In this installment of podcast, we’re joined by Alessandro Vozza ( Twitter/X , Github ) , a prominent figure in the Kubernetes and cloud-native community , who talks about his new project, Kubespaces, which aims to simplify Kubernetes deployment by offering a namespace-as-a-service. He highlights the importance of maintaining the full feature set of Kubernetes while ensuring security and isolation for multi-tenant environments. Alessandro’s vision includes leveraging the Kubernetes API to create a seamless, cloud-agnostic deployment experience, ultimately aiming to fulfill the promises of platform engineering and serverless computing. He also discusses the future trends in Kubernetes and the significance of environmental sustainability in technology.

Chris Engelbert: Hello, everyone. Welcome back to the next episode of simplyblock’s Cloud Commute podcast. Today, I have another incredible guest. I know I say that every time, but he’s really incredible. He’s been around in the Kubernetes space for quite a while. And I think, Alessandro, the best way is just to introduce yourself. Who are you? What have you done in the past, and what are you doing right now?

Alessandro Vozza: Thank you for having me. Well, I’m Alessandro, yes, indeed. I’ve been around for some time in the cloud-native community. I’m Italian, from the south of Italy, and I moved to Amsterdam, where I live currently, about 20 years ago, to get my PhD in chemistry. And then after I finished my PhD, that’s my career. So I went through different phases, always around open source, of course. I’ve been an advocate for open source, and a user of open source since the beginning, since I could lay my hands on a keyboard.

That led me to various places, of course, and various projects. So I started running the DevOps meetup in Amsterdam back in the day, 10, 11 years ago. Then from there, I moved to the OpenStack project and running the OpenStack community. But when I discovered Kubernetes, and what would become the Cloud Native Computing Foundation, I started running the local meetup. And that was kind of a turning point for me. I really embraced the community and embraced the project and started working on the things. So basically what I do is organize the meetup and organize the KCDs, the Kubernetes Community Days in Amsterdam, in Utrecht, around the country. That kind of led me through a natural process to be a CNCF Ambassador, which are people that represent or are so enthusiastic about the way the Cloud Native Computing Foundation works and the community, that are naturally elected to be the face or the ambassadors for the project, for the mission.

At this moment, I still do that. It’s my honor and pleasure to serve the community, to create, to run monthly meetups and KCDs and help other communities thrive as well. So the lessons learned in the Netherlands, in the meetups and in the conferences, we try to spread them as much as possible. We are always available for other communities to help them thrive as well. So that’s been me in a nutshell. So all about community. I always say I’m an average programmer, I’m an average engineer, but where I really shine is to organize these events and to get the people together. I get a kick out of a successful event where people form connections and grow together. So that’s what drives me in my very core.

Chris Engelbert: I like how you put this. You really shine in bringing engagement to the community, helping people to shine themselves, to grow themselves. I think that is a big part of being a developer advocate or in the developer relations space in general. You love this sharing of information, helping other people to get the most out of it.

Alessandro Vozza: Actually, I used to be, or I still do play the bass, electric bass and double bass. And the bass player stays in the back next to the drummer and he creates the conditions so the other members of the band shine. So the guitar player usually stays in front, the bass player is the guy that stays back and is happy to create the foundations and cover the music to really shine. And that’s maybe my nature. So maybe it reflects from the fact that I always love playing the bass and being that guy in a band.

Chris Engelbert: I love that. That’s a great analogy. I never thought about that, but that is just brilliant. And I actually did the same thing in the past, so there may be some truth to that. So we met a few weeks ago in Amsterdam, actually at AWS Summit Amsterdam.

And I invited you because I thought you were still with the previous company, but you’re doing something new right now. So before that, you were with Solo.io , an API gateway, networking, whatever kind of thing. But you’re doing your own thing. So tell us about it.

Alessandro Vozza: Yeah. So it was a great year doing DevRel and so much fun going and speaking about service mesh, which is something that I really believe it’s going to, it’s something that everybody needs, but I know it’s a controversial, but it’s something that I really, you got to believe in it. You know, when you are a developer advocate, when you represent a company or community, the passion is important. You cannot have passion for something you don’t believe in, for something that you don’t completely embrace. And that was great. And we had so much fun for about a year or a bit more. But then I decided that I’m too young to settle, as always, like I’m only 48, come on, I have a good 10 years of engineering work to do. So I decided that I wanted to work on something else, on something mine, more, more mine, more an idea that I had, and I want to see it develop.

