(Intro music) >> Welcome back. We're LIVE here from SuperComputing 22 in Dallas Paul Gillin, for Silicon Angle in theCUBE with my guest host Dave... excuse me. And our, our guest today, this segment is Kim Leyenaar who is a storage performance architect at Broadcom. And the topic of this conversation is, is is networking, it's connectivity. I guess, how does that relate to the work of a storage performance architect? >> Well, that's a really good question. So yeah, I have been focused on storage performance for about 22 years. But even, even if we're talking about just storage the entire, all the components have a really big impact on ultimately how quickly you can access your data. So, you know, the, the switches the memory bandwidth, the, the expanders the just the different protocols that you're using. And so, and the big part of is actually ethernet because as you know, data's not siloed anymore. You have to be able to access it from anywhere in the world. >> Dave: So wait, so you're telling me that we're just not living in a CPU centric world now? >> Ha ha ha >> Because it is it is sort of interesting. When we talk about supercomputing and high performance computing we're always talking about clustering systems. So how do you connect those systems? Isn't that, isn't that kind of your, your wheelhouse? >> Kim: It really is. >> Dave: At Broadcom. >> It's, it is, it is Broadcom's wheelhouse. We are all about interconnectivity and we own the interconnectivity. You know, you know, years ago it was, 'Hey, you know buy this new server because, you know, we we've added more cores or we've got better memory.' But now you've got all this siloed data and we've got you know, we've got this, this stuff or defined kind of environment now this composable environments where, hey if you need more networking, just plug this in or just go here and just allocate yourself more. So what we're seeing is these silos really of, 'hey here's our compute, here's your networking, here's your storage.' And so, how do you put those all together? The thing is interconnectivity. So, that's really what we specialize in. I'm really, you know, I'm really happy to be here to talk about some of the things that that we do to enable high performance computing. >> Paul: Now we're seeing, you know, new breed of AI computers being built with multiple GPUs very large amounts of data being transferred between them. And the internet really has become a, a bottleneck. The interconnect has become a bottle, a bottleneck. Is that something that Broadcom is working on alleviating? >> Kim: Absolutely. So we work with a lot of different, there's there's a lot of different standards that we work with to define so that we can make sure that we work everywhere. So even if you're just a dentist's office that's deploying one server, or we're talking about these hyperscalers that are, you know that have thousands or, you know tens of thousands of servers, you know, we're working on making sure that the next generation is able to outperform the previous generation. Not only that, but we found that, you know with these siloed things, if, if you add more storage but that means we're going to eat up six cores using that it's not really as useful. So Broadcom's really been focused on trying to offload the CPU. So we're offloading it from, you know data security, data protection, you know, we're we do packet sniffing ourselves and things like that. So no longer do we rely on the CPU to do that kind of processing for us but we become very smart devices all on our own so that they work very well in these kind of environments. >> Dave: So how about, give, give us an example. I know a lot of the discussion here has been around using ethernet as the connectivity layer. >> Yes. >> You know, in in, in the past, people would think about supercomputing as exclusively being InfiniBand based. >> Ha ha ha. >> But give, give us an idea of what Broadcom is doing in the ethernet space. What, you know, what's what are the advantages of using ethernet? >> Kim: So we've made two really big announcements. The first one is our Tomahawk five ethernet switch. So it's a 400 gigi ethernet switch. And the other thing we announced too was our Thor. So we have, these are our network controllers that also support up to 400 gigi each as well. So, those two alone, it just, it's amazing to me how much data we're able to transfer with those. But not only that, but they're super super intelligent controllers too. And then we realized, you know, hey, we're we're managing all this data, let's go ahead and offload the CPU. So we actually adopted the Rocky Standards. So that's one of the things that puts us above InfiniBand is that ethernet is ubiquitous, it's everywhere. And InfiniBand is primarily just owned by one or two companies. And, and so, and it's also a lot more expensive. So ethernet is just, it's everywhere. And now with the, with the Rocky standards, we're working along with, it's, it's, it does what you're talking about much better than, you know predecessors. >> Tell us about the Rocky Standards. I'm not familiar with it. I'm sure some of our listeners are not. What is the Rocky standard? >> Kim: Ha ha ha. So it's our DNA over converged to ethernet. I'm not a Rocky expert myself but I am an expert on how to offload the CPU. And so one of the things it does is instead of using the CPU to transfer the data from, you know the user space over to the next, you know server when you're transferring it we actually will do it ourselves. So we'll handle it ourselves. We will take it, we will move it across the wire and we will put it in that remote computer. And we don't have to ask the CPU to do anything to get involved in that. So big, you know, it's a big savings. >> Yeah, I mean in, in a nutshell, because there are parts of the InfiniBand protocol that are essentially embedded in RDMA over converged ethernet. So... >> Right. >> So if you can, if you can leverage kind of the best of both worlds, but have it in an ethernet environment which is already ubiquitous, it seems like it's, kind of democratizing supercomputing and, and HPC and I know you guys are big partners with Dell as an example, you guys work with all sorts of other people. >> Kim: Yeah. >> But let's say, let's say somebody is going to be doing ethernet for connectivity, you also offer switches? >> Kim: We do, actually. >> So is that, I mean that's another piece of the puzzle. >> That's a big piece of the puzzle. So we just released our, our Atlas 2 switch. It is a PCIE Gen Five switch. And... >> Dave: What does that mean? What does Gen five, what does that mean? >> Oh, Gen Five PCIE, it's it's a magic connectivity right now. So, you know, we talk about the Sapphire Rapids release as well as the GENUWA release. I know that those, you know those have been talked about a lot here. I've been walking around and everybody's talking about it. Well, those enable the Gen Five PCIE interfaces. So we've been able to double the bandwidth from the Gen Four up to the Gen Five. So, in order to, to support that we do now have our Atlas two PCIE Gen Five switch. And it allows you to connect especially around here we're talking about, you know artificial intelligence and machine learning. A lot of these are relying on the GPU and the DPU that you see, you know a lot of people talking about enabling. So by in, you know, putting these switches in the servers you can connect multitudes of not only NVME devices but also these GPUs and these, these CPUs. So besides that we also have the storage component of it too. So to support that, we we just recently have released our 9,500 series HBAs which support 24 gig SAS. And you know, this is kind of a, this is kind of a big deal for some of our hyperscalers that say, Hey, look our next generation, we're putting a hundred hard drives in. So we're like, you know, so a lot of it is maybe for cold storage, but by giving them that 24 gig bandwidth and by having these mass 24 gig SAS expanders that allows these hyperscalers to build up their systems. >> Paul: And how are you supporting the HPC community at large? And what are you doing that's exclusively for supercomputing? >> Kim: Exclusively for? So we're doing the interconnectivity really for them. You know, you can have as, as much compute power as you want, but these are very data hungry applications and a lot of that data is not sitting right in the box. A lot of that data is sitting in some other country or in some other city, or just the box next door. So to be able to move that data around, you know there's a new concept where they say, you know do the compute where the data is and then there's another kind of, you know the other way is move the data around which is a lot easier kind of sometimes, but so we're allowing us to move that data around. So for that, you know, we do have our our tomahawk switches, we've got our Thor NICS and of course we got, you know, the really wide pipe. So our, our new 9,500 series HBA and RAID controllers not only allow us to do, so we're doing 28 gigabytes a second that we can trans through the one controller, and that's on protected data. So we can actually have the high availability protected data of RAID 5 or RAID 6, or RAID 10 in the box giving in 27 gigabytes a second. So it's, it's unheard of the latency that we're seeing even off of this too, we have a right cash latency that is sub 8 microseconds that is lower than most of the NVME drives that you see, you know that are available today. So, so you know we're able to support these applications that require really low latency as well as data protection. >> Dave: So, so often when we talk about the underlying hardware, it's a it's a game of, you know, whack-a-mole chase the bottleneck. And so you've mentioned PCIE five, a lot of folks who will be implementing five, gen five PCIE five are coming off of three, not even four. >> Kim: I know. >> So make, so, so they're not just getting a last generation to this generation bump but they're getting a two generations, bump. >> Kim: They are. >> How does that, is it the case that it would never make sense to use a next gen or a current gen card in an older generation bus because of the mismatch and performance? Are these things all designed to work together? >> Uh... That's a really tough question. I want to say, no, it doesn't make sense. It, it really makes sense just to kind of move things forward and buy a card that's made for the bus it's in. However, that's not always the case. So for instance, our 9,500 controller is a Gen four PCIE but what we did, we doubled the PCIE so it's a by 16, even though it's a gen four, it's a by 16. So we're getting really, really good bandwidth out of it. As I said before, you know, we're getting 28, 27.8 or almost 28 gigabytes a second bandwidth out of that by doubling the PCIE bus. >> Dave: But they worked together, it all works together? >> All works together. You can put, you can put our Gen four and a Gen five all day long and they work beautifully. Yeah. We, we do work to validate that. >> We're almost out our time. But I, I want to ask you a more, nuts and bolts question, about storage. And we've heard for, you know, for years of the aerial density of hard disk has been reached and there's really no, no way to excel. There's no way to make the, the dish any denser. What is the future of the hard disk look like as a storage medium? >> Kim: Multi actuator actually, we're seeing a lot of multi-actuator. I was surprised to see it come across my desk, you know because our 9,500 actually does support multi-actuator. And, and, and so it was really neat after I've been working with hard drives for 22 years and I remember when they could do 30 megabytes a second, and that was amazing. That was like, wow, 30 megabytes a second. And then, about 15 years ago, they hit around 200 to 250 megabytes a second, and they stayed there. They haven't gone anywhere. What they have done is they've increased the density so that you can have more storage. So you can easily go out and buy 15 to 30 terabyte drive, but you're not going to get any more performance. So what they've done is they've added multiple actuators. So each one of these can do its own streaming and each one of these can actually do their own seeking. So you can get two and four. And I've even seen a talk about, you know eight actuator per disc. I, I don't think that, I think that's still theory, but but they could implement those. So that's one of the things that we're seeing. >> Paul: Old technology somehow finds a way to, to remain current. >> It does. >> Even it does even in the face of new alternatives. Kim Leyenaar, Storage Architect, Storage Performance Architect at Broadcom Thanks so much for being here with us today. Thank you so much for having me. >> This is Paul Gillin with Dave Nicholson here at SuperComputing 22. We'll be right back. (Outro music)

(upbeat music) (logo swooshing) >> Good morning and welcome back to Dallas, ladies and gentlemen, we are here with theCUBE Live from Supercomputing 2022. David, my cohost, how are you doing? Exciting, day two, feeling good? >> Very exciting. Ready to start off the day. >> Very excited. We have two fascinating guests joining us to kick us off. Please welcome Pete and Armando. Gentlemen, thank you for being here with us. >> Thank you for having us. >> Thank you for having us. >> I'm excited that you're starting off the day because we've been hearing a lot of rumors about Ethernet as the fabric for HPC, but we really haven't done a deep dive yet during the show. You all seem all in on Ethernet. Tell us about that. Armando, why don't you start? >> Yeah, I mean, when you look at Ethernet, customers are asking for flexibility and choice. So when you look at HPC, InfiniBand's always been around, right? But when you look at where Ethernet's coming in, it's really our commercial in their enterprise customers. And not everybody wants to be in the top 500, what they want to do is improve their job time and improve their latency over the network. And when you look at Ethernet, you kind of look at the sweet spot between 8, 12, 16, 32 nodes, that's a perfect fit for Ethernet in that space and those types of jobs. >> I love that. Pete, you want to elaborate? >> Yeah, sure. I mean, I think one of the biggest things you find with Ethernet for HPC is that, if you look at where the different technologies have gone over time, you've had old technologies like, ATM, Sonic, Fifty, and pretty much everything is now kind of converged toward Ethernet. I mean, there's still some technologies such as InfiniBand, Omni-Path, that are out there. But basically, they're single source at this point. So what you see is that there is a huge ecosystem behind Ethernet. And you see that also the fact that Ethernet is used in the rest of the enterprise, is used in the cloud data centers, that is very easy to integrate HPC based systems into those systems. So as you move HPC out of academia into enterprise, into cloud service providers, it's much easier to integrate it with the same technology you're already using in those data centers, in those networks. >> So what's the state of the art for Ethernet right now? What's the leading edge? what's shipping now and what's in the near future? You're with Broadcom, you guys designed this stuff. >> Pete: Yeah. >> Savannah: Right. >> Yeah, so leading edge right now, got a couple things-- >> Savannah: We love good stage prop here on the theCUBE. >> Yeah, so this is Tomahawk 4. So this is what is in production, it's shipping in large data centers worldwide. We started sampling this in 2019, started going into data centers in 2020. And this is 25.6 terabytes per second. >> David: Okay. >> Which matches any other technology out there. Like if you look at say, InfinBand, highest they have right now that's just starting to get into production is 25.6 T. So state of the art right now is what we introduced, We announced this in August, This is Tomahawk 5, so this is 51.2 terabytes per second. So double the bandwidth, out of any other technology that's out there. And the important thing about networking technology is when you double the bandwidth, you don't just double the efficiency, actually, winds up being a factor of six efficiency. >> Savannah: Wow. >> 'Cause if you want, I can go into that, but... >> Why not? >> Well, what I want to know, please tell me that in your labs, you have a poster on the wall that says T five, with some like Terminator kind of character. (all laughs) 'Cause that would be cool. If it's not true, just don't say anything. I'll just... >> Pete: This can actually shift into a terminator. >> Well, so this is from a switching perspective. >> Yeah. >> When we talk about the end nodes, when we talk about creating a fabric, what's the latest in terms of, well, the nicks that are going in there, what speed are we talking about today? >> So as far as 30 speeds, it tends to be 50 gigabits per second. >> David: Okay. >> Moving to a hundred gig PAM-4. >> David: Okay. >> And we do see a lot of nicks in the 200 gig Ethernet port speed. So that would be four lanes, 50 gig. But we do see that advancing to 400 gig fairly soon, 800 gig in the future. But say state of the art right now, we're seeing for the end node tends to be 200 gig E based on 50 gig PAM-4. >> Wow. >> Yeah, that's crazy. >> Yeah, that is great. My mind is act actively blown. I want to circle back to something that you brought up a second ago, which I think is really astute. When you talked about HPC moving from academia into enterprise, you're both seeing this happen, where do you think we are on the adoption curve and sort of in that cycle? Armando, do you want to go? >> Yeah, well, if you look at the market research, they're actually telling you it's 50/50 now. So Ethernet is at the level of 50%, InfinBand's at 50%, right? >> Savannah: Interesting. >> Yeah, and so what's interesting to us, customers are coming to us and say, hey, we want to see flexibility and choice and, hey, let's look at Ethernet and let's look at InfiniBand. But what is interesting about this is that we're working with Broadcom, we have their chips in our lab, we their have switches in our lab. And really what we're trying to do is make it easy to simple and configure the network for essentially MPI. And so the goal here with our validated designs is really to simplify this. So if you have a customer that, hey, I've been InfiniBand but now I want to go Ethernet, there's going to be some learning curves there. And so what we want to do is really simplify that so that we can make it easy to install, get the cluster up and running and they can actually get some value out the cluster. >> Yeah, Pete, talk about that partnership. what does that look like? I mean, are you working with Dell before the T six comes out? Or you just say what would be cool is we'll put this in the T six? >> No, we've had a very long partnership both on the hardware and the software side. Dell's been an early adopter of our silicon. We've worked very closely on SI and Sonic on the operating system, and they provide very valuable feedback for us on our roadmap. So before we put out a new chip, and we have actually three different product lines within the switching group, within Broadcom, we've then gotten very valuable feedback on the hardware and on the APIs, on the operating system that goes on top of those chips. So that way when it comes to market, Dell can take it and deliver the exact features that they have in the current generation to their customers to have that continuity. And also they give us feedback on the next gen features they'd like to see again, in both the hardware and the software. >> So I'm fascinated by... I always like to know like what, yeah, exactly. Look, you start talking about the largest supercomputers, most powerful supercomputers that exist today, and you start looking at the specs and there might be two million CPUs, 2 million CPU cores. Exoflap of performance. What are the outward limits of T five in switches, building out a fabric, what does that look like? What are the increments in terms of how many... And I know it's a depends answer, but how many nodes can you support in a scale out cluster before you need another switch? Or what does that increment of scale look like today? >> Yeah, so this is 51.2 terabytes per second. Where we see the most common implementation based on this would be with 400 gig Ethernet ports. >> David: Okay. >> So that would be 128, 400 gig E ports connected to one chip. Now, if you went to 200 gig, which is kind of the state of the art for the nicks, you can have double that. So in a single hop, you can have 256 end nodes connected through one switch. >> Okay, so this T five, that thing right there, (all laughing) inside a sheet metal box, obviously you've got a bunch of ports coming out of that. So what's the form factor look like for where that T five sits? Is there just one in a chassis or you have.. What does that look like? >> It tends to be pizza boxes these days. What you've seen overall is that the industry's moved away from chassis for these high end systems more towardS pizza boxes. And you can have composable systems where, in the past you would have line cards, either the fabric cards that the line cards are plug into or interfaced to. These days what tends to happen is you'd have a pizza box and if you wanted to build up like a virtual chassis, what you would do is use one of those pizza boxes as the fabric card, one of them as the line card. >> David: Okay. >> So what we see, the most common form factor for this is they tend to be two, I'd say for North America, most common would be a 2RU, with 64 OSFP ports. And often each of those OSFP, which is an 800 gig E or 800 gig port, we've broken out into two 400 gig ports. >> So yeah, in 2RU, and this is all air cooled, in 2RU, you've got 51.2 T. We do see some cases where customers would like to have different optics and they'll actually deploy 4RU, just so that way they have the phase-space density. So they can plug in 128, say QSFP 112. But yeah, it really depends on which optics, if you want to have DAK connectivity combined with optics. But those are the two most common form factors. >> And Armando, Ethernet isn't necessarily Ethernet in the sense that many protocols can be run over it. >> Right. >> I think I have a projector at home that's actually using Ethernet physical connections. But, so what are we talking about here in terms of the actual protocol that's running over this? Is this exactly the same as what you think of as data center Ethernet, or is this RDMA over converged Ethernet? What Are we talking about? >> Yeah, so RDMA, right? So when you look at running, essentially HPC workloads, you have the NPI protocol, so message passing interface, right? And so what you need to do is you may need to make sure that that NPI message passing interface runs efficiently on Ethernet. And so this is why we want to test and validate all these different things to make sure that that protocol runs really, really fast on Ethernet. If you look at NPIs officially, built to, hey, it was designed to run on InfiniBand but now what you see with Broadcom, with the great work they're doing, now we can make that work on Ethernet and get same performance, so that's huge for customers. >> Both of you get to see a lot of different types of customers. I kind of feel like you're a little bit of a looking into the crystal ball type because you essentially get to see the future knowing what people are trying to achieve moving forward. Talk to us about the future of Ethernet in HPC in terms of AI and ML, where do you think we're going to be next year or 10 years from now? >> You want to go first or you want me to go first? >> I can start, yeah. >> Savannah: Pete feels ready. >> So I mean, what I see, I mean, Ethernet, what we've seen is that as far as on, starting off of the switch side, is that we've consistently doubled the bandwidth every 18 to 24 months. >> That's impressive. >> Pete: Yeah. >> Nicely done, casual, humble brag there. That was great, I love that. I'm here for you. >> I mean, I think that's one of the benefits of Ethernet, is the ecosystem, is the trajectory the roadmap we've had, I mean, you don't see that in any of the networking technology. >> David: More who? (all laughing) >> So I see that, that trajectory is going to continue as far as the switches doubling in bandwidth, I think that they're evolving protocols, especially again, as you're moving away from academia into the enterprise, into cloud data centers, you need to have a combination of protocols. So you'll probably focus still on RDMA, for the supercomputing, the AI/ML workloads. But we do see that as you have a mix of the applications running on these end nodes, maybe they're interfacing to the CPUs for some processing, you might use a different mix of protocols. So I'd say it's going to be doubling a bandwidth over time, evolution of the protocols. I mean, I expect that Rocky is probably going to evolve over time depending on the AI/ML and the HPC workloads. I think also there's a big change coming as far as the physical connectivity within the data center. Like one thing we've been focusing on is co-packed optics. So right now, this chip is, all the balls in the back here, there's electrical connections. >> How many are there, by