Datacenter class containers for the masses
Ramkrishna, Sriram
What if we told you that there is a way to build a powerful kubernetes cluster that can perform data-center-class workloads in a form factor that you can run at your home, under your lab bench, or at a conference. What if we further told you that this hardware comes from a sustainable supply chain that will lower the carbon footprint of computing. This talk will detail an open hardware design, built for a "home" form factor, with a chassis that can hold from 4 to 12 nodes; that contains almost 100 compute cores; 2TB of memory; and over 30 TB of storage. Join us for an overview through photos, video demonstration, and chats with the designers. Perhaps you work with scalable computing technology every day in far-off data centers or hosted in public clouds. What if you could have similar computing capability in your home, in your home lab, or in the premises of your small organization or business? What if you could run 1000s of containers in under 2000 watts? There are many reasons, from latency limitations, to cost constraints, to concerns over data sovereignty that might require the deployment of on-premise computing. We will overview and demonstrate a new computing form factor that brings a data center class cluster using hyperscale technology that you can plug into your home's power outlet. We also integrate these clusters using materials from the circular economy, building on a sustainable supply chain that decomposes servers from top tier data centers and builds new products based on open designs. The power of open hardware and open software creates the possibilities of executing many compute intensive workloads in diverse locations without the need of a data center. This talk will demonstrate on open hardware design for a powerful deskside chassis that can hold from 4 to 12 nodes of scalable computing running from a single 110V/220V outlet and hosting a range of elastic k8s container workloads. Our short talk will include video demonstration, photos, and Q&A with the system designers.
 Hello, welcome to the data center class containers for the masses. I am Sri Ram Ram Krishna, principal ecosystem engineer for IT Renew. So I want to say welcome. It's virtual this year and I guess it would have been great if we could all have got together physically but here we are. But in any case, I hope you can learn something from this talk, certainly about the circular data center, how circular data center drives open hardware and a low cost form factor appliance that you can run real non-trivial workloads. So let's start with who am I? So my name is Sri Ram Ram Krishna. I am the principal ecosystems engineer for IT Renew working in the circular data center market, market segment. I work with upstream. So you might think that I may not have heard of a principal ecosystem engineer before, but I essentially work with upstream projects in various ecosystems like Kubernetes and open firmware and the open compute project. I'll swing a little bit about the open compute project and open firmware going forward. But these are the kind of things I work with. If it's near metal, then I'm going to be interested and I work primarily with liaison, sometimes as a technical contributor. So it's a very flexible position. So moving on, I think it's important that to understand the scope of this talk that we talk about the open compute project. And the open compute project was started by Facebook about some years back. And the idea is to build an ecosystem of data center companies that work together and collaborate on specifications and software or anything that drives the data center. And you might wonder why we want to do that. The reason it comes down to the fact that companies spend a lot of engineering time doing the same things over and over again. And instead of re-implementing the same thing every time for a new hydrogeneration or whatever it is, you collaborate with other companies and then maintain that together. And then you can spend more time focusing on discrete engineering wins to distinguish yourselves. And I think that's a much healthier way than, say, being permanently attached to a particular ecosystem going forward. So by doing this, we're more efficiently using our engineering resources that we have in each company. If you look at the members of OpenComputeProject, you can see that they represent a wide selection of industries. We have the microprocessors. We have hyperscalers. We have Google. We have NVIDIA networking companies like Cisco. So there is lots of different companies participating at the hardware level, at the software level. And all of them working together to make an open ecosystem to build efficient data centers. So when we talk about OpenCompute, a lot of it is about open hardware. And I think it's important to understand what the benefits of open hardware is. And so the first one is flexibility, right? Everything is standard-based and vendors are participating. Then it makes for great modular solutions. So if you have one from one company, they all interact together. They work together. And that's going to be great for everyone. And that also leads to high-density computing. So if you're able to build the other, you can build various different kinds of computing, like maybe high-end, high-density, low-density. And all of that is great because if you're building high-density computing, you want to be as efficient with space as possible. Now if you're building