Filling a gap in the market and a real need for developers to have a flexible environment, environments to deploy their applications. So fulfilling the promises of platform engineering as a self-service platform to deploy applications. So the idea goes around the namespace. What is a namespace? Of course, it’s what the unit of deployment in Kubernetes really, it’s this magical place where developers can be free and can deploy their application without the control within the guard rails of whatever the system means, the cluster administrator sets.

But developers really love freedom. So developers don’t want to have to interact even with the sysops or sysadmins. In fact, developers love Heroku. So Heroku, I think, is the hallmark of developer experience where you just can deploy whatever you want, all your code, all your applications in a place and it’s automatically exposed and you can manage by yourself everything about your application.

I want to reproduce that. I want to get inspired by that particular developer experience. But because I love Kubernetes, of course, and because I really believe that the Kubernetes APIs are the cornerstone, the golden standards of cloud-native application deployment. So I want to offer the same experience but through the Kubernetes API. So how you do that, and that’s, of course, like this evolving product, me and a bunch of people are still working on, define exactly what does it mean and how it’s going to work. But the idea is that we offer namespace-as-a-service. What really matters to developers is not the clusters, is not the VMs or the networks or all the necessary evil that you need to run namespaces. But what really matters is the namespace, is a place where they can deploy their application. So what if we could offer the best of both worlds, kind of like the promises of serverless computing, right? So you are unburdened by infrastructure. Of course, there is infrastructure somewhere, the cloud is just somebody else’s computer, right? So it’s not magic, but it feels like magic because of the clever arrangement of servers in a way that you don’t see them, but they are still there.

So imagine a clusterless Kubernetes. The experience of Kubernetes, the API really, so all the APIs that you learn to love and embrace without the burden of infrastructure. That’s the core idea.

Chris Engelbert: So that means it’s slightly different from those app platforms like Fargate or what’s the Azure and GCP ones, Cloud Run and whatever. So it’s slightly different, right? Because you’re still having everything Kubernetes offers you. You still have your CRDs or your resource definitions, but you don’t have to manage Kubernetes on its own because it’s basically a hosted platform. Is that correct?

Alessandro Vozza: Yeah. So those platforms, of course, they are meant to run single individual application pods, but they don’t feel like Kubernetes. I don’t understand. For me, because I love it so much, I think developers love to learn also new things. So developers will love to have a Kubernetes cluster where they can do what they like, but without the burden of managing it. But this CloudRun and ACI and Fargate, they are great tools, of course, and you can use them to put together some infrastructure, but they’re still limiting in what you can deploy. So you can deploy this single container, but it’s not a full-fledged Kubernetes cluster. And I think it’s still tripling in a way that you don’t have the full API at your disposal, but you have to go through this extra API layer. It’s a bespoke API, so you got to learn Cloud Run, you got to learn ACI, you got to learn Fargate, but they are not compatible with each other. They are very cloud specific, but a Kubernetes API is cloud agnostic, and that’s what I want to build.

What we seek to build is to have a single place where you can deploy in every cloud, in every region, in some multi-region, multi-cloud, but through the same API layer, which is the pure and simple Kubernetes API.

Chris Engelbert: I can see there’s two groups of people, the ones that say, just hide all the complexity from Kubernetes. And you’re kind of on the other side, I wouldn’t say going all the way, like you want the complexity, but you want the feature set, the possibilities that Kubernetes still offers you without the complexity of operating it. That’s my feeling.

Alessandro Vozza: Yeah, the complexity lies in the operation, in the upgrades, the security, to properly secure a Kubernetes cluster, it takes a PhD almost, so there’s a whole sort of ecosystem dedicated to secure a cluster. But in Kubespaces, we can take care of it, we can make sure that the clusters are secure and compliant, while still offering the freedom to the developers to deploy what they need and they like. I think we underestimate the developers, so they love to tinker with the platform, so they love freedom, they don’t want the burden, even to interact with the operation team.

And so the very proposal here is that you don’t need an operation team, you don’t need a platform engineering team, it’s all part of the platform that we offer. And you don’t even need an account in Azure or AWS, you can select which cloud and which region to deploy to completely seamlessly and without limits.

Chris Engelbert: Okay, so that means you can select, okay, I need a Kubernetes cluster namespace, whatever you want to call it, in Azure, in Frankfurt or in Western Europe, whatever they call it.

