From Austin, Texas, it's theCUBE, covering Pure Storage Accelerate 2019, brought to you by Pure Storage. Welcome back to theCUBE, Lisa Martin live on the Pure Accelerate floor in Austin, Texas. Dave Vellante is joining me and we're pleased to welcome a couple of guests from Core Scientific for the first time to theCUBE. We have Jim Benedetto, Chief Data Officer and John Curran, the SVP of Business Development. Gentlemen, welcome to theCUBE. Thank you. Thank you, pleasure to be here. So John, we're going to start with you, give our audience an overview of who Core Scientific is, what you guys do, what you deliver. Sure, well, we're a two-year-old startup, headquartered out of Bellevue, Washington. And we really focus on two primary businesses. We have a blockchain business and we have an AI business. In blockchain, we are one of the largest blockchain cryptocurrency hosting companies in North America. We've got facilities, four facilities in North Carolina, South Carolina, Georgia and Kentucky. And really the business there is helping companies to be able to take advantage of blockchain and then position them for the future. And then on the AI side of our business, really we operate that in two ways. One is we can also co-locate and host people just like we do on the blockchain side, but primarily we're focused on creating a public cloud focused on GPU-centric computing and artificial intelligence. And we're there to help really usher in the new age of AI. So you guys were founded, you said two years ago, from what I can tell you haven't raised a ton of dough. Is that true or are you guys quiet about that? We're very well-capitalized. Okay, so it hasn't hit crunch-base yet. Yeah, no, so we're very well-capitalized company. We've got, you know, to give you- Because what you do is not cheap. No, no, we've got about 675 megawatts of power under contract. So, you know, each one of our facilities is about 50 megawatts plus in size. So, no, it's not cheap. They're large installations and large build-outs. To even give you a comparison, the standard data center is about five to 10 megawatts. We won't even look at a facility or a plot of land unless we can supply at least 50 megawatts of power. So, I was going to ask you to kind of describe what's different between a sort of blockchain hosting and conventional databases or data centers. You kind of just did, but are there other sort of technical factors that you guys consider? Absolutely, I mean, we custom-build our own data centers from the ground up. We've got patent-pending technology and if you look at virtually every data center in the world today is built with one thing at its core and that's the CPU. The CPU is fundamentally different than the GPU. And if you try to retrofit CPU-based data centers for GPUs, you're not going to fully maximize the performance and the capabilities of the GPU. So, we build from the ground up, data centers focused with the GPU at the center and not the CPU at the center.  Is that a factor? Well, there's also a lot, the GPU at the center, but there's also a lot of supporting infrastructure. So, you've got to look at first off, the power density is very, very different. GPUs pull, they require significantly a lot more power than CPUs do. And then also just from a fluid dynamics perspective, it's very, the heating and the cooling of them is, again, fundamentally different. You're not looking at standard hot, cold aisles and raised floors. But the overall goal also is to be able to provide the supporting infrastructure, which is from an AI-ready design, is the interconnect networking and also the incredibly fast storage behind it. Because the name of the game with GPUs is different than with CPUs. With GPUs, the one thing you want to do is you want to get as much data into the GPU as fast as possible, because compute will very rarely be your limiting factor with the GPU. So, the supporting infrastructure is significantly more important than it is when you're doing with the CPUs. So, the standard narrative is, well, I don't know about cryptocurrency, but the underlying technology of blockchain is a lot of potential. I personally think they're very much related. And I wonder if you guys could comment on that. You started during the real sort of the latest, most recent sort of big uptick, big uptick. I know it's bounced back in cryptocurrency. And so you must have had a lot of activity in really in your early days. And then maybe the crypto winter affected you. Maybe some of those companies were so well capitalized. It was kind of their time to innovate, right? And yeah, there was some bad actors, but that's really not the core of it. So I wonder what you guys have seen in the blockchain market. We'll get to AI and pure and all that other stuff. But this is a great topic, so I wonder if you could comment. So, yes, there's certainly cyclicality in the blockchain market, right? And I think one of the key things is, being well capitalized allows you to invest through the downturns, the position you come out stronger as the market came out. And