Good afternoon, brilliant nerds, and welcome back to the Mile High City. We're here at Supercomputing 2023. My name is Savannah Peterson, and you're watching theCUBE. I'm joined by the fabulous Dave Nicholson, and we've also got a fabulous fellow analyst with us, Brian, welcome to the show. Thank you, fabulous. That's the nicest thing I've been called in weeks. That's because we were just getting to know each other. Brian, no, I'm kidding. Give it time, give it time, give it time. So Brian Bieler, you're with storagereview.com. Obviously, an event with a lot of storage as front of mind. What's the number one conversation or thing you're seeing day one here walking around the show floor? Well, I mean, the best thing about Supercomput is the stuff. This is the show. It is a physical show, for sure. This is the most stuff show of the calendar year.  You've been to dozens of them this year as well, I'm sure. And so many are focused on high-level messaging on maybe some solution stuff or as a service, but this is very much stuff-oriented. And so I realize the Supercomput audience is like, you've called them, what'd you call them, creative nerds? Yeah. Okay, so half are creative software nerds. The other half are creative hardware nerds, and here we jumble them all up. But you can talk to somebody about servers and GPUs and they'll have no idea, because I've never seen it before, because they're software nerds and the hardware nerds don't really necessarily know about all the software. So this is a great amalgamation of everybody, and it's such a global audience. I have fun learning just what, talking to a guy last night, waiting to get in. What's going on in India? I mean, that's where you are, what are you thinking about? Because it's so different than what we sort of get myopically focused on in my world anyway sometimes. So I think it's a great reset. I'm really glad you brought up the global nature of that. We had someone from Dell who lives in Romania on the show. We also had some Belgian guests earlier. There's a whole Korean pavilion behind me. Oh, absolutely. Japan has a sticker activation going on for boosting around the show floor. We talk a lot, big key theme here is the democratization of AI, and I feel like sometimes that's a real big buzzword, especially in the Valley. Coming to shows like this give me hope, and I'm curious if you guys agree, because I do see small startups, large enterprise, academics, government, and countries from all over the world collaborating to help build these future solutions. David, would you agree that's the good stuff? The magic? Or am I just drinking my own community Kool-Aid? I thought my role here was to always disagree with you, Savannah. We can, I mean. No, no. You know I don't mind a little confrontation. Yeah, no, no. No, I agree completely. It's interesting. I mean, it is absolutely a global gold rush in a lot of ways. Yeah. Number one thing, you know, when asked about the hype cycle, the answer is yes, the hype is a hype cycle, but it's real. I think that the evolution that AI will bring is real. You mentioned folks in coming from the hardware perspective or the software perspective, you focused on storage, right? For a period of time. How has that changed? And do people appreciate it? I mean, just anecdotally, I can tell you I've had conversations with people who struggle over this idea of creating a quote unquote persistence layer like it's never been done before. Right. What are your thoughts on the shifting sands of storage outside of the array, inside of the array, in the server, out of the server? I mean, there's a million ways to go with that. And just as a point of clarity, when you say in the valley, I assume you mean the Ohio River Valley? Or are you talking? That's exactly what I'm referring to.  So in the Ohio River Valley, we are very concerned about democratizing AI. So I'll give you that one callback, but I do think it's, I didn't really know that that was a theme, but it's something that we've been talking about for a long time is that there's all these tools available, whether it's storage, GPUs, compute, any of these things, but they're not equally accessible, I would argue, to organizations of all size. So we're here looking at the HPC audience today, but there's a lot of enterprise customers here too, looking to see what these guys are doing at the bleeding edge and how that will translate into enterprise solutions in the data center. Dell's here, we spent some time in their booth. We've got a number of GPU servers that are really great, but it's not just so easy as placing the order and throwing this in your rack. There's all sorts of new things. And to your point about storage, networking and storage are a big part of that because these GPU servers specifically are not storage heavy. They may have a drive per card in their configuration. So how do we fuel these GPUs? Because I'm going to drop a million or a couple million dollars and from an enterprise perspective into an enterprise data center to use AI to help research or improve our businesses or whatever we used to call business information or analytics three years ago. All the infrastructure's got to be there to support it. You said, are there changes? I mean, yeah, there are changes everywhere, but we're in this period that feels so fragmented. I don't know that there's one right answer because we can look at the banners scattered around here. You've got software-defined object storage that'll run on anything and it's cheap and deep. That's one thing. You've got these big parallel file systems, there's two over there, that's another thing. You've got the standard file unstructured players that have been after this market for decades. So it's wild. I don't know that there's any one thing happening. There's so many things happening which does make it even more challenging to sift through what's appropriate for your organization or your deployment. So in the world that is storage review, what I just heard you say is lots of job security. Because- Perpetual, yes. Perpetual job security, perpetual movement in change. Where do you think these enterprise instantiations are going to occur? Do you think people will default toward an older model of deploying things internally on-premises or does the sort of fear of missing out that people experience now, is that the final push where it's like, okay, no, by default, this is going to be SaaS. We want this as a service delivered by, whether it's a hyperscale cloud provider or some niche service provider. Is this yet another nudge in the direction of cloud or is it a validation of hybrid? Any thoughts? I mean, I think at the lowest level, the argument should start with your organization should be doing AI. So that's like foundational thing because if you're not involved, and I don't even think this is a Fortune 500 problem, I think this goes all the way down the stack. And depending on where you are in that stack, I think answers the question in terms of where you should be.  I think this is so important because I think there's a ton of gatekeeping in this industry that I find really frustrating that professionals that are in here that have been doing this for years will look at these infrastructures or storage or GPUs or servers and say, well, this is the way to do it with this software stack and this is the output and here's what you get. And if you're not doing it that way, you're doing it wrong. And I think that's a, I mean, it's a little sickening, honestly, because- I agree with you, it grosses me out. Because these organizations that are trying to do it and they're starting with a workstation, with a couple A6000s in it, you're still talking about a $50,000, $60,000 investment in hardware and they're learning and they're trying to do it and they're trying to get better and trying to figure it out. This is not AI, that's still AI. It's still productive and this workload that can start on a workstation, I think the question is, where does it go next? Does it go to on-prem infrastructure? Does it go into the cloud? Does it do both? And part of it's, I think about cost and availability. We were told just a week and a half ago that the wait for H100 systems, you place your order today, is somewhere around 40 weeks. And so NVIDIA's doing the pivot. That's pretty wild. Well, and the wait is for who? Not me getting one delivered to my house. There are very large organizations that are at the head of the line. Oh, absolutely, and they will command attention. Yes, so the average enterprise waiting for five of them versus someone who is buying as many as can come off of the assembly line, as can be produced. So that's perhaps a driver in terms of the where question. Is can I get access to the hardware? And everyone needs H100 and NVIDIA says, well look, we've got this shiny L40S, it's available now, relatively speaking, a couple weeks. And it's opening up the market I think too for AMD, Intel, and others with accelerators that come in with perhaps lower cost options that may not be quite so powerful, but the AI you can do today is better than the AI what you can do waiting for your GPUs to show up. Well, I mean, if we're talking about 40 weeks, that's a whole year of lost development, essentially. And there are a lot of cars that can get you over the finish line right now for a lot of different types of processing. Get you something, right? Which is I think is better than nothing. But the cloud, of course, is very much a player too. As you said, we recently did some work with OVH cloud who's got what would be considered by this audience sort of lower end V100s in the cloud. But again, I really think it's about accessibility and what can you get and affordability and how can you measure your investments in AI? If you're starting, it's a whole different set of metrics than if you're already succeeding and already have AI teams that can go in and leverage an Oracle cloud bare metal eight by H100. But that's not free either. I mean, that's a year commitment at a minimum and a lot of cycles that you've got to burn. So you've got to be ready to do it and to your point about data, you've got to be able to move the data to these GPUs. That's a whole nother issue with cloud based GPU computing. It really is, I think. And just for anyone listening, I thought this was cool. We had Johnny Dallas, the founder of ZEAT on last night and he's created a website, gpucost.com, that shows you the availability, the pricing and the providers of every one of these GPUs. And I've been scrolling through between some of our breaks and it is wild like you're talking about to see the delays that we're seeing now and anticipate what may happen as supply chain challenges become more complex and demand becomes higher and moving forward. Having a strategy about your hardware right now, I think is absolutely imperative. Building on that, I just think it's an awesome point and we haven't touched on it yet. And not as busy as it was last year because I think it's getting overshadowed by this very large AI presence in the room is quantum and hybrid quantum. And when we're talking about processing speed, how are the amount of compute we're going to need there? How do you think that's going to affect the market? It's just another tremendous shift, right? I think that's another strategy where maybe not today, right? But I think a lot of organizations, whether