Alessandro Vozza: Yeah. Okay, so yeah, it is still a thing, so people don’t want to be in clouds that don’t trust, so if you don’t want to be in Azure, you should not be forced to. So we offer several infrastructure pieces, clusters, even if the word cluster doesn’t even appear anywhere, because it’s by design, we don’t want people to think in terms of clusters, we want people to think in terms of namespaces and specifically tenants, which are just a collection of namespaces, right? So it’s a one namespace is not going to cut it, of course, you want to have multiple to assign to your teams, to group them in environments like that, prod or test, and then assign them to your team, to your teams, so they can deploy and they’re fun with their namespaces and tenants.

Chris Engelbert: Yeah, I think there’s one other thing which is also important when you select a cloud and stuff, you may have other applications or other services already in place, and you just want to make sure that you have the lowest latency, you don’t have to pay for throughput, and stuff like that. Something that I always find complicated with hosted database platforms, to be honest, because you have to have them in the same region somehow.

Alessandro Vozza: Yeah, that’s also a political reason, right? Or commercial reason that prevents you from that.

Chris Engelbert: Fair, fair. There’s supposed to be people that love Microsoft for everything.

Alessandro Vozza: I love Microsoft, of course, been there for seven years. I’m not a fanboy, maybe I am a little, but that’s all right. Everybody, that’s why the world is a beautiful place. Everybody is entitled to his or her opinion, and that’s all right.

Chris Engelbert: I think Microsoft did a great job with the cloud, and in general, a lot of the changes they did over the last couple of decades, like the last two decades, I think there are still the teams like the Office and the Windows team, which are probably very enterprise-y still, but all of the other ones. For me specifically, the Java team at Microsoft, they’re all doing a great job, and they seem to be much easier and much more community driven than the others.

Alessandro Vozza: I was so lucky because I was there, so I saw it with my own eyes, the unfolding of this war machine of Microsoft. There was this tension of beating Amazon at their own game. Seven years ago, we had this mission of really, really demonstrating that Microsoft was serious about open source, about cloud, and it paid off, and they definitely put Microsoft back on the map. I’m proud and very, very grateful to be here. You have been there, Microsoft joining the Linux Foundation, the Cloud Native Computing Foundation really being serious about Cloud Native, and now it works.

Chris Engelbert: I agree. The Post-Balmer era is definitely a different world for Microsoft. All right, let’s get back to Kubespaces, because looking at the time, we’re at 17. You said it’s, I think it’s a shared resource. You see the Kubernetes as a multi-tenant application, so how does isolation work between customers? Because I think that is probably a good question for a lot of security-concerned people.

Alessandro Vozza: Yeah, so of course, in the first incarnation would be a pure play SaaS where you have shared tenants. I mean, it’s an infrastructure share among customers. That’s by design the first iteration. There will be more, probably where we can offer dedicated clusters to specific customers. But in the beginning, it will be based on a mix of technologies between big cluster and Firecracker, which ensure better isolation of your workload. So it is indeed one piece of infrastructure where multiple customers will throw their application, but you won’t be able to see each other. Everybody gets his own API endpoint for Kubernetes API, so you will not be able. RBAC is great, and it works, of course, and it’s an arcane magic thing and it’s arcane knowledge. Of course, to properly do RBAC is quite difficult. So instead of risking to make a mistake in some cluster role or role, and then everybody can see everything, you better have isolation between tenants. And that comes with a popular project like big cluster, which has been already around for five years. So that’s some knowledge there already.

And even an other layer of isolation, things like Kata Container and Firecracker, they provide much better isolation at the container runtime level. So even if you escape from the container, from the jail of the container, you only can see very limited view of the world and you cannot see the rest of the infrastructure. So that’s the idea of isolating workloads between customers. You could find, of course, flaws in it, but we will take care of it and we will have all the monitoring in place to prevent it, it’s a learning experience. We want to prove to ourselves first and to customers that we can do this.

Chris Engelbert: Right. Okay. For the sake of time, a very, very… well, I think because you’re still building this thing out, it may be very interesting for you to talk about that. I think right now it’s most like a one person thing. So if you’re looking for somebody to help with that, now is your time to ask for people.