we've certainly seen that. Our growth in blockchain continues to really be substantial. And we're making all the right strategic investments, right? Whether it's blockchain or AI, because you have such significant power requirements, you've got to be very strategic about where you put the facilities. You're looking for facilities that have large sustained power capabilities, green. We've seen carbon taxes come in that'll adversely affect folks. We want to make sure we're positioned for long term in terms of the capabilities. And then some geopolitical uncertainty has certainly affected the blockchain side of the business and has driven more business to North America, which has been fantastic for us. To me, you're hosting innovation. You're doing blockchain and AI, I like saying, include crypto in there. I'm sure you've got, you have some cryptocurrency guys, right? And so we do cryptocurrency mining for ourselves as well. For yourselves, okay. But so, I mean, my take on it is a whole new internet is being built. And the crypto craze actually has funded a lot of that innovation.  And the big internet companies sort of co-opted them. So you had a dearth of innovation, that's now come back. You guys are hosting that innovation. It's kind of how I look at it. And I feel like we've seeded the base and there's going to be this massive explosion of innovation both in blockchain, crypto, AI, automation and you're in the heart of it. Yeah, I agree. I think crypto currencies or digital currencies are really just the first successful experiment of the blockchain. And I see, I agree with you. I think that it is revolutionary and is going to change as many industries as the internet did. And we're still in a very nascent stage of the technology, but at core, we're working to position ourselves to really be the underlying platform, almost like the Akamai of the early days of the internet, the underlying platform and the plumbing for both blockchain and AI applications. Right, I mean, whether it's smart contracts, like I say, new innovation, AI, it's all powering a next generation of distributed apps. Really, okay. So, sorry. I love this topic. I know you do. Okay, so where do these guys fit in? So do we. I mean, it's so exciting. I think it's misunderstood. I mean, the people who are into it are believers. I mean, like myself, I really believe in a value store. I believe in smart contracts and immutability. You know, and I believe in responsibility too and all that other good stuff. But so, innovation in private blockchain is just starting, right? You know, if you look at it, there's just, I think going to be multiple waves in the blockchain side. And you know, we want to be there to make sure that we're helping power and position folks from both an infrastructure as well as a software perspective.  It just, you know, shined a light on the whole topic. But, okay, bring us back to sort of commercial mainstream, what are you guys doing here? What's going on with Pure? So we have built, we were the first AI-ready certified data center and we've actually partnered very closely with Pure and NVIDIA. And as we went through the selection process of what type of stores we were going to be using to back our GPUs, we went through a variety of different evaluation criteria and Pure came out ahead and we've decided that we're going with Pure. And we, again, for me, it boils down to one thing. As a chief data officer is how much data can I get into those GPUs as fast as possible? And what you see is if you look at existing, you know, current cloud providers, you'll see that they're retrofitting CPU-based data centers for GPUs and you see a lot of problems with that where you're just not, the storage that they provide is not fast enough to drive quote unquote warm or cold data into the GPUs. So people end up using adding more and more GPUs to actually just increase GPU memory when they're usually running around a couple percent, like one or two percent, five percent compute, but you have to add more just for the memory because the storage is so slow. So you had, Jim, you were saying before when we were chatting earlier that you have had 20 years of experience looking at different storage vendors working with them. What were some of the criteria? But you talked about the speed and the performance. But in terms of, you also mentioned, John, about that green was a very important, is an important component of the way that you build data centers. Where was Pure's vision on sustainability evergreen? Where was that a factor in the decision to go with Pure? If you look at Pure's power density requirements and things like that, I think it's important. One thing that also, and this actually does apply from a sustainability perspective, where a lot of other storage vendors say that they're horizontally scalable forever. But they're actually running different heads and a variety of different ways.  