon calculators and the open source tool, Cloud Carbon Footprint, and Amazon's cloud carbon calculator.

And since then, the term GreenOps has become a term of art in cloud computing circles when we talk about reducing the environmental impact of cloud computing. But what is GreenOps in the first place? With me today is James Hall, the head of GreenOps at Greenpixie, the cloud computing startup, cloud carbon computing startup,

to help me shed some light on what this term actually means and what it's like to use GreenOps in the trenches. James, we have spoken about this episode as a bit of a intro and I'm wondering if I can ask you a little bit about where this term came from in the first place and how you ended up as the def facto head of GreenOps in your current gig.

Because I've never spoken to a head of GreenOps before, so yeah, maybe I should ask you that.

James Hall: Yeah, well, I've been with Greenpixie right from the start, and we weren't really using the term GreenOps when we originally started. It was cloud sustainability. It was about, you know, changing regions to optimize cloud and right sizing. We didn't know about the FinOps industry either. When we first started, we just knew there was a cloud waste problem and we wanted to do something about it.

You know, luckily when it comes to cloud, there is a big overlap between what saves costs and what saves, what saves carbon. But I think the term GreenOps has existed before we started in the industry. I think it, yeah, actually originally, if you go to Wikipedia, GreenOps, it's actually to do with arthropods and Trilobites from a couple million years ago, funnily enough, I'm not sure when it started becoming, you know, green operations.

But, yeah, it originally had a connotation of like data centers and IT and devices and I think Cloud GreenOps, where Greenpixie specializes, is more of a recent thing because, you know, it used to be about, yeah, well it is about how do you get the right data in front of the right people so they can start making better decisions, ultimately.

And that's kind of what GreenOps means to me. So Greenpixie are a GreenOps data company. We're not here to make decisions for you. We are not a consultancy.

We want get the carbon data in front of the right people so they can put climate impact as part of the decision making process. Because ultimately, data in and of itself is a catalyst for change.

You know, whether you use this data to reduce carbon or you choose to ignore it, you know, that's up to the organization. But it's all about being more informed, ignoring or, you know, changing your strategy around the carbon data.

Chris Adams: Cool. Thank you for that, James. You mentioning Wikipedia and Greenops being all about Trilobites and Arthropods, it makes me realize we definitely should add that to the show notes and that's the thing I'll quickly just do because I forgot to just do the usual intro folks. Yeah, my name's Chris Adams.

I am one of the policy director, technology and policy director at the Green Web Foundation, and I'm also the chair of the policy working group inside the Green Software Foundation. All the things that James and I'll be talking about, we'll do our best to judiciously add show notes so you can, you too can look up the origins of, well, the etymology of GreenOps and find out all about arthropods and trilobites and other.

And probably a lot more cloud computing as well actually. Okay. Thank you for that James. So you spoke a little and you did a really nice job of actually introducing what Greenpixie does. 'Cause that was something I should have asked you earlier as well. So I have some experience using these tools, like Cloud Carbon Footprint and so on to estimate the environmental impact of digital services. Right. And a lot of the time these things use billing data. So there are tools out there that do already do this stuff. But one thing that I saw that sets Greenpixie apart from some other tools as well, was the actual, the certification process, the fact that you folks have, I think, an ISO 14064 certification.

Now, not all of us read over ISO standards for fun, so can you maybe explain why that matters and what that actually, what that changes at all, or even what that certification means? 'Cause, It sounds kind of impressive and exciting, but I'm not quite sure, and I know there are other standards floating around, like the Software Carbon Intensity standard, for example.

Like yeah, maybe you could just provide an intro, then see how that might be different, for example.

James Hall: Yeah, so ISO 14064 is a kind of set of standards and instructions on how to calculate a carbon number, essentially based on the Greenhouse Gas Protocol. So the process of getting that verification is, you know, you have official auditors who are like certified to give out these certifications, and ultimately they go through all your processes, all your sources, all the inputs of your data, and kind of verify that the outputs and the inputs

make sense. You know, do they align with what the Greenhouse Gas Protocol tells you to do? And, you know, it's quite a, it's a year long process as they get to know absolutely everything about your business and processes, you really gotta show them under the hood. But from a customer perspective, it means you know, that it proves that

the methodology you're using is very rigorous and it gives them confidence that they can use yours. I think if a company that produces carbon data has an ISO badge, then you can probably be sure that when you put this data in your ESG reports or use it to make decisions, the auditors will also agree with it.