Alessandro Vozza: Yeah. If the ideas resonate and you want to build a product together, I do need backend engineers, front-end engineers, or just enthusiastic people that believe in the idea. It’s my first shot at building a product or building a startup. Of course, I’ve been building other businesses before, consulting and even a coworking space called Cloud Pirates. But now I want to take a shot at building a product and see how it goes. The idea is sound. There’s some real need in the market. So it’s just a matter of building it, build something that people want. So don’t start from your ideas, but just listen to what people tell you to build and see how it goes. So yeah, I’ll be very happy to talk about it and to accept other people’s ideas.

Chris Engelbert: Perfect. Last question, something I always have to ask people. What do you think will be the next big thing in Kubernetes? Is it the namespace-as-a-service or do you see anything else as well?

Alessandro Vozza: If I knew, of course, in the last KubeCon in Paris, of course, the trends are clear, this AI, this feeding into AI, but also helping AI thrive from Cloud Native. So this dual relationship with the Gen AI and the new trends in computing, which is very important. But of course, if you ask people, there will be WebAssembly on the horizon, not replacing containers, but definitely becoming a thing. So there are trends. And that’s great about this community and this technologies that it’s never boring. So there’s always something new to learn. And I’m personally trying to learn every day. And if it’s not WebAssembly, it’s something else, but trying to stay updated. This is fun. And challenges your convention, your knowledge every day. So this idea from Microsoft that I learned about growth mindset, what you should know now is never enough if you think ahead. And it’s a beautiful thing to see. So it’s something that keeps me every day.

Now I’m learning a lot of on-premise as well. These are also trying to move workloads back to the data centers. There are reasons for it. And one trend is actually one very important one. And I want to shout out to the people in the Netherlands also working on it is green computing or environmental sustainability of software and infrastructure. So within the CNCF, there is the Technical Advisory Group environmental sustainability, which we’re collaborating with. We are running the environmental sustainability week in October. So worldwide events all around getting the software we all love and care to run greener and leaner and less carbon intense. And this is not just our community, but it’s the whole planet involved. Or at least should be concerned for everybody concerned about the future of us. And I mean, I have a few kids, so I have five kids. So it’s something that concerns me a lot to leave a better place than I found it.

Chris Engelbert: I think that is a beautiful last statement, because we’re running out of time. But in case you haven’t seen the first episode of a podcast, that may be something for you because we actually talked to Rich Kenny from Interact and they work on data center sustainability, kind of doing the same thing on a hardware level. Really, really interesting stuff. Thank you very much. It was a pleasure having you. And for the audience, next week, same time, same place. I hope you’re listening again. Thank you.

Alessandro Vozza: Thank you so much for having me. You’re welcome.

The post Easy Developer Namespaces with Multi-tenant Kubernetes with Alessandro Vozza from Kubespaces appeared first on simplyblock.

In this installment , we’re talking to Rich Kenny from Interact , an environmental consultancy company, about how their machine-learning based technology helps customers to minimize their carbon footprint, as well as optimizing infrastructure cost. He sheds light on their innovative approach to optimize data center performance for sustainability.

Chris Engelbert: Hello, folks! Great to have you here for our first episode of the Cloud Commute Podcast by simplyblock. I’m really happy to have our first guest Richard. Who’s really interesting. He’s done a lot of things, and he’s going to talk about that in a second. But apart from that, you can expect a new episode every week from now on. So with that. Thank you, Richard, for being here. Really happy to have you on board, and maybe just start with a short introduction of yourself.

Rich Kenny: Yeah, cool. So my name’s Rich Kenny. I’m the managing director of Interact. We’re a machine learning based environmental consultancy that specializes in circular economy. And I’m also a visiting lecturer and research fellow at London South Bank University, in the School of engineering. So a bit of business, a bit of academia, a bit of research. I know a few things about a few things.

Chris Engelbert: You know a few things about it, a few things. That’s always better than most people.

Rich Kenny: Certainly better than knowing nothing about a lot of things.

Chris Engelbert: That’s fair. I think it’s good to know what you don’t know. That’s the important thing. Right? So you said you’re doing a little bit of university work, but you also have a company doing sustainability through AI management. Can you? Can you go and elaborate a little bit on that?