And when you start to try to build stuff like that, you get into all the different things of supercomputing where you've got, you know, split-brained scenarios and fencing and it's very complex. But their ability to scale horizontally with just, not even disk, but with just the storage is something that was really important to us. I think the other thing that's certainly interesting for our customers is you're looking at important workloads that they're driving out. And so the ability to do in-place upgrades, business continuity, right, to make sure that we're able to deliver them technology that doesn't disrupt their business when their business needs the results is critically important. And so Pure is a great choice for us from that perspective and the innovations they're driving on that side of the business has really been helpful. I read a stat on the Pure website where users of Core Scientific's infrastructure are seeing performance improvements of up to 800%. Are these, are you delighting the heck out of data scientists now? Is that what, those are the primary users? That is, that, it references what we see with people using GPUs in the public cloud. Again, going back to the thing that I just keep hammering on, driving data into that GPU. We had one customer that had somewhere around 14 or 15 GPUs running an analytics application in the public cloud. And we told them, keep all your CPU compute in one of the large cloud providers, but move just your GPU compute to us. And they went from 14 or 15 GPUs down to two, GB 100s in a DGX1, and backed by Pure Storage with Arista. And from 14 GPUs to two GPUs, they saw an 800% increase in performance. Now, there's a really important, additional part to that. So let's say, if I'm running a dashboard or running a query and a 0.5 second query gets an 800% increase in performance, how much do I really care? Now, if I'm the guy running 100 queries every single day, I probably do. But it's not just that. It's the fact that it allows, it doesn't just speed up things. It allows you to look at data that you were never able to look at before. So it's not just that they have an 800% performance increase. It's that instead of having tables with hundreds of millions of rows, they now can have tables with billions of rows. So data that was previously not looked at before, data that was previously not turned into actionable information to help drive their business, is now they're not getting visibility into data that they didn't have access to before.  Yeah, I'm a tech nerd at heart. It's kind of rare actually for a CDO. I've interviewed a lot of CDOs and most of them are kind of come from a data quality background or a governance and compliance world.  I mean, they dress like I do. Even quite a bit better. But the reason I ask that is it sounds like you're a different type of CDO.  Just so describe your role, because it's- I was with the company from the beginning. So I've held quite a few roles actually. I think maybe this might be my third title at this point. But in general, I'm a very technical person. I'm hands-on. I love technology. I've held CTO titles in the past as well. But I've kind of, I've always been very interested in data and interested in storage because that's where data lives. And it's just, it's a great fit for me. So I've always been interested in this because the narrative is that CDOs shouldn't be technical. They should be a business. And I get all that. But the flip side of that is when you talk to CDOs about AI projects, which is, not digital transformation, but specifically AI projects, they're not intimate. Most CDOs in healthcare, financial services, even government, they're not intimately involved. They're kind of like, yeah, Chief Data Officer, we'll let you know when we have a data quality problem. And I don't think that's right. I mean, I think the CDO should be intimately involved in those AI projects. And so. And I think a lot of times if you ask them, you ask a lot of people, they'll say, are you interested in deploying AI in your organization? And the answer is 100%, yes. And then the next follow-up question is, what would you like to do with it? And most of the time, the answer is, we don't know. I don't know. So what I have found is, as I go into organizations, I don't ask if people want to use AI. I ask, what are your problems? And I think the, what problems are you facing? What KPIs are you trying to optimize for? And there are some of those problems, there are some problems on that list that might not be able to be helped by AI, but usually there are problems on that list that can be helped by AI with the right data in the right place. So my translation of what you're asking is, how could you make more money? That's what it comes to. That's what you're asking, how could you cut costs or raise revenue? That's really ultimately what you get at buying new costumers. I think the other interesting thing about our partnership with Pure, and especially with regards to AIRI, right? AIRI is an exciting technology, but for a lot of companies, as they're looking to get started in AI, there's almost this moment of pause of how do I get started? And then, if I look at some of the greatest technology out there, it's like, okay, well, now I have to retrofit my data center to get it in there.  