they're these big HPC installments or enterprise are again have to be evaluating it to see where that puck is moving to try to have a strategy there. And I think if this GPU availability has taught us anything, it's that the planning is absolutely critical and it's not like the old days of pre-COVID where you could walk into your DISTY and buy whatever you wanted to buy and it'd be on your doorstep in a couple of days or weeks at worst, much more strategic. And there's so many more choices and quantum's another one where it's like, what am I trying to do with this? And really understanding what the output is that you're going after, what the benefits are of the technology and having a plan to consume that, again, either on-prem or in the cloud or wherever. I mean, you didn't bring up edge, that's the other big, that's the other. I was going to drive there, because yeah. Yeah, I mean, that's another one and another one where storage is making a big impact. We've got a project underway right now actually where we're developing our own LLM for scientific research. So Jordan, yeah, it's pretty fun. We're going to open source it too. But Jordan, who's on my team has a passion for astrophotography. And so when you rig up these high-res cameras to a telescope and you're out in the middle of nowhere, you've got all sorts of thermal issues, you've got power issues because you're going to have to use battery most likely to power these things. And you've got data issues because these guys do not want to get rid of any image they've ever taken because as the model gets better, what it does at a very high level is it takes all of these images, it runs through an inferencing engine at the edge or can run at the edge on a smaller GPU and clean up the images and then send back the final image to your data center for more deep processing on something A100, H100, whatever. This whole data modality is tremendously punishing because you've got all this data, you've got Starlink is your best in class communication at the far edge. And you've got thermals and humidity and snow or dust and all these other things that are really terrible. So we've run this rig in Arizona, it's going, we've got a new one running on Dell XR servers with these super dense, solid-ime SSDs that now go up to 61.44 terabytes in a single U.2, which is amazing. So a server that has four bays can now support whatever that's 61 times four, the big math, I know. And we can really do all that data collection but we're talking about data mobility to the cloud. We're looking at something where SneakerNet is still the fastest way to transport that data. And as much as we're all excited I'm excited about Flash and the high-end technologies here. There's two guys over there with tape libraries that are still fundamentally where a lot of this stuff goes to reside that none of us want to get rid of and tape, like, Flash is cool and all but tape's sort of still pretty badass. I don't know, can we say badass on this show? We can now. I give you permission. Too late, too late, live. My apologies. Don't apologize, it's all right. Well, John's flexible as long as it's the right audience. We're not gonna find anyone. We're giving our hot take, sometimes includes hot language. There we go. So there's absolutely nothing wrong with that. I was thinking about it. I saw, and this is the first time I've seen this, there's a couple booths giving away GPUs which is, first of all, that's how you know you're at supercomputing. But second of all, in the current state of things I thought they should have somebody guarding that depending on how nice it was. I would say so. I mean, you're watching the tracker. I mean, in each 100 these days is what, 30K retail or something like that? Yeah, men. Yeah, I mean, even the L4s which we've been using the A2s for the inferencing which is like the easy GPU solution. I think those guys in retail volume are like 24, 2300 bucks. I mean, it's not nothing. This is a chunk of change that we are talking about. Yeah, I'm, I'd like to get your take on this. I'll throw this out there. Okay. You can tell me what you think. I'm curious about the utilization of all of the GPUs that have been installed. Absolutely. Out, especially in hyperscale cloud providers. There is a race to make sure that they don't miss out. Along the way that those supply chain issues, if you will, that arise, get people to take a closer look at what you can do without those GPUs. So training and inference aren't the same thing. Inference doesn't have to have, inference when you're typing into an engine that is checking your spelling needs to happen right away. Inference doesn't always have to happen instantly. And so there are massive cost breaks when you move away from using dedicated, most expensive hardware down to other tiers. And so I see a battle shaping up among these sort of Nvidia ecosystem versus the, hey, wait, you can use more generic things, more cost effectively, number one. And number two, it'll be very interesting to see if in fact all of the people gobbling these GPUs right now are going to be able to effectively monetize them. You said first everybody should be doing AI. I'm sure you would agree that what you meant was first decide what the business problem is you're trying to solve or what the big, it goes without saying. Then you decide, are these tools something that I can work with? Feels like the hype cycle is driving a lot of activity which is great for all of us. It'll be interesting to see utilization wise. Do you have any insight into what that looks like now? I wish, it would be great if the clouds would be a hair more transparent about what is being used because that might actually influence some other people's decisions and some consumption models that may be important for supply chain as you go. Is anyone waiting to spin up a cluster of GPUs that are maybe virtualized with VMware running in AWS? Are people waiting? Is there a three month waiting list to get in? We're talking about 40 weeks. You can have a baby in 40 weeks but you can't get a GPU? It's kind of. I mean, I haven't compared it to baby delivery. I was going to say that was a really bold choice. That's a hard thing, I like it. I have four kids, everything gets compared to babies at some point. Mine are too old, I can't remember the whole process but I'll take your number as fact. I mean, I think if you walked into any one of these clouds and said I'm ready to sign a contract for a couple years for these eight way systems I don't think you have a big problem gaining access to it. In the immediacy of the cloud has always been the historical benefit of the cloud, right? But utilization, I mean, I think you even have to take that back to the workstations where we started at kind of the entry AI model or the lower cost influencing cards. It's like, if you're going to make the 50, 60, $100,000 investment in these pieces of equipment you want to make sure that that's up all the time. So we've got some great systems in from the major workstation providers that are here and one of the arguments we've been making lately is put these things in the data center and figure out how to intelligently provision them and share them with your team so that when you need one in your valley which is a different time zone than my valley we can get more utilization out of the machine and have better return on that hardware investment. But I think it's true through the whole stack. No one wants to drop a couple million dollars on a big time GPU stack from any of these vendors. We've been playing a lot with like the 9680 from Dell. Those things are absolutely amazing. It must be used all the time or you're wasting or at least not maximizing your investment on these things. So there's a lot of that to be said and a lot of that to be figured out still honestly in terms of how we keep these things pushing all the time and get those insights and then of course ask the right questions, as you said. That's such a good point. We had Grock with a Q, not with a K, not Elon's Grock on the show just before you and it was actually, we were talking about batches and how small batches can actually be incredibly expensive to run it to your point, not optimized and having inference tools like Grock, like other players in the game to help figure out when to run and how to optimize that makes the hardware worth the investment or not. I mean, to your point, I think it's a really interesting trade-off between... Plus they had a llama outside this morning. They did. I heard about that, which I still contend that it could be a wild herd of... Local llamas. Local llamas. Local llamas get loosened. That could be the headline. Could be a coincidence. SC-23 interrupted by local llama herd. But we're both from California, so we're not...  It's... We just fly over. It's on your way to Boston and New York. You'll see it out the window if you take a peek. Truth be told, I've been to Columbus twice in the last 30 days. You see? You're not so bad. You can come down south and hang out in the lab, which is one of the things like why I get so excited about hardware is because we've got a lab and we're touching these things and we're setting them up and we're going through the pains and much of it self-inflicted, I'll admit. We're not always perfect and clean and tidy in our approach, but it's very pragmatic in terms of getting these blade servers in. We've actually got four H100s in our lab right now, which is... I shouldn't say that when we're out of town. I was just going to say, what's your code? What's the address? Yeah, yeah, yeah. Kevin's manning the lab and we've got the intern on 24 hour watch. But we're doing all sorts of crazy stuff. We've got liquid nitrogen coming in tomorrow and we're going to do some overclocking world records, we hope. So there's so much out there, there's so much possibility. And I mean, you're talking too, I don't want to drive past this about what you do the work on. There's a lot of momentum around trying to do more AI work on CPUs. Exactly. And not just the GPUs. And of course, NVIDIA this week's talking a lot about Grace Hopper. We've seen systems from at least half a dozen vendors here that are either double grace systems or Grace Hopper super chips. I mean, there's so much potential. And there's to your point earlier about keeping busy and employed. I mean, I think there's going to be a lot of work. A lot of work needs to be done in exploring these solutions, looking past vendor claims and saying, what are these things really good at? And not necessarily siloing those, but isolating the benefits of ARM architectures, of DPUs, of all of these things and helping people sort out where the benefits are and to make reasonable investment decisions. My goodness, what a fantastic series of insights. I want to call out one last thing before I close the show.  Grace Hopper as a platform versus an H100. I feel like we can just get a little sexier with the naming. Brian Bealer, thank you so much for being here with us. Thanks for having me. Wonderful insights. And I look forward to having another chat with you again at some other NerdFest. David, always a pleasure to share the stage with you and thank all of you brilliant super compute fans for tuning in to our live coverage here from the mile high city. My name is Savannah Peterson. You're watching theCUBE, the leading source for emerging tech news.