the way? 9,000 plus on the back of that-- >> 9,352. >> I love how specific it is. It's brilliant. >> Yeah, so right now, all the SERDES, all the signals are coming out electrically based, but we've actually shown, we actually we have a version of Tomahawk 4 at 25.6 T that has co-packed optics. So instead of having electrical output, you actually have optics directly out of the package. And if you look at, we'll have a version of Tomahawk 5. >> Nice. >> Where it's actually even a smaller form factor than this, where instead of having the electrical output from the bottom, you actually have fibers that plug directly into the sides. >> Wow. Cool. >> So I see there's the bandwidth, there's radix's increasing, protocols, different physical connectivity. So I think there's a lot of things throughout, and the protocol stack's also evolving. So a lot of excitement, a lot of new technology coming to bear. >> Okay, You just threw a carrot down the rabbit hole. I'm only going to chase this one, okay? >> Peter: All right. >> So I think of individual discreet physical connections to the back of those balls. >> Yeah. >> So if there's 9,000, fill in the blank, that's how many connections there are. How do you do that many optical connections? What's the mapping there? What does that look like? >> So what we've announced for Tomahawk 5 is it would have FR4 optics coming out. So you'd actually have 512 fiber pairs coming out. So basically on all four sides, you'd have these fiber ribbons that come in and connect. There's actually fibers coming out of the sides there. We wind up having, actually, I think in this case, we would actually have 512 channels and it would wind up being on 128 actual fiber pairs because-- >> It's miraculous, essentially. >> Savannah: I know. >> Yeah. So a lot of people are going to be looking at this and thinking in terms of InfiniBand versus Ethernet, I think you've highlighted some of the benefits of specifically running Ethernet moving forward as HPC which sort of just trails slightly behind super computing as we define it, becomes more pervasive AI/ML. What are some of the other things that maybe people might not immediately think about when they think about the advantages of running Ethernet in that environment? Is it about connecting the HPC part of their business into the rest of it? What are the advantages? >> Yeah, I mean, that's a big thing. I think, and one of the biggest things that Ethernet has again, is that the data centers, the networks within enterprises, within clouds right now are run on Ethernet. So now, if you want to add services for your customers, the easiest thing for you to do is the drop in clusters that are connected with the same networking technology. So I think one of the biggest things there is that if you look at what's happening with some of the other proprietary technologies, I mean, in some cases they'll have two different types of networking technologies before they interface to Ethernet. So now you've got to train your technicians, you train your assist admins on two different network technologies. You need to have all the debug technology, all the interconnect for that. So here, the easiest thing is you can use Ethernet, it's going to give you the same performance and actually, in some cases, we've seen better performance than we've seen with Omni-Path, better than in InfiniBand. >> That's awesome. Armando, we didn't get to you, so I want to make sure we get your future hot take. Where do you see the future of Ethernet here in HPC? >> Well, Pete hit on a big thing is bandwidth, right? So when you look at, train a model, okay? So when you go and train a model in AI, you need to have a lot of data in order to train that model, right? So what you do is essentially, you build a model, you choose whatever neural network you want to utilize. But if you don't have a good data set that's trained over that model, you can't essentially train the model. So if you have bandwidth, you want big pipes because you have to move that data set from the storage to the CPU. And essentially, if you're going to do it maybe on CPU only, but if you do it on accelerators, well, guess what? You need a big pipe in order to get all that data through. And here's the deal, the bigger the pipe you have, the more data, the faster you can train that model. So the faster you can train that model, guess what? The faster you get to some new insight, maybe it's a new competitive advantage, maybe it's some new way you design a product, but that's a benefit of speed, you want faster, faster, faster. >> It's all about making it faster and easier-- for the users. >> Armando: It is. >> I love that. Last question for you, Pete, just because you've said Tomahawk seven times, and I'm thinking we're in Texas, stakes, there's a lot going on with that. >> Making me hungry. >> I know, exactly. I'm sitting out here thinking, man, I did not have big enough breakfast. How did you come up with the name Tomahawk? >> So Tomahawk, I think it just came from a list. So we have a tried end product line. >> Savannah: Ah, yes. >> Which is a missile product line. And Tomahawk is being kind of like the bigger and batter missile, so. >> Savannah: Love this. Yeah, I mean-- >> So do you like your engineers? You get to name it. >> Had to ask. >> It's collaborative. >> Okay. >> We want to make sure everyone's in sync with it. >> So just it's not the Aquaman tried. >> Right. >> It's the steak Tomahawk. I think we're good now. >> Now that we've cleared that-- >> Now we've cleared that up. >> Armando, Pete, it was really nice to have both you. Thank you for teaching us about the future of Ethernet and HCP. David Nicholson, always a pleasure to share the stage with you. And thank you all for tuning in to theCUBE live from Dallas. We're here talking all things HPC and supercomputing all day long. We hope you'll continue to tune in. My name's Savannah Peterson, thanks for joining us. (soft music)

>>You can put this in a conference. >>Good morning and welcome back to Dallas. Ladies and gentlemen, we are here with the cube Live from, from Supercomputing 2022. David, my cohost, how you doing? Exciting. Day two. Feeling good. >>Very exciting. Ready to start off the >>Day. Very excited. We have two fascinating guests joining us to kick us off. Please welcome Pete and Armando. Gentlemen, thank you for being here with us. >>Having us, >>For having us. I'm excited that you're starting off the day because we've been hearing a lot of rumors about ethernet as the fabric for hpc, but we really haven't done a deep dive yet during the show. Y'all seem all in on ethernet. Tell us about that. Armando, why don't you start? >>Yeah. I mean, when you look at ethernet, customers are asking for flexibility and choice. So when you look at HPC and you know, infinite band's always been around, right? But when you look at where Ethernet's coming in, it's really our commercial and their enterprise customers. And not everybody wants to be in the top 500. What they want to do is improve their job time and improve their latency over the network. And when you look at ethernet, you kinda look at the sweet spot between 8, 12, 16, 32 nodes. That's a perfect fit for ethernet and that space and, and those types of jobs. >>I love that. Pete, you wanna elaborate? Yeah, yeah, >>Yeah, sure. I mean, I think, you know, one of the biggest things you find with internet for HPC is that, you know, if you look at where the different technologies have gone over time, you know, you've had old technologies like, you know, atm, Sonic, fitty, you know, and pretty much everything is now kind of converged toward ethernet. I mean, there's still some technologies such as, you know, InfiniBand, omnipath that are out there. Yeah. But basically there's single source at this point. So, you know, what you see is that there is a huge ecosystem behind ethernet. And you see that also, the fact that ethernet is used in the rest of the enterprise is using the cloud data centers that is very easy to integrate HPC based systems into those systems. So as you move HPC out of academia, you know, into, you know, into enterprise, into cloud service providers is much easier to integrate it with the same technology you're already using in those data centers, in those networks. >>So, so what's this, what is, what's the state of the art for ethernet right now? What, you know, what's, what's the leading edge, what's shipping now and what and what's in the near future? You, you were with Broadcom, you guys design this stuff. >>Yeah, yeah. Right. Yeah. So leading edge right now, I got a couple, you know, Wes stage >>Trough here on the cube. Yeah. >>So this is Tomahawk four. So this is what is in production is shipping in large data centers worldwide. We started sampling this in 2019, started going into data centers in 2020. And this is 25.6 tets per second. Okay. Which matches any other technology out there. Like if you look at say, infin band, highest they have right now that's just starting to get into production is 25 point sixt. So state of the art right now is what we introduced. We announced this in August. This is Tomahawk five. So this is 51.2 terabytes per second. So double the bandwidth have, you know, any other technology that's out there. And the important thing about networking technology is when you double the bandwidth, you don't just double the efficiency, it's actually winds up being a factor of six efficiency. Wow. Cause if you want, I can go into that, but why >>Not? Well, I, what I wanna know, please tell me that in your labs you have a poster on the wall that says T five with, with some like Terminator kind of character. Cause that would be cool if it's not true. Don't just don't say anything. I just want, I can actually shift visual >>It into a terminator. So. >>Well, but so what, what are the, what are the, so this is, this is from a switching perspective. Yeah. When we talk about the end nodes, when we talk about creating a fabric, what, what's, what's the latest in terms of, well, the kns that are, that are going in there, what's, what speed are we talking about today? >>So as far as 30 speeds, it tends to be 50 gigabits per second. Okay. Moving to a hundred gig pan four. Okay. And we do see a lot of Knicks in the 200 gig ethernet port speed. So that would be, you know, four lanes, 50 gig. But we do see that advancing to 400 gig fairly soon. 800 gig in the future. But say state of the art right now, we're seeing for the end nodes tends to be 200 gig E based on 50 gig pan four. Wow. >>Yeah. That's crazy. Yeah, >>That is, that is great. My mind is act actively blown. I wanna circle back to something that you brought up a second ago, which I think is really astute. When you talked about HPC moving from academia into enterprise, you're both seeing this happen. Where do you think we are on the adoption curve and sort of in that cycle? Armand, do you wanna go? >>Yeah, yeah. Well, if you look at the market research, they're actually telling it's 50 50 now. So ethernet is at the level of 50%. InfiniBand is at 50%. Right. Interesting. Yeah. And so what's interesting to us, customers are coming to us and say, Hey, we want to see, you know, flexibility and choice and hey, let's look at ethernet and let's look at InfiniBand. But what is interesting about this is that we're working with Broadcom, we have their chips in our lab, we have our switches in our lab. And really what we're trying to do is make it easy to simple and configure the network for essentially mpi. And so the goal here with our validated designs is really to simplify this. So if you have a customer that, Hey, I've been in fbe, but now I want to go ethernet, you know, there's gonna be some learning curves there. And so what we wanna do is really simplify that so that we can make it easy to install, get the cluster up and running, and they can actually get some value out of the cluster. >>Yeah. Peter, what, talk about that partnership. What, what, what does that look like? Is it, is it, I mean, are you, you working with Dell before the, you know, before the T six comes out? Or you just say, you know, what would be cool, what would be cool is we'll put this in the T six? >>No, we've had a very long partnership both on the hardware and the software side. You know, Dell has been an early adopter of our silicon. We've worked very closely on SI and Sonic on the operating system, you know, and they provide very valuable feedback for us on our roadmap. So before we put out a new chip, and we have actually three different product lines within the switching group within Broadcom, we've then gotten, you know, very valuable feedback on the hardware and on the APIs, on the operating system that goes on top of those chips. So that way when it comes to market, you know, Dell can take it and, you know, deliver the exact features that they have in the current generation to their customers to have that continuity. And also they give us feedback on the next gen features they'd like to see again in both the hardware and the software. >>So, so I, I'm, I'm just, I'm fascinated by, I I, I always like to know kind like what Yeah, exactly. Exactly right. Look, you, you start talking about the largest super supercomputers, most powerful supercomputers that exist today, and you start looking at the specs and there might be 2 million CPUs, 2 million CPU cores, yeah. Ex alop of, of, of, of performance. What are the, what are the outward limits of T five in switches, building out a fabric, what does that look like? What are the, what are the increments in terms of how many, and I know it, I know it's a depends answer, but, but, but how many nodes can you support in a, in a, in a scale out cluster before you need another switch? What does that increment of scale look like today? >>Yeah, so I think, so this is 51.2 terras per second. What we see the most common implementation based on this would be with 400 gig ethernet ports. Okay. So that would be 128, you know, 400 giggi ports connected to, to one chip. Okay. Now, if you went to 200 gig, which is kind of the state of the art for the Nicks, you can have double that. Okay. So, you know, in a single hop you can have 256 end nodes connected through one switch. >>So, okay, so this T five, that thing right there inside a sheet metal box, obviously you've got a bunch of ports coming out of that. So what is, what does that, what's the form factor look like for that, for where that T five sits? Is there just one in a chassis or you have, what does that look >>Like? It tends to be pizza boxes these days. Okay. What you've seen overall is that the industry's moved away from chassis for these high end systems more towards pizza, pizza boxes. And you can have composable systems where, you know, in the past you would have line cards, either the fabric cards that the line cards are plugged into or interface to these days, what tends to happen is you'd have a pizza box, and if you wanted to build up like a virtual chassis, what you would do is use one of those pizza boxes as the fabric card, one of them as the, the line card. >>Okay. >>So what we see, the most common form factor for this is they tend to be two, I'd say for North America, most common would be a two R U with 64 OSF P ports. And often each of those OSF p, which is an 800 gig e or 800 gig port, we've broken out into two 400 gig quarts. Okay. So yeah, in two r u you've got, and this is all air cooled, you know, in two re you've got 51.2 T. We do see some cases where customers would like to have different optics, and they'll actually deploy a four U just so that way they have the face place density, so they can plug in 128, say qsf P one 12. But yeah, it really depends on which optics, if you wanna have DAK connectivity combined with, with optics. But those are the two most common form factors. >>And, and Armando ethernet isn't, ethernet isn't necessarily ethernet in the sense that many protocols can be run over it. Right. I think I have a projector at home that's actually using ethernet physical connections. But what, so what are we talking about here in terms of the actual protocol that's running over this? Is this exactly the same as what you think of as data center ethernet, or, or is this, you know, RDMA over converged ethernet? What, what are >>We talking about? Yeah, so our rdma, right? So when you look at, you know, running, you know, essentially HPC workloads, you have the NPI protocol, so message passing interface, right? And so what you need to do is you may need to make sure that that NPI message passing interface runs efficiently on ethernet. And so this is why we want to test and validate all these different things to make sure that that protocol runs really, really fast on ethernet, if you look at NPI is officially, you know, built to, Hey, it was designed to run on InfiniBand, but now what you see with Broadcom and the great work they're doing now, we can make that work on ethernet and get, you know, it's same performance. So that's huge for customers. >>Both of you get to see a lot of different types of customers. I kind of feel like you're a little bit of a, a looking into the crystal ball type because you essentially get to see the future knowing what people are trying to achieve moving forward. Talk to us about the future of ethernet in hpc in terms of AI and ml. Where, where do you think we're gonna be next year or 10 years from now? >>You wanna go first or you want me to go first? I can start. >>Yeah. Pete feels ready. >>So I mean, what I see, I mean, ethernet, I mean, is what we've seen is that as far as on the starting off of the switch side, is that we've consistently doubled the bandwidth every 18 to 24 months. That's >>Impressive. >>Yeah. So nicely >>Done, casual, humble brag there. That was great. That was great. I love that. >>I'm here for you. I mean, I think that's one of the benefits of, of Ethan is like, is the ecosystem, is the trajectory, the roadmap we've had, I mean, you don't see that in any other networking technology >>More who, >>So, you know, I see that, you know, that trajectory is gonna continue as far as the switches, you know, doubling in bandwidth. I think that, you know, they're evolving protocols. You know, especially again, as you're moving away from academia into the enterprise, into cloud data centers, you need to have a combination of protocols. So you'll probably focus still on rdma, you know, for the supercomputing, the a AIML workloads. But we do see that, you know, as you have, you know, a mix of the applications running on these end nodes, maybe they're interfacing to the, the CPUs for some processing, you might use a different mix of protocols. So I'd say it's gonna be doubling a bandwidth over time evolution of the protocols. I mean, I expect that Rocky is probably gonna evolve over time depending on the a AIML and the HPC workloads. I think also there's a big change coming as far as the physical connectivity within the data center. Like one thing we've been focusing on is co-pack optics. So, you know, right now this chip is all, all the balls in the back here, there's electrical connections. How >>Many are there, by the way? 9,000 plus on the back of that >>352. >>I love how specific it is. It's brilliant. >>Yeah. So we get, so right now, you know, all the thirties, all the signals are coming out electrically based, but we've actually shown, we have this, actually, we have a version of Hawk four at 25 point sixt that has co-pack optics. So instead of having electrical output, you actually have optics directly out of the package. And if you look at, we'll have a version of Tomahawk five Nice. Where it's actually even a smaller form factor than this, where instead of having the electrical output from the bottom, you actually have fibers that plug directly into the sides. Wow. Cool. So I see, you know, there's, you know, the bandwidth, there's radis increasing protocols, different physical connectivity. So I think there's, you know, a lot of things throughout, and the protocol stack's also evolving. So, you know, a lot of excitement, a lot of new technology coming to bear. >>Okay. You just threw a carrot down the rabbit hole. I'm only gonna chase this one. Okay. >>All right. >>So I think of, I think of individual discreet physical connections to the back of those balls. Yeah. So if there's 9,000, fill in the blank, that's how many connections there are. How do you do that in many optical connections? What's, what's, what's the mapping there? What does that, what does that look like? >>So what we've announced for TAMA five is it would have fr four optics coming out. So you'd actually have, you know, 512 fiber pairs coming out. So you'd have, you know, basically on all four sides, you'd have these fiber ribbons that come in and connect. There's actually fibers coming out of the, the sides there. We wind up having, actually, I think in this case, we would actually have 512 channels and it would wind up being on 128 actual fiber pairs because >>It's, it's miraculous, essentially. It's, I know. Yeah, yeah, yeah, yeah. Yeah. So, so, you know, a lot of people are gonna be looking at this and thinking in terms of InfiniBand versus versus ethernet. I think you've highlighted some of the benefits of specifically running ethernet moving forward as, as hpc, you know, which is sort of just trails slightly behind supercomputing as we define it, becomes more pervasive AI ml. What, what are some of the other things that maybe people might not immediately think about when they think about the advantages of running ethernet in that environment? Is it, is it connecting, is it about connecting the HPC part of their business into the rest of it? What, or what, what are the advantages? >>Yeah, I mean, that's a big thing. I think, and one of the biggest things that ethernet has again, is that, you know, the data centers, you know, the networks within enterprises within, you know, clouds right now are run on ethernet. So now if you want to add services for your customers, the easiest thing for you to do is, you know, the drop in clusters that are connected with the same networking technology, you know, so I think what, you know, one of the biggest things there is that if you look at what's happening with some of the other proprietary technologies, I mean, in some cases they'll have two different types of networking technologies before they interface to ethernet. So now you've got to train your technicians, you train your, your assist admins on two different network technologies. You need to have all the, the debug technology, all the interconnect for that. So here, the easiest thing is you can use ethernet, it's gonna give you the same performance. And actually in some cases we seen better performance than we've seen with omnipath than, you know, better than in InfiniBand. >>That's awesome. Armando, we didn't get to you, so I wanna make sure we get your future hot take. Where do you see the future of ethernet here in hpc? >>Well, Pete hit on a big thing is bandwidth, right? So when you look at train a model, okay, so when you go and train a model in ai, you need to have a lot of data in order to train that model, right? So what you do is essentially you build a model, you choose whatever neural network you wanna utilize, but if you don't have a good data set that's trained over that model, you can't essentially train the model. So if you have bandwidth, you want big pipes because you have to move that data set from the storage to the cpu. And essentially, if you're gonna do it maybe on CPU only, but if you do it on accelerators, well guess what? You need a big pipe in order to get all that data through. And here's the deal. The bigger the pipe you have, the more data, the faster you can train that model. So the faster you can train that model, guess what? The faster you get to some new insight, maybe it's a new competitive advantage. Maybe it's some new way you design a product, but that's a benefit of speed you want faster, faster, faster. >>It's all about making it faster and easier. It is for, for the users. I love that. Last question for you, Pete, just because you've said Tomahawk seven times, and I'm thinking we're in Texas Stakes, there's a lot going on with with that making >>Me hungry. >>I know exactly. I'm sitting up here thinking, man, I did not have a big enough breakfast. How do you come up with the name Tomahawk? >>So Tomahawk, I think you just came, came from a list. So we had, we have a tri end product line. Ah, a missile product line. And Tomahawk is being kinda like, you know, the bigger and batter missile, so, oh, okay. >>Love this. Yeah, I, well, I >>Mean, so you let your engineers, you get to name it >>Had to ask. It's >>Collaborative. Oh good. I wanna make sure everyone's in sync with it. >>So just so we, it's not the Aquaman tried. Right, >>Right. >>The steak Tomahawk. I >>Think we're, we're good now. Now that we've cleared that up. Now we've cleared >>That up. >>Armando P, it was really nice to have both you. Thank you for teaching us about the future of ethernet N hpc. David Nicholson, always a pleasure to share the stage with you. And thank you all for tuning in to the Cube Live from Dallas. We're here talking all things HPC and Supercomputing all day long. We hope you'll continue to tune in. My name's Savannah Peterson, thanks for joining us.