Rich Kenny: Yeah. So we’ve got a product that looks at the performance of enterprise IT, so it’s servers, storage, networking. It’s got the world’s largest data set behind it, and some very advanced mathematical models and energy calculations and basically allows us to look at data, center hardware and make really really good recommendations for lower carbon compute, reconfiguration of assets, product life extension, basically lets us holistically look at the it performance of an estate, and then apply very advanced techniques to reduce that output. So, saving cost of energy and carbon to do the same work better. We’ve done about 400 data centers now, in the last 3 years, and we saw an average of about 70% energy reduction, which is also quite often a 70% carbon reduction in a lot of cases as well from a scope two point of view. There’s nothing like you on the market at the moment, and we’ve been doing this, as a business, for probably 3.5 or 4 years, and as a research project for the better part of 7 years.

Chris Engelbert: So, how do I have to think about that? Is it like a web UI that shows you how much energy is being used and you can zoom right into a specific server and that would give you a recommendation like, I don’t know, exchange the graphics card or or storage, or whatever.

Rich Kenny: So specifically it looks at the configuration and what work it’s capable of doing. So, every time you have a variation of configuration of a server it is more or less efficient. It does more or less work per watt . So what we do is we apply a massive machine learning dataset to any make model generation configuration of any type of server, and we tell you how much work it can do, how effectively it can do it. What the utilization pathway looks like. So it’s really great to be able to apply that to existing data center architecture. Once you’ve got the utilization and the config and say you could do the same work you’re doing with 2,000 servers in this way, with 150 servers in this way. And this is how much energy that would use, how much carbon that will generate, and how much work it will do. And we can do things like carbon shifting scenarios. So we can take a service application, say a CRM, that’s in 20 data centers across a 1000 machines, using fractional parts of it and say, this service is using X amount of carbon costing this much energy. So basically, your CRM is costing X to run from an energy and carbon point of view. And you could consolidate that to Z, for example. So the ability to look at service level application level and system level data and then serve that service more efficiently. So we’re not talking about sort of rewriting the application, because that’s one step low down the stack. We’re talking about how you do the same work more efficiently and more effectively by looking at the hardware itself and the actual, physical asset. And it’s a massive, low hanging fruit, because no one’s ever done this before. So, it is not unusual to see consolidation options of 60+% of just waste material. A lot of it is doing the same work more effectively and efficiently. And that drives huge sustainability based outcomes, because you’re just removing stuff you don’t need. The transparency bit is really important, because quite often you don’t know what your server can do or how it does it, like, I bought this, it’s great, it’s new, and it must be really really effective. But the actual individual configuration, the interplay between the CPU, RAM, and the storage determines actually how good it is at doing its job, and how much bang you get for your buck and you can see, you know, intergenerational variance of 300%. Like, you know, we’ve got the L360, all the L360s are pretty much the same of this generation. But it is not. There’s like a 300% variance depending on how you actually build the build of materials.

Chris Engelbert: Alright! So I think it sounds like, if it does things more efficiently, it’s not only about carbon footprint, it’s also about cost savings, right? So I guess that’s something that is really interesting for your customers, for the enterprise is buying that?

Rich Kenny: Yes absolutely. It’s the first time they’re saving money while working towards sustainability outcomes other than what you would do in cloud for, like GreenOps, where, realistically, you’re doing financial operations and saying, I’m gonna reduce carbon, but realistically, I’m reducing compute, reducing wastage, or removing stranded applications. We’re doing the exact same thing on the hardware level and going “how do you do the same work efficiently rather than just doing it?” And so you’re going to get huge cost savings in the millions. You get thousands of tons of carbon reduction, and none of it has an impact on your business, because you’re just eradicating waste.

Chris Engelbert: Right? So that means your customers are mostly the data center providers?

Rich Keynn: Oh no, it’s mostly primary enterprise, truth be told, because the majority of data centers operate as a colo or hyper scale. Realistically, people have got 10 other people’s co-located facilities. The colos [editor: colocation operator] are facility managers. They’re not IT specialists. They’re not experts in computers. They’re experts in providing a good environment for that computer. Which is why all the efficiency metrics geared towards the data center have historically been around buildings. Since it’s been about “how do we build efficiently? How do we cool efficiently? How do we reduce heat, density?” All this sort of stuff. None of that addresses the question “why is the building there?” The building’s there to serve, storage and compute. And every colocation operator washes their hands of that, and goes “it’s not our service. Someone else is renting the space. We’re just providing the space.” So you have this real unusual gap, which you don’t see in many businesses where the supplier has a much higher level of knowledge than the owner. So when you’re talking to someone saying “I think you should buy this server,” the manufacturer tells you what to buy, and the colo tells you where to put it, but in-between that, it’s the IT professional, who really has no control over the situation. The IT provider doesn’t tell me how good it is and the colo doesn’t tell me how to effectively run it. So what I get is my asset and I give it to someone else to manage, meaning, what you get is this perfect storm of nobody really trying to serve it better, and that’s what we do. We come in and let you know ”there’s this huge amount of waste here.”