Let's see here. What is the appropriate poem to start out for y'all? How about the poem that's the first poem in the book? It's called What It Look Like. I actually don't read it out a whole bunch. Let me get my clock going. And if we're going to do questions, you can raise your hand in the middle of it. That's what I always hated about church. I couldn't ask the question during church. So you're sitting there and the preacher says something crazy, so I'm going to ask you about that. All right, OK. So if you have a question, if it sounds really crazy, I will stop. I will answer it. And that'll be fun, and then we'll move on. All right, so this is just called What It Look Like. There's not that much to say about it.  I don't especially care for Duke Ellington at a birthday party. I care less and less about the shapes of shapes because forms change, and nothing is more durable than feeling. My uncle used the money I gave him to buy a few vials of what looked like candy after the party where my grandma sang in an outfit that was obviously made for a West African king. My motto is never mistake what it is for what it looks like. My generosity, for example, is mostly a form of vanity.  This only looks like a footnote in my report concerning the party. Trill stands for what is truly real, though it may be hidden in the houses just over the hills between us, by the hands on the bars between us. That picture of my grandmother with my uncle when he was a baby is not trill. What it is is the feeling felt seeing garbage men drift along the pre-dawn avenues, a sloppy, slow rain taking its time to the coast. Milk toast is not trill, nor is bouliabase. Bakushan is Japanese for a woman who is beautiful only when viewed from behind. Like I was saying, my motto is never mistake what it looks like for what it is else you end up like that Negro Othello. Was Othello a Negro?   And that's OK. No one will tell you you are the king. No one really wants a king anyway. So that was weird. I guess I could have said some stuff, like trill. Everybody knows about trill. That's trill. It's a portmanteau. Portmanteau. When you put two words together, trill. That's very trill. And what else should I have said? Yeah, Bakushan, that's true. That's what that word means. Othello, you know, he was a Moor. All right, so here's the second poem in the book. And this is the one I usually start out with. And you'll see very quickly how it's a very different kind of poem than the previous one. The only thing they share is the befuddlement. So when you hear weird stuff in it. So you need to know this. Potascola, there's a few things. Potascola is a town between Pittsburgh and Columbus if you're going west. So for me, just being on the highway and seeing a town called Potascola, I thought, oh, that's got to be in a poem. So that's why it's there. And then the other thing, the poem is sort of about a drive and then seeing something happen to a deer. But the other thing you should know about it is the muscadine, which I'm sure doesn't get up to Minnesota. Y'all know about the muscadine? So that's in there. And so it's just like this little berry. The joke I tell is that they can probably sell it in whole foods in Minnesota. But in South Carolina, it just is like a weed. It just grows on the side of the road. So they have muscadine wine.  But I don't even know if it gets up above, say, North Carolina or maybe by Virginia even, it can't sort of grow in those terrains. So whenever I read it out, I got to tell people, muscadine, look forward and hold foods. $5 a berry. All right, so that's it. That's all you got to know. The deer. Outside Potascola, I saw the deer with a soft white belly. The deer with two eyes as blind as holes. I saw a leap from a bush beside the highway as if a moment before it left, it had been a bush beside the highway. And I saw how, if I wished it, I could be the deer, or creature bony as a branch in spring. And when I closed my eyes, I found the scent of muscadine. The berry, my mother plucked sundaes from the roadside where fumes toughened its speckled skin and seed slept suspended in a mucus thick as the sleep of an embryo. It is the ugliest berry along the road. But chewed, it reminded me of speed. And I saw, when I was the deer, that I didn't have to be a deer.  Though it is not like this for the deer, it is not shame because the deer is not human. It is only almost human when it looks on the road and leaps covering at least 30 feet in a blink.   I remember a friend told me how when he was eight or nine, a half-naked woman ran to the car window crying her man was after her with a knife, but his mother locked the doors and sped away. Someone tell him his mother was not a coward. That's what he thinks. Tell him it was because he and his little brother were in the car that she would not let the troubled world inside. It was no one's fault. The mind separated from the body. I could almost see the holes of her eyes. The white fuzz on her tongue. The raised buds soft as a bed of pink seeds. The hold of a mouth stretched wide enough to hold a whole baby inside. I could almost see its eyes at the back of her throat. I could definitely hear its cries. So what I'll tell you about that one is that do not ask any questions. Because I can't answer them. Sometimes I can write a poem. Like in the first poem, there's a fellow and at the end, and it's not everybody's gonna know, ODB, I should just say, I just assume everybody knows who Old Dirty Bastard is. Only certain of us in the audience will know. If you don't know who Old Dirty Bastard is, it's exactly what it sounds like. Somebody whose name should be Old Dirty Bastard. That's the last poem. So we had Old Dirty Bastard, and then at the end when I do a fellow and then I say, you are blind to your power, brother bastard, like the king who wanders his kingdom searching for the king, y'all know who that is. All the English major, that's King Lear. But I never say it, right? I don't so, so there's Old Dirty Bastard. Some people will know that, and then some people will be like, oh, there's a King Lear reference. He didn't actually say King Lear. We move on, so I can explain that one. That's all I'm saying to you. The deer, I can't explain it. What's happening, the eyes in the back of the throat and the, I don't know, it just, it felt right. And I like those kinds of poems. I like the poems where I sort of can't quite explain them. I'm mostly reading from the front of the book. Here's another one. So at one point, I decided I was gonna write a poem for every state. I got the idea from Sufjohn Stevens, this other singer, he's, I mean, those of us who know who Old Dirty Bastard is and Sufjohn Stevens, we should talk. Those are people I wanna hang out with. And King Lear. So if you know one of those, you're probably a third of my friend. I got a third of interest in you. So Sufjohn Stevens had this project and so he was like, I'm gonna write a, I thought he was gonna do a record maybe, a record for every, the 50 States Project, which is ridiculous. So he did like two or three. And they're good, the Michigan one and then the Illinois, and then he got on to some other stuff. So similarly, I was like, yeah, I'm gonna do that too. So I have like a New York poem and then I did a New Jersey poem and I was done. So I'll try this one. The reason that I, you know, this is just like for your information, I guess. The reason that I'm gonna read this one is because the dude who's in that, who shows up in the deer poem is, he shows up in this poem too. So they're totally unrelated, but it's just like, you know, when you have friends who have like, I think his life is more exciting than mine. So most of the stuff he does is not even like, I can't even bring it up now, the kind of stuff that he does. And he tells me about it. And occasionally we're together. So like, here's the scenario. And I will say that the poem is, even though it's sort of even my imagination, it is, you know, it's true, but it's not fact. If you can distinguish between those two things. But the thing is, should I tell you this story before I read the poem? I'm gonna tell you. So we go to this party and in New York, this is a little hoity-toity, really sophisticated party. It had like a vice room. This is what they do in New York. So like everybody at the front, it's like we're having a good time, but if you want to get in trouble, you can go to the vice room. So that's where he was. And so I was just sitting on the couch and then every time a woman would come up to me and start talking, he would show up and be like, don't talk to her, what's your name? You know, that kind of thing. So this is my friend. So in the night, he doesn't get lucky. It's like six o'clock with the last people at the party, because he's like, okay, now those women left, let me work on these women. He just was trying to like, get hooked up. And it never worked out. I just sat on the couch, I took a nap. And then at the end of the night, he apologized and he was like, man, I'm sorry for abandoning you, trying to get hooked up, man. And I was like, man, you know what? I was half asleep, don't worry about it. And then I wrote a poem about it. New York poem. And again, those are all the facts. So this is like underneath all of that. And you'll know the moment. I was thinking about him being concerned every time a woman that I wasn't interested in wanted to have a conversation with me. So that's just peripheral to the poem. So all of that is just the stuff underneath it. So it's called New York poem. In New York, from a rooftop in Chinatown, one can see the sci-fi bridges and aisles of buildings where there are more miles of shortcuts and alternative takes than there are miles Davis alternative takes. There is a white girl who looks hijacked with feeling in her glittering jacket and her boots that look made of dinosaur skin. And R is saying to her, I love you. I love you again and again. On a Chinatown rooftop in New York, anything can happen. Someone says, abattoir is such a pretty word for slaughterhouse. Someone says, mermaids are just fish ladies.  