>> From theCUBE studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> In the words of my colleague CTO David Nicholson, Broadcom buys old cars, not to restore them to their original luster and beauty. Nope. They buy classic cars to extract the platinum that's inside the catalytic converter and monetize that. Broadcom's planned 61 billion acquisition of VMware will mark yet another new era and chapter for the virtualization pioneer, a mere seven months after finally getting spun out as an independent company by Dell. For VMware, this means a dramatically different operating model with financial performance and shareholder value creation as the dominant and perhaps the sole agenda item. For customers, it will mean a more focused portfolio, less aspirational vision pitches, and most certainly higher prices. Hello and welcome to this week's Wikibon CUBE Insights powered by ETR. In this Breaking Analysis, we'll share data, opinions and customer insights about this blockbuster deal and forecast the future of VMware, Broadcom and the broader ecosystem. Let's first look at the key deal points, it's been well covered in the press. But just for the record, $61 billion in a 50/50 cash and stock deal, resulting in a blended price of $138 per share, which is a 44% premium to the unaffected price, i.e. prior to the news breaking. Broadcom will assume 8 billion of VMware debt and promises that the acquisition will be immediately accretive and will generate 8.5 billion in EBITDA by year three. That's more than 4 billion in EBITDA relative to VMware's current performance today. In a classic Broadcom M&A approach, the company promises to dilever debt and maintain investment grade ratings. They will rebrand their software business as VMware, which will now comprise about 50% of revenues. There's a 40 day go shop and importantly, Broadcom promises to continue to return 60% of its free cash flow to shareholders in the form of dividends and buybacks. Okay, with that out of the way, we're going to get to the money slide literally in a moment that Broadcom shared on its investor call. Broadcom has more than 20 business units. It's CEO Hock Tan makes it really easy for his business unit managers to understand. Rule number one, you agreed to an operating plan with targets for revenue, growth, EBITDA, et cetera, hit your numbers consistently and we're good. You'll be very well compensated and life will be wonderful for you and your family. Miss the number, and we're going to have a frank and uncomfortable bottom line discussion. You'll four, perhaps five quarters to turn your business around, if you don't, we'll kill it or sell it if we can. Rule number two, refer to rule number one. Hello, VMware, here's the money slide. I'll interpret the bullet points on the left for clarity. Your fiscal year 2022 EBITDA was 4.7 billion. By year three, it will be 8.5 billion. And we Broadcom have four knobs to turn with you, VMware to help you get there. First knob, if it ain't recurring revenue with rubber stamp renewals, we're going to convert that revenue or kill it. Knob number two, we're going to focus R&D in the most profitable areas of the business. AKA expect the R&D budget to be cut. Number three, we're going to spend less on sales and marketing by focusing on existing customers. We're not going to lose money today and try to make it up many years down the road. And number four, we run Broadcom with 1% GNA. You will too. Any questions? Good. Now, just to give you a little sense of how Broadcom runs its business and how well run a company it is, let's do a little simple comparison with this financial snapshot. All we're doing here is taking the most recent quarterly earnings reports from Broadcom and VMware respectively. We take the quarterly revenue and multiply by four X to get the revenue run rate and then we calculate the ratios off of the most recent quarters revenue. It's worth spending some time on this to get a sense of how profitable the Broadcom business actually is and what the spreadsheet gurus at Broadcom are seeing with respect to the possibilities for VMware. So combined, we're talking about a 40 plus billion dollar company. Broadcom is growing at more than 20% per year. Whereas VMware's latest quarter showed a very disappointing 3% growth. Broadcom is mostly a hardware company, but its gross margin is in the high seventies. As a software company of course VMware has higher gross margins, but FYI, Broadcom's software business, the remains of Symantec and what they purchased as CA has 90% gross margin. But the I popper is operating margin. This is all non gap. So it excludes things like stock based compensation, but Broadcom had 61% operating margin last quarter. This is insanely off the charts compared to VMware's 25%. Oracle's non gap operating margin is 47% and Oracle is an incredibly profitable company. Now the red box is where the cuts are going to take place. Broadcom doesn't spend much on marketing. It doesn't have to. It's SG&A is 3% of revenue versus 18% for VMware and R&D spend is almost certainly going to get cut. The other eye popper is free cash flow as a percentage of revenue at 51% for Broadcom and 29% for VMware. 51%. That's incredible. And that my dear friends is why Broadcom a company with just under 30 billion in revenue has a market cap of 230 billion. Let's dig into the VMware portfolio a bit more and identify the possible areas that will be placed under the microscope by Hock Tan and his managers. The data from ETR's latest survey shows the net score or spending momentum across VMware's portfolio in this chart, net score essentially measures the net percent of customers that are spending more on a specific product or vendor. The yellow bar is the most recent survey and compares the April 22 survey data to April 21 and January of 22. Everything is down in the yellow from January, not surprising given the economic outlook and the change in spending patterns that we've reported. VMware Cloud on AWS remains the product in the ETR survey with the most momentum. It's the only offering in the portfolio with spending momentum above the 40% line, a level that we consider highly elevated. Unified Endpoint Management looks more than respectable, but that business is a rock fight with Microsoft. VMware Cloud is things like VMware Cloud foundation, VCF and VMware's cross cloud offerings. NSX came from the Nicira acquisition. Tanzu is not yet pervasive and one wonders if VMware is making any money there. Server is ESX and vSphere and is the bread and butter. That is where Broadcom is going to focus. It's going to look at VSAN and NSX, which is software probably profitable. And of course the other products and see if the investments are paying off, if they are Broadcom will keep, if they are not, you can bet your socks, they will be sold off or killed. Carbon Black is at the far right. VMware paid $2.1 billion for Carbon Black. And it's the lowest performer on this list in terms of net score or spending momentum. And that doesn't mean it's not profitable. It just doesn't have the momentum you'd like to see, so you can bet that is going to get scrutiny. Remember VMware's growth has been under pressure for the last several years. So it's been buying companies, dozens of them. It bought AirWatch, bought Heptio, Carbon Black, Nicira, SaltStack, Datrium, Versedo, Bitnami, and on and on and on. Many of these were to pick up engineering teams. Some of them were to drive new revenue. Now this is definitely going to be scrutinized by Broadcom. So that helps explain why Michael Dell would sell VMware. And where does VMware go from here? It's got great core product. It's an iconic name. It's got an awesome ecosystem, fantastic distribution channel, but its growth is slowing. It's got limited developer chops in a world that developers and cloud native is all the rage. It's got a far flung R&D agenda going at war with a lot of different places. And it's increasingly fighting this multi front war with cloud companies, companies like Cisco, IBM Red Hat, et cetera. VMware's kind of becoming a heavy lift. It's a perfect acquisition target for Broadcom and why the street loves this deal. And we titled this Breaking Analysis taming the VMware beast because VMware is a beast. It's ubiquitous. It's an epic software platform. EMC couldn't control it. Dell used it as a piggy bank, but really didn't change its operating model. Broadcom 100% will. Now one of the things that we get excited about is the future of systems architectures. We published a breaking analysis about a year ago, talking about AWS's secret weapon with Nitro and it's Annapurna custom Silicon efforts. Remember it acquired Annapurna for a measly $350 million. And we talked about how there's a new architecture and a new price performance curve emerging in the enterprise, driven by AWS and being followed by Microsoft, Google, Alibaba, a trend toward custom Silicon with the arm based Nitro and which is AWS's hypervisor and Nick strategy, enabling processor diversity with things like Graviton and Trainium and other diverse processors, really diversifying away from x86 and how this leads to much faster product cycles, faster tape out, lower costs. And our premise was that everyone in the data center is going to competes, is going to need a Nitro to be competitive long term. And customers are going to gravitate toward the most economically favorable platform. And as we describe the landscape with this chart, we've updated this for this Breaking Analysis and we'll come back to nitro in a moment. This is a two dimensional graphic with net score or spending momentum on the vertical axis and overlap formally known as market share or presence within the survey, pervasiveness that's on the horizontal axis. And we plot various companies and products and we've inserted VMware's net score breakdown. The granularity in those colored bars on the bottom right. Net score is essentially the green minus the red and a couple points on that. VMware in the latest survey has 6% new adoption. That's that lime green. It's interesting. The question Broadcom is going to ask is, how much does it cost you to acquire that 6% new. 32% of VMware customers in the survey are increasing spending, meaning they're increasing spending by 6% or more. That's the forest green. And the question Broadcom will dig into is what percent of that increased spend (chuckles) you're capturing is profitable spend? Whatever isn't profitable is going to be cut. Now that 52% gray area flat spending that is ripe for the Broadcom picking, that is the fat middle, and those customers are locked and loaded for future rent extraction via perpetual renewals and price increases. Only 8% of customers are spending less, that's the pinkish color and only 3% are defecting, that's the bright red. So very, very sticky profile. Perfect for Broadcom. Now the rest of the chart lays out some of the other competitor names and we've plotted many of the VMware products so you can see where they fit. They're all pretty respectable on the vertical axis, that's spending momentum. But what Broadcom wants is that core ESX vSphere base where we've superimposed the Broadcom logo. Broadcom doesn't care so much about spending momentum. It cares about profitability potential and then momentum. AWS and Azure, they're setting the pace in this business, in the upper right corner. Cisco very huge presence in the data center, as does Intel, they're not in the ETR survey, but we've superimposed them. Now, Intel of course, is in a dog fight within Nvidia, the Arm ecosystem, AMD, don't forget China. You see a Google cloud platform is in there. Oracle is also on the chart as well, somewhat lower on the vertical axis, but it doesn't have that spending momentum, but it has a big presence. And it owns a cloud as we've talked about many times and it's highly differentiated. It's got a strategy that allows it to differentiate from the pack. It's very financially driven. It knows how to extract lifetime value. Safra Catz operates in many ways, similar to what we're seeing from Hock Tan and company, different from a portfolio standpoint. Oracle's got the full stack, et cetera. So it's a different strategy. But very, very financially savvy. You could see IBM and IBM Red Hat in the mix and then Dell and HP. I want to come back to that momentarily to talk about where value is flowing. And then we plotted Nutanix, which with Acropolis could suck up some V tax avoidance business. Now notice Symantec and CA, relatively speaking in the ETR survey, they have horrible spending momentum. As we said, Broadcom doesn't care. Hock Tan is not going for growth at the expense of profitability. So we fully expect VMware to come down on the vertical axis over time and go up on the profit scale. Of course, ETR doesn't measure the profitability here. Now back to Nitro, VMware has this thing called Project Monterey. It's essentially their version of Nitro and will serve as their future architecture diversifying off x86 and accommodating alternative processors. And a much more efficient performance, price in energy consumption curve. Now, one of the things that we've advocated for, we said this about Dell and others, including VMware to take a page out of AWS and start developing custom Silicon to better integrate hardware and software and accelerate multi-cloud or what we call supercloud. That layer above the cloud, not just running on individual clouds. So this is all about efficiency and simplicity to own this space. And we've challenged organizations to do that because otherwise we feel like the cloud guys are just going to have consistently better costs, not necessarily price, but better cost structures, but it begs the question. What happens to Project Monterey? Hock Tan and Broadcom, they don't invest in something that is unproven and doesn't throw off free cash flow. If it's not going to pay off for years to come, they're probably not going to invest in it. And yet Project Monterey could help secure VMware's future in not only the data center, but at the edge and compete more effectively with cloud economics. So we think either Project Monterey is toast or the VMware team will knock on the door of one of Broadcom's 20 plus business units and say, guys, what if we work together with you to develop a version of Monterey that we can use and sell to everyone, it'd be the arms dealer to everyone and be competitive with the cloud and other players out there and create the de facto standard for data center performance and supercloud. I mean, it's not outrageously expensive to develop custom Silicon. Tesla is doing it for example. And Broadcom obviously is capable of doing it. It's got good relationships with semiconductor fabs. But I think this is going to be a tough sell to Broadcom, unless VMware can hide this in plain site and make it profitable fast, like AWS most likely has with Nitro and Graviton. Then Project Monterey and our pipe dream of alternatives to Nitro in the data center could happen but if it can't, it's going to be toast. Or maybe Intel or Nvidia will take it over or maybe the Monterey team will spin out a VMware and do a Pensando like deal and demonstrate the viability of this concept and then Broadcom will buy it back in 10 years. Here's a double click on that previous data that we put in tabular form. It's how the data on that previous slide was plotted. I just want to give you the background data here. So net score spending momentum is the sorted on the left. So it's sorted by net score in the left hand chart, that was the y-axis in the previous data set and then shared and or presence in the data set is the right hand chart. In other words, it's sorted on the right hand chart, right hand table. That right most column is shared and you can see it's sorted top to bottom, and that was the x-axis on the previous chart. The point is not many on the left hand side are above the 40% line. VMware Cloud on AWS is, it's expensive, so it's probably profitable and it's probably a keeper. We'll see about the rest of VMware's portfolio. Like what happens to Tanzu for example. On the right, we drew a red line, just arbitrarily at those companies and products with more than a hundred mentions in the survey, everything but Tanzu from VMware makes that cut. Again, this is no indication of profitability here, and that's what's going to matter to Broadcom. Now let's take a moment to address the question of Broadcom as a software company. What the heck do they know about software, right. Well, they're not dumb over there and they know how to run a business, but there is a strategic rationale to this move beyond just doing portfolios and extracting rents and cutting R&D, et cetera, et cetera. Why, for example, isn't Broadcom going after coming back to Dell or HPE, it could pick up for a lot less than VMware, and they got way more revenue than VMware. Well, it's obvious, software's more profitable of course, and Broadcom wants to move up the stack, but there's a trend going on, which Broadcom is very much in touch with. First, it sells to Dell and HPE and Cisco and all the OEM. so it's not going to disrupt that. But this chart shows that the value is flowing away from traditional servers and storage and networking to two places, merchant Silicon, which itself is morphing. Broadcom... We focus on the left hand side of this chart. Broadcom correctly believes that the world is shifting from a CPU centric center of gravity to a connectivity centric world. We've talked about this on theCUBE a lot. You should listen to Broadcom COO Charlie Kawwas speak about this. It's all that supporting infrastructure around the CPU where value is flowing, including of course, alternative GPUs and XPUs, and NPUs et cetera, that are sucking the value out of the traditional x86 architecture, offloading some of the security and networking and storage functions that traditionally have been done in x86 which are part of the waste right now in the data center. This is that shifting dynamic of Moore's law. Moore's law, not keeping pace. It's slowing down. It's slower relative to some of the combinatorial factors. When you add up in all the CPU and GPU and NPU and accelerators, et cetera. So we've talked about this a lot in Breaking Analysis episodes. So the value is shifting left within that middle circle. And it's shifting left within that left circle toward components, other than CPU, many of which Broadcom supplies. And then you go back to the middle, value is shifting from that middle section, that traditional data center up into hyperscale clouds, and then to the right toward infrastructure software to manage all that equipment in the data center and across clouds. And look Broadcom is an arms dealer. They simply sell to everyone, locking up key vectors of the value chain, cutting costs and raising prices. It's a pretty straightforward strategy, but not for the fate of heart. And Broadcom has become pretty good at it. Let's close with the customer feedback. I spoke with ETRs Eric Bradley this morning. He and I both reached out to VMware customers that we know and got their input. And here's a little snapshot of what they said. I'll just read this. Broadcom will be looking to invest in the core and divest of any underperforming assets, right on. It's just what we were saying. This doesn't bode well for future innovation, this is a CTO at a large travel company. Next comment, we're a Carbon Black customer. VMware didn't seem to interfere with Carbon Black, but now that we're concerned about short term disruption to their tech roadmap and long term, are they going to split and be sold off like Symantec was, this is a CISO at a large hospitality organization. Third comment, I got directly from a VMware practitioner, an IT director at a manufacturing firm. This individual said, moving off VMware would be very difficult for us. We have over 500 applications running on VMware, and it's really easy to manage. We're not going to move those into the cloud and we're worried Broadcom will raise prices and just extract rents. Last comment, we'll share as, Broadcom sees the cloud data center and IoT is their next revenue source. The VMware acquisition provides them immediate virtualization capabilities to support a lightweight IoT offering. Big concern for customers is what technology they will invest in and innovate, and which will be stripped off and sold. Interesting. I asked David Floyer to give me a back of napkin estimate for the following question. I said, David, if you're running mission critical applications on VMware, how much would it increase your operating cost moving those applications into the cloud? Or how much would it save? And he said, Dave, VMware's really easy to run. It can run any application pretty much anywhere, and you don't need an army of people to manage it. All your processes are tied to VMware, you're locked and loaded. Move that into the cloud and your operating cost would double by his estimates. Well, there you have it. Broadcom will pinpoint the optimal profit maximization strategy and raise prices to the point where customers say, you know what, we're still better off staying with VMware. And sadly, for many practitioners there aren't a lot of choices. You could move to the cloud and increase your cost for a lot of your applications. You could do it yourself with say Zen or OpenStack. Good luck with that. You could tap Nutanix. That will definitely work for some applications, but are you going to move your entire estate, your application portfolio to Nutanix? It's not likely. So you're going to pay more for VMware and that's the price you're going to pay for two decades of better IT. So our advice is get out ahead of this, do an application portfolio assessment. If you can move apps to the cloud for less, and you haven't yet, do it, start immediately. Definitely give Nutanix a call, but going to have to be selective as to what you actually can move, forget porting to OpenStack, or do it yourself Hypervisor, don't even go there. And start building new cloud native apps where it makes sense and let the VMware stuff go into manage decline. Let certain apps just die through attrition, shift your development resources to innovation in the cloud and build a brick wall around the stable apps with VMware. As Paul Maritz, the former CEO of VMware said, "We are building the software mainframe". Now marketing guys got a hold of that and said, Paul, stop saying that, but it's true. And with Broadcom's help that day we'll soon be here. That's it for today. Thanks to Stephanie Chan who helps research our topics for Breaking Analysis. Alex Myerson does the production and he also manages the Breaking Analysis podcast. Kristen Martin and Cheryl Knight help get the word out on social and thanks to Rob Hof, who was our editor in chief at siliconangle.com. Remember, these episodes are all available as podcast, wherever you listen, just search Breaking Analysis podcast. Check out ETRs website at etr.ai for all the survey action. We publish a full report every week on wikibon.com and siliconangle.com. You can email me directly at david.vellante@siliconangle.com. You can DM me at DVellante or comment on our LinkedIn posts. This is Dave Vellante for theCUBE Insights powered by ETR. Have a great week, stay safe, be well. And we'll see you next time. (upbeat music)