high-density computing, then you really want to have efficient power. So optimized power is also something that everybody is working on. And so whether it's rack-level power versus individual server power, we want to be able to work together on being efficient and having less costs and fewer points of failure. Now if you're having high-density computing, that's going to generate a lot of heat. And that means we really want to tackle the cooling problem. And by all working in concert, we can figure out how we can cool these high-density computing machines better together. The other thing we can also do is the output from the rack-scale servers can also be repurposed. There's a lot of heat that's generated. We can do something with that and apply it somewhere else. So those are kind of the interesting ideas that are happening around the Open Compute Project. There's also the streamlined maintenance. If you're going to have lots of servers, then it makes sense that you want to have an efficient way to manage all of them. So there are teams of companies that are looking into that. And so all of these fit together to create a data center that's going to be advantageous going forward. Some of the projects that we have in the Open Compute, and I'm going to focus on the ones that's important to us in the circular data center, one is the open system firmware. As I'll explain later what the circular data center is, but when manufacturers finish a product line, they tend to over chime, that support goes away. And so if we have firmware that is open source, then we can continue a lot of these products that may have been, which are no longer being maintained because of limited manpower or whatever, the community can move forward and be able to support it going forward. So that's one of the great things about open source is we can maintain things as a community and so forth. And then there's rack and power, and rack and power is really about focusing on the cooling and the power management of these racks and the servers, another one where we actually look at specifications for the chassis and the racks and everything else. So these are interesting projects for us going forward. And of course another bit of concern is the security as well. We want to make sure we have good security. So that's another interesting ecosystem for us from the circular data center. I didn't really define what the circular data center is. And the circular data center, if we distill it down is really the idea of taking components from Microsoft, Facebook, Dropbox, these kind of hyperscalers and then recertifying them and deploying them to second tier markets. If you know anything about asset management, what happens is these folks, they buy these assets at premium prices because they want to be at the very edge of high performance. And then after three years, they refresh their equipment. And what happens to those components is that the circular data center takes them and then recertifies them and then redeploy them. And this has got a lot of advantages because it's an under-interferable supply chain of ID components. We take in about 18 to 25,000 components approximately. And so that's a lot of components. And we can use them and build products from them and extend the life of these products. Now, that leads to the lower carbon footprint. And the thing you should understand that is when you build or manufacture these IT components, there is an upfront cost. There's a cost of manufacturing, the cost of getting the parts like the rare earth metals and the silicon and putting it in the manufacturing process. So there's a huge carbon footprint that is already there at the beginning. Now when you buy from the circular data supply chain, you don't have that upfront carbon footprint cost. And so it ends up that you're actually getting extremely useful pieces of equipment at a much lower cost. And because there's no upfront carbon cost, you're lowering your carbon footprint. And they're just as good as anything else. After all, it's used by top tier hyperscalers. So it's completely more than adequate for most people's needs in the second tier markets. This is a slide that sort of gives you a flow of what happens. I like to go through it too much because I believe that we don't have a lot of time in this session. So what I encourage you to do is go back and sort of look through this. And if you have questions, I'm happy to answer them. So let's get down to the meat. This is talking about accessible brach scale servers. And so this is a deck side scale for node rack server. It has four sleds. It has a 1600 watt power supply with a micro-trivial fit switch that connects all the nodes together. You can, based on different configurations, you can have four nodes or up to 12 nodes. For the four node configuration, you get up to 96 cores plus one terabyte of memory. There's a lot of NVMe storage options. And you can also add an optional 32 port 100-gigant switch. Now the thing that's great about this is that it's an open design. And the chassis is designed using open source CAD tools. And we publish the specs and rather the assets, design assets in GitHub on the OCP umbrella. And they're also using the OCP spec for the drawer. So all these drawers you see there is based on published specifications. And what that means is that you can actually redesign them based on the specification of something else. And this is where that flexibility was talking about in the open hardware slide. So