In New York, not everyone is forgiven. Dear New York, dear girl with a barcode tattooed on the side of your face and everyone writing poems about and inside and outside the subways. Dear people underground in New York, on the sci-fi bridges and aisles of New York, on the rooftops of Chinatown where Miles Davis is pumping in and someone is telling me about contra-nems. How cleave and cleave are the same word looking in opposite directions. I now know bolt is to lock and bolt is to run away. That's how I think of New York. Someone jonesing for Grace Jones at the party and someone jonesing for Grace. So yeah, so that's all underneath it. So here's the rest of that story. So then, so I write the poem, I don't tell my mama write it and then I'm like, well, it's the New York poem, I should send it to the New Yorker. Send it now, send it to the New Yorker, of course, they take it and then it gets published and then he sees it and all the people who were at the party sees it and he says to me, man, my wife's that poem ruined my marriage, my wife saw that poem. I was like, man, your marriage was already ruined. So, so, and then he gave me a Grace Jones record at the end. Like who's looking for Grace and who's looking for Grace Jones? Oh, you know, this is just a side note. I was thinking about this when I saw this, when I wrote the poem, so when I say like the difference between fact and truth, like there was no girl, I didn't come across a girl who had a barcode tattooed on the side of her face, but you know, it's a weird enough and wild enough place that's very easy to believe, right? So I was like, what's the wildest thing I can do? Oh, I know, somebody's got a barcode tattooed on their face and then what happened? Gucci Mane got a two ice cream cone tattooed on the side of his face and that's fact. So I'm saying like, which is crazier that this dude's got an ice cream cone tattooed? Y'all probably don't know what I'm talking about Gucci Mane. Anyway, so I was like, he trumped my poem.  Anyway, that's a side note. That has nothing to do with anything. So it sounds like we are talking about hip hop today. That's not what I was planning on doing, but it's sort of our theme, at least for the, I'll read this poem, which is a slightly more serious poem or intense poem. Maybe it's a rated R poem, but it looks directly at it and then I'll read y'all some other stuff because I've just been hanging around in this first section but it's thinking about, maybe it's thinking about that, like what does it mean to like a dude who would have an ice cream cone tattooed on his face? Like what does that say about me? If that's like somebody that I really like. You know what I mean? So the poem again, think about that. That's what's up underneath the poem. So and this one, not that it matters, I guess, it's the truest, the most factual of everything that I've read, which is to say like I ain't making much of it up. Oh, here's another reference in it. I know y'all don't know about this. UGK, International Players Anthem. Y'all know that? Okay, so there's a reference to that in there too. So when I say it, it's a parenthetical line. It still is the same thing, like the International Players Anthem is like a pimp's cold. The whole song is about like the life of a pimp. So that'll help if you don't know the song. But otherwise you should check it out. It's pretty good, International. It's also part of, it's such a bouncy tune and then you start thinking like, what is he saying to me? So, all right. As traffic, as traffic, sounds like the hook in a chart topper, a rapper mouths squatting like a gilded animal in the middle of a bustling boulevard of bumpers and bumping bikini rumps. Chains, chains, chains. But it is meant to conjure my half brother and the girls, the news says he'd kidnapped or persuaded with knuckles before the police rushed in, knocking him like a lover, no longer loved to the motel floor. His long arm was chained to a cell phone. The one time I met him, he called me brother and said our father had more children like us all over town.  Foolishly, I did not think the worst of the music I adore had anything to do with having power over anyone else. The naked women as bountiful as traffic, the half naked men who cannot grow stiff without looking at reflections of themselves while the camera glares an inch from their genitals must have wanted before porn simply to play hardcore, like the hardcore rappers paid to be wrapped in chains of rhyme and the arms of women working for men who want to fill the soft pockets of everything with something of themselves. A camera swelled over the locks on my brother's body in the courtroom the way the police lights swelled over the girls he trafficked miles from money and taxed for gas back home and the protection he offered them from the belligerent Johns and when called for protection from himself. Before the judge denied bail, the ruling was on the news.  He will live in a cell with the beautiful solitude chained about his throat growing over time as permanent and illegible as what has been scratched, tooth and nail into the cells. The music I have been playing all my life is about pimps and who will be pimped. But when my daughter is listening, I play something else. All right, all right, let's see, let's go to another section. I was talking about this one. Thank you, thank you. Thank you. I was talking about this one because I was asked just about typos and poems. So this poem, Barbarism, was in the New York Times magazine. Maybe the Sunday before last. So you know that's a lot of people, a lot of people saw it. So I saw it online right before it came out in the print version. And I saw that in the poem, they had a typo. It was just one letter. So in this, you know, in my poem, I said he'd, he apostrophe D sworn to never let his hair been cut again. But in the magazine version, for whatever reason, I guess the D is next to the S. They had, he's sworn, as in present tense, he has sworn to never let his hair be cut again. So when I saw it, I was like, this is about, you know, not, you know, staying next to you, what you believe. So I was like, well, it's just one letter. You know, what does it matter? What does it matter? Of course, then I got like a little onslaught of people saying that poem makes no sense. I was like, oh, it's a D, it's not an S. I should have said something, but I didn't. So, so I feel like I ain't gotta read it and not have corrected. It wasn't a poem that I read out a whole bunch. So, and you, I guess I could say that too, just about like my approach to the poems. I do like to try to like, you know, swerve and surprise. And this poem kind of has some of that, but I, this almost didn't make it into the book because I thought it was like too sweet that makes any sense. I know that's what people think poems are supposed to be. That's just, it gets boring after a while. But I'm glad I put it in and they selected it. I didn't ask them to pick this one. So I was like, I guess it's all right, except that they screwed up one letter in it. But, you know, so, so that's why I'm gonna read it just because it's gotta be, I gotta correct it for the universe. And there's nothing, no, that's what I mean. Like I don't have to do a whole bunch of talking about what's happening in it. And so in that regard, I always think like, does that, is that really worth my time when I think about poems? But I did write it, so I guess it means something. It's called a barbarism. It was light and lustrous and somehow luckless. The hair I cut from the head of my father-in-law. It was pepper blanched and wind scuffed, thin as a blown bulb's filament. It stuck to the teeth of my clippers like a dark language. The static covering his mind stuck to my fingers. It mingled in half-hearted tufts with the dust. Because every barber's got a gift for mine reading in his touch, I could hear what he would not say. He'd sworn to never let his hair be cut again after his daughter passed away. I told him how my own boy, his grandchild, weeps when my clippers bite behind his ear. But I could not say how the blood there tastes. I almost showed him how I bowed my own head to the razor in my hands. How a mirror is used to taper the nape. Science and religion come to the same conclusion. Someday, all the hair on the body will fall away. I'm certain he will only call on me for a few more years. The crown of his head is already smoother than any part of his face. It shines like the light and tiny bulbs of sweat before the sweat evaporates. All right, so you know it's just about haircuts. Let me see how we're doing with time here. I do have one or two new things to try. Yeah, I'll do this one. Actually, it's just going to turn out, because this one too, this one's called the carpenter ant. Maybe this is the last one and I'll end up with just some newer stuff. Although I don't know if I should end on the new stuff. It might not be that good. Maybe I'll read this one and I'll end on something else in the book if I think about what it is. So this one is behind it, since we're going to do, as I said. I never know what's going to happen when I get up here. So behind this poem is actually Kendrick Lamar. But it's from when he did Thebes on a Record with BJ, that kid from Chicago, and the song is called His Pain. So you wouldn't know that. And I actually, I read this poem once and I said to the audience, anybody that knows where this reference comes from, I give $100. And then the dude did know. So I'm not going to say that, but it's changed. I changed it a little bit, but it is a line that comes up in that song, His Pain. But the poem really has nothing to do with