'Cause the auditors on the other side, you know, your assurers or from EY and PWC, they'll be using the same set of guidance basically. So it's kind of like getting ahead of the auditing process in the same way, like a security ISO would mean the security that the chief security officer that would need to, you know, check a new vendor that they're about to procure from.

If you've got the ISO already, you know they meet our standards for security, it saves me a job having to go and look through every single data processing agreement that they have.

Chris Adams: Gotcha. Okay. So there's a few different ways that you can kind of establish trust. And so one of the options is have everything entirely open, like say Cloud Carbon Footprint or OpenCost has a bunch of stuff in the open. There's also various other approaches, like we maintain a library called CO2.js, where we try to share our methodologies there and then one of the other options is certification. That's another source of trust. I've gotta ask, is this common? Are there other tools that have this? 'Cause when I think about some of the big cloud calculators, do you know if they have this, let's say I'm using say, a very, one of the big three cloud providers.

Do these have, like today, do you know if they actually have the same certification or is that a thing I should be looking for or I should be asking about if I'm relying on the numbers that I'm seeing from our providers like this.

James Hall: Yeah, they actually don't. Well, technically, Azure. Azure's tool did get one in 2020, but you need to get them renewed and reordered as part of the process. So that one's kind of becoming invalid. And I'm not sure AWS or Google Cloud have actually tried, to be honest, but it's quite a funny thought that, you know, it's arguably because this ISO the, data we give you on GCP and AWS is more accurate than the data, or at least more reliable than the data that comes directly out the cloud providers.

Chris Adams: Okay. Alright. Let's, make sure we don't get sued. So I'm just gonna stop there before we go any further. But that's like one of the things that it provides. Essentially it's an external auditor who's looked through this stuff. So rather than being entirely open, that's one of the other mechanisms that you have.

Okay, cool. So maybe we can talk a little bit more about open source. 'Cause I actually first found out about Greenpixie a few years ago when the Green Software Foundation sent me to Egypt, for COP 27 to try and talk to people about green software. And I won't lie, I mostly got blank looks from most people.

You know, they, the, I, there are,

people tend to talk about sustainability of tech or sustainability via tech, and people tend not to see them as, most of the time I see people like conflating the two rather than actually realizing no, we're talking about of the technology, not just how it's good for stuff, for example, and he told me, I think one of your colleagues, Rory, was this, yeah.

He was telling me a bit about, that Greenpixie was initially using, when you just first started out, you started looking at some tools like Cloud Carbon Footprint as maybe a starting point, but you've ended up having to make various changes to overcome various technical challenges when you scale the use up to like a large, to well, basically on a larger clients and things like that. Could you maybe talk a little bit about some of the challenges you end up facing when you're trying to implement GreenOps like this? Because it's not something that I have direct experience myself. And it's also a thing that I think a lot of people do reach for some open source tools and they're not quite sure why you might use one over the other or what kind of problems they, that they have to deal with when you start processing that, those levels of like billing and usage data and stuff like that.

James Hall: I think with the, with cloud sustainability methodologies, the two main issues are things like performance and the data volume, and then also the maintenance of it. 'Cause just the very nature of cloud is you know, huge data sets that change rapidly. You know, they get updated on the hour and then you've also got the cloud providers always releasing new services, new instance types, things like that.

So, I mean, like your average enterprises with like a hundred million spend or something? Yeah. Those line items of usage data, if you like, go down to the hour will be billions of rows and terabytes of data. And that is not trivial to process. You know, a lot of the tooling at the moment, including Cloud Carbon Footprint, will try to, you know, use a bunch of SQL queries to truncate it, you know, make it go up to monthly.

So you kind of take out the rows by, you know, a factor of 24 times 30 or whatever that is. It's about 740, I think. Something like that (720). Yeah. Yeah. So, and they'll remove things like, you know, there's certain fields in the usage data that will, that are so unique that when you start removing those and truncating it, you're really reducing the size of the files, but you are really losing a lot of that granularity.

'Cause ultimately this billing data is to be used by engineers and FinOps people. They use all these fields. So when you start removing fields because you can't handle the data, you're losing a lot of the familiarity of the data and a lot of the usability for the people who need to use it to make decisions.