hello and welcome to the cube i'm dave nicholson chief technology officer at thecube and we're here for a very special cube conversation with andy brown from broadcom andy welcome to the cube tell us a little about yourself a little bit my about myself my name is andy brown i'm currently the senior director of software architecture and performance analysis here within the data center solutions group at broadcom i've been doing that for about seven years prior to that i held various positions within the system architecture systems engineering and ic development organization but ultimately as well i spent some time in our support organization and managing our support team but ultimately have landed in the architecture organization as well as performance analysis great so a lot of what you do is around improving storage performance tell us more about that so let me give you a brief history of uh storage from from my perspective um you know i as i mentioned i go back about 30 years in my career and that would have started back in the ncr microelectronics days and originally with parallel scuzzy so that would be if anyone would remember the 5380 controller which was one of the original parallel scuzzy controllers that existed and built by ncr microelectronics at the time i've i've seen the advent of parallel scuzzy a stint of fiber channel ultimately leading into the serialization of those of the scuzzy standard into sas as well as sata and then ultimately leading to nvme protocols and the advent of flash moving from hard drives into a flash based media and as well on on that's on the storage side on the host side moving from parallel interfaces isa if everybody could remember that moving to pci pci express that's where we land today so andy we're square in the middle of the era of both nvme and sas what kinds of challenges does that overlap represent well i think you know obviously we've seen sas around for a while it was the conversion from parallel into a serial attached scuzzy and that really sas brings with it the ability to uh connect on really a high number of devices um and uh was was kind of the original scaling of devices and and really uh also enabled uh was was one of the things that enabled flash based media given the the speed and performance that came to the table of course nvme came in as well with the promise of of even higher speeds and as we saw flash media really really take a strong role in storage uh nvme came around and and really was focused on trying to address that whereas sas originated with hard drive technology nvme was really born out of how do we how do we most efficiently deal with flash based media you know sas with its but sas still carries a benefit on scalability nvme maybe has i don't want to say challenges there but it's definitely was not designed as much to be broadly scalable across many many say hundreds or thousands of devices but definitely addressed some of the performance issues that were coming up as flash media was becoming so uh uh was was increasing the overall storage performance that we could experience if you will let's talk about host interfaces like pcie what's the significance there um really uh the all the storage in the world all of the performance in the world and on the storage side is not of much use to you unless you can really feed it into the into the beast if you will into the cpu and into this the rest of the server subsystem and that's really where pci comes into play pci uh originally was in parallel form and then moved to serial with pci express as we know it today and and really has created a pathway to to to enable not not only storage performance but any other adapter or any other networking or other other types of technologies to just open up that pathway and feed the processor if and as we've moved through from pci to pci express pci 2.0 3.0 4.0 and just opening up those pipes has really enabled just a tremendous amount of flow of data into into the compute engine allowing it to be analyzed sorted used to analyze data big data uh ai type applications just those pipes are critical in those types of applications we know we've seen dramatic increases in performance going from one generation of pcie to the next but how does that translate into the worlds of sas sata and nvme um so from a performance perspective when we look at these different types of media whether it be sata sas or nvme um of course there are performance difference inherent in that media sata being probably the lowest performing with nvme uh topping out at higher performing although sas can perform quite well as a flash based you know as a protocol connected to flash based media and of course nvme from us an individual device scaling from a by one to a by four interface really that is where nvme kind of has enabled a bigger pipe directly to the storage media uh being able to scale up to buy four whereas sas is kind of limited to buy one maybe buy two in some cases although most servers only connect the sas device by one so from a difference perspective then you're really wanting to create a solution or or enable the infrastructure to be able to consume that performance that nvme is going to give you and i think that you know that is something where our solutions have really in in the recent generations shine at their ability to really now uh keep up with uh storage performance in nvme uh as well as provide that connectivity back down into the sas and sata world as well let's talk about your perspective on raid today so uh there's been a lot of uh views and opinions on raid over the years it's been a and those have been changing over time raid has been around for a very very long time uh probably about as long as again going back over my 30-year career uh it's been around for almost the entire time obviously raid originally was viewed as as something that was uh very very necessary uh devices fail they don't last forever but the data that's on them is very very important and people care about that so raid was brought about you know knowing that individual devices that are storing that data are going to fail and really took hold as a primary mechanism of protection but as time went on uh and and as performance moved up uh both in the server and both in in the media itself if we start talking about flash uh raid really took on people people started to look at traditional server storage raid uh but with maybe a more of a negative connotation i think that because uh to be quite honest it fell behind a little bit if you look at things like parity raid raid five and rate six very very effective and efficient means of protecting your data very storage efficient but ultimately had some penalties a primarily around wright performance random rights in raid 5 volumes was not keeping up with what really needed to be there and um i think that really shifted uh opinions of raid that hey it's just it's just not it's not going to keep up and we need to move on to other avenues and and we've seen that we've seen disaggregated storage and other solutions pop up to protect your data obviously in cloud environments and things like that it's shown up and uh and they have been successful so one of the drawbacks with raid is always the performance tax associated with generating parity for parity rate what has broadcom done to address those potential bottlenecks we've really solved the raid performance issue the right performance issue we're we're in our latest generation of controllers we're exceeding a million rate five right iops which is enough to satisfy many many many applications as a matter of fact even in virtual environments aggregated solutions we have multiple applications and then as well in the rebuild arena we really have through our architecture through our hardware automation have been able to move the bar on that to where the rebuild not only the rebuild times have been brought down dramatically in sas based or in i'm sorry in flash based solutions but the performance that you can observe while those rebuilds are going on is almost immeasurable so in most applications you would almost observe no performance deficiencies during a rebuild operation which is really night and day compared to where things were just a few short years ago so the fact that you've been able to dramatically decrease the time necessary for a raid rebuild is obviously extremely important but give us your overall performance philosophy from broadcom's point of view you know over the years we have recognized that performance is is obviously critically important for our products and the ability to analyze performance from many many angles is critically important there are literally infinite ways you can look at performance in a storage subsystem what we have done in our labs and in our solutions through not only hardware scaling in our in our in our labs but also through automation scripts and things like that allowed us to collect a substantial amount of data to look at the performance of our solutions from every angle you know iops bandwidth application level performance small topologies large topologies just just many many aspects it's still honestly only scratches the surface of all the possible uh performance points that you could gather but it it has we have moved the bar dramatically in that regard and and it's something that our customers really demanded of us um you know storage technology has gotten more complex and you have to look at it from a lot different angles especially on the performance front to make sure that there are no holes there that somebody's going to run into so based on specific customer needs and requests you look at performance from a variety of different angles um what are some of the trends that you're seeing specifically in storage performance today and moving into the future yeah emerging trends within the storage industry i think that to look at the emerging trends you really need to go back and look at where we started we started uh in compute where people were you would have basically your uh your server that would be under the desk in a small business operation and individual uh businesses would have their own uh set of set of servers and and the storage would really be localized to those obviously the industry has recognized that um that to some extent disaggregation of that we we see that obviously in what's happening in cloud uh in hyper-converged storage and things like that those afford a tremendous amount of flexibility uh and and are obviously uh great players in the storage world today but what with that flexibility is come some sacrifice in performance and actually quite substantial sacrifice and what we're observing is almost uh it comes back full circle the uh the need for inbox high performing server storage that is well protected uh and and with people with confidence that people have confidence that their data is protected and that they can uh extract the performance that they need for the demanding database applications that still exist today and they still operate in in the offices around the country and around the world that really need to protect their data on a local basis in the server and i think that from a trend perspective that's what we're seeing also from the standpoint of nvme store nvme itself is really started out with hey we'll just software rate that we'll just we'll just wrap software around that we can protect the data we had so many customers come back to us saying you know what we really need hardware raid on nvme and when they came to us we were ready we had a solution ready to go and we're able to provide that and now we're seeing going on demand we are we are complementary to other storage solutions out there server storage is not going to necessarily rule the world but it is surely has a place in the broader storage spectrum and we think we have the right solution for that speaking of servers and server-based storage why would for example a dell customer care about the broadcom components in that dell server so uh uh let's say you're configuring a dell server and you're going why does why does hardware raid matter what what what's important about that well i think when you look at today's hardware raid uh first of all you're going to see dramatically better performance you're going to see dramatically better performance in it's going to enable you to put raid 5 volumes a very effective and efficient mechanism for protecting your data a storage efficient mechanism you're going to use raid 5 volumes where you weren't able to do that before because when you're in the millions of iops range you really uh can satisfy a lot of application needs out there and and then you're going to also going to have rebuilt times that are lightning fast your performance is not going to degrade when you're when you're running those application especially database applications but not not only database but streaming applications uh bandwidth uh to to protected raid volumes is is almost almost imperceptibly different from just raw bandwidth to the media so the rate rate configurations in today's dell servers really afford you the opportunity to make use of that storage where you you may not have uh you may have already written it off as well ray just doesn't is not going to get me there quite frankly uh into this in in the storage servers that dell is providing uh with with raid technology uh there are huge windows open and what you can do today with applications well all of this is obviously good news for dell and dell customers thanks again andy for joining us for this cube conversation i'm dave nicholson for the cube [Music]

[Music] for decades the technology industry had marched the cadence of moore's law it was a familiar pattern system oems would design in the next generation of intel microprocessors every couple of years or so maybe bump up the memory ranges periodically and the supporting hardware would kind of go along for the ride upgrading its performance and bandwidth system designers they might beef up the cash maybe throwing some more spinning disk spindles at the equation to create a balanced environment and this was pretty predictable and consistent in the pattern and was reasonably straightforward compared to today's challenges this is all changed the confluence of cloud distributed global networks the diversity of applications ai machine learning and the massive growth of data outside of the data center requires new architectures to keep up as we've reported the traditional moore's law curve is flattening and along with that we've seen new packages with alternative processors like gpus npus accelerators and the like and the rising importance of supporting hardware to offload tasks like storage and security and it's created a massive challenge to connect all these components together the storage the memories and all of the enabling hardware and do so securely at very low latency at scale and of course cost effectively this is the topic of today's segment the shift from a world that is cpu centric to one where the connectivity of the various hardware components is where much of the innovation is occurring and to talk about that there is no company who knows more about this topic than broadcom and with us today is jazz tremblay who was general manager data center solutions group at broadcom jazz welcome to thecube hey dave thanks for having me really appreciate it yeah you bet now broadcom is a company that a lot of people might not know about i mean but the vast majority of the internet traffic flows through broadcom products like pretty much all of it it's a company with trailing 12-month revenues of nearly 29 billion and a 240 billion dollar market cap jazz what else should people know about broadcom well they've uh 99 of the internet traffic goes through broadcom silicon or devices and i think what people are not often aware of is how breath it is it starts with the devices phones and tablets that use our wi-fi technology or rf filters and then those connect to access points either at home at work or public access points using your wi-fi technology and if you're working from home you're using a residential or broadband gateway and that uses broadcom technology also from there you go to access networks core networks and eventually you'll work your way into the data center all connected by bartcom so really we're at the heart of enabling this connectivity ecosystem and we're at the core of it we're a technology company we invest about five billion dollars a year in r d and as you were saying or last year we achieved 27.5 billion of revenue and our mission is really to connect the ecosystem to enable what you said this transformation around the data centric world so talk about your scope of responsibility what's your what's your role generally and specifically with storage so i've been with the company for 16 years and i head up the data center solutions group which includes three product franchises a pci fabric storage connectivity and broadcom ethernet nics so my chart and my team's charter is really server connectivity inside the data center and and what specifically is broadcom doing in storage jazz so it's been quite a journey uh over the past eight years we've made a series of acquisition and built up a pretty impressive storage portfolio this first started with lsi and that's where i came from and the team here came from lsi that had two product franchises around storage the first one was server connectivity hba raid expanders for ssds and hdds the second product group was actually chips that go inside the hard drives so socs and preamps so that was an acquisition that we made and actually that's how i came into the broadcom group through lsi the next acquisition we made was plx the industry's leader in pcie fabrics they've been doing pcie switches for about 15 years we acquired the company and really saw an acceleration in the requirements for nvme attach and ai ml fabrics very specialized low latency fabrics after that we acquired a large system and software company brocade and dave if you recall brocade they're the market leader in fiber channel switching this is where if you're a financial or government institution you want to build a mission critical ultra secure really best in class storage network following brocade acquisition we acquired mulx that is now the number one provider of fibre channel adapters inside servers and the last acquisition for this puzzle was was actually broadcom where avago acquired broadcom and took on the broadcom name and there we acquired um ethernet switching capabilities and ethernet adapters that go into storage servers or external storage systems so with all this it's been quite the journey to build up this portfolio uh we're number one in each of these storage product categories and we now have four divisions that are focused on storage connectivity you know that's quite remarkable when you think about i mean i know all these companies that you were talking about and they were they were very quality companies but they were kind of bespoke and the fact that you had the vision to kind of connect the dots and now take responsibility for that integration we're going to talk about what that means in terms of competitive advantage but but i wonder if we could zoom out and maybe you could talk about the key storage challenges and elaborate a little bit on why connectivity is now so so important like what are the trends that are driving that shift that we talked about earlier from a cpu-centric world the one that's connectivity-centric i think at broadcom we recognize the importance of storage and storage connectivity and if you look at data centers whether it be private public cloud or hybrid data centers they're getting inundated with data if you look at the digital universe it's growing at about 23 keger day so over a course of four to five years you're doubling the amount of new information and that poses really two key challenges for the infrastructure the first one is you have to take all this data and for a good chunk of it you have to store it be able to access it and protect it the second challenge is you actually have to go and analyze and process this data and doing this at scale that's the uh the key challenge and what we're seeing these data centers uh getting a tsunami of data and historically they've been cpu-centric architectures and what that means is the cpu is at the heart of the data center and a lot of the workloads are processed by software running on the cpu we believe that we're currently transforming the architecture from cpu centric to connectivity centric and what we mean by connectivity centric is you architect your data center thinking about the connectivity first and the goal of the connectivity is to use all the components inside the data center the memory the spinning media the flash storage the networking the specialized accelerators the fpga all these elements and use them for what they're best at to process all this data and the goal uh dave is really to drive down power and deliver the performance so that we can achieve all the innovation we want inside the data centers so it's really a shift from cpu centric to uh bringing in more specialized components and architecting the the connectivity inside the data center to help we think that's a really important part okay so you have this need for connectivity at scale you mentioned and you're dealing with massive massive amounts of data i mean we're going to look back the last decade and say oh that you've seen nothing compared to to the when we get to 2030. but you at the same time you have to control costs so what are the technical challenges to achieving that vision so it's really challenging it's it's not that complex to build up faster bigger solution if you have no cost or or power budget and really the key challenges that our team is facing working with customers is first i'd say it's architectural challenges so we would all like to have one fabric that i think to connect all the devices and bring us all the characteristics that we need but the reality is we can't we can't do that so you need distinct fabrics inside the data center and you need them to work together you'll need an ethernet backbone in some cases you'll need a fiber channel network in some cases you'll need a small fabric for thousands or hundreds of thousands of hdds you will need pcie fabrics for aiml servers and and one of the key architectural challenges is which fabric do you use when and how do you develop these fabrics to meet their purpose-built needs the that's one thing the second architectural challenge dave is what i challenge my team with is example how do i double bandwidth while reducing net power double bandwidth reducing that power how do i take a storage controller and increase the iops by 10x and will i locate only 50 more power budget so that equation requires tremendous uh innovation and that's really what we focus on and power is becoming more and more important in that equation so you've got decisions from an architecture perspective as to which fabric to use you've got this architectural challenge around we need to innovate and do things smarter better to drive down power while delivering more performance then if you take those things together the problem statement becomes more complex so you've had these silicon devices with complex firmware on them that need to interoperate with multiple devices they're getting more and more complex so there's execution challenges and what we need to do and what we're investing to do is shift left quality so to do these complex devices they come out tight time to market with high quality and one of the key things that we've invested in is emulation of the environment before you tape out your silicon so effectively taking the application software running it on an emulation environment making sure that works running your tests before you tape out and that ensures quality silicon so it's it's challenging but the team loves challenges and that's kind of what we're facing on one hand architectural challenges on the other hand a new level of execution challenges so you're you're compressing the time to final tape out you know versus maybe traditional techniques and then you mentioned architecture my am i right jazz that you're essentially from an architectural standpoint trying to minimize the because your latency is so important you're trying to minimize the amount of data that you have to move around and actually bringing you know compute to the data is that the right way to think about it well i think there's multiple parts of the problem one of them is you need to do more data transactions example data protection with rate algorithms we need to do millions of transactions per second and the only way to achieve this with the minimal power impact is to hardware accelerate these that's one piece of investment the other investment is um you're absolutely right dave so it's shuffling the data around the data center so in the data center in some cases you need to have multiple pieces of the puzzle multiple ingredients processing the same data at the same time and you need advanced methodologies to share the data and avoid moving it all over the data center so that's another big piece of investment that we're focused on okay yeah so let's let's stay on that because i see this as disruptive you talk about spending five billion dollars you know a year in r d um and talk a little bit more about the disruptive technologies or the supportive technologies that you're introducing specifically to support this vision so let's break it down in a couple couple big industry problems that our team is focused on so the first one is i'll take an enterprise workload database if you want the fastest running database you want to utilize local storage nvme based drives and you need to protect that data and raid is the mechanism of choice to protect your data in local environments and there what we need to do is really just do the transactions a lot faster historically the storage has been a bit of a bottleneck in these types of applications for example our newest generation product we're doubling the bandwidth increasing iops by 4x but more importantly we're accelerating rate rebuilds by 50x and that's important dave if you are using a database in some cases you limit the size of that database based on how fast you can do those rebuilds so this 50x acceleration and rebuilds is something we're getting a lot of good feedback on for customers the the last metric we're really focused on is right latency so how fast can the cpu send the right to the storage connectivity subsystem and commit it to drives and we're improving that by 60x generation of regeneration so we're talking fully loaded latency 10 microseconds so from an enterprise workload it's about data protection much much faster using nvme drives that's one big problem the other one is if you're um if you look at dave youtube facebook tick tock the amount of user generated content specifically video content that they're producing on an hour-by-hour basis is mind-boggling and the hyperscale customers are really counting on us to help them scale the connectivity of hundreds of thousands of hard drive to store and access all that data in a very reliable way so there we're leading the industry in the transition to 24 gig sas and multi-actuator drives third big problem is around aiml servers so these are some of the highest performance servers that they basically need super low latency connectivity between gp gpus networking nvme drives cpus and orchestrate that all together and the fabric of choice for that is pcie fabric so here we're talking about 150 nanosecond latency in a pcie fabric fully non-blocking very reliable and here we're helping the industry transition from pca gen 4 to pcie gen 5. and the last piece is okay i've got a aiml server i have a storage system with hard drives or a storage server in the enterprise space all these devices systems need to be connected to the ethernet backbone and my team is heavily investing in ethernet mix transitioning to 100 gig 200 gig 400 gig and putting capabilities optimized for uh for storage workloads so those are kind of the four big things that we're focused on at the industry level from a connectivity perspective dave yeah and that makes a lot of sense and really resonates uh particularly as we have that shift from a cpu centric to a connectivity center because the other thing you said i mean you talk about 50x raid rebuild times you know one thing a couple of things you know in storage is if you ask the question what happens when something goes wrong because it's all about recovery you can't lose data and the other thing you mentioned is write latency which has always been you know the problem okay reads i can read out of cash but ultimately you've got to get it to where it's persisted so some real technical challenges there that you guys are dealing with absolutely dave yeah and uh these these are these are the type of problems that gets the engineers excited give them really tough tough technical problems to go solve i wonder if we could take a couple of examples or an example of scaling with a large customer for instance obviously hyperscalers or take a company like dell i mean they're a big company big customer take us through that so i we use the word scale a lot at broadcom we work with some of the industry leaders and data centers and oems and scale means different things to them so example if i'm working with a hyperscaler that is getting inundated with data and they need half a million storage controllers to store all that that data well their scale problem is can you deliver and dave you know how much of a hot topic that is these days so they need a partner that can scale from a delivery perspective but if i take a company like example dell that's very focused on storage from storage servers their acquisition of emc they have a very broad portfolio of data center storage offerings and scale to them from a broadcom from a connected by broadcom perspective means that you need to have the investment scale to meet their end-to-end requirements all the way from a low end storage connectivity solution for booting a server all the way up to a very high-end all-flash array or high-density hdd system so they want a company a partner that can invest and has a scale to invest to meet their end-to-end requirements second thing is their different products are unique and have different requirements and you need to adapt your collaboration model for example some products within dell portfolio might say i just want a storage adapter plug it in the operating system will automatically recognize it i need this turnkey i want to do minimal investment this is not an area of high differentiation for me at the other end of the spectrum they may have applications where they want deep integration with their management and our silicon tools so that they can deliver the highest