we can reimagine things that may not have been thought of before because maybe a new market segment has come up. So because of that, we're able to, if we wanted to, say, make it more AI friendly, we could replace one rack with GPUs. You can design all of that, whatever it is, and then be able to build a new appliance. So that's one of the great things about this open design. And of course, all of them is out in the open for anybody to take a look at. Now a lot of my pictures I've shown ahead are rendered images. And I really do want to show one that I have at home. This is a discovery that I have at home. It has a laptop there that's kind of the admin node that manages the rest of the servers. I have two network switches there. I ran out of ports. That's why there's a second one. And there's a 32 port 100 gigabit switch, which is pretty interesting having one of those. I'm not using it at the moment. That's why you don't see a lot of wires there. But it's pretty awesome. And we have, it's running Kubernetes using Rancher. And then there's the hardware is managed by Digital Rebar. Both have the links there for you. Now this is a screenshot of the Rackin Digital Rebar. And from here, you could, I can access all the four nodes. I can reboot them. I can part them down using IPMI. I can put them back up. Everything you would expect from a data center, I can actually wipe them, wipe the nodes and reinstall. I'm using Ubuntu at the moment. But I can also do something else. I can do Fedora or something like that. So you know, there's all kinds of flexibility. Now my Kubernetes is run by Rancher. Maybe some of you are already familiar with that. I'm sadly only using 1% of the CPU in this screenshot, but I actually have 192 CPUs there. I have a total of 98 cores. Sorry. So I've got plenty of horsepower. I was born there for many years. But 1TB memory. And I'm told I have 440 pods that I can use. And that leads to a lot of containers. Lots and lots of containers of all different kinds. And I can run all of this at home or in a lab or whatever. So it's pretty cool to be able to have all these containers and be able to run them and do various neat things. But if you don't have to stop at a cluster, we can actually do other things with them as well. It could be a render-blender farm or maybe that's a blender-render farm. I get confused at times. There's also, if you're doing research, that requires a lot of heavy compute. So there's a chance there as well. If testing, Q&A, you could even deploy it to run your business if it's going to be a medical office or a lawyer's office or something. And all of that, you can be done without a data center. So I think that's pretty awesome. And I think you can find all kinds of uses for something of this form factor. So to sum up, I'm running a real cluster at home. And of course, it can also be run at your office. It can run in a lab. Lots of places where it can run. It's built from re-certified top-tier components. The design of the machine is also open and easily available. It depends on ecosystems that we care about, based on open source, open hardware, and collaboration. It is extremely carbon-friendly, planet-friendly, and it sends a life of existing service through community support that we participated in. I got some useful links for you. There is all the graphical assets, the spec files are under the open compute and GitHub discovery link. So the project is called Discovery. The name of the project is called Sesame Faster. If you go to thesesimmy.com, the product webpage, and it's the product webpage, it has additional information. We have a booth. You can head over there. We have some videos and informational PDFs. I talked a lot about sustainability and carbon footprint. This is a report that gives you some numbers on what that means, what the carbon footprint is, and everything else. Finally, the last link is really a PDF. If you're interested in what the costs are for this machine or any other machine based on the configurations, you can check that out here as well. So that's pretty much the end of my talk. I hope you enjoyed it and it was informative to you to really understand this idea of being able to have computational power while still keeping a low carbon footprint. I think a powerful story and I hope people get that from this talk. I'm happy to answer any questions. Thank you very much for coming.
 Hello, welcome to the data center class containers for the masses.  I am Sri Ram Ram Krishna, principal ecosystem engineer for IT Renew.  So I want to say welcome.  It's virtual this year and I guess it would have been great if we could all have got together  physically but here we are.  But in any case, I hope you can learn something from this talk, certainly about the circular  data center, how circular data center drives open hardware and a low cost form factor appliance  that you can run real non-trivial workloads.  So let's start with who am I?  So my name is Sri Ram Ram Krishna.  I am the principal ecosystems engineer for IT Renew working in the circular data center  market, market segment.  I work with upstream.  So you might think that I may not have heard of a principal ecosystem engineer before,  but I essentially work with upstream projects in various ecosystems like Kubernetes and  open firmware and the open compute project.  I'll swing a little bit about the open compute project and open firmware going forward.  But these are the kind of things I work with.  