And what we've been able to do with AIRI in the cloud is really to be able to help people jump start that, to get started right away. So rather than, let me think for six months or 12 months or 18 months on what would I analyze? Start analyzing, get started. And you can do it on a very cost-effective OPEX model as opposed to a capital-intensive CapEx model. All right, so I got to ask you, and Pure will be pissed off that I'm asking this question, because you're talking about AIRI as a, it's real and I want some color on that, but I felt like when the first announcement came out with NVIDIA, it was like rushed so that Pure could have another first. It was drawing, like, we beat the competition, but the way you're talking is AIRI is real, you're using it, it's a tangible solution, it's a core solution in our facility. It's a core thing that we go to market with and it's something that we're seeing customer demand to go out and really start to drive some business value. So, absolutely. A core component of helping them jump start that AI. Well, you guys just, I think, an hour or so ago announced your new partnership level with Pure. John, take us away as we wrap here with the news. Yeah, so, well, we're really excited. We're one of a handful of elite-level MSP partners for Pure. I think there's only a few of us in the world, so that's exciting and we're really the one who is focused on bringing AIRI to the cloud. And so, it's a unique partnership, it's a deep partnership, and it allows us to really coordinate our technical teams, our sales teams, and be able to bring this technology across the industry. And so, we're excited, it's just the start, but it's a great start and we're looking forward to nothing but upside from here. Fantastic, you have to come back guys and talk to us about a customer who's done a jump start with AIRI and just taking the world by storm. So, we thank you both for stopping by the Cube. All right, John, Jim, thank you so much for your time. Thank you, really appreciate it. For Dave Vellante, I'm Lisa Martin. You're watching the Cube from Pure Accelerate 2019.


How y'all doing? My name's Savannah Peterson, coming to you from Detroit, Michigan, where theCUBE is excited to be at KubeCon. Our guest this afternoon is a wonderfully brilliant woman who's been leading in the space for over eight years. Please welcome Garima Kapoor. Garima, thanks for being with us. Thank you for having me. It's a pleasure. Good to see you. Good to see you up to you. What's going on here at KubeCon? Saw you at VMware Explorer. Yes. Welcome back to theCUBE. What's going on for you guys here? What's the message? What's the story? So KubeCon, like I always say, it's our event. It's our audience. So, you know, Minayo, I don't know if you've been keeping track. Minayo did reach like a billion docker downloads recently. So, congratulations. This is your tribe right here. Yes, it is our tribe. We're going to have these native infrastructure. Come on. Yes. You know, this audience understands us. We understand them. You know, you were asking, when did we start the company? So we started in 2014. And if you see, Kubernetes was born in 2015 in all sorts of ways. So we kind of literally grew up together along with the Kubernetes journey. So all the decisions that we took were just, you know, making sure that we address the Kubernetes and the cloud native audience as the first class citizens when it comes to storage. So I think that has been very instrumental in leading us up to the point where we have reached the billion docker downloads and we are the most loved object storage out there. So do you like your younger brother, Kubernetes, or not? Is this a family like it's along? It does get along. I think in Kubernetes space, what we are seeing from customer standpoint as well, right? They are warming up to Kubernetes and they are using Kubernetes as a framework to deploy anything at scale. And especially when you're offering storage as a service to whether it is for your internal audience or to the external audience, Kubernetes becomes extremely instrumental because it makes multi-tenancy extremely easy. It makes access control points extremely easy for different user sets and so on. So Kubernetes is definitely the way to go. I think enterprises need to just have a little bit more skill set when it comes to Kubernetes overall because I think there are still little bit areas in which they need to invest in. But I think this is the right direction. This is the right way. If you want multi-tenant, you need Kubernetes for compute. You need Kubernetes for storage. You guys hit an interesting spot here with Kubernetes. You have a product that targets builders but also it's a service that's consumed. Yes, yes. How do you see those two lanes shaping out as the world starts to grow, the ecosystem's growing? You've got products for builders and products for people who are developers consuming services. How do you see that shaking out? Is there