quality highest performance to their customers so they need a partner that can scale from an r d investment perspective from a silicon software and hardware perspective but they also need a company that can scale from support and business model perspective and give them the flexibility that their end customers need so dell is a great company to work with we have a long lasting relationship with them and the relationship is very deep in some areas example server storage and it's also quite broad they they are adopters of the vast majority of our storage uh connectivity products well and i imagine it was i want to talk about the uniqueness of broadcom and again it's i'm in awe of the fact that somebody had the vision you guys your team uh obviously your ceo was one of the visionaries in the industry had the sense to to look out and say okay we can put these these pieces together so i would imagine a company like dell you've they're able to consolidate their their vendor their supplier base and push you for integration in an innovation in innovation how unique is that is the broadcom model what's compelling you know to your customers about that model so i think what's unique from a storage perspective is the breadth of the portfolio and also the scale at which we can invest so you know if you look at some of the things we talked about from a scale perspective how data centers throughout the world are getting inundated with data dave they need help and we need to equip them with cutting edge technology to increase performance drive down power improve reliability so so they need partners that in each of the the product categories that they you partner with them on you know we can invest with scale so that's i think one of the first things the second thing is if you look at this connectivity-centric data center you need multiple types of fabric and whether it be cloud customers or large oems they are organizing themselves to be able to look at things holistically they're no longer product company they're very data center architecture companies and um so it's good for them to have a partner that can look across product groups across division says okay this is the innovation we need to bring to market these are the problems we need to go solve and they really appreciate that and i think the last thing is a flexible business model within example my division we're we offer different business models different engagement and collaboration models with technology but there's another division that if you want to innovate at the silicon level and build custom silicon for you like many of the hyper scalers or other companies are doing that division is just focus on that so i i feel like broadcom is unique from a storage perspective its ability to innovate breadth a portfolio and the flexibility in the collaboration model to help our customers solve their customers problems so you're saying you can deal with merchant products slash open products or you can do highly you know high customization where does software differentiation fit into this model so it's it's actually one of the most important elements uh i think a lot of our customers take it for granted that will take care of the silicon we'll anticipate the requirements and deliver the performance that they need but from a software firmware driver utilities that is where a lot of differentiation lies some cases will offer an sdk model where you know customers can build their entire applications on top of that in some cases they want a complete turnkey solution where you take technology integrate it into server and the operating system recognizes it and you have out of box drivers from broadcom so we need to offer them that flexibility because you know their needs are quite quite broad there so last question what's the future of the business look like to jazz tremblay give us your point of view on that well uh it's it's fun i gotta tell you dave we're having uh we're having a great time we've got i've got a great team they're uh the world's experts on storage connectivity and working with them is a pleasure and we've got a rich great set of customers that are giving us cool problems to go solve and we're excited about it so i think this is really you know with the acceleration of all this digital transformation that we're seeing we're excited we're having fun and i think there's a lot of problems to be solved and we also have a responsibility i think the ecosystem in the industry is counting on our team to deliver the innovation from a storage connectivity perspective and i'll tell you dave we're having fun it's great but we take that responsibility uh pretty seriously jazz great stuff i really appreciate you laying all that out very important role you guys are playing you have a really unique perspective thank you thank you dave and thank you for watching this is dave vellante for the cube and we'll see you next time you

(upbeat music) >> For decades the technology industry had marched the cadence of Moore's law. It was a familiar pattern. System OEMs would design in the next generation of Intel microprocessors, every couple of years or so maybe bump up the memory ranges periodically and the supporting hardware would kind of go along for the ride, upgrading its performance and bandwidth. System designers then they might beef up the cache, maybe throwing some more spinning disc spindles at the equation to create a balanced environment. And this was pretty predictable and consistent in the pattern and was reasonably straightforward compared to is challenges. This has all changed. The confluence of cloud, distributed global networks, the diversity of applications, AI, machine learning and the massive growth of data outside of the data center requires new architectures to keep up. As we've reported the traditional Moore's Law curve is flattening. And along with that we've seen new packages with alternative processors like GPUs, NPUs, accelerators and the like and the rising importance of supporting hardware to offload tasks like storage and security. And it's created a massive challenge to connect all these components together, the storage, the memories and all of the enabling hardware and do so securely at very low latency at scale and of course, cost effectively. This is the topic of today's segment. The shift from a world that is CPU centric to one where the connectivity of the various hardware components is where much of the innovation is occurring. And to talk about that, there is no company who knows more about out this topic than Broadcom. And with us today is Jas Tremblay, who is general manager, data center solutions group at Broadcom. Jas, welcome to theCUBE. >> Hey Dave, thanks for having me, really appreciate it. >> Yeah, you bet. Now Broadcom is a company that a lot of people might not know about. I mean, but the vast majority of the internet traffic flows through Broadcom products. (chuckles) Like pretty much all of it. It's a company with trailing 12 month revenues of nearly 29 billion and a 240 billion market cap. Jas, what else should people know about Broadcom? >> Well, Dave, 99% of the internet traffic goes through Broadcom silicon or devices. And I think what people are not often aware of is how breadth it is. It starts with the devices, phones and tablets that use our Wi-Fi technology or RF filters. And then those connect to access points either at home, at work or public access points using our Wi-Fi technology. And if you're working from home, you're using a residential or broadband gateway and that uses Broadcom technology also. From there you go to access networks, core networks and eventually you'll work your way into the data center, all connected by Broadcom. So really we're at the heart of enabling this connectivity ecosystem and we're at the core of it, we're a technology company. We invest about 5 billion a year in R&D. And as you were saying our last year we achieved 27.5 billion of revenue. And our mission is really to connect the ecosystem to enable what you said, this transformation around the data-centric world. >> So talk about your scope of responsibility. What's your role generally and specifically with storage? >> So I've been with the company for 16 years and I head up the data center solutions group which includes three product franchises PCA fabric, storage connectivity and Broadcom ethernet nics. So my charter, my team's charter is really server connectivity inside the data center. >> And what specifically is Broadcom doing in storage, Jas? >> So it's been quite a journey. Over the past eight years we've made a series of acquisition and built up a pretty impressive storage portfolio. This first started with LSI and that's where I came from. And the team here came from LSI that had two product franchises around storage. The first one was server connectivity, HBA raid, expanders for SSDs and HDDs. The second product group was actually chips that go inside the hard drives. So SOCs and pre amps. So that was an acquisition that we made and actually that's how I came into the Broadcom group through LSI. The next acquisition we made was PLX, the industry's leader in PCIe fabrics. They'd been doing PCIe switches for about 15 years. We acquired the company and really saw an acceleration in the requirements for NVMe attached and AI ML fabrics, very specialized, low latency fabrics. After that, we acquired a large system and software company, Brocade, and Dave if you recall, Brocade they're the market leader in fiber channel switching, this is where if you're financial or government institution you want to build a mission critical, ultra secure really best in class storage network. Following Brocade acquisition we acquired Emulex that is now the number one provider of fiber channel adapters inside servers. And the last acquisition for this puzzle was actually Broadcom where Avago acquired Broadcom and took on the Broadcom name. And there we acquired ethernet switching capabilities and ethernet adapters that go into storage servers or external storage systems. So with all this it's been quite the journey to build up this portfolio. We're number one in each of these storage product categories. And we now have four divisions that are focused on storage connectivity. >> That's quite remarkable when you think about it. I mean, I know all these companies that you were talking about and they were very quality companies but they were kind of bespoke in the fact that you had the vision to kind of connect the dots and now take responsibility for that integration. We're going to talk about what that means in terms of competitive advantage, but I wonder if we could zoom out and maybe you could talk about the key storage challenges and elaborate a little bit on why connectivity is now so important. Like what are the trends that are driving that shift that we talked about earlier from a CPU centric world to one that's connectivity centric? >> I think at Broadcom, we recognize the importance of storage and storage connectivity. And if you look at data centers whether it be private, public cloud or hybrid data centers, they're getting inundated with data. If you look at the digital universe it's growing at about 23% a day. So over a course of four to five years you're doubling the amount of new information and that poses really two key challenges for the infrastructure. The first one is you have to take all this data and for a good chunk of it, you have to store it, be able to access it and protect it. The second challenge is you actually have to go and analyze and process this data and doing this at scale that's the key challenge and what we're seeing these data centers getting a tsunami of data. And historically they've been CPU centric architectures. And what that means is the CPU's at the heart of the data center. And a lot of the workloads are processed by software running on the CPU. We believe that we're currently transforming the architecture from CPU centric to connectivity centric. And what we mean by connectivity centric is you architect your data center thinking about the connectivity first. And the goal of the connectivity is to use all the components inside the data center, the memory, the spinning media, the flash storage, the networking, the specialized accelerators, the FPGA all these elements and use them for what they're best at to process all this data. And the goal Dave is really to drive down power and deliver the performance so that we can achieve all the innovation we want inside the data centers. So it's really a shift from CPU centric to bringing in more specialized components and architecting the connectivity inside the data center to help. We think that's a really important part. >> So you have this need for connectivity at scale, you mentioned, and you're dealing with massive, massive amounts of data. I mean, we're going to look back to the last decade and say, oh, you've seen nothing compared to when we get to 2030, but at the same time you have to control costs. So what are the technical challenges to achieving that vision? >> So it's really challenging. It's not that complex to build up faster, bigger solution, if you have no cost or power budget. And really the key challenges that our team is facing working with customers is first, I'd say it's architectural challenges. So we would all like to have one fabric that aim to connect all the devices and bring us all the characteristics that we need. But the reality is, we can't do that. So you need distinct fabrics inside the data center and you need them to work together. You'll need an ethernet backbone. In some cases, you'll need a fiber channel network. In some cases, you'll need a small fabric for thousands or hundreds of thousands of HDDs. You will need PCIe fabrics for AI ML servers. And one of the key architectural challenges is which fabric do you use when and how do you develop these fabrics to meet their purpose built needs. That's one thing. The second architectural challenge, Dave is what I challenge my team with is example, how do I double bandwidth while reducing net power, double bandwidth, reducing net power? How do I take a storage controller and increase the IOPS by 10X and will allocate only 50% more power budget? So that equation requires tremendous innovation. And that's really what we focus on and power is becoming more and more important in that equation. So you've got decisions from an architecture perspective as to which fabric to use. You've got this architectural challenge around we need to innovate and do things smarter, better, to drive down power while delivering more performance. Then if you take those things together the problem statement becomes more complex. So you've had these silicon devices with complex firmware on them that need to inter-operate with multiple devices. They're getting more and more complex. So there's execution challenges and what we need to do. And what we're we're investing to do is shift left quality. So to do these complex devices that they come out time to market with high quality. And one of the key things Dave that we've invested in is emulation of the environment before you tape out your silicon. So effectively taking the application software, running it on an emulation environment, making sure that works, running your tests before you tape out and that ensures quality silicon. So it's challenging, but the team loves challenges. And that's kind of what we're facing, on one hand architectural challenges, on the other hand a new level of execution challenges. >> So you're compressing the time to final tape out versus maybe traditional techniques. And then, you mentioned architecture, am I right Jas that you're essentially from an architectural standpoint trying to minimize the... 'cause your latency's so important you're trying to minimize the amount of data that you have to move around and actually bringing compute to the data. Is that the right way to think about it? >> Well, I think that there's multiple parts of the problem. One of them is you need to do more data transactions, example data protection with rate algorithms. We need to do millions of transactions per second. And the only way to achieve this with the minimal power impact is to hardware accelerate these. That's one piece of investment. The other investment is, you're absolutely right, Dave. So it's shuffling the data around the data center. So in the data center in some cases you need to have multiple pieces of the puzzle, multiple ingredients processing the same data at the same time and you need advanced methodologies to share the data and avoid moving it all over the data center. So that's another big piece of investment that we're focused on. >> So let's stay on that because I see this as disruptive. You talk about spending $5 billion a year in R&D and talk a little bit more about the disruptive technologies or the supportive technologies that you're introducing specifically to support this vision. >> So let's break it down in a couple big industry problems that our team is focused on. So the first one is I'll take an enterprise workload database. If you want the fastest running database you want to utilize local storage and NVMe based drives and you need to protect that data. And raid is the mechanism of choice to protect your data in local environments. And there what we need to do is really just do the transactions a lot faster. Historically the storage has been a bit of a bottleneck in these types of applications. So example our newest generation product. We're doubling the bandwidth, increasing IOPS by four X, but more importantly we're accelerating raid rebuilds by 50X. And that's an important Dave, if you are using a database in some cases, you limit the size of that database based on how fast you can do those rebuilds. So this 50X acceleration in rebuilds is something we're getting a lot of good feedback on for customers. The last metric we're really focused on is write latency. So how fast can the CPU send the write to the storage connectivity subsystem and committed to drives? And we're improving that by 60X generation over generation. So we're talking fully loaded latency, 10 microseconds. So from an enterprise workload it's about data protection, much, much faster using NVMe drives. That's one big problem. The other one is if you look at Dave YouTube, Facebook, TikTok the amount of user generated content specifically video content that they're producing on an hour by hour basis is mind boggling. And the hyperscale customers are really counting on us to help them scale the connectivity of hundreds of thousands of hard drive to store and access all that data in a very reliable way. So there we're leading the industry in the transition to 24 gig SaaS and multi actuator drives. Third big problem is around AI ML servers. So these are some of the highest performance servers, that they basically need super low latency connectivity between GPGPUs, networking, NVMe drives, CPUs and orchestrate that all together. And the fabric of choice for that is PCIe fabric. So here, we're talking about 115 nanosecond latency in a PCIe fabric, fully nonblocking, very reliable. And here we're helping the industry transition from PCA gen four to PCIe gen five. And the last piece is okay, I've got a AI ML server, I have a storage system with hard drives or a storage server in the enterprise space. All these devices, systems need to be connected to the ethernet backbone. And my team is heavily investing in ethernet mix transitioning to 100 gig, 200 gig, 400 gig and putting capabilities optimized for storage workloads. So those are kind of the four big things that we're focused on at the industry level, from a connectivity perspective, Dave. >> And that makes a lot of sense and really resonates particularly as we have that shift from a CPU centric to a connectivity centric. And the other thing you said, I mean, you're talking about 50X rate rebuild times, a couple of things you know in storage is if you ask the question, what happens when something goes wrong? 'Cause it's all about recovery, you can't lose data. And the other thing you mentioned is write latency, which has always been the problem. Okay, reads, I can read out cache but ultimately you've got to get it to where it's persisted. So some real technical challenges there that you guys are dealing with. >> Absolutely, Dave. And these are the type of problems that gets the engineers excited. Give them really tough technical problems to go solve. >> I wonder if we could take a couple of examples or an example of scaling with a large customer, for instance obviously hyperscalers or take a company like Dell. I mean they're big company, big customer. Take us through that. >> So we use the word scale a lot at Broadcom. We work with some of the industry leaders and data centers and OEMs and scale means different things to them. So example, if I'm working with a hyperscaler that is getting inundated with data and they need half a million storage controllers to store all that data, well their scale problem is, can you deliver? And Dave, you know how much of a hot topic that is these days. So they need a partner that can scale from a delivery perspective. But if I take a company like example Dell that's very focused on storage, from storage servers, their acquisition of EMC. They have a very broad portfolio of data center storage offerings and scale to them from a connected by Broadcom perspective means that you need to have the investment scale to meet their end to end requirements. All the way from a low end storage connectivity solution for booting a server all the way up to a very high end all flash array or high density HDD system. So they want a company a partner that can invest and has a scale to invest to meet their end to end requirements. Second thing is their different products are unique and have different requirements and you need to adapt your collaboration model. So example, some products within Dell portfolio might say, I just want a storage adaptor, plug it in, the operating system will automatically recognize it. I need this turnkey. I want to do minimal investment, is not an area of high differentiation for me. At the other end of the spectrum they may have applications where they want deep integration with their management and our silicon tools so that they can deliver the highest quality, highest performance to their customers. So they need a partner that can scale from an R&D investment perspective from silicon software and hardware perspective but they also need a company that can scale from support and business model perspective and give them the flexibility that their end customers need. So Dell is a great company to work with. We have a long lasting relationship with them and the relationship is very deep in some areas, example server storage, and is also quite broad. They are adopters of the vast majority of our storage connectivity products. >> Well, and I imagine it was. Well I want to talk about the uniqueness of Broadcom again, I'm in awe of the fact that somebody had the vision, you guys, your team obviously your CEO was one of the visionaries of the industry, had the sense to look out and say, okay, we can put these pieces together. So I would imagine a company like Dell, they're able to consolidate their vendor their supplier base and push you for integration and innovation. How unique is the Broadcom model? What's compelling to your customer about that model? >> So I think what's unique from a storage perspective is the breadth of the portfolio and also the scale at which we can invest. So if you look at some of the things we talked about from a scale perspective how data centers throughout the world are getting inundated with data, Dave, they need help. And we need to equip them with cutting edge technology to increase performance, drive down power, improve reliability. So they need partners that in each of the product categories that you partner with them on, we can invest with scale. So that's, I think one of the first things. The second thing is, if you look at this connectivity centric data center you need multiple types of fabric. And whether it be cloud customers or large OEMs they are organizing themselves to be able to look at things holistically. They're no longer product company, they're very data center architecture companies. And so it's good for them to have a partner that can look across product groups across divisions says, okay this is the innovation we need to bring to market. These are the problems we need to go solve and they really appreciate that. And I think the last thing is a flexible business model. Within example, my division, we offer different business models, different engagement and collaboration models with technology. But there's another division that if you want to innovate at the silicon level and build custom silicon for you like many of the hyperscalers or other companies are doing that division is just focus on that. So I feel like Broadcom is unique from a storage perspective it's ability to innovate, breadth of portfolio and the flexibility in the collaboration model to help our customers solve their customers problems. >> So you're saying you can deal with merchant products slash open products or you can do high customization. Where does software differentiation fit into this model? >> So it's actually one of the most important elements. I think a lot of our customers take it for granted that will take care of the silicon will anticipate the requirements and deliver the performance that they need, but from a software, firmware, driver, utilities that is where a lot of differentiation lies. Some cases we'll offer an SDK model where customers can build their entire applications on top of that. In some cases they want to complete turnkey solution where you take technology, integrate it into server and the operating system recognizes it and you have outer box drivers from Broadcom. So we need to offer them that flexibility because their needs are quite broad there. >> So last question, what's the future of the business look like to Jas Tremblay? Give us your point of view on that. >> Well, it's fun. I got to tell you, Dave, we're having a great time. I've got a great team, they're the world's experts on storage connectivity and working with them is a pleasure. And we've got a rich, great set of customers that are giving us cool problems to go solve and we're excited about it. So I think this is really, with the acceleration of all this digital transformation that we're seeing, we're excited, we're having fun. And I think there's a lot of problems to be solved. And we also have a responsibility. I think the ecosystem and the industry is counting on our team to deliver the innovation from a storage connectivity perspective. And I'll tell you, Dave, we're having fun. It's great but we take that responsibility pretty seriously. >> Jas, great stuff. I really appreciate you laying all that out. Very important role you guys are playing. You have a really unique perspective. Thank you. >> Thank you, Dave. >> And thank you for watching. This is Dave Vellante for theCUBE and we'll see you next time.