If it's near metal, then I'm going to be interested and I work primarily with liaison, sometimes  as a technical contributor.  So it's a very flexible position.  So moving on, I think it's important that to understand the scope of this talk that we  talk about the open compute project.  And the open compute project was started by Facebook about some years back.  And the idea is to build an ecosystem of data center companies that work together and collaborate  on specifications and software or anything that drives the data center.  And you might wonder why we want to do that.  The reason it comes down to the fact that companies spend a lot of engineering time doing the  same things over and over again.  And instead of re-implementing the same thing every time for a new hydrogeneration or whatever  it is, you collaborate with other companies and then maintain that together.  And then you can spend more time focusing on discrete engineering wins to distinguish  yourselves.  And I think that's a much healthier way than, say, being permanently attached to a particular  ecosystem going forward.  So by doing this, we're more efficiently using our engineering resources that we have in  each company.  If you look at the members of OpenComputeProject, you can see that they represent a wide selection  of industries.  We have the microprocessors.  We have hyperscalers.  We have Google.  We have NVIDIA networking companies like Cisco.  So there is lots of different companies participating at the hardware level, at the software level.  And all of them working together to make an open ecosystem to build efficient data centers.  So when we talk about OpenCompute, a lot of it is about open hardware.  And I think it's important to understand what the benefits of open hardware is.  And so the first one is flexibility, right?  Everything is standard-based and vendors are participating.  Then it makes for great modular solutions.  So if you have one from one company, they all interact together.  They work together.  And that's going to be great for everyone.  And that also leads to high-density computing.  So if you're able to build the other, you can build various different kinds of computing,  like maybe high-end, high-density, low-density.  And all of that is great because if you're building high-density computing, you want to  be as efficient with space as possible.  Now if you're building high-density computing, then you really want to have efficient power.  So optimized power is also something that everybody is working on.  And so whether it's rack-level power versus individual server power, we want to be able  to work together on being efficient and having less costs and fewer points of failure.  Now if you're having high-density computing, that's going to generate a lot of heat.  And that means we really want to tackle the cooling problem.  And by all working in concert, we can figure out how we can cool these high-density computing  machines better together.  The other thing we can also do is the output from the rack-scale servers can also be repurposed.  There's a lot of heat that's generated.  We can do something with that and apply it somewhere else.  So those are kind of the interesting ideas that are happening around the Open Compute  Project.  There's also the streamlined maintenance.  If you're going to have lots of servers, then it makes sense that you want to have an efficient  way to manage all of them.  So there are teams of companies that are looking into that.  And so all of these fit together to create a data center that's going to be advantageous  going forward.  Some of the projects that we have in the Open Compute, and I'm going to focus on the ones  that's important to us in the circular data center, one is the open system firmware.  As I'll explain later what the circular data center is, but when manufacturers finish a  product line, they tend to over chime, that support goes away.  And so if we have firmware that is open source, then we can continue a lot of these products  that may have been, which are no longer being maintained because of limited manpower or whatever,  the community can move forward and be able to support it going forward.  So that's one of the great things about open source is we can maintain things as a community  and so forth.  And then there's rack and power, and rack and power is really about focusing on the  cooling and the power management of these racks and the servers, another one where we  actually look at specifications for the chassis and the racks and everything else.  So these are interesting projects for us going forward.  And of course another bit of concern is the security as well.  We want to make sure we have good security.  So that's another interesting ecosystem for us from the circular data center.  I didn't really define what the circular data center is.  And the circular data center, if we distill it down is really the idea of taking components  from Microsoft, Facebook, Dropbox, these kind of hyperscalers and then recertifying them  and deploying them to second tier markets.  If you know anything about asset management, what happens is these folks, they buy these  assets at premium prices because they want to be at the very edge of high performance.  And then after three years, they refresh their equipment.  And what happens to those components is that the circular data center takes them and then  recertifies them and then redeploy them.  And this has got a lot of advantages because it's an under-interferable supply chain of  ID components.  