that. It's just that when I heard the line, I don't know why God keeps blessing me. I was like, oh man, that would be fat for a poem. So I just, I put it in the poem. The carpenter ant, and it's one sentence, it's one long sentence. It was when or because she became two kinds of mad, both a nail biting into a plank and a screw cranking into a wood beam, the aunt, I shouldn't say her name, went at the fullest hour of the night, the moon there like an unflowered bulb in a darkness like mud or covered in darkness like a bulb or a skull is covered in mud. The small brown aunt who, before she went mad, taught herself to carpenter and unhinged in her madness, the walls she claimed were bugged with tiny red-eyed devices planted by the state or Satan's agents, ghost of atheists, her foes or worst, the walls were full of the bugs she believed crawled from her former son-in-laws crooked mouth. The aunt who knows, as all creatures know, you have to be rooted in something tangible as wood if you wish to dream in peace, took her hammer with its claw like a mandible to her own handmade housing humming, I don't know why God keeps blessing me, softly, madly, and I understood. I was with her when the Paul Bearers carried a box made of mahogany from her church to a hearse to a hole in the earth. It made me think of the carpenter aunt who carries within its blood an evolved self-destructive property and on its face mandibles twice the size of its body and can carry on its back as I have seen on TV a rotted bird or branch great distances to wherever the queen is buried. Kingdom Anomalia, phylum Arthropoda, tribe Camponotini, the species that lives on wood is like mud, rain, and time, the carpenter's enemy, yes. But I would love to devour the house I live in until it is a permanent part of me. I would love to shape as Peruntha Chan, the master sculptor, carpenter, and architect of India is said to have shaped a beautiful tree into the coffin in which I am to be buried. I know whatever we place in a coffin, the coffin remains empty. I know nothing buried is buried. I don't know why God keeps blessing me. I don't know why God keeps blessing me. All right, so let's try. So by the time I tell you this story for this poem, we will be out of time. So let me see if I can tell it to you really quickly. I do have like a bunch of long poems I've been working on and it's really about finding my half-brothers. And I will say, I mean, when the poems are true, they're true. So like the half-brother that's in that poem asked traffic who went to jail for human sex trafficking. I do searches for these guys because I only met them once, the two. So one time when I did a search, I found them on Myspace. So they went to Myspace once in like 2009 and they put up all of this stuff and they answered these questions about it. It was really to find women. So I found, I was like, hey, I see you guys are here, but they never went back. They never got back on the site. But then I just started writing poems around it. So this is one of those poems. And so I have a whole bunch of this stuff going, but this is the one I'm gonna try for you. So one of the questions was like, how jeet up are you? And then the questions are like, you're handing out for a question or are you yawning? Oh, I thought you had a question. And then so it was like, how jeet up are you? And then so they were answering you, what would you wear to this and what would you wear to that? So I sort of wrote my own poem answering those questions. So it's called, how jeet up are you? The first part are the questions and then the second part of it are the answers to the questions. What would you put on to attend your daddy's sentencing? What would you put on if you went with your father to work filling a swamp of dirt for a real estate company developing a residential area called Magnolia Plantation? What would you wear to a party thrown under plastic palm trees around a shabby pool with no deep end at a motel called Oceanside? What would you wear to visit your big brother at the hospital after they moved him from the ER to the ICU? What would you wear in a house of mirrors? What would you wear in a house of God? What would you wear to visit your father in prison? What would you wear if you was in a music video? What would you put on if you was in a shoe store selling nothing but oxfords and penny loafers? What would you put on if you knew the news lady and her cameraman was coming to interview you about a crime you witnessed? What would you put on if your mama let you drive her car to visit your girl across town Saturday night? What would you wear if you drove half a day to see your girl downstate and when you got there it was way past the time where her parents said you could visit after they saw what you was wearing but you waited three, four hours until she snuck out the back door so you could walk with her up and down the neighborhood with dogs barking in the moonlight. I would wear the necklace my daddy gave me when he came home after a year locked away. I would put on Timboots to keep the mud from swallowing all the places I stood. I would roll my pants, legs up and wade in the water and gaze at the parts of me turned blue.  I'd wear a mask of silence and blind you. I'd wear a mask of myself and fit the same mask on you. I'd wear a year of sins around my neck and beg God to loosen the noose. I'd wear my father's disillusionment and fortitude. I'd put on a fitted cap so the shade over my eyes would move as I moved. I would never wear a white man's shoes. I'd put on sunglasses. I would wear a t-shirt that says I am the news. I would wear a tattoo of my daughter's name above my muscle. I would wear the moonlight like a tattoo. All right. So this is the last one. This is the last one. So that's not that much to say about it. Other than, yeah, my mom, actually my mother and my father, my stepdad are actually prison guards. So, you know, it's pretty true. Yeah, this was fairly accurate too, I guess, as far as things go in poems. So this is the only one I'll read that sort of riffs on the title. There's like three poems in the book. One of each of the three sections that has like something about how to be drawn. So this one's called How to be Drawn to Trouble. And thank y'all, you're a good audience. And then we gonna do Q and A, is that right? Or something? 1240. So, okay, so we'll see. All right, so this is the last one. How to be drawn to Trouble. The people I live with are troubled by the way I have been playing Please, Please, Please by James Brown and the Famous Flames All Evening. But they won't say. I've got a lot of my mother's music in me. James Brown is no longer a headwind of hot grease and squealing for ladies with leopard-skinned intentions, stoned on horns and money. Once I only knew his feel-good music. While my mother watched Convict's Dream, I was in my bedroom pretending to be his echo. I loved the way he says, Please, 10 times straight, bending one syllable until it sounds like three. Trouble is one of the ways we discover the complexities of the soul. Once my mother bit the wrist of a traffic cop, but was not locked away because like him, she was an officer of the state. She was a guard at the prison in which James Brown was briefly imprisoned. There had been broken man-made laws, a car-chase melee, a roadblock of troopers and sunblock. I for one don't trust the police because they go around looking to eradicate trouble. T-R-O, you better believe in trouble. Trouble is how we learn what the soul is. James Brown, that brother could spice up any sentence he uttered or was given. His accent made it sound like he was pleading whether he was speaking or singing. A woman can make a man sing. After another of my mother's disappearances, my father left her bags on the porch. My father believes a man should never dance in public. Under no circumstances should a grown man have hair long enough to braid.  I might weep too and break, but think about the good things. My mother and I love James Brown in a cape and sweat like glitter that glows like little bits of gold. In the photo she took with him, he holds her wrist oddly, probably unintentionally covering her scar. There's the trouble of being misunderstood and the trouble of being soul brother, number one soul brother, God, father, dynamite. After that, the trouble of shouting, I got to get out. I got to get down. I got to get on up the road. For many years, there was a dancing competition between my mother and father, though rarely did they actually dance. They did not scuffle like drums or cymbals, but like something sluggish and close to earth. You know how things work when they don't work. I want to think about the good things. The day after the God, father or soul finished signing just that all over everything in the prison, all my mother wanted to talk about were his shoes. For some reason, he had six or seven pairs of Italian leather beneath his bunk, suggesting where he'd been, even if for the moment he wasn't going anywhere.  There are theories about freedom, and there is a song that says, none of us are free. My mother had gone out Saturday night and came home Sunday, an hour or so before church. She punched clean through the porch window when we wouldn't let her in. I can still hear all the love buried under all the noise she made, but sometimes I hear it wrong. It's not James Brown making trouble, it's trouble he's drawn to. Baby, you've done me wrong, took my love, and now you're gone. It's trouble he's asking to stay. My father might've said please when my mother was beating the door and then calling to me from the window. I might've heard her say please just before or just after the glass and then the skin along her wrist broke. Please, please, please, please, please. That's how James Brown says it. Please, please, please, please, please, honey, please don't go. All right, y'all.


