Show notes
Summer rewind: When we say 'the cloud' what we mean is 'the data centre'. Globally, data centres are projected to consume over 1000 terawatt hours in 2026. What does that mean for energy production, distribution, and consumption? Guest Phil Harris, Cerio President and CEO, joins thinkenergy to shed light on something we all rely on but may not fully understand. From efficiency to sustainability, environmental concerns to Cerio's role improving how data centres manage energy. Listen in for the future of cloud computing. Related links Cerio: https://www.cerio.ai/ Phil Harris on LinkedIn: https://www.linkedin.com/in/paharris/ Trevor Freeman on LinkedIn: https://www.linkedin.com/in/trevor-freeman-p-eng-8b612114 Hydro Ottawa: https://hydroottawa.com/en To subscribe using Apple Podcasts: https://podcasts.apple.com/us/podcast/thinkenergy/id1465129405 To subscribe using Spotify: https://open.spotify.com/show/7wFz7rdR8Gq3f2WOafjxpl To subscribe on Libsyn: http://thinkenergy.libsyn.com/ --- Subscribe so you don't miss a video: https://www.youtube.com/user/hydroottawalimited Follow along on Instagram: https://www.instagram.com/hydroottawa Stay in the know on Facebook: https://www.facebook.com/HydroOttawa Keep up with the posts on X: https://twitter.com/thinkenergypod --- Transcript: [00:00:00] Trevor Freeman: Hi everyone, and welcome to the summer edition of Think Energy. As a reminder, we are in podcast vacation mode, and while our normal day-to-day work continues, we are on a brief pause from our regularly scheduled episodes to recharge, rethink, plan for the fall. But we don't want to leave you without anything to listen to. So, we've pulled some of our favorite insights and episodes from the past year related to the energy transition and where we are. So, welcome to episode two of our summer rewind, the August episode. So, as a reminder, this summer, we're looking at that collision between digital infrastructure and physical infrastructure, how the world of evolving technology is shaping and influencing and changing the way that we interact with energy and, in fact, interact with the energy grid as well. Last month, we looked at my conversation with Lynn Pettis from Overstory and how Overstory and Hydro Ottawa have partnered together to use satellite imagery and AI to protect our grid. In part two of our summer rewind today, or the second episode, we're looking at the world of data centres, and we're hearing lots about data centres as AI grows and takes kind of more of an ever-present role in our day-to-day lives. And I had a conversation with Phil Harris from Cerio. So, we're going to dive back into that episode and look at kind of the staggering energy footprint of AI data centres, of the cloud, etc., and how this boom is really changing how we do data centre design and really forcing a change in how we do data centre design just because of the sheer magnitude of energy required here. And we're going to look at kind of what this means for the future of global power distribution. So, sit back, relax, hopefully somewhere cool in the heat of the summer, and listen to this episode of Summer Rewind with Phil Harris from Cerio. [00:02:18] Podcast Intro: Welcome to Think Energy, a podcast that dives into the fast-changing world of energy through conversations with industry leaders, innovators, and people on the front lines of the energy transition. Join me, Trevor Freeman, as I explore the traditional, unconventional, and up-and-coming facets of the energy industry. If you have any thoughts, feedback, or ideas for topics we should cover, please reach out to us at thinkenergy@hydroottawa.com. [00:02:49] Trevor Freeman: Hi everyone, and welcome back. Data centres have come up a number of times on this show, and for very good reason. They have become a key underpinning technology for so much of our lives. Every time we pull out that phone from our pockets to pull up directions or buy something online, or doom scroll on your social media or news site of choice, every time you use your phone, stream a movie, leverage an AI model, whatever you end up using your phone for. It's funny, as I read this list, I'm sure there's like some university student out there who's thinking, man, what is this old man talking about? We don't use our phones for that. Whatever the kids are doing these days, whatever we're doing these days with our phones, with our computers, our tablets, etc., all of that leverages infrastructure that most of us have never seen, and quite frankly, probably don't really understand. We talk about the cloud like it's this amorphous, nebulous thing. But in reality, we're talking about real hardware in a real building that uses real energy, mainly electricity, a lot of water. And this isn't really new. Like, we've been leveraging centralized data centres for many years now. But what is changing is the scale of the data centres that we're seeing now and the pace of growth in computing power that we need to do the things that we want to do and that our data centres are able to deliver. So, just to throw a few numbers at it, the traditional data centre servers that maybe powered the early days of on-demand online streaming