We take in about 18 to 25,000 components approximately.  And so that's a lot of components.  And we can use them and build products from them and extend the life of these products.  Now, that leads to the lower carbon footprint.  And the thing you should understand that is when you build or manufacture these IT components,  there is an upfront cost.  There's a cost of manufacturing, the cost of getting the parts like the rare earth metals  and the silicon and putting it in the manufacturing process.  So there's a huge carbon footprint that is already there at the beginning.  Now when you buy from the circular data supply chain, you don't have that upfront carbon  footprint cost.  And so it ends up that you're actually getting extremely useful pieces of equipment at a  much lower cost.  And because there's no upfront carbon cost, you're lowering your carbon footprint.  And they're just as good as anything else.  After all, it's used by top tier hyperscalers.  So it's completely more than adequate for most people's needs in the second tier markets.  This is a slide that sort of gives you a flow of what happens.  I like to go through it too much because I believe that we don't have a lot of time in  this session.  So what I encourage you to do is go back and sort of look through this.  And if you have questions, I'm happy to answer them.  So let's get down to the meat.  This is talking about accessible brach scale servers.  And so this is a deck side scale for node rack server.  It has four sleds.  It has a 1600 watt power supply with a micro-trivial fit switch that connects all the nodes together.  You can, based on different configurations, you can have four nodes or up to 12 nodes.  For the four node configuration, you get up to 96 cores plus one terabyte of memory.  There's a lot of NVMe storage options.  And you can also add an optional 32 port 100-gigant switch.  Now the thing that's great about this is that it's an open design.  And the chassis is designed using open source CAD tools.  And we publish the specs and rather the assets, design assets in GitHub on the OCP umbrella.  And they're also using the OCP spec for the drawer.  So all these drawers you see there is based on published specifications.  And what that means is that you can actually redesign them based on the specification of  something else.  And this is where that flexibility was talking about in the open hardware slide.  So we can reimagine things that may not have been thought of before because maybe a new  market segment has come up.  So because of that, we're able to, if we wanted to, say, make it more AI friendly, we could  replace one rack with GPUs.  You can design all of that, whatever it is, and then be able to build a new appliance.  So that's one of the great things about this open design.  And of course, all of them is out in the open for anybody to take a look at.  Now a lot of my pictures I've shown ahead are rendered images.  And I really do want to show one that I have at home.  This is a discovery that I have at home.  It has a laptop there that's kind of the admin node that manages the rest of the servers.  I have two network switches there.  I ran out of ports.  That's why there's a second one.  And there's a 32 port 100 gigabit switch, which is pretty interesting having one of  those.  I'm not using it at the moment.  That's why you don't see a lot of wires there.  But it's pretty awesome.  And we have, it's running Kubernetes using Rancher.  And then there's the hardware is managed by Digital Rebar.  Both have the links there for you.  Now this is a screenshot of the Rackin Digital Rebar.  And from here, you could, I can access all the four nodes.  I can reboot them.  I can part them down using IPMI.  I can put them back up.  Everything you would expect from a data center, I can actually wipe them, wipe the nodes and  reinstall.  I'm using Ubuntu at the moment.  But I can also do something else.  I can do Fedora or something like that.  So you know, there's all kinds of flexibility.  Now my Kubernetes is run by Rancher.  Maybe some of you are already familiar with that.  I'm sadly only using 1% of the CPU in this screenshot, but I actually have 192 CPUs there.  I have a total of 98 cores.  Sorry.  So I've got plenty of horsepower.  I was born there for many years.  But 1TB memory.  And I'm told I have 440 pods that I can use.  And that leads to a lot of containers.  Lots and lots of containers of all different kinds.  And I can run all of this at home or in a lab or whatever.  So it's pretty cool to be able to have all these containers and be able to run them and  do various neat things.  But if you don't have to stop at a cluster, we can actually do other things with them  as well.  It could be a render-blender farm or maybe that's a blender-render farm.  I get confused at times.  There's also, if you're doing research, that requires a lot of heavy compute.  So there's a chance there as well.  If testing, Q&A, you could even deploy it to run your business if it's going to be a  medical office or a lawyer's office or something.  And all of that, you can be done without a data center.  So I think that's pretty awesome.  And I think you can find all kinds of uses for something of this form factor.  So to sum up, I'm running a real cluster at home.  And of course, it can also be run at your office.  It can run in a lab.  Lots of places where it can run.  It's built from re-certified top-tier components.  