Chris Engelbert: Yeah, that makes sense. So it’s the people or the companies that co-locate their hardware in a data center.

Rich Kenny: Right, or running their own data centers on premise, running their own server rooms, or cabinets. We do work sometimes with people that have got as few as 8 servers. And we might recommend changing the RAM configuration, switching out CPUs. Things like that can have 20, 30, 40% benefits, but cost almost nothing. So it could be that we see a small server estate that’s very low utilized, but massively over-provisioned on RAM. Mostly because someone, some day, 10 years ago, bought a server and went “stick 2 TB in it.” And we’d ask, “how much are you using?” With the answer: “200 gigs.” “So you’ve got 10 times more RAM than you need, even at peak, can you just take out half your RAM, please.” It sounds really counterintuitive to take out that RAM and put it on the side. If you scale up again, you can just plug it back in again next week. But you know you’ve been using this for 8 to 10 years, and you haven’t needed anywhere near that. It’s just sitting there, drawing energy, doing nothing, providing no benefit, no speed, no improvement, no performance, just hogging energy. And we’d look at that and go “that’s not necessary.”

Chris Engelbert: Yeah, and I think because you brought up the example of RAM, most people will probably think that a little bit of extra RAM can’t be that much energy, but accumulated over a whole year it comes down to something.

Rich Kenny: Yeah, absolutely like RAM can be as much as 20 or 30% of the energy use of a server sometimes. From a configuration level. CPU is the main driver, of up to 65% of the energy use of a service. I mean, we’re talking non GPU-servers. When it gets to GPUs, we’re getting orders of magnitude. But RAM still uses up to 30% of the power on some of these servers. And if you’re only using 10% of that, you can literally eradicate almost 20% of the combined energy – just by decommissioning either certain aspects of that RAM or just removing it and putting it on the shelf until you need it next year, or the year after. The industry is so used to over-provisioning that they scale at day one, to give it scale at year five. It would be more sensible though to provision for year one and two, with an ability to upgrade, to grow with the organization. What you’ll see is that you’ll decrease your carbon energy footprint year on year, you won’t overpay month one for the asset, and then in year two you can buy some more RAM in year three you can buy some more RAM, and in year four you can change out the CPUs with a CPU you’re buying in year four. By the time you need to use it, you haven’t paid a 300% premium for buying the latest and greatest at day one. That said, it’s also about effective procurement. You know, you want 20 servers, that’s fine, but buy the servers you want for year one and year two, and then, year three, upgrade the components. Year four, upgrade. Year five, upgrade. You know, like incremental improvement. It means you’re not paying a really high sunk energy cost at year one. Also you’re saving on procurement cost, because you don’t buy it the second it’s new. Two years later it’s half the price. If you haven’t used it to its fullest potential in years one and two, you fundamentally get a 50% saving if you only buy it in year three. But nobody thinks like that. It’s more like “fire and forget.”

Chris Engelbert: Especially for CPUs. In three years time, you have quite some development. Maybe a new generation, same socket, lower TDP, something like that. Anyhow, you shocked me with the 30%. I think I have to look at my server in the basement.

Rich Kenny: It’s crazy. Especially now that we get persistent RAM, which actually doesn’t act like RAM, it more acts like store in some aspects and stores the data in the memory. That stuff is fairly energy intensive, because it’s sitting there, constantly using energy, even when the system isn’t doing anything. But realistically, yeah, your RAM is a relatively big energy user. We know, for every sort of degree of gigabytes, you’ve got an actual wattage figure. So it’s not inconsequential, and that’s a really easy one. That’s not exactly everything we look at, but there’s aspects of that.

Chris Engelbert: Alright, so we had CPUs, and we had RAM. You also mentioned graphics cards. I think if you have a server with a lot of graphic cards it’s obvious that it’ll use a lot of energy. You had RAM. Anything else that comes to mind? I think hard disk drives are probably worse than SSDs and NVMe drives.