Hello, welcome to SSUnitech. So, see this side and this is continuation of SSIS tutorial. So, today we gonna discuss about logins part 2. So, in our last video we have discussed basics about logins and we have discussed 2 log providers. So, if you haven't watched last video of this video series. So, I would strongly recommend to watch that video before going forward. So, let's start with SSIS log provider for SQL profiler. The SQL server profiler log provider which writes traces that you can view using SQL server profiler. The default filename extension of this provider would be .trc. So, go to on ssdt and this is our example as we have discussed in our last video. So, I am going to use that one. Go to on logging. Here, I would like to add one more. This is for SQL server profiler. And here I need to configure. Then I need to add a file. So, we can click on new. Then create file. We can browse. And here I would like to use SQL profiler.trc. I can click on open. Then okay. Go to on details. So, I would like to use on error and go to on advance. It will capture the machine name, operator name, source name, text message and data bytes. Now click on okay. Now save this package and execute. So, once our package will be executed, package will be failed because in our execute SQL task we have specified one divided by zero. That is not possible. So, cancel this and go to on folder. And this is our trace file. So, I would like to open this and it will be opened in SQL server profiler. So, this is our SQL server profiler. And here, as we can see, this is our event class. So, this is our operator name. And this is our source name. That is fine. And this is our text data. So, in our text data, as we can see, executing the query, select one divided by zero, filled with the following error divided by zero error in countered. So, this is our error. So, we can cancel. So, this is for SQL server profiler. Next lock provider would be windows event log. So, go to on ssgt and here go to on logging. And I would like to use windows event log. Now we can click on add and we can select. So, here in configuration, we are not having anything. Go to on details. So, we want to capture all the information which we have captured in our last lock provider. So, I can click on okay. Now we can save this and execute our package. So, package should be filled. That is fine. Stop this package. Now we need to check the windows event log. So, here we need to go to on event viewer. So, inside this event viewer, go to on windows log then application. It would take few seconds. So, here as we can see error. So, in this error, select one divided by zero, filled with the following error divided by zero error in countered. So, this is our error, which has been captured in windows log event. And our next and last provider would be xml file. So, ssis log provider for the xml file. So, it will write log entries to the xml files. The default file name extension of this provider would be dot xml. So, go to on ssgt then go to on login. In this login, I would like to add for xml files as well. So, this is for xml. So, here again we need to go to on configuration then create a new connection and we want to generate a file create file then we can browse. And here I want to capture log data dot xml. Now we can click on open. That is fine. Go to on detail. So, we want to capture all the informations which we have captured in our last block provider. So, click on OK. Now we can save it and click on start. So, packets should be filled. That is fine. Stop this packets and go to on folder. So, here as we can see this is our xml. So, we can open in notepad. So, it has xml data and we can see over here and we will try to read the error message. So, this is our error message. Select 1 divided by 0 filled with the following error divided by 0 error encountered. So, that is fine. So, these are the log providers or label in SSIS where we can store our log message. So, here we cannot use SQL Server profile log provider in packets that is running in 64-bit mode. So, we need to remember this. Next, as we have seen the SQL Server log provider uses the OLADB connection manager. Others like text file, SQL Server profiler, XML file log providers uses file connection managers. The windows event log provider doesn't use any connection manager because it writes directly to the windows event log. So, I hope you have understand how we can use logging in our SSIS package and how we can store the logs in our different different formats which is our label in SSIS. As we have discussed, there is five formats. So, thank you so much for watching this video. If you like this video, please subscribe our channel to get many more videos. Don't forget to press the bell icon to get the notification of our newly uploaded videos. Thank you so much.


So I'm actually really excited about to talk about this new feature that we've added. So this is what we're calling distributed BPF trace deployment. So I mean, let me tell a little story, like we, yeah, Sean and I, we've been working. So my colleague, Sean, we work a lot on BPF stuff and we write a lot of custom BPF code and a lot of the data that you actually see in the Pixie platform is being driven by those BPF code that we write that's kind of collecting that HTTP data that you're seeing or the stats that you're seeing. But it takes a lot of work for us to do that and, and you know, it's kind of, it's our code, it's kind of hidden away and down in the, in the guts of Pixie. And we kind of ask ourselves, like, wouldn't it be cool if we could really open this up to the community? Right. We'll have others be able to write BPF code and get access to all sorts of cool data and just dynamically plug it into the Pixie platform. Right. So we thought that would be really neat. And so what we, we focused on with this feature is, is really achieving that. We wanted to kind of put a feature in such that you can pull BPF code that you have existing probes from BPF trace, for example, stuff that's checked in to the BPF trace repo. When you see that on the slide, you see kind of, there's, there's a rich set of tools out there in the community already. And we'll take those probes, we'll kind of, you know, you write us a simple script and we'll take it and we'll run with it. We'll, we'll take care of all the orchestration. We'll deploy it on all the nodes in, in the cluster for you. We'll start collecting that data and pushing it up into the Pixie platform. And so you can use the power of the, the Pixie platform to then query the data and get access to all the, the information that, that it's pumping out and we'll do that all automatically for you. So that was the dream that we had. And again, so we're kind of ready now to kind of give off the first demo of this. I would say, so like, what does this mean for you, like for all of you in the audience?  And what that's going to mean for you, like with this feature is we have now this kind of open source collection of scripts that we're going to have that rely on these BPF trace sources. And you'll be able to run these things, right? So we're going to have a rich set of scripts out there that are, that are backed by, by the community. And you're going to be able to run these and get all sorts of cool data to, to debug different scenarios or figure out what's happening in your cluster. So that's going to be kind of the story for, for a good chunk of you. And for the power users or the people who play with BPF more often, what it really means is you can use BPF trace to write your own scripts. So you can say, hey, Pixie, you guys don't have the data that I want. There's just really interesting data that, you know, from the kernel, I want to see like what's happening in my, my, my TCP stack, you know, I already have a BPF trace script for it or, or I want to write one from scratch, you know, go for it. You can write it. And then we can take that and deploy it across the cluster for you, collect all the data. And again, you can then visualize it and see what's happening with your own custom scripts. So that's kind of in a nutshell what, what we're doing with the distributed BPF trace deployment feature. And if there's no questions with that, I'll go into the demo. So kind of show this off. This is pretty fresh, but I'm going to, going to show what we've been able to do. So first of all, as I mentioned, there's already a rich set of BPF trace scripts out there, you know, in the open source community. So this is one, this is the one I'm actually going to demo with. This is called the TCP retransmission script. And what this does is it's looking for, it's a probe that goes into the kernel, and it's essentially monitoring to see whenever a TCP retransmission happens. And this is useful to figure out if there's something misconfigured in your network, or if there's just too much traffic and you're getting a lot of TCP retransmissions because buffers are backed up. And so, you know, Dale, Dale Hamel has already kind of written this stuff. It's really cool, you know, it's out there. Can we plug this in dynamically into the Pixie platform? So I'm going to switch over to the Pixie platform here. And so what you would do is, I mean, let's say we're starting off, this is kind of the front page, we're looking at all the namespaces. What you would do is we have a script now that's called the TCP retransmits and it doesn't do anything initially, right? So we haven't run it yet. What we can do is take a quick look at the Pixie script. And what you can see is I've pretty much just embedded the program here into our Pixie script, which is saying we plugged it in. We had to tweak a few things here and there, but for the most part, it's just copy-paste, right? So we've plugged it in here and then the bottom half of the script is then we say what to do with that data. So the first half is kind of saying this is the BPF trace script and this is what we want you to deploy on all the nodes of the cluster. And then the second half is our just native query language that lets us play around with that data. And so let's just run it and see what happens. So let's, and I do want to change a few things here. So we will, just so we make this be a completely fresh thing, I'm going to change the name of the probe. So it's a brand new fresh probe. It's going to push data to a brand new fresh table. And because I know this probe generates quite a bit of data, I'm actually interested in looking at traffic being, I have a web app. It's called online boutique. It's the same one that James was showing off earlier where we're capturing HTTP data from it. It's an e-commerce site. We just want to see what's happening for that particular service. So I'm just going to filter for data on that. Okay, so we run it. What you see now what's happening behind the scenes here is it's deploying, so the Pixi framework is taking that BPF trace code, distributing it to all the nodes in the cluster and running it and then starting to collect the brand new data that's being pumped out from those probes. And that data is being pushed out into tables and then we use that data to then run queries and create cool visualizations like this one. And so what we're seeing here, this was, if you recall, the script was measuring the number of TCP retransmits. And so what we see is on the left here, we're seeing the pods. So we see a recommendation service, a checkout service and a front-end service. And on kind of the right kind of half of it, what you're seeing is the services that they're talking to. So what these recommendation service, the checkout service and the front-end are actually talking to. And what we see is, there's some retransmits happening in the system. There was nine retransmits happening from the recommendation service here. The checkout service had three, the front-end had one. Now this was a snapshot. I just ran the query once. It had just deployed it. So it just kind of collected a little bit of data and then sent the data for us to visualize. So I'm gonna rerun it now because it's had time to collect more data and it's gonna refresh. And we're gonna see now the updated view. So same, interesting thing, same three pods, the front-end pod, the checkout service pod and the recommendation service pod are talking to a bunch of different services. It seems to be the case that, it's always these three pods that are having retransmits and they're having quite a few, which is indicative of something's going on. If this amount of retransmissions is not normal, right? And so this is helping us visualize what's actually happening in the cluster. And this is a great example of what I mean by, we start with BPF Trace and we get the whole power of the PIX, the platform where we're able to actually, take that raw data and turn it into visualizations like this so we can kind of look at it and say, okay, what's going on visually in this cluster? Where are the problem points in the bottlenecks? And so we definitely see that there's these three services having a problem. Now I'm gonna cut to the chase a little bit here. What I actually went and did in the cluster is I went into one particular node for the sake of this demo and actually kind of put a little gremlin in there that what it's doing is it's introducing packet loss. So it's corrupting 5% of the packets that are coming out from that node. So that kind of represents a faulty node in the system, something that's having a problem. And it's no coincidence that the pods that are mapped onto that node, so online boutique has like 10 or so pods. The three that map onto that node are indeed the frontend service, the checkout service and the recommendation service. And so it's no coincidence that we see visually here that these three pods are experiencing a lot of retransmits because they're sending out corrupted packets. The receiver gets them and says, these are bad packets, you know, it'll time out and then the TCP stack will retransmit those packets again, right? So you can use these sort of scripts to debug these sort of scenarios or other issues like where you're having performance bottlenecks where the socket buffers, you're just sending too much traffic, for example, and you're getting retransmits, stuff's backing up, all sorts of different scenarios.