The design of the machine is also open and easily available.  It depends on ecosystems that we care about, based on open source, open hardware, and collaboration.  It is extremely carbon-friendly, planet-friendly, and it sends a life of existing service through  community support that we participated in.  I got some useful links for you.  There is all the graphical assets, the spec files are under the open compute and GitHub  discovery link.  So the project is called Discovery.  The name of the project is called Sesame Faster.  If you go to thesesimmy.com, the product webpage, and it's the product webpage, it has additional  information.  We have a booth.  You can head over there.  We have some videos and informational PDFs.  I talked a lot about sustainability and carbon footprint.  This is a report that gives you some numbers on what that means, what the carbon footprint  is, and everything else.  Finally, the last link is really a PDF.  If you're interested in what the costs are for this machine or any other machine based  on the configurations, you can check that out here as well.  So that's pretty much the end of my talk.  I hope you enjoyed it and it was informative to you to really understand this idea of being  able to have computational power while still keeping a low carbon footprint.  I think a powerful story and I hope people get that from this talk.  I'm happy to answer any questions.  Thank you very much for coming.
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Hello, welcome to the data center class containers for the masses. I am Sri Ram Ram Krishna, principal ecosystem engineer for IT Renew. So I want to say welcome. It's virtual this year and I guess it would have been great if we could all have got together physically but here we are. But in any case, I hope you can learn something from this talk, certainly about the circular data center, how circular data center drives open hardware and a low cost form factor appliance that you can run real non-trivial workloads. So let's start with who am I? So my name is Sri Ram Ram Krishna. I am the principal ecosystems engineer for IT Renew working in the circular data center market, market segment. I work with upstream. So you might think that I may not have heard of a principal ecosystem engineer before, but I essentially work with upstream projects in various ecosystems like Kubernetes and open firmware and the open compute project. I'll swing a little bit about the open compute project and open firmware going forward. But these are the kind of things I work with. If it's near metal, then I'm going to be interested and I work primarily with liaison, sometimes as a technical contributor. So it's a very flexible position. So moving on, I think it's important that to understand the scope of this talk that we talk about the open compute project. And the open compute project was started by Facebook about some years back. And the idea is to build an ecosystem of data center companies that work together and collaborate on specifications and software or anything that drives the data center. And you might wonder why we want to do that. The reason it comes down to the fact that companies spend a lot of engineering time doing the same things over and over again. And instead of re-implementing the same thing every time for a new hydrogeneration or whatever it is, you collaborate with other companies and then maintain that together. And then you can spend more time focusing on discrete engineering wins to distinguish yourselves. And I think that's a much healthier way than, say, being permanently attached to a particular ecosystem going forward. So by doing this, we're more efficiently using our engineering resources that we have in each company. If you look at the members of OpenComputeProject, you can see that they represent a wide selection of industries. We have the microprocessors. We have hyperscalers. We have Google. We have NVIDIA networking companies like Cisco. So there is lots of different companies participating at the hardware level, at the software level. And all of them working together to make an open ecosystem to build efficient data centers. So when we talk about OpenCompute, a lot of it is about open hardware. And I think it's important to understand what the benefits of open hardware is. And so the first one is flexibility, right? Everything is standard-based and vendors are participating. Then it makes for great modular solutions. So if you have one from one company, they all interact together. They work together. And that's going to be great for everyone. And that also leads to high-density computing. So if you're able to build the other, you can build various different kinds of computing, like maybe high-end, high-density, low-density. And all of that is great because if you're building high-density computing, you want to be as efficient with space as possible. Now if you're building high-density computing, then you really want to have efficient power. So optimized power is also something that everybody is working on. And so whether it's rack-level power versus individual server power, we want to be able to work together on being efficient and having less costs and fewer points of failure. Now if you're having high-density computing, that's going to generate a lot of heat. And that means we really want to tackle the cooling problem. And by all working in concert, we can figure out how we can cool these high-density computing machines better