Rich Kenny: Yeah, that’s an interesting one. So storage is a really fascinating one for me, because I think we’re moving back towards tape storage. As a carbon-efficient method of storage. And people always look at me and go “why would you say that?” Well, if you accept the fact that 60 to 70% of data is worthless, as in you may use it once but never again. That’s a pretty standard metric. I think it may be as high as 90%. I mean data that doesn’t get used again. However, 65% of the data will never get used. And what we have is loads of people moving that storage to the cloud and saying that they can now immediately access data whenever they want, but will never use or look at it again. So it sits there, on really high-available SSDs and I can retrieve this information I never want, instantly.

Well, the SSD wears over time. Every time you read or write, every time you pass information through it, it wears out a bit more. That’s just how flash memory works. HDDs have a much longer life cycle than SSDs, but lower performance. Your average hard drive uses around six watts an hour and an SSD uses four. So your thinking is “it is 34% more efficient to use SSDs.” And it is, except that there’s an embodied cost of the SSD. The creation of the SSD. Is 1015x higher than that of a hard drive. So if you’re storing data that you never use, no one’s ever using that six watts read and write. It just sits there with a really high sunk environmental cost until it runs out, and then you may be able to re use it. You might not. But realistically, you’re going to get through two or three life cycles of SSDs for every hard drive. If you never look at the data, it’s worthless. You’ve got no benefit there, but there’s a huge environmental cost for all materials and from a storage point of view. Consequently, take another great example. If you’ve got loads of storage on the cloud and you never read it, but you have to store it. Like medical data for a hundred years. Why are you storing that data on SSDs, for a hundred years, in the cloud and paying per gigabyte? You could literally save a million pounds worth of storage onto one tape and have someone like Iron Mountain run your archive as a service for you. You can say, if you need any data, they’ll retrieve it and pass it into your cloud instance. And there’s a really good company called Tes in the UK. Tes basically has this great archival system. And when I was talking to them, it really made sense of how we position systems of systems thinking. They run tape. So they take all your long term storage and put it on tape. But they give you an RCO of six hours. You just raise a ticket, telling them that you need the information on this patient, and they retrieve it, and put it into your cloud instance. You won’t have it immediately, but no one needs that data instantaneously. Anyhow, it’s sitting there on NVMe storage , which has a really high environmental energy cost, not to forget the financial cost, just to be readily available when you never need it. Consequently stick it in a vault on tape for 30 years and have someone bring it when you need it. You know you drop your cost by 99 times.

Chris Engelbert: That makes a lot of sense, especially with all data that needs to be stored for regulatory reasons or stuff like that. And I think some people kinda try to solve that or mitigate it a little bit by using some tearing technologies going from NVMe down to HDD, and eventually, maybe to something like S3, or even S3 Glacier. But I think that tape is still one step below that.

Rich Kenny: Yeah S3 Glacier storage. I heard a horror story of guys moving from S3 Glacier storage as an energy and cost saving mechanism, but not understanding that you pay per file, and not per terabyte or gigabyte. Ending with a cost of six figures to move the data over. Still they say, it’s going to save them three grand a year. But now the payback point is like 50 decades.

It’s like you don’t realize when you make these decisions. There’s a huge egress cost there, whereas how much would it have cost to take that data and just stick it onto a tape? 100? 200 quid. You know, you talk about significant cost savings and environmentally, you’re not looking after the systems. You’re not looking after the storage. You’re using an MSP to hold that storage for you, and then guarantee your retrieval within timescales you want. It’s a very clever business model that I think we need to revisit when tape is the best option, and for long term storage archival storage. From an energy point of view and a cost point of view, it’s very clever and sustainability wise. It’s a real win. So yeah. Tape as a service. It’s a thing. You heard it here first.

Chris Engelbert: So going from super old technology to a little bit newer stuff. What would drive sustainability in terms of new technologies? I hinted at a lower TDP for new CPUs. Probably the same goes for RAM. I think the chips get lower in wattage? Or watt-usage over time? Are there any other specific factors?