intersections there? You seem to be hitting that. There is definitely an intersection and I think it's getting merged because a lot of these users are the ones who dictate what kind of stack they want as part of their application ecosystem overall. So that is where, when an application, for example, in the big data workloads, they tell their IT or their storage department, this is the S3 compatible storage that they want their applications to run on or sit on. So the bridge is definitely becoming very narrow in that way from builders versus the service, consumers overall. And I think at the end of the day, people need to get their job done. From application users perspective, they want to just get in and get out. They don't want to deal with the underlying complexity when it comes to storage or any of the framework, right? So I think what we enable is for the builders to make sure they have extremely easy, simple, high performance software service that they can offer it to their customers, which is S3 compatible. So now they can take their applications wherever they need to go, whether it is Edge, whether it is on-prem, whether it is any of the public cloud, wherever you need to be, go be with it with mankind. I mean, I want to get your thoughts on a really big trend that's happening now that's right in your area of expertise. That is, people are realizing that, hey, I don't necessarily need AWS S3 for storage. I can do my own storage or build my own. So there's a cost slash value for commodity storage. When does a company decide to what to do there? Do they do their own? You see Cloudflare, you see Wasabi, other companies emerging.  What's this all about? Yeah, so there are a couple of things going on in this space, right? So firstly, I think cloud model is the way to go. And what we mean by cloud is not public cloud. It's the cloud operating model overall, right? You need to build the applications the correct way so that they can consume cloud native infrastructure correctly. So I think that is what is going on. And secondly, I think cloud is great for your burst workloads. It's all about productivity. It's all about getting your applications to the market as fast as you can. And that is where, of course, Minayo comes into play when you can develop your applications natively on something like Minayo. And when you take it to production, it's very easy, no matter where you go. And thirdly, I think when it comes to the cost perspective, you know, what we offer to the customers is predictability of the cost and no surprise in the bills when it comes, which is extremely important to like a CFO of a company because everyone knows that cloud is not the cheapest place to run your sustainable workloads.  It happens all the time. So I think if you take that uncertainty out of it and have more predictability around it, I think that is where the true value lies. You're really hitting on a theme that we've been hearing a lot on theCUBE today, which is standardization, predictability. Yes. Everyone always wants to move fast, but I think we're actually stepping away from that Mark Zuckerberg parody of move fast and break things and let's move fast, but know how much it's gonna cost and also decrease the complexity for our teams. And jump break things. Yeah, yeah, yeah. And try, you know, minimize the collateral damage. Yes. And yeah, I love that you're enabling folks like that. How is, I'm curious because I see that your background, you have a PhD in philosophy. So we don't always see philosophy and DevOps and Kubernetes in the same conversation. So how does this translate into your leadership within your team and Minaya's culture? So it's PhD in financial management and financial economics. So that is where my specialization lies. And I think after that I came to Bay Area. So once you're in Bay Area, you cannot escape technology. It is just the way things are. You cannot escape startups. You cannot escape technology overall. So that's how I got introduced to it. And yeah, it has been a great journey so far. And from the culture standpoint of you, I always tell like, if I can learn technology, anyone can learn technology. So what we look for is the right attitude, the right kind of passion to learn is what is most important in this world if you want to succeed. And that's what I tell everyone who joins Minayo. Two months, three months, you'll be up and going. I'm not too worried about it, but I think. And past pedigree doesn't always play into it because the changing technology, you could level up. So people can get into this and be contributing. I think one of the reasons why we have been successful, the way we have been successful with storage is because we've not hired storage experts. Because they come with their own legacy and mindset of how to build things. And we're like, and we always came from a point of view, we are not a storage company. We are a data company and we want to be close to the data. So when you come with that mindset, you build a product directly attacking data, not just like in traditional appliance world