together. The other thing we can also do is the output from the rack-scale servers can also be repurposed. There's a lot of heat that's generated. We can do something with that and apply it somewhere else. So those are kind of the interesting ideas that are happening around the Open Compute Project. There's also the streamlined maintenance. If you're going to have lots of servers, then it makes sense that you want to have an efficient way to manage all of them. So there are teams of companies that are looking into that. And so all of these fit together to create a data center that's going to be advantageous going forward. Some of the projects that we have in the Open Compute, and I'm going to focus on the ones that's important to us in the circular data center, one is the open system firmware. As I'll explain later what the circular data center is, but when manufacturers finish a product line, they tend to over chime, that support goes away. And so if we have firmware that is open source, then we can continue a lot of these products that may have been, which are no longer being maintained because of limited manpower or whatever, the community can move forward and be able to support it going forward. So that's one of the great things about open source is we can maintain things as a community and so forth. And then there's rack and power, and rack and power is really about focusing on the cooling and the power management of these racks and the servers, another one where we actually look at specifications for the chassis and the racks and everything else. So these are interesting projects for us going forward. And of course another bit of concern is the security as well. We want to make sure we have good security. So that's another interesting ecosystem for us from the circular data center. I didn't really define what the circular data center is. And the circular data center, if we distill it down is really the idea of taking components from Microsoft, Facebook, Dropbox, these kind of hyperscalers and then recertifying them and deploying them to second tier markets. If you know anything about asset management, what happens is these folks, they buy these assets at premium prices because they want to be at the very edge of high performance. And then after three years, they refresh their equipment. And what happens to those components is that the circular data center takes them and then recertifies them and then redeploy them. And this has got a lot of advantages because it's an under-interferable supply chain of ID components. We take in about 18 to 25,000 components approximately. And so that's a lot of components. And we can use them and build products from them and extend the life of these products. Now, that leads to the lower carbon footprint. And the thing you should understand that is when you build or manufacture these IT components, there is an upfront cost. There's a cost of manufacturing, the cost of getting the parts like the rare earth metals and the silicon and putting it in the manufacturing process. So there's a huge carbon footprint that is already there at the beginning. Now when you buy from the circular data supply chain, you don't have that upfront carbon footprint cost. And so it ends up that you're actually getting extremely useful pieces of equipment at a much lower cost. And because there's no upfront carbon cost, you're lowering your carbon footprint. And they're just as good as anything else. After all, it's used by top tier hyperscalers. So it's completely more than adequate for most people's needs in the second tier markets. This is a slide that sort of gives you a flow of what happens. I like to go through it too much because I believe that we don't have a lot of time in this session. So what I encourage you to do is go back and sort of look through this. And if you have questions, I'm happy to answer them. So let's get down to the meat. This is talking about accessible brach scale servers. And so this is a deck side scale for node rack server. It has four sleds. It has a 1600 watt power supply with a micro-trivial fit switch that connects all the nodes together. You can, based on different configurations, you can have four nodes or up to 12 nodes. For the four node configuration, you get up to 96 cores plus one terabyte of memory. There's a lot of NVMe storage options. And you can also add an optional 32 port 100-gigant switch. Now the thing that's great about this is that it's an open design. And the chassis is designed using open source CAD tools. And we publish the specs and rather the assets, design assets in GitHub on the OCP umbrella. And they're also using the OCP spec for the drawer. So all these drawers you see there is based on published specifications. And what that means is that you can actually redesign them based on the specification of something else. And this is where that flexibility was talking about in the open hardware slide. So we can reimagine things that may not have been thought of before because maybe a new market segment has come up. So because of that, we're able to, if we wanted to, say, make it more AI friendly, we could replace one rack with GPUs. You can design all of that, whatever it is, and then be able to build a new appliance. So that's one of the great things about this open design. And of course, all of them is out in the open for anybody to take a look at. Now a lot of my pictures I've shown ahead are rendered images. And I really do want to show one that I have at home. This