So one of the big challenges is how do you make a processor that can easily handle billions of line items without, you know, falling over. And CCF, one of the issues was the performance really when you start trying to apply it to big data sets. And then on the other side is the maintenance.

You know, arguably it's probably not that difficult to make a methodology of a point in time, but you know, over the six months it takes you to create it, it's way out date. You know, they've released a hundred new instance types across the three providers. There's a new type of storage, there's a brand new services, there's new AI models out there.

And so now, like Greenpixie's main job is how do we make sure the data is more, we have more coverage of all the skews that come out and we can deliver the data faster and customers have more choices of how to ingest it. So if you give customers enough choice and you give it to them quick enough and it's, you know, covering all of their services, then you know, that's what those, lack of those three things is really what's stopping people from doing GreenOps, I think.

Chris Adams: Ah, okay, so one of them was, one of the things you mentioned was just the volume, the fact that you've got, you know, hours multiply the number of different, like a thousand different computers or thousands of computers. That's a lot of data. And then there's a, there's like one of the issues about like the metrics issue, like you, if you wanna provide a simple metric, then you end up losing a lot of data.

So that's one of the things you spoke about. And the other one was just the idea of models themselves not being, there's natural cost associated with having to maintain these models. And as far as I'm aware, there aren't, I mean, are there any kind of open sources of models so that you can say, well this is what the figures probably would be for an Amazon EC, you know, 6XL instance, for example.

That's the stuff you're talking to when you say the models that you, they're hard to actually up to, hard to keep up to date, and you have to do that internally inside the organization. Is that it?

James Hall: Yes, we've got a team dedicated to doing that. But ultimately, like there will always be assumptions in there. 'Cause some of these chip sets you actually can't even get your hands on. So, you know, if Amazon release a new instance type that uses an Intel Xeon 7850C, that is not commercially available.

So how do you get your hands on an Intel Xeon 7850B that is commercially available and you're like, okay, it, these six things are similar in terms of performance in hardware. So we're using this as the proxy for the M5 large or whatever it is. And then once you've got the power consumption of those instance types,

then you can start saying, okay, this is how we, this is how we're mapping instances to real life hardware. And then that's when you've gotta start being really transparent about the assumptions, because ultimately there's no right answer. All you can do is tell people, this is how we do it. Do you like it?

Do you?

And you know, over the four years we've been doing this, you know, there's been a lot of trial and error. Actually, right at the start, one of the questions was, what are my credentials? How did I end up as head of GreenOps? I wouldn't have said four years ago I have any credentials to be, you know, a head of GreenOps.

So it was a while when I was the only head of GreenOps in the world, according to a Sales Navigator. Why me? But I think it's like, you know, they say if you do 10,000 hours of anything, you kind of, you become good at it. And I wouldn't say I'm a master by any means, but I've made more mistakes and probably tried more things than anybody else over the four years.

So, you know, just, from the war stories, I've seen what works. I've seen what doesn't work. And I think that's the kind of, that's the kind of experience people wanna trust. And why Greenpixie made me the head of GreenOps.

Chris Adams: Okay. All right. Thanks for that, James. So maybe this is actually a nice segue to talk about a common starting point that lots of people do actually have. So over the last few years, we've also seen people talk about move from not moved away, not just talking about DevOps, but talking about like FinOps.

This idea that you might apply kind of some financial thinking to how you purchase and consume, say, cloud services for example. And this tends to, as far as I understand, kinda nudge people towards things like serverless or certain kinds of ways of buying it in a way, which is almost is, you know, very much influenced by fi by I guess the financial sector.

And you said before that there's some overlap, but it's not totally over there, it's not, you can't just basically take a bunch of FinOps practices and think it's gonna actually help here. Can we explore that a bit and maybe talk a little bit about what folks get wrong when they try to like map this straight across as if it's the same thing?

Please.

James Hall: Yeah, so one of the big issues is cost proxies, actually. Yeah, a lot of FinOps as well, how do you fix, or how do you optimize from a cost perspective? What already exists? You know, you've already emitted it. How do you now make it cheaper? The first low hanging fruit that a finance guy trying to reduce their cloud spend would do is things like, you know, buy the instances up front.

So you've paid for the full year and now you've been given a million hours of compute.

That would might, that might cut your bill in half, but if anything that would drive your usage up, you know, you've got a million hours, you are gonna use them.

Chris Adams: Commit to, so you have to commit to then spending a billion. You're like, "oh, great. I have the cost, but now I definitely need to use these." Right?