Rich Kenny: Yeah, I think the big one for me is the new DDR5 RAM is really good. It unlocks a lot of potential at CPU level, as in like the actual, most recent jump in efficiency is not coming from CPUs. Moore’s law slowed down in 2015. I still think it’s not hitting the level it was. But the next generation for us is ASICs based, as in applications specific interface chips. There’s not much further the CPU can go. We can still get some more juice out of it, but it’s not doubling every 2 years. So the CPU is not where it’s at. Whereas the ASICs is very much where it’s at now, like specific chips built for very specific functions. Just like Google’s TPUs. For example, they’re entirely geared towards encoding for Youtube. 100x more efficient than a CPU or a GPU at doing that task. We saw the rise of the asset through Bitcoin, right? Like specific mining assets. So I think specific chips are really good news, and new RAM is decent.

Additionally, the GPU wars is an interesting one for me, because we’ve got GPUs, but there’s no really definable benchmark for comparison of how good a GPU is, other than total work. So we have this thing where it’s like, how much total grunt do you have? But we don’t really have metrics of how much grunt per watt? GPUs have always been one of those things to power supercomputers with. So it does 1 million flops, and this many MIPS, and all the rest of it. But the question has to be “how good does it do it? How good is it doing its job?” It’s irrelevant how much total work it can do. So we need a rebalancing of that. That’s not there yet, but I think it will come soon, so we can understand what GPU specific functions are. The real big change for us is behavioral change. Now, I don’t think it’s technology. Understanding how we use our assets. Visualizing the use in terms of non economic measures. So basically being decent digital citizens, I think, is the next step. I don’t think it’s a technological revolution. I think it’s an ethical revolution. Where people are going to apply grown-up thinking to technology problems rather than expecting technology to solve every problem. So yeah, I mean, there are incremental changes. We’ve got some good stuff. But realistically, the next step of evolution is how we apply our human brains to solve technological problems rather than throw technology at problems and hope for the solution.

Chris Engelbert: I think it’s generally a really important thing that we try not to just throw technology at problems, or even worse, create technology in search of a problem all the time.

Rich Kenny: We’re a scale up business at Interact. We’re doing really, really well but we don’t act like a scale up. Last year I was mentoring some startup guys and some projects that we’ve been doing in the Uk. And 90% of people were applying technology to solve a problem that didn’t need solving. The question I would ask these people is “what does this do? What is this doing? And does the world need that?”

Well, it’s a problem. I feel like you’ve created a problem because you have the solution to a problem. It’s a bit like an automatic tin opener. Do we need a Diesel powered chainsaw tin opener to open tins? Or do we already kind of have tin openers? How far do we need to innovate before it’s fundamentally useless.

I think a lot of problems are like, “we’ve got AI, and we’ve got technology, so now we’ve got an app for that.” And it’s like, maybe we don’t need an app for that. Maybe we need to just look at the problem and go, “is it really a problem?” Have you solved something that didn’t need solving? And a lot of ingenuity and waste goes into solving problems that don’t exist. And then, conversely, there’s loads of stuff out there that solves really important problems. But they get lost in the mud, because they can’t articulate the problem it’s solving.

And in some cases you know, the ones that are winning are the ones that sound very attractive. I remember there was a med-tech one that was talking about stress management. And it was providing all these data points on what levels of stress you’re dealing with. And it’s really useful to know that I’m very stressed. But other than telling me all these psychological factors, I am feeling stressed. What? What is the solution on the product other than to give me data telling me that I’m really stressed? Well, there isn’t any. It doesn’t do anything. It just tells you that data. And it’s like, right? And now what? And then we can take that data. It’ll solve the problem later on. It’s like, no, you’re just creating a load of data to tell me things that I don’t really think has any benefit. If you’ve got the solution with this data, we can make this inference, we can, we can solve this problem that’s really useful. But actually, you’re just creating a load of data and going. And what do I do with that? And you go. Don’t know. It’s up to you. Okay, well, it tells me that it looks like I’m struggling today. Not really helpful. Do you know what I mean?

Chris Engelbert: Absolutely! Unfortunately, we’re out of time. I could chat about that for about another hour. You must have been so happy when the proof of work finally got removed from all the blockchain stuff. Anyway, thank you very much. It was very delightful.

I love chatting and just laughing, because you hear all the stories from people. Especially about things you normally are not part of, as with the RAM. Like I said, you completely shocked me with 30% up. Obviously, RAM takes some amount of energy. But I didn’t know that it takes that much.

Anyway, I hope that some other folks actually learned something, too. And apply the little bit of ethical bring thinking in the future. Whenever we create new startups, whenever we build new data centers, employ new hardware or and think about sustainability.

Rich Kenny: Thank you very much. Appreciate it.

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