is a discovery that I have at home. It has a laptop there that's kind of the admin node that manages the rest of the servers. I have two network switches there. I ran out of ports. That's why there's a second one. And there's a 32 port 100 gigabit switch, which is pretty interesting having one of those. I'm not using it at the moment. That's why you don't see a lot of wires there. But it's pretty awesome. And we have, it's running Kubernetes using Rancher. And then there's the hardware is managed by Digital Rebar. Both have the links there for you. Now this is a screenshot of the Rackin Digital Rebar. And from here, you could, I can access all the four nodes. I can reboot them. I can part them down using IPMI. I can put them back up. Everything you would expect from a data center, I can actually wipe them, wipe the nodes and reinstall. I'm using Ubuntu at the moment. But I can also do something else. I can do Fedora or something like that. So you know, there's all kinds of flexibility. Now my Kubernetes is run by Rancher. Maybe some of you are already familiar with that. I'm sadly only using 1% of the CPU in this screenshot, but I actually have 192 CPUs there. I have a total of 98 cores. Sorry. So I've got plenty of horsepower. I was born there for many years. But 1TB memory. And I'm told I have 440 pods that I can use. And that leads to a lot of containers. Lots and lots of containers of all different kinds. And I can run all of this at home or in a lab or whatever. So it's pretty cool to be able to have all these containers and be able to run them and do various neat things. But if you don't have to stop at a cluster, we can actually do other things with them as well. It could be a render-blender farm or maybe that's a blender-render farm. I get confused at times. There's also, if you're doing research, that requires a lot of heavy compute. So there's a chance there as well. If testing, Q&A, you could even deploy it to run your business if it's going to be a medical office or a lawyer's office or something. And all of that, you can be done without a data center. So I think that's pretty awesome. And I think you can find all kinds of uses for something of this form factor. So to sum up, I'm running a real cluster at home. And of course, it can also be run at your office. It can run in a lab. Lots of places where it can run. It's built from re-certified top-tier components. The design of the machine is also open and easily available. It depends on ecosystems that we care about, based on open source, open hardware, and collaboration. It is extremely carbon-friendly, planet-friendly, and it sends a life of existing service through community support that we participated in. I got some useful links for you. There is all the graphical assets, the spec files are under the open compute and GitHub discovery link. So the project is called Discovery. The name of the project is called Sesame Faster. If you go to thesesimmy.com, the product webpage, and it's the product webpage, it has additional information. We have a booth. You can head over there. We have some videos and informational PDFs. I talked a lot about sustainability and carbon footprint. This is a report that gives you some numbers on what that means, what the carbon footprint is, and everything else. Finally, the last link is really a PDF. If you're interested in what the costs are for this machine or any other machine based on the configurations, you can check that out here as well. So that's pretty much the end of my talk. I hope you enjoyed it and it was informative to you to really understand this idea of being able to have computational power while still keeping a low carbon footprint. I think a powerful story and I hope people get that from this talk. I'm happy to answer any questions. Thank you very much for coming.
Hello, welcome to the data center class factor appliance that you can run real market segment. I work with upstream. So you might think that I may not have heard of a software or anything that drives the data center. things over and over again. And instead of re-implementing the same thing every time for a the microprocessors. We have hyperscalers. We together to make an open ecosystem to build efficient data centers. So when we talk about kinds of computing, like maybe high-end, way to manage all of them. So there are teams of that's important to us in the circular data power management of these racks and the servers, And we can use them and build products from them data supply chain, you don't have that upfront of equipment at a much lower cost. And because through this. And if you have questions, I'm have four nodes or up to 12 nodes. For the four the chassis is designed using open source CAD because maybe a new market segment has come up. would expect from a data center, I can actually years. But 1TB memory. And I'm told I have 440 containers. Lots and lots of containers of all home or in a lab or whatever. So it's pretty cool if you don't have to stop at a cluster, we can chance there as well. If testing, Q&A, you could without a data center. So I think that's pretty uses for something of this form factor. So to sum up, I'm running a real cluster at home. And of course, it can also be run at your office. It can The design of the machine is also open and easily about, based on open source, open hardware, and are under the open compute and GitHub discovery carbon footprint. This is a report that gives you carbon footprint. I think a powerful story and I