What is it you're looking for this time the answer to a riddle? So close to cracking the case very I get the Christie. This is just beginning


Love is the source of all creation. It is the consciousness that actually forms the created universes, dimensions, and worlds that we live within. As we've discussed previously, looking into reality with a dualistic mind yields a perspective of three-ness. Time is observed as past, present, and future. Space is seen as having the x, y, and z axes. And size is observed as the microcosm, the everyday world, and the macrocosm. This is the ever-present trinity of reality. But everything in this trinity, from atomic particles to the greatest of galaxies, are held together by forces that we have given particular names, which are sometimes seen as separate as well. Subatomic particles are held together by the strong force, molecules by electromagnetism, planets are held in orbit by gravity. But what if these forces are not actually so different? What if it was all the same force manifesting in various ways through different dimensions?


Welcome back everyone to theCUBE's coverage of NVIDIA's GTC, the conference for the era of AI. I'm John Furrier with Dave Vellante. We're here for three days getting all the action with our run and gun pop up cube. We'll do whatever it takes to get that story where there's dropping in one camera, three cameras, full stage, whatever it takes theCUBE is there. We've got you covered and we have here our CUBE contributor, CUBE collective member, Sarbjeet Joel, analyst, friend of theCUBE, out there doing the analyst notebook. I call it because he doesn't have a notebook. He's got an iPhone and he's got probably a notebook but Sarbjeet, great to see you. One of the things I love about how you attack events is you really kind of go out the keynote. By the way, your keynote tweet when viral, just getting that data out there really fast, really does the community great service. I want to say thanks for that. And number two is you always like to go and check out all the sessions, check out the hallway conversation. So I love, I call it the analyst notebook section because you're kind of notebook and it's a good summary. So thanks for coming on. Thanks John. Actually, I saw your coverage from yesterday with Zeus and you and David. I think that segment summed up the first two days after you guys had a session with Jensen Q&A, right? So that was awesome. Yep.  Also we saw the keynote, Jensen was well documented. It's a new era. It's not a pre-recorded era. It's a generative era. Everything's changed. How software's built changed. The computer has changed. It's now a system.  And you got Neo Retriever, which is such a rag which is retrieval augmentation generation. And then you got robotics and the thing you didn't talk about is the telecom side. Again, tell us what you're hearing in the hallways. Hallways discussions are like, my sort of interpretation is that things don't change as fast as what Jensen wants to change. So it's a new paradigm shift, right? So going from CP to GPU, the way we program our systems, especially the systems of record, we're not going to change that to be programmed by GNAI, for example, right? Because there's a lot of hallucination problems and like we're trying to figure that stuff out if you will, right? Over time, these things will improve. Of course there's code generation in place. And I'm a coder at heart and I've coded many systems and I have played with the GNAI code generation. It's not that good.  It's just, it does the basic stuff, right? It does the coding, but it doesn't do programming, what I call it. So, long story short, this is just the beginning. It will take a while for AI to give the fruit what we are promising through these narratives. So I think it's going to be hurry up and wait, but definitely they are killing it with their, you know, compute speed and having the memory sitting next to the computer and the multi-terabyte, you know. I want to get your, first of all, great analysis. I want to get your take on the show itself because, you know, you got this as a stake in the ground as an inflection point. You got people here that shouldn't be here, right? I don't say that they shouldn't be here. They shouldn't be here in the sense of in the classical GDC fashion. It's a fricking developers conference. Yet you got hedge fund guys, you got VCs, you can start up popping up. A lot of money to be made. This is clearly the next wave, so a lot of people are here. So this represents kind of like that cultural moment in time. But you got to look at this and say, is it an enterprise show or is it a consumer show? Because AI today, if you look at all the hyperscale investments on the AI side, it's essentially an investment in the consumer hyperscalers. Meta, for instance. ByteDance, Tencent. You name all those companies. Those are consumer-oriented social media networking companies.  Where's the demand and where's the supply going to go? Because remember, one of the things that's coming out and the idea is that there's still a huge demand for the product. Okay, software, no one's got a chance against CUDA. Clearly, they got an edge there. But NVIDIA doesn't sell software. They sell GPUs. They're a chip company. No, but they want to sell software now. They are going to sell software. They're selling a license for CUDA. For CUDA. For GPU. For GPU per year. So they are going to make money from that. They're selling GPUs. So actually they are- Are they selling GPUs or are they selling a license to the software on the GPU? They are trying to do both. Actually that messaging is confusing in many ways because it also collides with their customers. It collides with what AWS is doing. It collides with what Google Cloud is doing. They are trying to give that as a service to the builders, if you will, right? They are the platforms. They are past platform as a service. It happens, historically speaking, it happens to many companies when they are a technology provider and they want to be a service provider, they get lost in that transition. Most of the companies get lost and they don't. Explain that. So in what way that they're too focused on the platform, not on the ecosystem, or where they get lost? No, okay. Technology provider versus service provider. So when you are providing the technology, you are giving it to every service provider so they can build stuff and give it to the builders of these applications, right? That's the technology provider. You are working with many service providers. You're enabling people to do stuff. Exactly. So if you try to be the service provider, now you are competing with other service providers and then it muddies the waters. VMware wanted to do their own public cloud and they scripted that, sort of canceled that, right? That was the main reason because then nobody will pick up VMware stock to put in. It's the classic strategy problem. You're stuck in the middle between two strategies. Are you saying that Nvidia is trying to be a service provider or are they still leaning to technology provider or are they telegraphing a little bit of a service provider? I think they are telegraphing some, they have inclination to be service provider in some sense. And I hope I am wrong, reading that wrong because if they are trying to do that, they're going to stumble. That's what my- Jensen said on his speech, we are building a data center, just selling it part by part. And that's what the GPUs, they do in the allocations. So they are providing a service. I mean, they're clearly the DGX cloud is a service or is that technology? So it's again, the lines are blurring. It's a great point. And again, it's a critical question for Nvidia because I was saying earlier on the show floor when I was wandering around and talking to some influencers and some executives, they asked me and I said, hey, you can't have an ecosystem play with AI Foundry if you're going to be a closed garden. So if you're a closed garden, ecosystems don't thrive because the control points to closed garden, meaning I'm a monolithic system and I'm going to basically sell you as a service and charge on the software license per GPU, which is basically a GPU license. So, you know, that's going to be a tough call. Will AI Foundry, will that flower up and grow? Or is it a red herring? Is it a stalking horse? But on the other hand, playing Davos advocate here, like John Ford does on CNBC, on the other hand, he has a segment, right? The two hand- On the other hand. On one hand, on the other hand. On the other hand, what Jensen and Company, what they have done is they have put a lot of energy behind all these researchers in different domains to use the computing to describe their industries digitally. So the whole idea of digital twin is very revolutionary in my point of view because you can create these products using digital twins before even you muck around with the physicality of these systems. So that's huge actually. It saves a lot of time and money and agony, you know? So mRNA vaccine is one example, you know? Like building cars. There are cars on the floor here of this show, right? There's auto industry heavily represented here and there's telco. There's like financials, all kind of industries are like. Okay, so let me ask you a question. So as you walk the show floor here, which by the way, it could be bigger, it is pretty tight, small space, this place is kind of bustling out of the seams here. If you had to look forward next year, okay, we heard this question earlier, what's gonna be different next year at GTC? What's gonna change in the next 12 months in the industry? What's gonna the show floor gonna look like in your opinion? If you had to throw a dart at the board, what would you say? I think this show will be bigger, definitely. There will be more use cases.  