(upbeat music) >> Hello and welcome to theCUBE. I'm Dave Nicholson, Chief Technology Officer at theCUBE and we are here for a very special Cube Conversation with Andy Brown from Broadcom. Andy, welcome to theCUBE, tell us a little about yourself. >> Well, a little bit about myself, my name is Andy Brown, I'm currently the Senior Director of Software Architecture and Performance Analysis here within the Data Center Solutions Group at Broadcom. I've been doing that for about seven years prior to that, I held various positions within the system architecture, systems engineering, and IC development organization, but ultimately as well as spent some time in our support organization and managing our support team. But ultimately have landed in the architecture organization as well as performance analysis. >> Great, so a lot of what you do is around improving storage performance, tell us more about that. >> So let me give you a brief history of storage from my perspective. As I mentioned, I go back about 30 years in my career and that would've started back in the NCR Microelectronics days. And originally with Parallel SCSI, so that would be, if anyone would remember the the 5380 Controller, which was one of the original Parallel SCSI controllers that existed in built by NCR Microelectronics at the time, I've seen the advent of Parallel SCSI, a stint of fiber channel, ultimately leading into the serialization of the SCSI standard into SaaS, as well as SATA, and then ultimately leading to NVMe protocols and the advent of flash moving from hard drives into a flash based media and as well on that's on the storage side on the host side, moving from parallel interfaces, ISA if everybody could remember that, moving to PCI, PCI Express and that's where we land today. >> So Andy, we are square in the middle of the era of both NVMe and SaaS. What kinds of challenges does that overlap represent? >> Well, I think obviously we've seen SaaS around for a while, it was the conversion from parallel into a serial attached SCSI and that really SaaS brings with it, the ability to connect really a high number of devices and was kind of the original scaling of devices. And really also enabled was one of the things that enabled flash based media, given the the speed and performance that came to the table. Of course NVMe came in as well with the promise of even higher speeds. And as we saw flash media really, really take a strong role in storage. NVMe came around and really was focused on trying to address that, whereas SaaS originated with hard drive technology. NVMe was really born out of how do we most efficiently deal with flash based media, SaaS with its. But SaaS still carries a benefit on scalability and NVMe maybe has, I don't want to say challenges there, but it's definitely was not designed as much to be broadly scale across many, many, say high hundreds or thousands of devices. But definitely addressed some of the performance issues that were coming up as flash media was becoming. So it was increasing the overall storage performance that we could experience if you will. >> Let's talk about host interfaces, PCIe. What's the significance there? >> Really all the storage in the world, all the performance in the world on the storage side, is not of much use to you unless you can really feed it into the beast, if you will, into the CPU and into the the rest of the service subsystem. And that's really where PCI comes into play. PCI originally was in parallel form and then moved to serial with the PCI Express as we know it today, and really has created a pathway to enable not only storage performance but any other adapter or any other networking or other types of technologies to just open up that pathway and feed the processor. And as we've moved through from PCI to PCI Express PCI 2.0 3.0 4.0, and just opening up those pipes has really enabled just a tremendous amount of flow of data into the compute engine, allowing it to be analyzed, sorted used to analyze data, big data, AI type applications. Just those pipes are critical in those types of applications. >> We know we've seen dramatic increases in performance, going from one generation of PCIe to the next. But how does that translate into the worlds of SaaS, SATA and NVMe? >> So from a performance perspective when we look at these different types of media whether it be SATA, SaaS or NVMe, of course, there are performance difference inherent in that media, SATA being probably the lowest performing with NVMe topping out at higher performing although SaaS can perform quite well as a flash based as protocol connected to flash based media. And of course, NVMe from an individual device scaling, from a by one to a by four interface, really that is where NVMe kind of has enabled a bigger pipe directly to the storage media, being able to scale up to by four whereas SaaS can limit it to by one, maybe by two in some cases, although most servers only connect the SaaS device of by one. So from a different perspective then you're really wanting to create a solution or enable the infrastructure to be able to consume that performance at NVMe is going to give you. And I think that is something where our solutions have really in the recent generation shined, at their ability to really now keep up with storage performance and NVMe, as well as provide that connectivity back down into the SaaS and SATA world as well. >> Let's talk about your perspective on RAID today. >> So there've been a lot of views and opinions on RAID over the years, it's been and those have been changing over time. RAID has been around for a very, very long time, probably about as long as again, going back over my 30 year career, it's been around for almost the entire time. Obviously RAID originally was viewed as some thing that was very, very necessary devices fail. They don't last forever, but the data that's on them is very, very important and people care about that. So RAID was brought about knowing that individual devices that are storing that data are going to fail, and really took cold as a primary mechanism of protection. But as time went on and as performance moved up both in the server and both in the media itself if we start talking about flash. RAID really took on, people started to look at traditional server storage RAID, well, maybe a more of a negative connotation. I think that because to be quite honest, it fell behind a little bit. If you look at things like parity RAID 5 and RAID 6, very, very effective efficient means of protecting your data, very storage efficient, but ultimately had some penalty a primarily around right performance, random rights in RAID 5 volumes was not keeping up with what really needed to be there. And I think that really shifted opinions of RAID that, "Hey it's just not, it's not going to keep up and we need to move on to other avenues." And we've seen that, we've seen disaggregated storage and other solutions pop up and protect your data obviously in cloud environments and things like that have shown up and they have been successful, but. >> So one of the drawbacks with RAID is always the performance tax associated with generating parody for parody RAID. What has Broadcom done to address those potential bottlenecks? >> We've really solved the RAID performance issue the right performance issue. We're in our latest generation of controllers we're exceeding a million RAID 5 right IOPS which is enough to satisfy many, many, many applications as a matter of fact, even in virtual environments aggregated solutions, we have multiple applications. And then as well in the rebuild arena, we really have through our architecture, through our hardware automation have been able to move the bar on that to where the rebuild not only the rebuild times have been brought down dramatically in SaaS based or in I'm sorry in flash based solutions. But the performance that you can observe while those rebuilds are going on is almost immeasurable. So in most applications you would almost observe no performance deficiencies during a rebuild operation which is really night and day compared to where things were just few short years ago. >> So the fact that you've been able to, dramatically decrease the time necessary for a RAID rebuild is obviously extremely important. But give us your overall performance philosophy from Broadcom's point of view. >> Over the years we have recognized that performance is obviously a critically important for our products, and the ability to analyze performance from many many angles is critically important. There are literally infinite ways you can look at performance in a storage subsystem. What we have done in our labs and in our solutions through not only hardware scaling in our labs, but also through automation scripts and things like that, have allowed us to collect a substantial amount of data to look at the performance of our solutions from every angle. IOPS, bandwidth application level performance, small topologies, large topologies, just many, many aspects. It still honestly only scratches the surface of all the possible performance points that you could gather, but we have moved them bar dramatically in that regard. And it's something that our customers really demanded of us. Storage technology has gotten more complex, and you have to look at it from a lot different angles, especially on the performance front to make sure that there are no holes there that somebody's going to run into. >> So based on specific customer needs and requests, you look at performance from a variety of different angles. What are some of the trends that you're seeing specifically in storage per performance today and moving into the future? >> Yeah, emerging trends within the storage industry. I think that to look at the emerging trends, you really need to go back and look at where we started. We started in compute where people were you would have basically your server that would be under the desk in a small business operation and individual businesses would have their own set of servers, and the storage would really be localized to those. Obviously the industry has recognized that to some extent, disaggregation of that, we see that obviously in what's happening in cloud, in hyper-converged storage and things like that. Those afford a tremendous amount of flexibility and are obviously great players in the storage world today. But with that flexibility has come some sacrifice and performance and actually quite substantial sacrifice. And what we're observing is almost, it comes back full circle. The need for inbox high performing server storage that is well protected. And with people with confidence that people have confidence that their data is protected and that they can extract the performance that they need for the demanding database applications, that still exists today, and that still operate in the offices around the country and around the world, that really need to protect their data on a local basis in the server. And I think that from a trend perspective that's what we're seeing. We also, from the standpoint of NVMe itself is really started out with, "Hey, we'll just software rate that. We'll just wrap software around that, we can protect the data." We had so many customers come back to us saying, you know what? We really need hardware RAID on NVMe. And when they came to us, we were ready. We had a solution ready to go, and we're able to provide that, and now we're seeing ongoing on demand. We are complimentary to other storage solutions out there. Server storage is not going to necessarily rule a world but it is surely has a place in the broader storage spectrum. And we think we have the right solution for that. >> Speaking of servers and server-based storage. Why would, for example, a Dell customer care about the Broadcom components in that Dell server. >> So let's say you're configuring a Dell server and you're going, why does hardware where RAID matter? What's important about that? Well, I think when you look at today's hardware RAID, first of all, you're going to see a dramatically better performance. You're going to see dramatically better performance it's going to enable you to put RAID 5 volumes a very effective and efficient mechanism for protecting your data, a storage efficient mechanism. You're going to use RAID 5 volumes where you weren't able to do that before, because when you're in the millions of IOPS range you really can satisfy a lot of application needs out there. And then you're going to also going to have rebuilt times that are lightning fast. Your performance is not going to degrade, when you're running those application, especially database applications, but not only database, but streaming applications, bandwidth to protected RAID volumes is almost imperceptively different from just raw bandwidth to the media. So the RAID configurations in today's Dell servers really afford you the opportunity to make use of that storage where you may not have already written it off as well RAID just doesn't, is not going to get me there. Quite frankly, into this in the storage servers that Dell is providing with RAID technology, there are huge windows open in what you can do today with applications. >> Well, all of this is obviously good news for Dell and Dell customers, thanks again, Andy for joining us, for this Cube Conversation, I'm Dave Nicholson for theCUBE. (upbeat music)

(upbeat music) >> Hello everyone, and welcome to this CUBE conversation where we're going to go deep into system performance. We're here with an expert. Kim Leyenaar is the Principal Performance Architect at Broadcom. Kim. Great to see you. Thanks so much for coming on. >> Thanks so much too. >> So you have a deep background in performance, performance assessment, benchmarking, modeling. Tell us a little bit about your background, your role. >> Thanks. So I've been a storage performance engineer and architect for about 22 years. And I'm specifically been for abroad with Broadcom for I think next month is going to be my 14 year mark. So what I do there is initially I built and I manage their international performance team, but about six years ago I moved back into architecture, and what my roles right now are is I generate performance projections for all of our next generation products. And then I also work on marketing material and I interface with a lot of the customers and debugging customer issues, and looking at how our customers are actually using our storage. >> Great. Now we have a graphic that we want to share. It talks to how storage has evolved over the past decade. So my question is what changes have you seen in storage and how has that impacted the way you approach benchmarking. In this graphic we got sort of big four items that impact performance, memory processor, IO pathways, and the storage media itself, but walk us through this data if you would. >> Sure. So what I put together is a little bit of what we've seen over the past 15 to 20 years. So I've been doing this for about 22 years and kind of going back and focusing a little bit on the storage, we looked back at hard disk, they ruled for. And nearly they had almost 50 years of ruling. And our first hard drive that came out back in the 1950s was only capable of five megabytes in capacity. and one and a half iOS per second. It had almost a full second in terms of seat time. So we've come a long way since then. But when I first came on, we were looking at Ultra 320 SCSI. And one of the biggest memories that I have of that was my office is located close to our tech support. And I could hear the first question was always, what's your termination like? And so we had some challenges with SCSI, and then we moved on into SAS and data protocols. And we continued to move on. But right now, back in the early 2000s when I came on board, the best drives really could do maybe 400 iOS per second. Maybe two 250 megabytes per second, with millisecond response times. And so when I was benchmarking way back when it was always like, well, IOPS are IOPS. We were always faster than what the drives to do. And that was just how it was. The drives were always the bottleneck in the system. And so things started changing though by the early 2000s, mid 2000s. We started seeing different technologies come out. We started seeing that virtualization and multi-tenant infrastructures becoming really popular. And then we had cloud computing that was well on the horizon. And so at this point, we're like, well, wait a minute, we really can't make processors that much faster. And so everybody got excited to include (indistinct) and the home came out but, they had two cores per processor and four cores per processor. And so we saw a little time period where actually the processing capability kind of pulled ahead of everybody else. And memory was falling behind. We had good old DVR, 2, 6, 67. It was new with the time, but we only had maybe one or two memory channels per processor. And then in 2007 we saw disk capacity hit one terabyte. And we started seeing a little bit of an imbalance because we were seeing these drives are getting massive, but their performance per drive was not really kind of keeping up. So now we see a revolution around 2010. And my co-worker and I at the time, we have these little USB discs, if you recall, we would put them in. They were so fast. We were joking at the time. "Hey, you know what, wonder if we could make a raid array out of these little USB disks?" They were just so fast. The idea was actually kind of crazy until we started seeing it actually happen. So in 2010 SSD started revolutionizing storage. And the first SSDs that we really worked with these plaint LS-300 and they were amazing because they were so over-provisioned that they had almost the same reader, right performance. But to go from a drive that could do maybe 400 IOS per second to a drive like 40,000 plus iOS per second, really changed our thought process about how our storage controller could actually try and keep up with the rest of the system. So we started falling behind. That was a big challenge for us. And then in 2014, NVMe came around as well. So now we've got these drives, they're 30 terabytes. They can do one and a half million iOS per second, and over 6,000 megabytes per second. But they were expensive. So people start relegating SSDs more towards tiered storage or cash. And as the prices of these drives kind of came down, they became a lot more mainstream. And then the memory channels started picking up. And they started doubling every few years. And we're looking now at DVR 5 4800. And now we're looking at cores that used to go from two to four cores per processor up to 48 with some of the latest different processes that are out there. So our ability to consume the computing and the storage resources, it's astounding, you know, it's like that whole saying, 'build it and they will come.' Because I'm always amazed, I'm like, how are we going to possibly utilize all this memory bandwidth? How are we going to utilize all these cores? But we do. And the trick to this is having just a balanced infrastructure. It's really critical. Because if you have a performance mismatch between your server and your storage, you really lose a lot of productivity and it does impact your revenue. >> So that's such a key point. Pardon, begin that slide up again with the four points. And that last point that you made Kim about balance. And so here you have these, electronic speeds with memory and IO, and then you've got the spinning disc, this mechanical disc. You mentioned that SSD kind of changed the game, but it used to be, when I looked at benchmarks, it was always the D stage bandwidth of the cash out to the spinning disc was always the bottleneck. And, you go back to the days of you it's symmetrics, right? The huge backend disk bandwidth was how they dealt with that. But, and then you had things the oxymoron of the day was high spin speed disks of a high performance disk. Compared to memories. And, so the next chart that we have is show some really amazing performance increases over the years. And so you see these bars on the left-hand side, it looks at historical performance for 4k random IOPS. And on the right-hand side, it's the storage controller performance for sequential bandwidth from 2008 to 2022. That's 22 is that yellow line. It's astounding the increases. I wonder if you could tell us what we're looking at here, when did SSD come in and how did that affect your thinking? (laughs) >> So I remember back in 2007, we were kind of on the precipice of SSDs. We saw it, the writing was on the wall. We had our first three gig SAS and SATA capable HPAs that had come out. And it was a shock because we were like, wow, we're going to really quickly become the bottleneck once this becomes more mainstream. And you're so right though about people work in, building these massive hard drive based back ends in order to handle kind of that tiered architecture that we were seeing that back in the early 2010s kind of when the pricing was just so sky high. And I remember looking at our SAS controllers, our very first one, and that was when I first came in at 2007. We had just launched our first SAS controller. We're so proud of ourselves. And I started going how many IOPS can this thing, even handled? We couldn't even attach enough drives to figure it out. So what we would do is we'd do these little tricks where we would do a five 12 byte read, and we would do it on a 4k boundary, so that it was actually reading sequentially from the disc, but we were handling these discrete IOPS. So we were like, oh, we can do around 35,000. Well, that's just not going to hit it anymore. Bandwidth wise we were doing great. Really our limitation and our bottleneck on bandwidth was always either the host or the backend. So, our controllers are there basically, there were three bottlenecks for our storage controllers. The first one is the bottleneck from the host to the controller. So that is typically a PCIe connection. And then there's another bottleneck on the controller to the disc. And that's really the number of ports that we have. And then the third one is the discs themselves. So in typical storage, that's what we look at. And we say, well, how do we improve this? So some of these are just kind of evolutionary, such as PCIE generations. And we're going to talk a little bit about that, but some of them are really revolutionary, and those are some of the things that we've been doing over the last five or six years to try and make sure that we are no longer the bottleneck. And we can enable these really, really fast drives. >> So can I ask a question? I'm sorry to interrupted but on these blue bars here. So these all spinning disks, I presume, out years they're not. Like when did flash come in to these blue bars? is that..you said 27 you started looking at it, but on these benchmarks, is it all spinning disc? Is it all flash? How should we interpret that? >> No, no. Initially they were actually all hard drives. And the way that we would identify, the max iOS would be by doing very small sequential reads to these hard drives. We just didn't have SSDs at that point. And then somewhere around 2010 is where we.. it was very early in that chart, we were able to start incorporating SSD technology into our benchmarking. And so what you're looking at here is really the max that our controller is capable of. So we would throw as many drives as we could and do what we needed to do in order to just make sure our controller was the bottleneck and what can we expose. >> So the drive then when SSD came in was no longer the bottleneck. So you guys had to sort of invent and rethink sort of how, what your innovation and your technology, because, I mean, these are astounding increases in performance. I mean, I think in the left-hand side, we've built this out pad, you got 170 X increase for the 4k random IOPS, and you've got a 20 X increase for the sequential bandwidth. How were you able to achieve that level of performance over time? >> Well, in terms of the sequential bandwidth, really those come naturally by increases in the PCIe or the SAS generation. So we just make sure we stay out of the way, and we enable that bandwidth. But the IOPS that's where it got really, really tricky. So we had to start thinking about different things. So, first of all, we started optimizing all of our pathways, all of our IO management, we increased the processing capabilities on our IO controllers. We added more on-chip memory. We started putting in IO accelerators, these hardware accelerators. We put in SAS poor kind of enhancements. We even went and improved our driver to make sure that our driver was as thin as possible. So we can make sure that we can enable all the IOPS on systems. But a big thing happening a few couple of generations ago was we started introducing something called tri capable controllers, which means that you could attach NVMe. You could attach SAS or you could attach SATA. So you could have this really amazing deployment of storage infrastructure based around your customized needs and your cost requirements by using one controller. >> Yeah. So anybody who's ever been to a trade show where they were displaying a glass case with a Winchester disc drive, for example, you see it's spinning and its actuators is moving, wow, that's so fast. Well, no. That's like a tourist slower. It's like a snail compared to the system's speed. So it's, in a way life was easy back in those days, because when you did a right to a disk, you had plenty of time to do stuff, right. And now it's changed. And so I want to talk about Gen3 versus Gen4, and how all this relates to what's new in Gen4 and the impacts of PCIe here, you have a chart here that you've shared with us that talks to that. And I wonder if you could elaborate on that, Kim. >> Sure. But first, you said something that kind of hit my funny bone there. And I remember I made a visit once about 15 or 20 years ago to IBM. And this gentleman actually had one of those old ones in his office and he referred to them as disk files. And he never until the day he retired, he'd never stopped calling them disc files. And it's kind of funny to be a part of that history. >> Yeah. DASD. They used to call it. (both laughing) >> SD, DASD. I used to get all kinds of, you know, you don't know what it was like back then, but yeah. But now nowadays we've got it quite easily enabled because back then, we had, SD DASD and all that. And then, ATA and then SCSI, well now we've got PCIe. And what's fabulous about PCIe is that it just has the generations are already planned out. It's incredible. You know, we're looking at right now, Gen3 moving to Gen4, and that's a lot about what we're going to be talking about. And that's what we're trying to test out. What is Gen4 PCIe when to bias? And it really is. It's fantastic. And PCIe came around about 18 years ago and Broadcom is, and we do participate and contribute to the PCIe SIG, which is, who develops the standards for PCIe, but the host in both our host interface in our NVMe desk and utilize the standards. So this is really, really a big deal, really critical for us. But if you take a look here, you can see that in terms of the capabilities of it, it's really is buying us a lot. So most of our drives right now NVMe drives tend to be by four. And a lot of people will connect them. And what that means is four lanes of NVMe and a lot of people that will connect them either at by one or by two kind of depending on what their storage infrastructure will allow. But the majority of them you could buy, or there are so, as you can see right now, we've gone from eight gig transfers per second to 16 gig of transfers per second. What that means is for a by four, we're going from one drive being able to do 4,000 to do an almost 8,000 megabytes per second. And in terms of those 4k IOPS that really evade us, they were really really tough sometimes to squeeze out of these drives, but now we're got 1 million, all we have to 2 million, it's just, it's insane. You know, just the increase in performance. And there's a lot of other standards that are going to be sitting on top of PCIe. So it's not going away anytime soon. We've got to open standards like CXL and things like that, but we also have graphics cards. You've got all of your hosts connections, they're also sitting on PCIe. So it's fantastic. It's backwards, it's orbits compatible, and it really is going to be our future. >> So this is all well and good. And I think I really believe that a lot of times in our industry, the challenges in the plumbing are underappreciated. But let's make it real for the audience because we have all these new workloads coming out, AI, heavily data oriented. So I want to get your thoughts on what types of workloads are going to benefit from Gen4 performance increases. In other words, what does it mean for application performance? You shared a chart that lists some of the key workloads, and I wonder if we could go through those. >> Yeah, yeah. I could have a large list of different workloads that are able to consume large amounts of data, whether or not it's in small or large kind of bytes of data. But as you know right now, and I said earlier, our ability to consume these compute and storage resources is amazing. So you build it and we'll use it. And the world's data we're expected to grow 61% to 175 zettabytes by the year 2025, according to IDC. So that's just a lot of data to manage. It's a lot of data to have, and it's something that's sitting around, but to be useful, you have to actually be able to access it. And that's kind of where we come in. So who is accessing it? What kind of applications? I spend a lot of time trying to understand that. And recently I attended a virtual conference SDC and what I like to do when I attend these conferences is to try to figure out what the buzz words are. What's everybody talking about? Because every year it's a little bit different, but this year was edge, edge everything. And so I kind of put edge on there first in, even you can ask anybody what's edge computing and it's going to mean a lot of different things, but basically it's all the computing outside of the cloud. That's happening typically at the edge of the network. So it tends to encompass a lot of real time processing on those instant data. So in the data is usually coming from either users or different sensors. It's that last mile. It's where we kind of put a lot of our content caching. And, I uncovered some interesting stuff when I was attending this virtual conference and they say only about 25% of all the usable data actually even reach the data center. The rest is ephemeral and it's localized, locally and in real time. So what it does is in the goal of edge computing is to try and reduce the bandwidth costs for these kinds of IOT devices that go over a long distance. But the reality is the growth of real-time applications that require these kinds of local processing are going to drive this technology forward over the coming years. So Dave, your toaster and your dishwasher they're, IOT edge devices probably in the next year, if they're not already. So edge is a really big one and consumes a lot of the data. >> The buzzword does your now is met the metaverse, it's almost like the movie, the matrix is going to come in real time. But the fact is it's all this data, a lot of videos, some of the ones that I would call out here, you mentioned facial recognition, real-time analytics. A lot of the edge is going to be real-time inferencing, applying AI. And these are just a massive, massive data sets that you again, you and of course your customers are enabling. >> When we first came out with our very first Gen3 product, our marketing team actually asked me, "Hey, how can we show users how they can consume this?" So I actually set up a head to environment. I decided I'm going to learn how to do this. I set up this massive environment with Hadoop, and at the time they called big data, the 3V's, I don't know if you remember these big 3Vs, the volume, velocity and variety. Well Dave, did you know, there are now 10 Vs? So besides those three, we got velocity, we got valued, we got variability, validity, vulnerability, volatility, visualization. So I'm thinking we need just to add another beat of that. >> Yeah. (both laughing) Well, that's interesting. You mentioned that, and that sort of came out of the big data world, a dupe world, which was very centralized. You're seeing the cloud is expanding, the world's getting, you know, data is by its very nature decentralized. And so you've got to have the ability to do an analysis in place. A lot of the edge analytics are going to be done in real time. Yes, sure. Some of it's going to go back in the cloud for detailed modeling, but we are the next decade Kim, ain't going to be like the last I often say. (laughing) I'll give you the last word. I mean, how do you see this sort of evolving, who's going to be adopting this stuff. Give us a sort of a timeframe for this kind of rollout in your world. >> In terms of the timeframe. I mean really nobody knows, but we feel like Gen5, that it's coming out next year. It may not be a full rollout, but we're going to start seeing Gen5 devices and Gen5 infrastructure is being built out over the next year. And then follow very, very, very quickly by Gen6. And so what we're seeing though is, we're starting to see these graphics processors, These GPU's, and I'm coming out as well, that are going to be connecting, using PCIe interfaces as well. So being able to access lots and lots and lots of data locally is going to be a really, really big deal and order because worldwide, all of our companies they're using business analytics. Data is money. And the person that actually can improve their operational efficiency, bolster those sales and increase your customer satisfaction. Those are the companies that are going on to win. And those are the companies that are going to be able to effectively store, retrieve and analyze all the data that they're collecting over the years. And that requires an abundance of data. >> Data is money and it's interesting. It kind of all goes back to when Steve jobs decided to put flash inside of an iPhone and the industry exploded, consumer economics kicked in 5G now edge AI, a lot of the things you talked about, GPU's the neural processing unit. It's all going to be coming together in this decade. Very exciting. Kim, thanks so much for sharing this data and your perspectives. I'd love to have you back when you got some new perspectives, new benchmark data. Let's do that. Okay. >> I look forward to it. Thanks so much. >> You're very welcome. And thank you for watching this CUBE conversation. This is Dave Vellante and we'll see you next time. (upbeat music)