services, for example, they used anywhere from 5 to 15 kilowatts per rack. But modern server racks that are used to power AI searches, for example, can hit anywhere from 60 to 100 kilowatts per rack. This is great from a power output per rack perspective, but it means massive energy needs. And that is showing up in the size of load requests that we're seeing from new data centres. New data centres today are asking for service connections that are orders of magnitude higher than those built even just 5 years ago. Globally, data centres are projected to consume over 1,000 terawatt-hours in 2026. And just a quick kind of refresher from high school or wherever you would have learned this, a terawatt is 1,000 gigawatts, which is 1,000 megawatts. So, 1,000 terawatt-hours, which is roughly equivalent to the annual electricity demand from the country of Japan, an entire country. So, given all of this, there are a lot of incentives to find ways to maximize efficiency and reduce some of that energy demand. And that's where my next guest, Phil Harris, and his company, Cerio, come into play. I'll let Phil get into the details of exactly what Cerio does, but essentially, their goal is to reimagine the data centre to maximize sustainability and reduce energy needs. Phil is Cerio's President and CEO, and has been in the networking and data centre industry for over 35 years, including at well-known companies like Intel and Cisco, to name two. And I'm really excited about this conversation, one, to understand how do we make data centres a little bit more efficient, or maybe a lot more efficient, but also just to really understand, like, what are we talking about when we talk about a data centre? What is actually happening, what is physically inside these buildings? And we'll get into a little bit of that in our conversation. So, Phil, welcome to the show. [00:07:05] Phil Harris: Well, thanks, Trevor. I appreciate it. [00:07:07] Trevor Freeman: So, Phil, obviously, we're here today to talk about your work building sustainable data centres, or trying to make data centres a little bit more sustainable. But before we get into that, you know, you've spent your career, you know, decades of your career at different tech giants, let's call them, Intel, Cisco, to two to mention. You've seen quite a bit of change, no doubt, over your time. Has that change, like does this industry change linearly? Does it grow fairly steady, or is it kind of big jumps? And are we on the cusp of any major shifts? What can you kind of tell us about the future of this sector, data, tech, etc.? [00:07:54] Phil Harris: It's interesting. I think as companies start, and I was at companies like Cisco, for example, when it was a very small company to where it was a very large company, and this should be no surprise to anybody, the bigger the company gets, the harder it is to change. And they really find that the only way they change is when they absolutely have to, not because they want to. And that's a combination of just inertia and shareholders' expectations and a whole bunch of things. So, I would say that the bigger the company is, the harder it is for them to react. And so, I think small, nimble companies tend to do much better when there's a lot of transformational technology and development and changes in the overall ecosystem we live in. I think your, the second part of your question, you know, I look at the current situation as a point in time where a lot of companies will have to make some significant changes simply because we are hitting two new walls: technological walls, commercial walls, geopolitical walls, that are really sort of confining what people can do. So, I think what's about to happen is we're about to see a significant change. And this is not atypical in the industry. If we think about back into the start of what we would think of today as computer science around mainframes that were happening in the '60s, you know, for about a decade and a half, two decades, there was a lot of dominance around a particular way of doing things. And then some new innovational technology came along that rapidly changed that, scaled out, and it went from a very dominant set of players to a much larger number of smaller players who could then provide more innovation and more scale and more choice. And I think we're about to see that transition occurring as well. [00:09:47] Trevor Freeman: So, is this, is there sort of like an analogous time, 10 years ago, 20 years ago, are we on the cusp of like the big, the big change that we've seen before? Like, what would you compare this to, you know, in the last 20, 30 years? [00:10:01] Phil Harris: Yeah, I mean, I think there's been eras of compute. And if we say, I mean, we can find analogies outside of the compute world, but let's just stay in the computer science world. I gave the mainframe example as one, and then we went to what we call client-server, which scaled out rapidly. Telephony, we went from large, big telephone exchanges that started in the government space, went to very large organizations. Now, basically, we've completely scaled out how we make phone calls, to use that now 20th-century terminology. Nobody really