James Hall: Yeah, exactly. And like, yeah, you say commitments. Like I promise AWS I'm gonna spend $2 million, so I'm gonna do whatever it takes to spend that $2 million. If I don't spend $2 million, I'll actually have to pay the difference. So if I only do a million in compute, I'm gonna have to pay a million and get nothing for it.

So I'm gonna do as much compute as humanly possible to get the most bang for my back. And I think that's where a lot of the issues is with using costs. Like if you tell someone something's cheap, they're not gonna use less, they're gonna be like, "this looks like a great deal." I'm guilty of it myself. I'll buy clothes I don't need 'cause it's on a clearance sale.

You know? And that's kind of how cloud operates. But when you start looking at, when you get a good methodology that really looks at the usage and the nuances between chip sets and storage tiers, you know, there is a big overlap between, you know, cutting the cost from a 2X large to a large that may halve your bill, and it will halve your carbon. And that's the kind of things you need to be looking out for. You need a really nuanced methodology that really looks at the usage more than just trying to use costs.

Chris Adams: Okay, so that's one place where it's not so helpful. And you said a little bit like there are some places where it does help, like literally just having the size of the machine is one of the things you might actually do. Now I've gotta ask, you spoke before about like region shifting and stuff, something you mentioned before.

Is there any incentive to do anything like that when you are looking at buying stuff in this way? Or is there any kind of, what's the word I'm after, opinion that FinOps or GreenOps has around things like that because as far as I can tell, there isn't, there is very rarely a financial incentive to do anything like that.

If anything, it costs, usually costs more to use, maybe say, run something in, say Switzerland for example, compared to running an AWS East, for example. I mean, is that something you've seen, any signs of that where people kind of nudge people towards the greener choice rather than just showing like a green logo on a dashboard for example?

James Hall: Well, I mean, this is where GreenOps comes into its own really, because I could tell everyone to move to France or Switzerland, but when you come to each individual cloud environment, they will have policies and approved regions and data sovereignty things, and this is why all you can do is give them the data and then let the enterprise make the decision. But ultimately, like we are working with a retailer who had a failover for storage and compute, but they had it all failing over to one of the really dirty regions, like I think they were based in the UK and they failed over to Germany, but they did have Sweden as one of the options for failover, and they just weren't using it.

There's no particular reason they weren't using it, but they had just chosen Germany at one point. So why not just make that failover option Sweden? You know, if it's within the limits of your policies and what you're allowed to do. But, the region switching is completely trivial, unfortunately, in the cloud.

So you know, you wouldn't lift and shift your entire environment to another place because there are performance, there are cost implications, but again, it's like how do you add sustainability impact to the trade-off decision? You know, if increasing your cost 10% is worth a 90% carbon reduction for you, great.

Please do it if you know the hours of work are worth it for you. But if cost is the priority, where is the middle ground where you can be like, okay, these two regions are the same, they have the same latency, but this one's 20% less carbon. That is the reason I'm gonna move over there. So it's all about, you've already, you can do the cost benefit analysis quite easily, and many people do.

But how do you enable them to do a carbon benefit analysis as well? And then once they've got all the data in front of them, just start making more informed decisions. And that's why I think the data is more important than, you know, necessarily telling them what the processes are, giving them the, here's the Ultimate Guide to GreenOps. You know, data's just a catalyst for decisions and if you just need to give them trustworthy data. And then how many use cases does trustworthy data have? You know, how many, how long is a piece of string? I've seen many, but every time there's a new customer, there's new use cases.

Chris Adams: Okay, cool. Thank you for that. So, one thing that we spoke before in this kind of pre-call was the fact that, sustainability is becoming somewhat more mainstream. And there's now, within the kind of FinOps foundation or the people who are doing stuff for FinOps are starting to kind of wake up to this and trying to figure out how to incorporate some of this into the way they might kind of operate a team or a cloud or anything like that.

And you. I believe you told me about a thing called FOCUS, which is, this is like something like a standardization project across all the FinOps and then, and now there's a sustainability working group, particularly inside this FOCUS group. For people who are not familiar with this, could you tell me what FOCUS is and what this sustainability working group as well working on?

You know, 'cause working groups are supposed to work on stuff, right?