and so on, so forth. So I think those things have been very instrumental in terms of getting the right people on board, making sure that they're very aligned with how we do things and the DNF, the companies look for passion. And that's actually counterintuitive, but it makes sense. In new markets, it doesn't always seem you take the boilerplate, skill set, or person. We're doing journalism, but we don't hire journalists. No, it's adventurers and explorers and curious. Exactly, exactly. I think also for you to disrupt any space, you cannot approach it from how they approach the problem. You need to completely turn the tables upside down, as they say, right? You need to disrupt it and have the surprise element. And I think that is what always makes the technology very special. You cannot follow the path that others have followed. You need to come from a different space, different mindset altogether. So that is where it's important that you, like I said, adventurers and explorers are the people. That is for sure. Talk to us about the company. Are you growing, scaling? How do people find out more? Oh yeah, for sure. So people can find out more by visiting our website, min.io. We are growing, we just closed last year, end of last year, we closed our series V round, unicorn valuation and so on and so forth. She says unicorn valuation is so casually. I just want to point that out. That's probably like a true strong female leader. I love that, I love that. Thank you. Yes, so in terms of, you know, in terms of growth and scalability, we are growing the team. We are, you know, onboarding more commercial customers to the platform. So yeah, it's growth all across, growth from the community standpoint, both growth from commercial number standpoint. So, yeah. Congratulations. Yeah, thank you. Yeah, that's very exciting. Grima, thank you so much for being with us. Thank you for having me. John, as always, thanks for hanging out. And to all of you, thank you so much for tuning into theCUBE, especially for this exciting edition for all of us here in Detroit, Michigan, where we're coming to you from KubeCon. See you back here in a little bit.


Good morning. Good afternoon everyone. My name is Wang Yi. I am a cloud software engineer for Intel I have been working on starting X project for more than two years Today the topic I'm going to share with you is time-sensitive networking enabling on starting X Okay, let's start my sharing Here is the agenda. Firstly, I will brief the concept of time-sensitive networking Through the introduction, you will have a basic understanding of what TSM is Secondly, I will introduce how we enable the TSM on starting X platform Next, I will share the details about how we verify the TSM functionality we enabled In the last part, I'm going to discuss the future work about the TSM on starting X TSM is not a single technology. It is a set of standards developed by the IEEE 802.1 working group The TSM standards defined some new functions for internet networking such as traffic shipping, frame preemption, traffic scheduling, ingress policy, and seamless redundancy, etc These new functions provide a whole new layer of control for managing internet traffic For time-sensitive traffic, TSM can guarantee determinism with bounded low latency low jitter, and extremely low packet loss Furthermore, TSM can allow non-time-sensitive traffic to be carried through the same network That means critical and non-critical traffic can coexist in the same network And TSM still can guarantee the timely delivery of critical traffic The TSM standards were designed for four aspects respectively synchronization, latency, reliability, and the result management Synchronization means all nodes in a TSM network should share a common understanding of time Then the behavior of the nodes could be coordinated and scheduled on the same time basis IEEE 802.1 AS will define for this purpose Roughly speaking, the standard at 0.2.1 AS is a subset of IEEE 15 ADS standard 15 ADS standard is also called precision time protocol The abbreviation is PTP With PTP, it is possible to synchronize distributed clocks with an accuracy of less than 1 microsecond, where internet networks latency is for deterministic and prioritized packet transmission TSM has defined a couple of standards for that such as 0.2.1 AV, 0.2.1 QVU, QPV, and QCH Reliability is for robust transmission There are three standards defined IEEE at 0.2.1 CB, QCA, and QCI The last one is resource management It is for consistent network configuration TSM has defined a few standards to achieve automatic configuration for a whole TSM network Real-time transmission services are required by many industries such as industrial automation, transportation, automotive, etc Industrial Internet of Things is one of the most important user scenarios for starting X That's why we need to enable TSM on starting X platform In this page, I'd like to explain a little bit more about the standard at 0.2.1 QVU That is one of the TSM's standards we enable on starting X The idea of at 0.2.1 QVU is there are some