makes telephone calls anymore. And we went through this with cloud computing and the internet, where there was a change in the approach to the way we did things that suddenly gave us a scale-out mentality rather than a scale-up mentality. And I think that's what we have to key in on here, is that we can, someone, I was on a panel yesterday where we were talking about scale. And I said, well, to scale or not to scale, that is not the question. It's how do we scale? Do we continue to scale up, which is the current model, or do we start to think about scaling out, which is a more distributed model? So, we go from a small number of big things to a large number of smaller things. And typically in computer science, whatever you want to, storage, compute, memory, telephony, everything we've ever done goes through this arc. [00:11:32] Trevor Freeman: Yeah, it's interesting, and there's, obviously, my brain's going to immediately try and find those similarities between my world that I live in on the energy side of things. And it's the same question. There is no path where we're not expanding the amount of energy we need, we're not going to be using more energy. But there are different ways to do that. And there are different paths we can take: the business-as-usual, the just grow, grow, grow, centralized energy production and large-scale transmission, or there's a combination of like grow those things, but also find alternative methods, more DERs, more sort of like close to consumer energy sources and storage, etc., etc. And people that listen to this podcast know I kind of go on ad nauseam about this. So, lots of similarities there. Another kind of framing or foundational thing that I want to talk through before we really get into the meat of our conversation is helping ground both myself and our listeners in what exactly we're talking about here. So, we all use, whether we know it or not, we use, you know, like cloud computing constantly, whether it's in our calls, how we're using the internet, using AI more frequently now. What is the physical reality behind that? What's actually happening? What is, you know, the term "data centre"? What is a data centre for our listeners here? What does that look like? [00:13:17] Phil Harris: Yeah, let's start there. And that's a great question. We started recognizing that the amount of power and space required for computers in companies and government and all sorts of different applications was getting larger than we could put in a room in a closet near maybe where people were using it. We had to start to create dedicated space, because the power requirements, the cooling requirements, just the noise—you can't hear this, but just in my basement, I have a few different compute systems that my wife continually tells me is keeping the neighbors awake. The reality is the environmental aspect of these things became very difficult. So, we created these purpose-built locations that had then different requirements in terms of access and facilities and power and cooling and staffing. And so, they became a new way of thinking about building compute infrastructure at a building level, not just at the individual computers themselves. So, a data centre is usually a very large room, or building, I should say, that houses large amounts of compute and storage and other networking equipment. There's a whole range of different technologies that go into a data centre that allows us to process information. That's what a data centre is. To give you some analogies, in the US, there's about nearly 6,000 data centres, depending on how you measure a data centre. In Canada, we have about 400. In Europe, there's about 750 that we can identify as standalone data centres. You can probably find more places where computers are outside of people's homes, but that's about the ratio we're looking at. [00:15:10] Trevor Freeman: And we're seeing, I think, and tell me if I'm wrong here, like all this talk about the AI proliferation, data centre proliferation, we're seeing an expansion of these. Is that we're seeing the size of these data centres expand, or we're seeing just more of them popping up? Like, what does it mean when we say we're seeing like data centre growth because of AI? What does that mean? [00:15:36] Phil Harris: Well, it's fascinating because now our worlds collide. Because the way we now think about how to describe a data centre isn't in the square footage or the number of computers. It's in how much power it consumes. And we now measure it in megawatts. It starts in 10 megawatts, or single-digit megawatts for very small data centres, into average-sized data centres in the tens of megawatts, up to now the hundreds and the gigawatts of consumption that you look at these hyperscalers. But I think we have to put this into a sort of a human scale. It helps us to put this in human scale. If I were to go back to ChatGPT, actually about now 15 months ago, ChatGPT-4, if you were to put that data centre footprint into the province of Ontario, for example, where you and I both are right now, it would be the equivalent of a million internal combustion engine cars dr…
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