James Hall: Yeah, so as exactly as you said, FOCUS is a standardization of billing data. So you know, when you get your AWS bill, your Azure bill, they have similar data in them. But they will be completely different column names. Completely different granularities, different column sizes. And so if you're trying to make a master report where you can look at all of your cloud and all of your SaaS bills, you need to do all sorts of data transformations to try and make the columns look the same.

You know, maybe AWS has a column that goes one step more granular than Azure, or you're trying to, you know, do a bill on all your compute, but Azure calls it virtual machines. AWS calls it EC2. So you either need to go and categorize them all yourself to make a, you know, a master category that lets you group by all these different things or, you know, thankfully FOCUS have gone and done that themselves, and it started off as a, like a Python script you could run on your own data set to do the transformation for you, but slowly more cloud providers are adopting the FoCUS framework, which means, you know, when you're exporting your billing data, you can ask AWS give me the original or give me a FOCUS one. So they start giving you the data in a way where it's like, I can easily combine all my data sets. And the reason this is super interesting for carbon is because, you know, carbon is a currency in many ways, in the fact that the,

Chris Adams: there's price on it in Europe. There's a price on it in the UK. Yeah.

James Hall: There's a price on it, but also like the way Azure will present you, their carbon data could be, you know, the equivalent of yen, AWS could be the equivalent of dollars.

They're all saying CO2 E, so you might think they're equivalent, but actually they're almost completely different currencies. So this effort of standardization is how do we bring it back? Maybe like, don't give us the CO2 E, but how do we go a few steps before that point and like, how do we start getting similar numbers?

So when we wanna make a master report for all the cloud providers, it's apples to apples, not apples to oranges. You know, how do we standardize the data sets to make the reporting, the cross cloud reporting more meaningful for FinOps people?

Chris Adams: Ah, I see. Okay. So I didn't realize that the FOCUS stuff has actually listing, I guess like what the, let's, call them primitives, like, you know, compute and storage. Like they all have different names for that stuff, but FOCUS has a kind of shared idea for what the concept of cloud compute, a virtual machine might be, and likewise for storage.

So that's the thing you are trying, you're trying to apply, attach a carbon value to in these cases, so you can make some meaningful judgment or so you can present that information to people.

James Hall: Yeah, it's about making the reports at the same, but also how do you make the numbers, the source of the numbers more similar? 'Cause currently, Azure may say a hundred tons in their dashboard. AWS may say one ton in their dashboard. You know, the spend and the real carbon could be identical, but it's just the formula behind it is so vastly different that you're coming out with two different numbers.

Chris Adams: I see. I think you're referring to at this point here. Some places they might share a number, which is what we refer to as a location based figure. So that's like, what was kind of considered on the ground based on the power intensity from the grid in like a particular part of the world.

And then a market based figure might be quite a bit lower. 'Cause you said, well, we've purchased all this green energy, so therefore we are gonna kind of deduct that from what a figure should be. And that's how we'd have a figure of like one versus 100. But if you're not comparing these two together. It's gonna, these are gonna look totally different.

And you, like you said, it's not apples. With apples. It's apples with very, yeah. It's something totally different. Okay. That is helpful.

James Hall: It gets a lot more confusing than that 'cause it's not just market and location based. Like you could have two location based numbers, but Azure are using the grid carbon intensity annual average from 2020 because that's what they've got approved. AWS may be using, you know, Our World in Data 2023 number, you know, and those are just two different sources for grid intensity.

And then what categories are they including? Are they including Scope 3 categories? How many of the scope 2 categories are they including? So when you've got like a hundred different inputs that go into a CO2 number, unless all 100 are the same, you do not have a meaningful comparison between the two.

Even location/market based is just one aspect of what goes into the CO2 number, and then where do they get the kilowatt hour numbers from? Is it a literal telemetry device? Or are they using a spend based property on their side? Because that's not completely alien to cloud providers to ultimately rely on spend at the end of the day.

So does Azure use spend or does AWS use spend? What type of spend are they using? And that's where you need the transparency as well, because if you don't understand where the numbers come from, it could be the most accurate number in the world, but if they don't tell you everything that went into it, how are you meant to know?

Chris Adams: I see. Okay. That's really interesting. 'Cause the Green Web Foundation, the organization I'm part of, there is a gov, there's a UK government group called the Government Digital Sustainability Alliance. And they've been doing these really fascinating lunch and learns and

one thing that showed up was when the UK government was basically saying, look, these are, this is the carbon footprint, you know, on a kind of per department level. Like this is what the Ministry of Justice is, or this is what say the Ministry of Defense might be, for example. And that helps explain why you had figures where you had a bunch of people saying the carbon footprint of all these data centers is really high.