(bright upbeat music) >> Welcome back. Lisa Martin here talking with Laureen Knudsen, a CUBE alumni. She's the Chief Transformation Officer at Broadcom and a founding member of the BizOps Coalition. Laureen, I'm excited to talk to you about an interesting topic today. Welcome back to the program. >> Thank you so much. Glad to be here. >> So we're going to be, yeah, we're going to be talking about the pros and cons of adding a Chief Digital Officer. You say, there may be some friction there, but it's going to be temporary as the benefits will be long lasting. So let's dive right in. Talk to me about what the role of a Chief Digital Officer is. Is this something that a CIO can take on? >> In some organizations, I think the CIO is taking on this role. And it's primarily focusing on what we're calling the digitization of the organization. So it's across more than just IT though. So it's looking at what kind of digital marketing should you be doing? What are your competitors doing? How can you make the most bang for your buck essentially across your entire organization? So it also includes parts that generally haven't been included in digital transformations, like your legal team or your finance team and the interactions with them. Can your contracts be digitized? Can they be made more efficient and more automated, right? So it's looking at the entire organization both internally and externally and looking at the strategy for how do you accomplish that and how do you truly make your organization as effective as it can be. >> Is this person almost like a bridge between the different lines of business and IT to get that external, internal focus? >> Yes, yeah, many people in IT don't have that business knowledge. That's a really good point. And so this person will need to have not only business knowledge but technical knowledge so they can essentially translate, right, the verbiage that is used in the different organizations and the jargon that's used to make it, to make the understanding between the two of what's needed more smooth, you know, the communication more smooth within the organization. Also focusing on customer value and making sure that, that both sides are saying the same, you know, when they use the same words, they're saying the same things. So doing that translation in that organization, across the entire company. >> Looking at it from the holistic perspective, you know, I know that the BizOps Coalition survey also showed that something that we hear that digital transformation isn't just about the technology. It's got to be all of the factors coming together aligned on business outcomes, aligned on what's the impact and the value to the customer. How is the Chief Digital Officer role going to facilitate that, not just understanding, but putting in practice that digital transformation is not just about technology? >> Well, and again, 95% of companies are confirming that, that right now they're focusing much more on business outcomes than just on technology. And so, there really is that need to, you know, what does that mean, right? When you're focusing on business outcomes, it often includes a lot of technology, but it's, you know, there's a different path to take to make sure that you're focusing on your customer outcomes. There's a lot of organizations that are looking at their apps and realizing their customers find the most value when they never have to use them. So how do you accomplish that, right? That's not adding new features in, that's not doing something new for the customer other than making it, making sure everything runs so smoothly that they never have to access your app. You know, we're running into that with a lot of business organizations like insurance companies or banking, phone, you know, telco companies, things like that where people really don't want to use the products you're creating for them if they don't have to. >> Right, adoption is always something that we talk about that can be a KPI but also a challenge. One of the things that I noticed that information that, that Broadcom provided was that Gartner says, in the next 12 months, 67% of organizations are going to be looking at hiring a Chief Digital Officer. Let's have you talk us through what are some of the forcing functions behind that? Obviously the last year has been quite, filled with quite a bit of uncertainty but we look back a couple of decades, there wasn't talk of a Chief Digital Officer. So, why this, why is there such a big uptick in the need for this role? >> Well, it's interesting 'cause Gartner originally talked about the Chief Digital Officer in about 2010 to 2012 timeframe where they were talking about the need for it. And it was a lot of, I think fast moving companies and the companies that really have made a lot of advancements in their effectiveness and their customer centricity have really grabbed onto this concept whether they've called it a Chief Digital Officer or not, but in the last year, it's forced everyone to have a digital footprint in the market. If you'll notice even your local restaurants that are family owned now have some sort of way to order their food digitally, right? So we're digitizing the entire thing and COVID is really, required every company to look at much more how they can do things electronically, any type of, you know, digitization whether it's like I've said before the marketing, or even how do you handle all of your contracts when there's no in-person signature and no, you know, fax machines to send things back and forth, right? It's all about making sure that all of that's secure and protected. So it's going across the entire organization. And that's really creating that need for somebody to be able to look at how your company can do all of those different things. Because quite frankly, the CIO already has a day job, right? Your Chief Marketing Officer already has a day job. So trying to look at how to be really innovative in these areas creates a gap, right? And people aren't finding that extra time to be able to do that and to look at how to be really streamlining their organizations and taking that innovation in with both internal and external viewpoints. >> Well, it'd be, imagine you mentioned, you know, the CIO, the CMO, the CFO having day jobs, but also one of the things it sounds to me like is important for this CDO role is to have objectivity. To be able to rise above all the different functions, the different technology stocks and probably silos that are there and really look holistically across the organization. So talk to me about some of the skills that are really required from the Chief Digital Officer. Is this someone that needs to have both an IT background and a business background, does it matter? >> I think as long as they have the knowledge of either side, that where they came from, isn't going to matter but you're going to, the problem is going to be finding the people with those dual skill sets, right? Because you're going to need somebody that can understand your business and your technology side to marry the two together. But they're also going to need to understand all the intricacies of the legal aspects that need to go into creating your products or the financial aspects of tracking what happens with your products. So they're really going to need to be not only very well educated and have a lot of experience, but the other thing they're going to need is that emotional empathy and that ability to work with everybody in the organization. Essentially if they do their job right, they'll be coming in and working with every other Vice President or chief in your organization. So there'll be helping to influence all of those people. And that can create a lot of conflict at first because you're having somebody else come in to give the CIO insights into how they can innovate technologically or to give the Chief Marketing Officer information on new ways that they can do their jobs, that they can digitize the marketing to be more effective and the right frame of mind to be able to do that. You know, hiring is going to be another place where these people will have a large imprint because they're going to need the knowledge to be able to interview all across the board for people that can help them get these new innovations into place. For example, if marketing needs to expand into more of a digital footprint to actually get the, the imprints that they need, right? How do you interview for that, when as a marketing leader, you've never run a digital part, a digital organization before. So it's really having the ability to partner with every other department in the organization and work with them, which, you know, to your point that can cause some conflicts to start off with but in the long run, it'll, it should be well worth it. >> Well, it sounds like that friction is probably unavoidable in the beginning as this person really works to understand all of the inner machinations of the organization and really identify what's best for the overall business. You mentioned empathy. And I think that's something that we've heard a lot about in the last year as leaders really needing to adopt that. And it sounds like this role for it to be such a catalyst of IT and business alignment, as it sounds like it really can be, that empathetic gene really needs to be turned on pretty high, I think. >> A 100%, right? They need to be able to be really understanding of the organization and the other people that they're working with, that those people do have a great bit of knowledge about the company that they're joining, right, generally and that they'll understand their jobs on a day-to-day basis. But the innovation parts, right, is where the Chief Digital Officer will come in. And if the Chief Digital Officer does this well, they can actually have a really big impact on the corporate culture as well which is a huge area that people are focusing on these days especially as every employee is remote. So it's a big job and a big ask and it's going to be really important for companies to hire the person with the best fit for their organization in this new role. >> You mentioned culture and that's something that is imperative but digital transformations won't be successful without the right cultural transformation. But that's easier said than done especially for organizations that have been around a while. And they're so used to the way they've done business for decades that it's hard to change that mindset, but it sounds like the Chief Digital Officer role should be one that is an influencer of that cultural change. How do you see them being able to do that within a, you know, stodgy, legacy institution? What are some of the things that they would be able to unlock? >> They should be able to re-energize portions of the company, right? If you're bringing in innovative ideas into a company that has had some difficulty hiring, right? There's a lot of companies that before the pandemic hit, were only starting to look at agile practices and things because quite frankly they couldn't hire anyone out of college to work there and they were afraid most of their workforce would retire out. So they're trying to get those people that want to be innovative, the high, the people that graduated top of their class. You're going to need the organization to change. And this is a perfect example of somebody that can come in and be a catalyst for all of that. So if they're coming up with new innovative ideas, if your marketing department wasn't transforming into a highly digital marketing department, they can come help invigorate that, right? And come up with a plan to get people in but also to train the people that are there that do want to learn these new skills in order bring the whole organization along with them. And I think they can have a huge impact if they, and get those innovative culture cycles changing. >> I'm curious if you think that, you know, given the last year and the amount of uncertainty that the pandemic has brought to the market, to the economy, now some of the challenges that leaders say, we're still going to have similar challenges in 2021. We still have a good percentage of our workforce remote. Is the role that the Chief Digital Officer can play, is that potentially going to help companies, really, is it going to help make a difference between those companies that really, not just survive this time but thrive like the winners versus the losers of tomorrow? >> I think it can, right? And a lot of this is going to be how the people that hire in the Chief Digital Officer and how much that team is willing to work with them. One of the things that we notice is the companies that do advance their culture a lot and advance in their customer centricity, the leadership level of the organization acts as a team as much as they expect to the frontline crews to act as teams. So you've got to be working together. And that goes all the way through, right? Your HR departments can't be incenting one group to work against another. You can't incent two people to have a goal, you know, to reach a goal in a different way and incent them differently so that they end up working against each other, right? This has to start being a real collaborative effort and it'll end up impacting the entire organization. But it's those companies that start looking at their leadership organization as a team, where they're all playing to make the same goals, to make their customers the most successful they can be. That's when you really start getting those changes and you really see a Chief Digital Officer having an impact versus those organizations where, you know, they'll be on the job for two to three years and it'll just go away because they've, you know, fought against themselves and not form that team culture. >> The impact is, can be tremendous from what I'm hearing. When we think about digital transformation, you know, people, processes, technology, that culture that's so important, we're also talking about that in the context of how do organizations use all their data and make the most sense of it. As more data sources become available, data's coming in faster, how does the Chief Digital Officer align with all of the data folks within an organization so that they can all have access to the right information to make data-driven decisions that are really for internal and externally looking benefits? >> Right, they can help make sense of the data that the company is collecting. One of the main things we're hearing right now is a lot of organizations are collecting a ton of data and they're either, you know, having some organization that creates metrics out of it. And that group just doesn't know really what the business does. They're relatively new to the business as a lot of data organizations are. So they go grab standard metrics and just provide, you know, shove as many metrics out. That's their output point, right? Where they get brownie points for every metric they create. And so we're hearing from a lot of leaders that, that they're getting literally hundreds of metrics a month and they have no idea what they're supposed to be doing with them or what this data is supposed to be showing them. And that's really of no benefit to anybody, right? It's a waste of time all through the organization. So the Chief Digital Officer, again, will be looking at what are the right business metrics to be tracking for that business and be working with those data officers to get the right innovation in so that you can see how well you're transforming, how well your company is actually doing, how much your customers actually do like what you're creating and the impact of the changes that you're making. So another thing we're being asked a lot of is, you know, I'm funding things and I'm being told they'll provide my customers value but when they get released I have no idea if they are, right? And the Chief Data Officer will help, be putting all the metrics that tie that in and showing telemetry gets built in. So that they've got the metrics that you need to truly run your business well. And so again, that'll be another part of the organization that the Chief Digital Officer would be working with. Along with the CIO, they'll be working with the data organizations as well. >> Well, there's so much opportunity that the chief Digital Officer role can deliver and unlock value in an organization as you've talked about. It'll be interesting, Laureen to see what happens in the next 12 months. Do we see what Gartner's predicting, 67% of companies are going to be adopting this role. I'm curious to see what the BizOps Coalition finds in the next year or so but thank you for sharing this insight. And this definitely sounds like a role where every day will be interesting, unique and not boring. (gentle upbeat music)

>>From around the globe. It's the cube with digital coverage of an AI ops virtual forum brought to you by Broadcom. >>Welcome to this preview of Broadcom's AI ops virtual forum on your host, Lisa Martin. And joining me to give you a sneak peek of this event. That's on December 3rd is streaming of Boston Rajagopal or Raj, the head of AI ops at Broadcom. Raj. This has meant it's coming up in a couple of weeks. Excited, >>Good to be here. I am excited, Lisa, uh, you know, um, customers are poised for growth, uh, in 2021. And, uh, they, uh, we believe they all, they will also come out of the pandemic to grow their business and serve, uh, their customers. Uh, you know, well, they have two key challenges. How do you grow at the same time, operate with efficiency, right? These two challenges are decision-makers are struggling with every day at scale. That is why they do digital transformation at scale. And our key influencers like it, operators and SRE personas are helping our decision-makers in our customers to drive the efficiency. They are trying to, uh, focus on converting outputs to outcomes. That's what AI ops is all about. And you're going to hear from us. >>Yeah. And we've got a panel of experts here. Rich lane, senior research analyst for Forrester is going to be joining us as well as nastier, the global product management at Verizon. And of course, Raj, you're going to be hearing some of the latest trends for AI ops. Why now is the time Raj, what are some of the key takeaways that you think those key influencers and those decision makers are going to walk away from this event? >>So the, you know, our decision makers and key influencers have a single question in mind when they deal with enterprise large enterprise scenarios, the questions that they get asked by their skill level execs are, are you ready? Are you ready? When remote work is the norm, are you ready when you have to optimize your investments? And are you ready when you have to accelerate your transformation at scale to operate as a digital enterprise, all of this requires them to think and act differently from people process technology. And how do you bring all of this together? Under the ages of what we call AI ops is what they're going to learn about. >>Another thing too, is you're going to hear the latest industry trends on AI ops from Raj and the panel of experts that mentioned a minute ago, how organizations like yours are finding value from AI ops and something that Raj talked about a minute ago is understanding why now is the time to be ready for AI ops. So Raj and I look forward to you joining us along with our other panelists, December 3rd, register for the Broadcom AI ops virtual forum today.

>>from around the globe. It's the Cube with digital coverage of AI ops Virtual Forum Brought to you by Broadcom Welcome back to the AI Ops Virtual Forum. Lisa Martin here with Srinivasan Rajagopal, the head of products and strategy at Broadcom Raj Welcome. >>Good to be here, Lisa. >>I'm excited for our conversation, so I wanted to dive right into a term that we hear all the time. Operational excellence, right? We hear it everywhere in marketing, etcetera. But why is it so important to organizations as they head into 2021 tell us how ai ops as a platform can help? >>Yeah. Thank you. First off, I wanna I wanna welcome our viewers back and I'm very excited Toe share more info on this topic. You know, here's what we believe. As we work with large organizations, we see all our organizations are poised toe get out off the pandemic and look for growth for their own business and helping customers get through this tough time. So fiscal year 2021 we believe, is going to be a combination off, you know, resiliency and agility at the at the same time. So operational excellence is critical because the business has become mawr digital, right? There are gonna be three things that are gonna be more sticky. You know, remote work is gonna be more sticky. Um, cost savings and efficiency is going to be an imperative for organizations. And the continued acceleration of digital transformation off enterprises at scale is going to be in reality. So when you put all these three things together as a team, that is, you know, that's working behind the scenes toe help the businesses succeed. Operational excellence is going to be make or break for organizations. >>Russia with that said, if we kind of strip it down to the key capabilities, what are those key capabilities that companies need to be looking for in an AI ops solution? >>Yeah, you know. So first foremost AI ops means many things to many, many folks. So let's take a moment to simply define it. The way we defined AI ops is it's a system off intelligence human augmented system that brings together full visibility across app, infra and network elements that brings together despite of data sources on provides actionable intelligence and uniquely offers intelligent automation. Now the technology many folks draw is the self driving car, right? I mean, we are in the world of Tesla's, but, you know, but self driving data center is is too far away, right? Autonomous systems are still far away. However, you know, application off the I M l techniques toe help deal with volume velocity, veracity of information. Eyes is critical. So that's how we look at AI ops and some of the key capabilities that we that we that we work with our customers to help them around 48 years. Right? First one is eyes and years. What we call full stack, observe ability. If you do not know what is happening in your systems, you know that that serve up your business services, it's gonna be pretty hard to do anything in terms of responsiveness, right? So from stack of their ability, the second piece is what we call actionable insights. So when you have disparaged data sources, tool sprawls, data coming at you from, you know from database systems, I T systems, customer management systems, ticketing systems, how do you find the needle from the haystack? And how do you respond rapidly from a myriad off problems? A sea off read The third area is what we call intelligent automation. Well, Identifying the problem toe Act on is important and then acting on. Automating that and creating a recommendation system where you know you could be proactive about that is even more important. And finally, all of this focuses on efficiency. What about effectiveness? Effectiveness comes when you create a feedback loop when what happens in production is related to your support systems and your developers so that they can respond rapidly. So we call that continuous feedback. So these are the four key capabilities that you know you should look for in an AI ops system. And that's what we offer us. >>Alright, Russia. There's four key capabilities that businesses need to be looking for. I'm wondering how those help to align business and i t. It's again like operational excellence. It's something that we talk about a lot is the alignment of business and I t a lot more challenging. Is your something done right? But I want you to explain how can a iob help with that alignment and align? I t outputs to business outcomes. >>So you know, one of the things I'm going to say something that this, that is that is simple. But it's harder. Alignment is not on systems. Alignment is with people, right? So when people align when organizations aligned, when cultures align, dramatic things can happen. So in the context off AI ops, we see when when saris aligned with the develops engineers and information architects. And, uh, you know, I t operators, you know, they enable organizations to reduce the gap between intent and outcome or output an outcome that said, you know, these personas need mechanisms toe help them better align, right, help them Better visual. I see the you know what we call single source of truth, right? So there are four key things that I wanna call out when we work with large enterprises. We find that customer journey alignment with the you know what we call I T systems is critical. So how do you understand your business imperatives and your customer journey goals? Whether it is card toe purchase or whether it is, you know, Bill shock scenarios and swan alignment on customer journey to your I T systems is one area that you can reduce the gap. The second area is how do you create a scenario where your teams can find problems before your customers do right out. It's scenarios and so on. So that's the second area off alignment. The third area off alignment is how can you measure business impact driven services right? There are several services that an organization off course as the 19 system. Some services are more critical to the business. Well, then, others and thes change in a dynamic environment. So how do you How do you understand that? How do you measure that? And how? How do you find the gaps there? So that that's the 3rd 80 off alignment that we that we help. And last but not least, there are. There are things like NPS scores and others that that help us understand alignment. But those are more long term. But in the in the context off, you know, operating digitally. You want to use customer experience and, you know single business outcome as as a key alignment factor, and then work with your systems of engagement and systems of interaction, along with your key personas to create that alignment. It's a people process technology challenge, actually. >>So where is one of the things that you said there is that it's imperative for the business toe. Find a problem before a customer does. And you talked about outages there. That's always a goal for businesses, right to prevent those outages. How can Ai ops help with that? >>Yeah, so, you know, out they just talk, you know, go to resiliency off a system, right? And they also goto have, you know, agility off the same system. You know, if you are a customer and if you're ripping up your mobile happened, it takes more than you know, three milliseconds. You know, you're probably losing that customer, right? So I would just mean different things, you know? And there's an interesting website called don't detector dot com that actually tracks all the outages of publicly available services, whether it's your bank or your, you know, telecom service or mobile service and so on and so forth. In fact, the key question around outages for from from you know, executives are the question of Are you ready? Right? Are you ready to respond to the needs off your customers and your business? Are you ready toe rapidly to solve an issue that is impacting customer experience and therefore satisfaction. Are you creating a digital trust system where customers can be, You know, you know, customers can feel that their information is secure when they transact with you. All of these getting toe the notion of resiliency and outages. Now, you know, one of the things that I often you know work with customers around, you know, that we find is the radius off. Impact is important when you deal with outages. What I mean by that is problems occur, right? How do you respond? How quickly do you take? Two seconds? Two minutes, 20 minutes. Two hours, 20 hours. Right To resolve that problem. That radius of impact is important. That's where you know you have to bring again. People process technology together to solve that. And the key thing is, you need a system of intelligence that can aid you your teams, you know, look at the same set of parameters so that you can respond faster. That's the key here. >>But as we look at digital transformation at scale, Raj, how does a apps help influence that? >>You know, I'm gonna take a slightly long winded way to answer this question. See, when it comes to digital transformation at scale, the focus on business purpose and business outcome becomes extremely critical. And then the alignment off that to your digital supply chain right are the are the are the key factors that differentiate vintners in the in their digital transformation game. Really? What we have seen with with winners is they operate very differently. Like, for example, you know, 19 assures its digital business outcomes by shoes per second, right apple buy iPhones per per minute. Tesla by model threes per month. Are you getting getting it right? I mean, you wanna have, ah, clear business outcome, which is a measure off your business. In effect, I mean, easy right, which which my daughter use. And I use very well, right? You know, they measured by revenue per hour, right? I mean, so these are key measures, and when you have a key business outcome measure like that, you can align everything else because you know what these measures you know, for a bank, it may be deposits per month. Right now, when you move money from checking account to savings account or when you do direct deposits, those are you know, banks need liquidity and so on and so forth. But, you know, the key thing is that single business outcome has a starburst effect inside the I T. Organization that touches a single money movement from checking account to savings account can touch about 75 disparage systems internally. Right? So those think about right. I mean, all we're doing is moving money from checking accounts savings account. Now that goats in tow, a IittIe production system, there are several applications. There is a database there is there are infrastructures, their load balancers, that our webs, you know, the Web server components, which then touches your your middleware component, which is a queuing system right, which then touches your transactional system on. Do you know which may be on your mainframes what we call mobile toe mainframe scenario, right? And we're not done yet. Then you have a security and regulatory compliance system that you have to touch a fraud prevention system that you have to touch right, a State Department regulation that you may have to meet and on and on and on, right? This is the challenge that I t operation teams phase. And when you have millions of customers transacting right? Certainly this challenge cannot be, you know, managed by, you know, human beings alone. So therefore, you need a system off intelligence that augments human intelligence and acts as you, you know, your your eyes and ears in of a toe point pinpoint. Their problems are right. So digital transformation at scale really requires a well thought out ai ops system a platform and open extensible platform that you know, that is heterogeneous in nature because their stools problems in organizations. There is, uh, you know, a lot of data bases in systems. There are million's off, you know, customers and hundreds off partners and vendors, you know, making up that digital supply chain. So, you know, AI ops is at the center off, enabling an organization achieved digital up, you know, transformation at scale. Last but not least, you need continuous feedback loop. Continuous feedback loop is the ability for a production system toe. Inform your develops teams your finance teams, your customer experience teams your cost Modeling teams about what is going on say that they can so that they can reduce the intent outcome gap. All of this need to come together. What we call biz obs for ideal abs. >>That was a great example of how you talked about the Starburst effect. Actually never thought about it in that way. When you give the banking example but what you should is the magnitude of systems, the fact that people alone really need help with that and why intelligent automation and air ops could be transformative and enable that scale. Raj, it's always a pleasure to talk with you. Thanks for joining me today. Yeah, >>great to be here >>and we'll be right back with our next segment.