Right now it's all like experimentation. So there might be fewer use cases which are in sort of pre-production stage, if you will. So that's what I'm expecting. What's your note in your notebook that you've been collecting all the observations here in the hallway sessions? What's the big takeaway this year from your perspective as you compile all the data? What's it telling you? I think the main thing is that you can't avoid NVIDIA and their stack if you are serious about gen AI and AI in general and gen AI in particular. So that message is loud and clear. Other people are trying to catch up, AMD's of the world and Intel's of the world, right? So the programmability of these chips is super important. The one thing actually I tweeted a few days back I think maybe after the keynote that we need standards to lower the cost of doing AI and also not only the cost but having lower power consumption. So we need specialized chips so we can use lower power because the whole idea is that when you have a computer if it is idle like 70% of your GPUs or CPUs are idle you're wasting a lot of energy and energy is... Power is a new envelope. That's the new constraint that design around. I think one of the things I think is going to be different and this is interesting that you brought that up, power is I think you're going to see a lot more competition. I think NVIDIA has raised the bar. It's a high bar on the gen AI systems approach. My big takeaway from this year is two things. One, the accelerated computing is a great narrative. I think Jensen hit a home run on that piece. I think this idea of a monolithic system that's not like a mainframe but it's like it's more distributed computing is going to pull forward a bunch of use cases for AI to be accelerated faster. So when you'll see more successes on use cases that are prime for what they're building with their hardware and their performance. The second thing that jumps out at me is I think this sets the standard now for what we've been calling clustered systems. A way has now been shown how to organize servers and multiple configurations. You mentioned power. We were just talking to the Broadcom executives this morning about power, ethernet, that whole spine thing. Infiniband is way more expensive on a port basis than you say ethernet, wide open, open standard and connects with PCIe is just as good of a switch in those configurations and with Broadcom's retimer. You're not going to go distance within the rack and ethernet lowers the power envelope in the rack and lowers your cooling requirements. So what you're seeing is a complete reconstruction of what a system is. So I think this idea of what the rack used to be. Member stack and rack those blades, throw the top of rack switch up there and connect the next rack. That's what the IT was for what, two decades? Yeah, more than that. I think now we're on an IT platform that's going to be clustered systems, my word. Maybe it's a better word, AI systems, that are going to have to work to support multiple workloads in a distributed computing paradigm. That's public cloud on premise edge and the software will have to be compatible to run in that super configuration. It's like a super cloud configuration and you're going to see the rise of NVIDIA clearly leading the way, but I think competition will come in and that's going to come down to who can design the best low power, high speed networking interconnects for these new systems and AMD's not going to lie down. All these other chips aren't going to lie down and let NVIDIA run to the end zone. We need the vendor diversity. That's the need of our actually. We have gone through this, like we want competition. We want competition. Two more observations. One is that can you do AI in colors, right? Or on-prem versus doing that in the cloud? So that was the discussion. And the answer observation is yes or no? The answer is yes, yeah. You can do it both places, okay? You can do it over both places, but I think the cloud guys are saying, no, no, no, the colos don't have enough power, what AI needs to give you the performance and do AI in a sort of pro manner. You can do rudimentary testing and all that stuff at colos, but I mean, you do want to do production. But if you could do distributed computing, I mean, Amazon's outpost was theoretically a good idea. You put an edge device, different hardware, but you don't need to use outposts, for instance, with a colo that uses all their power. Again, you optimize the racks in that facility and you build around the constraints of that power and then you find another colo. So I think the idea of having a diverse colo environment is just the nature of distributed computing. If the speeds and the interconnects, whether it's optical across campus, across the internet, then you have a whole nother arc, again, back to the systems design. Yes, systems thinking. So CNBC wrote an article today that Equinex is selling the pipe dream of AI. You know, like, I'm going to... I don't think there's a pipe dream. I think it's reality. I am going to their dinner, so I can't say much about that right now. CNBC is there or? No, no, Equinex. Okay. It's not a pipe dream. It's not a pipe dream. I think CNBC got that wrong. But somebody just wrote this. Pipe isn't like the fat pipe internet, but like pipe dream isn't not gettable. I think it's a pun there. Okay. So the other observation was, I'm kind of forgetting that, the second same thing now. The first observation was the... Your first observation was power. Yeah. The other thing was the session with all these scientists or these experts from different domains, Jensen did that today. So that was, I think, I opener from many angles, because these researchers also questioned the need for that much GPU, actually, during that talk to say, if you want to add two plus two, do you need a model with two trillion parameters to do that math, or you can just go to CPU and say, do this for me. So I think the switching of the computing needs on the fly between CPU and GPU, that is going to be the biggest sort of work in progress in next two to five years or so. I think the paradigm, that observation about that is a good one. I think in this place of what Jensen was saying about the word discovery versus design. Drug discovery, you're kind of fumbling around to discover something and then lock it in with the idea of the omniverse which they've been pulling as their digital twin platform. You can actually do all that in simulation and then design something. So it's drug design, not drug discovery, an example of finding cures to things. And that brings up my point about custom silicon, because if you're looking at what Broadcoms and these players are doing is that with automation and foundation open source, open standard foundation models and technologies, you can actually do all that automation in the front end and get chips to the market within three to seven months. Okay, and then a three-month production ramp. So within a year, you can have chips, custom chips designed for workloads. So I think you're going to start to see this notion of custom chips at scale, mass scale, designed for all workloads. So every workload that's in production, if it's a good workload, will be designed specifically for the workload. So I think AI, we're going into the systems thinking mindset with the notion of designing something, use case purpose built is the future. And I think AI is showing that you can do that and the benefits are multi-fold because now you have intelligence built in to the applications that's never seen before. So I think watch that custom silicon market, that's going to change the infrastructure game with clustered systems. Yeah, I'm with you on that. I think because having open standards, it makes economics better on all fronts, power, cooling, and diversity of vendors. Because if there's only one player in the game, they're going to charge anything. My final observation that I'll pass it off to you to get a reaction and then close out is the idea of software defined versus physical. And we had this conversation in context of storage. So for example, Pure Storage is a company that has flash arrays. You got Dell makes blade servers. So you got flash array. This is a physical where compute is in Pure's case, compute is on the flash array. And blades, the compute is on the blade. When you separate compute and storage, you're starting to think if you're not software defined, the physical fabric has to be, the physical materials has to be built for software defined. So I think if you're not looking at a software defined environment going forward, you might be in a tough hurt. What's your reaction to that? Am I overreacting on that or what? I think there might be some overreaction there, but you have a point there. Because if you are separating the compute from the physical things, it has to be software defined. If it's not, then it's like more like embedded software into that hardware. And that's old stack sort of paradigm. And the beauty of having software defined physical assets is that we can get the most juice are out of these things. And because most of these things will need power to run and upkeep and we want to shut these things down when we don't need them. So again, the switching of the computing from GPU to CPU or any other mechanism which emerges. Sorry guys, there's a lot of sound coming behind us. So I think that software defined everything is the future and we see that from happening. I see that happening. Everything's connected. Sharpe, G. Chowal, thanks for coming on theCUBE. Real quick vlog, what are you working on right now? What's getting your fancy right now? What's got your attention and what are you working on? What I'm working on is like I'm just extending my work with the soft economics of systems creation versus economics of systems operations. I am spending a lot of time on that. So because creation versus operation are two different things and at some point we switch to operations. In creation versus ops. Yeah, like dev versus ops, right? And I have said that many times dev ops has done a lot of damage to our industry. I was giving examples why, because the, you know. Sure, not sure I agree with that, but okay. That's another podcast, that was a whole nother one. We might have to debate that one, arm wrestle. Yes. Cool, well good to have you on theCUBE. Appreciate the commentary as always. Sargiccio all here, breaking it down with the analyst angle here. I'm John Furrier with Dave Vellante. As the music plays, we are going to exit out of day three of GTC. Thanks for watching. Thank you guys.