And then you said they, there were people talking about saying, well, we're comparing this to cloud looks great, but 'cause the figures for cloud are way lower. But the thing they, the thing that I was that people had to caveat that with, they basically said, well, we know that this makes cloud look way more efficient here, and it looks like it's much more, much lower carbon, but because we've only got this final kind of market based figure, we know that it's not a like for like comparison, but until we have that information, we're, this is the best we actually have. And this, is an organization which actually has like legally binding targets. They have to reduce emissions by a certain figure, by a certain date. This does seem like it has to be, I can see why you would need this transparency because it seems very difficult to see how you could meaningfully track your progress towards a target if you don't have access to that.

Right?

James Hall: Yeah. Well,

I always like to use the currency conversion analogy. If you had a dashboard where AWS is all in dollars, Azure, or your on premise is in yen. There's 149 yen in 1 dollar. So, but if you didn't know this one's yen and this one's dollars, you'd be like, "this one's 149 times cheaper. Why aren't we going all in on this one?"

But actually it's just different currencies. And they are the same at the end of the day. Under the hood, they're the same. But, know, just the way they've turned it into an accounting exercise has kind of muddied the water, which is why I love electricity metrics more. You know, they're almost like the, non fungible token of, you know, data centers and cloud.

'Cause you can use that to calculate location-based. You can use calculate market-based. You can use electricity to calculate water cooling and metrics and things like that. So if you can get the electricity, then you're well on your way to meaningful comparisons.

Chris Adams: And that's the one that everyone guards very jealously a lot of the time, right?

James Hall: Exactly. Yeah. Well that's directly related to your cost of running business and that is the proprietary information.

Chris Adams: I see. Okay. Alright, so we spoke, we've done a bit of a deep dive into the GSG protocol, scope 3, supply chain emissions and things like that. If I may, you mentioned, you, referenced this idea of war stories before. Right. And I. It's surprisingly hard to find people with real world stories about okay, making meaningful changes to like cloud emissions in the world.

Do you have any like stories that you've come across in the last four years that you think are particularly worth sharing or that might be worth, I dunno, catch people's attention, for example. Like there's gotta be something that you found that you are allowed to talk about, right.

James Hall: Yeah, I mean, MasterCard, one of our Lighthouse customers, they've spoken about the work we're doing with them a lot in, at various FinOps conferences and things like that. But they're very advanced in their GreenOps goals. They have quite ambitious net zero goals and they take their IT sustainability very seriously.

Yeah, when we first spoke to them. Ultimately the name of the game was to get the cloud measurement up to the point of their on-premise. 'Cause their on-premise was very advanced, daily electricity metrics with pre-approved, CO2 numbers or CO2 carbon coefficients that multiplied the, you multiply the electricity with.

But they were getting, having no luck with cloud, essentially, you know, they spend a lot in the cloud and, but they, they were honestly like, rather than going for just the double wins, which is kind of what most people wanna do, where it's like, I'm gonna use this as a mechanism to save more money.

They honestly wanted to do no more harm and actually start making decisions purely for the sustainability benefits. And we kind of went in there with the FinOps team, worked on their FinOps reporting, combined it with their FinOps recommendations and the accountability, which is their tool of choice.

But then they started having more use cases around. How do they use our carbon data, not our electricity data from the cloud or like, because we have a big list of hourly carbon coefficients. They wanna use that data to start choosing where they put their on-premise data centers as well, and like really making the sustainability impact a huge factor in where they place their regions, which I think is a very interesting one. 'Cause we had only really focused on how do we help people in their public cloud. But they wanted to align their on-premise reporting with their cloud reporting and ultimately start even making decisions. Okay, I know I need to put a data center in this country.

Do I go AWS, Azure, or on-prem for this one? And what is the sustainability impact of all three? And, you know, how do I weigh that against the cost as well? And it's kind of like the golden standard of making sustainability a big part of the trade-off decision. 'Cause they would not go somewhere, even if it saved them 50% of their cost, if it doubled their carbon. They're way beyond that point. So they're a super interesting one. And even in public sector as well, like the departments we are working with are relatively new to FinOps and they didn't really have like a proper accountability structure for their cloud bill. But when you start adding carbon data to it, you are getting a lot more eyes onto the, onto your bills and your usage.