traffic queues Packages to be transmitted will fall into one of them According to their QOS priority Each queue has a gate The control module called Time Aware Shaper can open, close these gates at a specific point in time So the Time Aware Shaper can close the gates for non-critical traffic queues while transmitting critical traffic In this way, the delivery of critical traffic can be guaranteed It already has many support for TSM In your space, there are some utilities The package IPR2 includes a set of utilities For example, the Utility IP can be used to create and config Linux Wayland Network TC can be used to config QDisk ETH2 is a utility to config the behavior of its network interface cards Linux PTP is an open source project It is an implementation of PTP protocol We can use it from time synchronization on Linux platform In Linux kernel space, there are some software components called QDisk that is queuing display From software's depth perspective, QDisk is a lower layer in the network stack It is used to control traffic such as prioritize schedule and shape, et cetera Linux already implemented a couple of QDisk such as TEPRO, MQPRO, CBS, ETF, et cetera They implemented different TSM standards TEPRO called Time Aware Priority Shaper It implemented a 0.2.1 QBV standard ETF called earliest tick time first It is based on a feature called Launch Time provided by a few network interface cards The idea is we could pre-compact expected transmission time for each packet Then, the hardware will follow the configuration to send packages at a specific time In this way, we could achieve better determinism RGB and IGC are Intel network interface card drivers They have TSM support Here in the TSM work we have done on Stunning X We enabled two TSM standards 802.1 AS and 802.1 QBV in Stunning X card containers Regarding hardware, we choose Intel i210 network interface card because it has native hardware support for TSM For software, we use Stunning X 4.0 release Of course, the latest master version is also working We choose the card container as our first step to enable TSM on Stunning X rather than generic container The reason is when we started this work, Stunning X were using Sennheiser 7.6 The current version is 3.18 The version is kind of low It doesn't have some TSM features we require The card container is more like a virtual machine It has its own kernel image This gives us the chance to customize a kernel image with required TSM features For kernel image, we choose Ubuntu 20.04 as the base image We also installed required TSM utility into it Choosing Ubuntu 20.04 rather than a lower version such as 18.04 is to get the latest TSM utilities which supports the TSM features we require 18.04 doesn't meet our requirements To enable TSM in card containers, here is what we have done on Stunning X platform We made a customized Linux kernel with TSM support for card containers We also built a container image with the TSM stack We figured out a solution to pass through I210 network interface card into card containers We also figured out a solution for time synchronization in card containers The last one is we enabled TEPRO and ETF2Q disk in card containers Due to time limitation, I don't have time to go deep into each item So if you are hoping to learn more details, you could refer to the document in Stunning X community Below is the link In order to verify the TSM functionality we enabled on Stunning X platform We set up an experimental TSM network As shown in the picture, the TSM network consists of one TSM switch and four nodes The TSM switch is a generic PC with a control TSM switch card The TSM switch card is a PCIe card with 4, 1 gig ethernet ports It is based on Intel's second way FGA And it can support 802.1 AS and 802.1 QBV The four nodes are all in Intel's Hariskania NUCs It has 1 Intel, 1 Intel, I210 NIC One of the four nodes were installed with Stunning X Simplex The rest three nodes were installed with Ubuntu Here is the software architecture for TSM verification The left part is the Stunning X node On Stunning X platform, we created a card container By using the container image with the TSM stack we created Then we path through the Intel I210 NIC of the host into the card container In the card container, we did time synchronization and enabled to kill disks TPRO and ATF by utilizing these TSM utilities A small program TSM sender were running in the container It periodically send a packet to the Ubuntu on the right side In Ubuntu, we did time synchronization too And a TSM receiver program were running on the Ubuntu platform It received the packet from the card container And dumped the time information for later analysis The Ubuntu node is the receiver side, we don't need to enable kill disks Doing time synchronization is enough for the test The time synchronization across the whole TSM network is a little complex We used five steps to achieve it In the first step, we synchronized the system clocks of the TSM switch and the Stunning X node With an external clock by NTP protocol In the second step, we synchronized