And ultimately we help them create that more of a FinOps function just with the carbon data. 'Cause people find carbon data typically more interesting than spend data. But if you put them on the same dashboard, now it's all about how do you market efficient usage? And I think that's one of the main, use cases of GreenOps is to get more eyes or more usage.

So, 'cause the more ideas you've got piling in, the more use cases you find and.

Chris Adams: Okay. Alright, so we spoke, so you spoke about carbon as one of the main things that people are caring about, right. And we're starting to develop more of an awareness that maybe some data centers might themselves be exposed to kind of climate risks themselves. Because I know they were built on a floodplain, for example.

And you don't want a data center on a floodplain in the middle of a flood, for example. Right. but there's also like the flip side, you know, that's too much water. But there are cases where people worry about not enough water, for example. I mean, is that something that you've seen people talk about more of?

Because there does seem to be a growing awareness about the water footprint of digital infrastructure as well now. Is that something you're seeing people track or even try to like manage right now?

James Hall: Well,

we find that water metrics are very popular in the US more so than the CO2 metrics, and I think it's because the people there feel the pain of lack of water. You know, you've got the Flint water crisis. In the UK, we've got an energy crisis stopping people from building homes. So what you really wanna do is enable the person who's trying to use this data to drive efficiency, to tell as many different stories as

is possible,. You know, the more metrics and the more choice they have of what to present to the engineers and what to present to leadership, the better outcomes they're gonna get. Water is a key one because data centers and electricity production uses tons of water. And the last thing you wanna do is, you know, go to a water scarce area and put a load of servers in there that are gonna guzzle up loads of water. One, because if that water runs out, your whole data center's gonna collapse. So it's, you're exposing yourself to ESG risk. And also, you know, it doesn't seem like the right thing to do. There are people trying to live there who need to use that water to live.

But you know, you've got data centers sucking that water out, so you know, can't you use this data to again, drive different decisions, could invoke an emotional response that helps people drive different decisions or build more efficiently. And if you're saving cost at the end of that as well, then everyone's happy.

Chris Adams: So maybe this is actually one thing we can talk about because, or just like, drill into before we kind of, move on to the next question and wrap up. So we, people have had incentives to track cost and cash for obvious reasons, carbon, as you're seeing more and more laws actually have opinions about carbon footprint and being able to report that people are getting a bit more aware of it.

Like we've spoken about things like location based figures and market based figures. And we have previous episodes where we've explored and actually kind of helped people define those terms. But I feel comfortable using relatively technical terminology now because I think there is a growing sophistication, at least in certain pockets, for example.

Water still seems to be a really new one, and it seems to be very difficult to actually have, find access to meaningful numbers. Even just the idea of like water in the first place. Like you, when you hear figures about water being used, that might not be the same as water. Kind of.

It's not, it might not be going away, so it can't be used. It might be returned in a way that is maybe more difficult to use or isn't, or is sometimes it's cleaner, sometimes it's dirtier, for example. But this, it seems to be poorly understood despite being quite an emotional topic. Have you, yeah, what's your experience been like when people try to engage with this or when you try to even find some of the numbers to present to people and dashboards and things?

James Hall: Yeah. So yeah, surprisingly, all the cloud providers are able to produce factors. I think it's actually a requirement that when you have a data center, you know what the power usage effectiveness is, so what the overhead electricity is, and you know what the water usage effectiveness is. So you know, what is your cooling system, how much water does it use, how much does it withdraw?

Then how much does it actually consume? So the difference between withdrawal and consumption, is withdrawal is you let you take clean water out, you're able to put clean water back relatively quickly. Consumption is you have either poisoned the water with some kind of, you know, you've diluted it or you know, with some kind of coolant that's not fit for human consumption or you've now evaporated it.

And there is some confusion sometimes around "it's evaporated, but it'll rain. It'll rain back down." But, you know, a lake's evaporation and redeposition processs is ike a delicate balance. If it, you know, evaporates 10,000 liters a day and rains 10,000 liters a day after, like a week of it going into the clouds and coming back down the mountain nearby.

If you then have a data center next to it that will accelerate the evaporation by 30,000 leases a day, you really upset the delicate balance that's in there and that, you know, you talk about are these things sustainable? Like financial sustainability is, do you have enough money and income to last a long time, or will your burn rate run out next month?

And it's the same with, you know, sustainability. I think fresh water is a limiting resource in the same way a company's bank balance is their limiting resource. There's a limited amount of electricity, there's a limited amount of water out there.

I think it was the cEO of Nvidia. I saw a video of him on LinkedIn that said, right now the limit to your cloud environment is how much money you can spend on it.

But soon it will be how much electricity is there? You know, you could spend a trillion dollars, but if there's no more room for electricity, there's no more electricity to be produced, then you can't build anymore data centers or solar farms. And then water's the other side of that.

I think water's even worse because we need water to even live. And you know what happens when there's no more water because the data centers have it. I think it invokes a much more emotional response. When you have good data that kind of is backed by good sources, you can tell an excellent story of why you need to start reducing.

Chris Adams: Okay, well hopefully we can see more of those numbers because it seems like it's something that is quite difficult to get access to at the moment. Water's it, water in particular. Alright, so we're coming to time now and one thing we spoke about in the prep call was talking about the GSG protocol.

We did a bit but nerd like nerding into this and you spoke a little bit about yes, accuracy is good, but you can't just only focus on accuracy if you want someone to actually use any of the tools or you want people to adopt stuff, and you said that in the GHG protocol, which is like the gold standard for people working out kind of the, you know, carbon footprint of things.

You said that there were these different pillars inside of that matter. And if you just look at accuracy, that's not gonna be enough. So can you maybe expand on that for people who maybe aren't as familiar with the GSG protocol as you? Because I think there is something that, I think, that there, there's something there that's worth, I think, worth exploring.

James Hall: Yeah. So it just as a reminder for those out there, the pillars are accuracy, yes, completeness, consistency, transparency, and relevance. A lot of people worry a lot about the accuracy, but, you know, just to give an example that if you had the most amazing, accurate number for your entire cloud environment, you know, 1,352 tons 0.16 grams, but you are one engineer under one application, running a few resources, the total carbon number is completely

useless to you, to be honest. Like how do you make, use that number to make a decision for your tiny, you know, maybe five tons of information. So really you've got to balance all of these things. You know, the transparency is important because you need to build trust in the data. People need to understand where it comes from.

The relevance is, you know, again, are you filtering on just the resources that are important to me? And the consistency touches on, aWS is one ton versus Azure is 100 tons. You can't decide which cloud provider to go into based on these numbers because you know, they're marking their own homework. They've got a hundred different ways to calculate these things. And then the completeness is around, if you're only doing compute, but 90% is storage, you are missing out on loads of information. You know, you could have a super accurate compute for Azure, but if you've got completely different numbers for AWS and you dunno where they come from, you've not got a good data set, a good GreenOps data set to be able to drive decisions or use as a catalyst.

So you really need to prioritize all five of these pillars in an equal measure and treat them all as a priority rather than just go for full accuracy.

Chris Adams: Brilliant. We'll sure make a point of sharing a link to that in the show notes for anyone else who wants to dive into the world of pillars of sustainability reporting, I suppose. Alright. Okay. Well, James, I think that takes us to time. So just before we wrap up, there's gonna be usual things like where people can find you, but are there any particular projects that are catching your eye right now that you are kind of excited about or you'd like to direct people's attention to? 'Cause we'll share a link to the company you work for, obviously, and possibly yourself on LinkedIn or whatever it is. But is there anything else that you've seen in the last couple of weeks that you find particularly exciting in the world of GreenOps or kind of the wider sustainable software field?

James Hall: Yeah, I mean, a lot of work being done around AI sustainability is particularly interesting. I recommend people go and look at some of the Hugging Face information around which models are more electrically efficient. And from a Greenpixie side, we've got a newsletter now for people wanting to learn more about GreenOps and in fact, we're building out a GreenOps training and certification that I'd be very interested to get a lot of people's feedback on.

Chris Adams: Cool. Alright, well thank you one more time. If people wanna find you on LinkedIn, they would just look up James Hall Greenpixie, presumably right? Or something like that.

James Hall: Yeah, and go to our website as well.

Chris Adams: Well James, thank you so much for taking me along to this deep dive into the world of GreenOps ,cloud carbon reporting and all the, and the rest. Hope you have a lovely day and yeah. Take care of yourself mate. Cheers.

James Hall: Thanks so much, Chris.

Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, or wherever you get your podcasts. And please do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners.

Chris Adams: To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode.

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