the PTP clock of the TSM switch with its system clock In the first step, we synchronized the PTP clocks of the node 1 and node 2 With the PTP clock of the TSM switch In the first step, we synchronized the system clock of the node 2 with its PTP clock In the last step, we synchronized the system clock of the card container with its PTP clock Through the five steps, the three components, the TSM switch, node 1 and node 2, are on the same time basis We didn't form time synchronization on node 3 and node 4 Because in our test, we didn't use them for critical traffic transmission We have three performance indicators to measure the TSM performance It is to prove TSM is functional on Stunning X platform As shown in the top figure, it is a complete period In the first step, we print the time when the interval starts When the sender program wakes up from the sleep state TX program is the time the sender program calls the socket function to send a packet TX kernel-net scheduler represents the time we preset when a packet should be sent by the hardware Rx hardware is the time when the NIC on the received side receives the packet Rx program is the time the received program receives the packet by the socket function in the user space All the time information was collected by the test program, the TSM sender and the TSM receiver Based on them, we can calculate the three indicators The first one is scheduled times It is the interval between interval start and the Rx hardware It can indicate the determinism TSM technology brings to the system RTL specification latency is the interval between interval start and the TX program It indicates the real-time performance of the OS system It doesn't depend on TSM technology TSM network jitter is the jitter of the scheduled times It shows the variance of the scheduled times It is also a determinism indicator of TSM performance In the test, we set the period as two milliseconds When packet is sent per cycle under the scheduled time, that is the time when a packet should be sent waiting a period while the hardware is set as 1,250 microseconds During the test, around 10,000 packets were sent from the starting X node to the Ubuntu node The right figure is the test result The top figure is the scheduled times As you can see, the scheduled times for all packets are around 1,253 microseconds The variance is very small It shows the determinism performance is very good Let me explain a little more about the value 1,253 we got Roughly speaking, it is composed of two parts 1,250 microseconds comes from the scheduled time we set And a little more than 3 microseconds is spent on the link From the starting X-NIC where the TSM switch to the NIC of the Ubuntu node The bottom left figure is IT application latency The value varies in a wide range From, as you can see, from 3 microseconds to 7,058 microseconds Since we didn't use IT kernel for both the starting X host platform and the card containers The result is expected This performance can be improved by utilizing IT kernel The bottom left figure is the TSM network jitter You can see a very, very sharp peak It shows the variance of the scheduled time is extremely small Less than 100 nanoseconds And I know in some critical industrial user scenarios The jitter of the scheduled time is required to be less than 1 microsecond Our test result shows that TSM technology can meet the requirement The second test is a stress test We remain the same configuration for the first test In addition, we launched an IPerf program on node 3 The IPerf program sends massive traffic to node 4 through the TSM switch We use this way to emulate non-critical traffic The massive non-critical traffic and the time sensitive traffic co-existed in the same network On the right side, you can see the IPerf sends data to the network At a rate of around 956 megabits per second The pulse of the TSM switch and the knock are both 1 gigabits So 956 megabits is almost the maximum rate we can achieve But that rate of the IPerf received side is around 371 megabits Not 956 megabits The reason is we enabled 802.1 QB way on the TSM switch And so 40% time slice was allocated for IPerf traffic On the left side, you can see we got a similar result with the previous test This test result proves that TSM can allow critical and non-critical traffic Co-exist in the same network And the TSM still can guarantee timely delivery of critical traffic Though we already enabled TSM in studying its card containers We still have much TSM work to do on studying its platform For example, we need to spot TSM in generic containers And the IT performance is not good, we need to optimize it And currently we can fix the TSM network manually In the future, we need to enable automatic configuration for production Another interesting topic is how to share the TSM capability among containers Given the number of TSM needs on a host is limited But now we only have a recipe for the integration work In the future, we need to do further integration with studying its platform That's all for my sharing, thank you for your time