>>from around the globe. It's the Cube with digital coverage of AI ops. Virtual Forum Brought to You by Broadcom >>Welcome to this preview of Broadcom's AI Ops Virtual Forum on your host Lisa Martin, and joining me to give you a sneak peek of this event that's on December 3rd is Srinivasan, Rajagopal or Raj, the head of a I Ops at Broadcom Raj, this event is coming up in a couple of weeks. Excited. >>Good to be here. I am excited, Lisa. You know, um, customers are poised for growth in 2021 and, uh, they are we believe they all. They will also come out off the pandemic toe, grow their business and serve their customers, you know? Well, they have to key challenges. How do you grow at the same time, operate with efficiency, right. These two challenges our decision makers are struggling with every day at scale. That is why they do digital transformation at scale. And our key influencers like I t operators and SRE personas are helping our decision makers in our customers to drive the efficiency they are trying toe focus on converting outputs to outcomes. That's what the eye ops is all about and you're gonna hear it from us. >>Yeah, We've got a panel of experts here. Rich Lane, senior research analyst for Forrester, is going to be joining us as well as Guzman nastier the global product management at Verizon. And, of course, Raj, you're gonna be hearing some of the latest trends for AI ops. Why, now is the time, Raj, What are some of the key takeaways that you think those key influencers and those decision makers are gonna walk away from this event empowered with >>So the You know, our decision makers and a key influencers have a single question in mind when they deal with enterprise large enterprise scenarios, the questions that they get asked by their C level execs are Are you ready? Are you ready when remote work is the norm? Are you ready when you have to optimize your investments and are you ready when you have to accelerate your transformation at scale toe operate as a digital enterprise? All of this requires them to think and act differently from people process technology. And how do you bring all of this together under the ages off what we call a I ops is what they're gonna learn about. >>Another thing, too, is you're going to hear the latest industry trends on AI ops from Raj and the panel of experts that we mentioned a minute ago. How organizations like yours are finding value from a I ops and something that Raj talked about a minute ago is understanding why Now is the time to be ready for I also Raj and I look forward to you joining us along with our other Panelists. December 3rd register for the Broadcom AI Ops Virtual form today.

>> From around the globe it's the CUBE with digital coverage of Devops Virtual Forum, brought to you by Broadcom. >> Continuing our conversations here at Broadcom's DevOps Virtual Forum. Lisa Martin here, please do welcome back to the program. Serge Lucio, the general manager of the Enterprise Software Division at Broadcom. Hey Serge welcome. >> Thank you. Good to be here. >> So I know you were just participating with the BizOps manifesto that just happened recently. I just had the chance to talk with Jeffrey Hammond and he unlocked this really interesting concept but I wanted to get your thoughts on, spiritual co-location as really a necessity for BizOps to succeed in this unusual time in which we're living. What are your thoughts on spiritual co-location in terms of cultural change versus adoption of technologies? >> Yeah, it's quite interesting, right. When we think about the major impediments for DevOps implementation, that means all about culture, right? And swore over the last 20 years we've been talking about silos. We'd be talking about the paradox for these teams too when it goes to align. And in many ways it's not so much about these teams aligning but about being in the same car, in the same books, right? It's really about fusing those teams around kind of the common purpose, a common objective. So to me this is really about kind of changing this culture where people start to look at kind of OKRs instead of the key objective that drives the entire team. Now, what it means in practice is really that's we need to change a lot of behaviors, right? It's not about the ER key, it's not about roles. It's about, you know, who can do what and when, and, you know, driving a bias towards action. It's also means that we need, I mean, especially in this COVID times it becomes very difficult, right? To drive kind of a kind of collaboration and affinity between these teams. And so I think there's a significant role that especially tools can play in terms of providing this conference feedback from teams to be in that preface spiritual qualification. >> Well, and it talked about culture being it's something that, you know, we're so used to talking about DevOps with respect to velocity, all about speed here. But of course this time everything changed so quickly but going from the physical spaces to everybody being remote really does take. It's very different than you can't replicate it digitally but there are collaboration tools that can kind of really be essential to help that cultural shift, right? >> Yeah, so to me we tend to talk about collaboration in a very mundane way, right? Of course we can use zoom. We can all get into the same room. But the point when I think when Jeff says spiritual co-location, it's really about, we all share the same objective. Do we have a means for instance, our pipeline, right? When you talk about DevOps probably we all started thinking about this continuous delivery pipeline that basically drives the automation, the orchestration across the team. But just thinking about a pipeline, right? At the end of the day, it's all about what is the meantime to feed back to these teams. If I'm a developer and I commit code, how long does it take for, you know, that code to be processed through pipeline or quick and I get feedback? If I am a finance person, who's funding a product or a project, what is my meantime to beat back? And so a lot of, kind of a, when we think about the pipeline, I think what's been really inspiring to me in the last year or so is that there is much more of an adoption of that door effect metrics. There is way more of a focus around value stream management. And to me, this is really when we talk about collaboration it's really a balance. How do you provide that feedback to the different stakeholders across the life cycle in a very timely matter? And that's what we would need to get to in terms of kind of this notion of collaboration. It's not so much about people being in the same physical space. It's about, you know, when checking code, you know, to do I guess the system to automatically identify what I'm going to break. If I'm about to release some allocation, how can the system help me reduce my change builder rate? Because it's able to predict that some issue was introduced in the application or the product. So I think there's a great role of technology and AI candidates to actually provide kind of that new level of collaboration. >> So we'll get to AI in a second but I'm curious, what are some of the metrics you think that really matter right now is organizations are still in some form probably of transformation to this new almost 100% remote workforce. >> So I'll just say first I'm not a big fan of metrics. And the reason being that, you know, you can look at a change failure rate, right, or a leak time or cycle time. And those are interesting metrics, right? The trend on metric is absolutely critical. But what's more important these I'll do get to the root cause. What is taught to you lead to that metric to degrade or improve over time. And so I'm much more interested and we, you know, fruit for Broadcom. Are we more interested in understanding what are the patterns that contribute to this? So I'll use a very mundane example. You know, we know that cycle time is heavily influenced by organizational boundaries. So, you know, we talk a lot about silos, but we we've worked with many of our customers doing value stream mapping. And oftentimes what you see is that really the boundaries of your organization creates a lot of idle time, right? So to me, it's less about the metrics. I think the door metrics are pretty, you know, valid set metrics but what's way more important is to understand, what are the anti parents? What are the things that we can detect through the data that actually are affecting those metrics? And I mean, over the last 10, 20 years, we've learned a lot about kind of what are the anti parents within our large enterprise customers? And there are plenty of them. >> What are some of the things that you're seeing now with respect to patterns that have developed over the last seven to eight months? >> So I think the two areas which clearly are evolving very quickly are on kind of the front end of the life cycle where DevOps is more and more embracing value stream management, value stream mapping. And I think what's interesting is that in many ways, the product is becoming the new silo. The notion of a product is very difficult by itself to actually define. People are starting to recognize that a value stream is not its own little kind of island. That in reality, when I did find a product this product, oftentimes as dependencies on our products and that in fact, you're looking at kind of a network of value streams, if you will. So on that and there is clearly kind of a new sets if you will of anti-patterns where, you know, products are being defined as a set of OTRs. They have interdependencies and you have to have a new set of silos. On the other hand the other kind of key movement to ease around the SRE space, where I think there is a cultural clash. While the DevOps side is very much embracing this notion of OTRs and value stream mapping and value management. On the other end, you have IT operations teams. We still think business services, right? For them they think about configure items, think about infrastructure. And so, you know, it's not uncommon to see, you know, teams where, you know, the operations team is still thinking about hundreds of thousands, tens of thousands of business services. And so there is this boundary where I think, well, SRE has been put in place, and there's lots of thinking about what kind of metrics can be defined. I think, you know, going back to culture, I think there's a lot of cultural evolution that's still required for, you know, true operations teams. >> And that's a hard thing. Cultural transformation in any industry pandemic or not is a challenging thing. You now talked about AI and automation of minutes ago. How do you think those technologies can be leveraged by DevOps leaders to influence their successes and their ability to collaborate and maybe see eye to eye with the SREs? >> Yeah, so there're kind of too, so even for myself, right? As a leader of , you know, 1500 people organization, there's a number of things I don't see, right, on a daily basis. And I think the technologies that we have at our disposal today from the AI are able to mine a lot of data and expose a lot of issues that as leaders we may not be aware of. And some of these are pretty kind of easy to understand, right? We all think we're agile. And yet when you start to understand, for instance, what is the is a work in progress, right, during the sprint? When you start to analyze the data you can detect for instance, that maybe the teams are over committed, that there is too much work in profits. You can start to identify kind of interprocess either from a technology or from a people point of view, which were hidden. You can start to understand that maybe the change failure rate is dragging. So I believe that there is a fundamental role to be played by the tools to expose again these anti parents. To make these things visible to the teams to be able to even compare teams, right? One of the things that's amazing is now we have access to tons of data not just from a given customer, but across a large number of customers. And so we start to compare all of these teams kind of operate and what's working, what's not working. >> Thoughts on AI and automation as a facilitator of spiritual co-location? >> Yeah, absolutely. It's, you know, there's a the problem we all face is the unknown, right? The velocity, the volume, variety of the data, every day we don't really necessarily completely appreciate what is the impact of our actions, right? And so AI can really act as a safety net that enables us to understand what is the impact of our actions. And so, yeah, in many ways, the ability to be informed in a timely matter to be able to interact with people on the basis of data and collaborate on the data in the actual matter, I think is a very powerful enabler on, in that respect. I mean, I've seen countless of times that for instance at the SRE boundary to basically show that we'll turn the quality attributes of an incoming release, right? And exposing that to an operations person, an SRE person and enabling that collaboration dialogue through there is a very, very powerful tool. >> Do you have any recommendations for how teams can use, you know, the SRE folks, the DevOps says can use AI and automation in the right ways to be successful rather than some ways that aren't going to be non-productive. >> Yeah, so to me there's a part that the question really is when we talk about data. There are different ways you can use data, right? So you can do a lot of analytics, predictive analytics. So I think there is a tendency to look at, let's say a specific KPI, like an availability KPI or change failure rate. And to basically do a regression analysis and projecting all these things is going to happen in the future. To me that's a bad approach. The reason why I fundamentally think it's a better approach is because we, our systems the way we develop software is a non-leader kind of system, right? Software development is not linear in nature. And so I think there's a, this is probably the worst approach is to actually focus on metrics. On the other hand if you start to actually understand at a more granular level, what are the things which are contributing to this, right? So if you start to understand, for instance that whenever maybe, you know, you affect a specific part of the application that translates into production issues. So we have, I've actually a customer who identified that over 50% of their unplanned outages were related to specific components in your architecture. And whenever these components were changed this resulted in this implant outages. So if you start to be able to basically establish causality, right? Cause an effect between kind of data across the last cycle. I think this is the right way to use AI. And so pharma to be, I think it's way more about kind of a classification problem. What are the causes of problems that do exist and affect things as opposed to an hourly predictive which I don't think is as powerful? >> So I mentioned in the beginning of our conversation that just came off the BizOps manifesto. You're one of the authors of that. I want to get your thoughts on DevOps and BizOps overlapping, complimenting each other. What, from the BizOps perspective, what does it mean to the future of DevOps? >> Yeah, so it's interesting, right? If you think about DevOps, there's no founding document, right? We can refer to the Phoenix project. I mean, there are a set of documents which have been written, but in many ways there is no clear definition of what DevOps is. If you go to the DevOps Institute today you'll see that, you know, they are specific trainings for instance on value management on SRE. And so in many ways, the problem we have as an industry is that there are set practices between agile, DevOps, SRE, value stream management, Ital, right? And we all basically talk about the same things, right? We all talk about essentially accelerating in the meantime to feedback, but yet we don't have a common framework to talk about that. The other key thing is that we add to wait for genius, Jean Kim's last book to really start to get into the business aspect, right? And for value mapping to start to emerge for us to start as an industry, right? IT to start to think about what is our connection with the business aspect, what's our purpose, right? And ultimately it's all about kind of driving these business outcomes. And so to me, BizOps is really about kind of putting a lens on kind of this critical element that it's not business and IT that we in fact need to fuse business and IT. That I need needs to transform itself to recognize that it's this value generator, right? It's not a cost center. And so the relationship to me, it's more than BizOps provides kind of this over all kind of framework, if you will. That set the context for what is the reason for IT to exist. What are the core values and principles that IT needs to embrace to, again, change from cost center to value center. And then we need to start to use this as a way to start to unify some of, again, the core practices, whether it's agile, DevOps, value stream mapping, SRE. So, I think over time, my hope is that we start to organize a lot of our practices, language and cultural elements. >> Last question Serge in the last few seconds we have here, talking about this, the relation between BizOps and DevOps. What do you think as DevOps evolves? And as you talked to circle some of your insights, what should our audience keep their eyes on in the next six to 12 months? >> So to me the key challenge for the industry is really around. So we were seeing a very rapid shift towards kind of project to product, right? Which we don't want to do is to recreate kind of these new silos, these hard silos. So that's one of the big changes that I think we need to be really careful about. Because it is ultimately, it is about culture. It's not about kind of how we segment the work, right? And any true culture that we can overcome kind of silos. So back to, I guess, with Jeffrey's concept of kind of the spiritual co-location, I think it's really about that too. It's really about kind of focusing on the business outcomes on kind of aligning, on driving engagement across the teams, but not for create kind of a new set of silos which instead of being vertical are going to be these horizontal products. >> Great advice Serge that looking at culture as kind of a way of really addressing and helping to reduce, replace challenges. We thank you so much for sharing your insights and your time at today's DevOps Virtual Forum. >> Thank you. Thanks for your time. Serge Lucio, Lisa Martin, we'll be right back. (upbeat music)

>>From around the globe. It's the queue with digital coverage of dev ops virtual forum brought to you by Broadcom. >>Hi, Lisa Martin here covering the Broadcom dev ops virtual forum. I'm very pleased to be joined today by a cube alumni, Jeffrey Hammond, the vice president and principal analyst serving CIO is at Forester. Jeffrey. Nice to talk with you today. >>Good morning. It's good to be here. Yeah. >>So a virtual forum, great opportunity to engage with our audiences so much has changed in the last it's an understatement, right? Or it's an overstated thing, but it's an obvious, so much has changed when we think of dev ops. One of the things that we think of is speed, you know, enabling organizations to be able to better serve customers or adapt to changing markets like we're in now, speaking of the need to adapt, talk to us about what you're seeing with respect to dev ops and agile in the age of COVID, what are things looking like? >>Yeah, I think that, um, for most organizations, we're in a, uh, a period of adjustment, uh, when we initially started, it was essentially a sprint, you know, you run as hard as you can for as fast as you can for as long as you can and you just kind of power through it. And, and that's actually what, um, the folks that get hub saw in may when they ran an analysis of how developers, uh, commit times and a level of work that they were committing and how they were working, uh, in the first couple of months of COVID was, was progressing. They found that developers, at least in the Pacific time zone were actually increasing their work volume, maybe because they didn't have two hour commutes or maybe because they were stuck away in their homes, but for whatever reason, they were doing more work. >>And it's almost like, you know, if you've ever run a marathon the first mile or two in the marathon, you feel great and you just want to run and you want to power through it and you want to go hard. And if you do that by the time you get to mile 18 or 19, you're going to be gassed. It's sucking for wind. Uh, and, and that's, I think where we're starting to hit. So as we start to, um, gear our development chops out for the reality that most of us won't be returning into an office until 2021 at the earliest and many organizations will, will be fundamentally changing, uh, their remote workforce, uh, policies. We have to make sure that the agile processes that we use and the dev ops processes and tools that we use to support these teams are essentially aligned to help developers run that marathon instead of just kind of power through. >>So, um, let me give you a couple of specifics for many organizations, they have been in an environment where they will, um, tolerate Rover remote work and what I would call remote work around the edges like developers can be remote, but product managers and, um, you know, essentially scrum masters and all the administrators that are running the, uh, uh, the SCM repositories and, and the dev ops pipelines are all in the office. And it's essentially centralized work. That's not, we are anymore. We're moving from remote workers at the edge to remote workers at the center of what we do. And so one of the implications of that is that, um, we have to think about all the activities that you need to do from a dev ops perspective or from an agile perspective, they have to be remote people. One of the things I found with some of the organizations I talked to early on was there were things that administrators had to do that required them to go into the office to reboot the SCM server as an example, or to make sure that the final approvals for production, uh, were made. >>And so the code could be moved into the production environment. And so it actually was a little bit difficult because they had to get specific approval from the HR organizations to actually be allowed to go into the office in some States. And so one of the, the results of that is that while we've traditionally said, you know, tools are important, but they're not as important as culture as structure as organization as process. I think we have to rethink that a little bit because to the extent that tools enable us to be more digitally organized and to hiring, you know, achieve higher levels of digitization in our processes and be able to support the idea of remote workers in the center. They're now on an equal footing with so many of the other levers, uh, that, that, um, uh, that organizations have at their disposal. Um, I'll give you another example for years. >>We've said that the key to success with agile at the team level is cross-functional co located teams that are working together physically co located. It's the easiest way to show agile success. We can't do that anymore. We can't be physically located at least for the foreseeable future. So, you know, how do you take the low hanging fruits of an agile transformation and apply it in, in, in, in the time of COVID? Well, I think what you have to do is that you have to look at what physical co-location has enabled in the past and understand that it's not so much the fact that we're together looking at each other across the table. It's the fact that we're able to get into a shared mindspace, uh, from, um, uh, from a measurement perspective, we can have shared purpose. We can engage in high bandwidth communications. It's the spiritual aspect of that physical co-location that is actually important. So one of the biggest things that organizations need to start to ask themselves is how do we achieve spiritual colocation with our agile teams? Because we don't have the, the ease of physical co-location available to us anymore? >>Well, the spiritual co-location is such an interesting kind of provocative phrase there, but something that probably was a challenge here, we are seven, eight months in for many organizations, as you say, going from, you know, physical workspaces, co-location being able to collaborate face to face to a, a light switch flip overnight. And this undefined period of time where all we were living with with was uncertainty, how does spiritual, what do you, when you talk about spiritual co-location in terms of collaboration and processes and technology help us unpack that, and how are you seeing organizations adopted? >>Yeah, it's, it's, um, it's a great question. And, and I think it goes to the very root of how organizations are trying to transform themselves to be more agile and to embrace dev ops. Um, if you go all the way back to the, to the original, uh, agile manifesto, you know, there were four principles that were espoused individuals and interactions over processes and tools. That's still important. Individuals and interactions are at the core of software development, processes and tools that support those individual and interact. Uh, those individuals in those interactions are more important than ever working software over comprehensive documentation. Working software is still more important, but when you are trying to onboard employees and they can't come into the office and they can't do the two day training session and kind of understand how things work and they can't just holler over the cube, uh, to ask a question, you may need to invest a little bit more in documentation to help that onboarding process be successful in a remote context, uh, customer collaboration over contract negotiation. >>Absolutely still important, but employee collaboration is equally as important if you want to be spiritually, spiritually co-located. And if you want to have a shared purpose and then, um, responding to change over following a plan. I think one of the things that's happened in a lot of organizations is we have focused so much of our dev ops effort around velocity getting faster. We need to run as fast as we can like that sprinter. Okay. You know, trying to just power through it as quickly as possible. But as we shift to, to the, to the marathon way of thinking, um, velocity is still important, but agility becomes even more important. So when you have to create an application in three weeks to do track and trace for your employees, agility is more important. Um, and then just flat out velocity. Um, and so changing some of the ways that we think about dev ops practices, um, is, is important to make sure that that agility is there for one thing, you have to defer decisions as far down the chain to the team level as possible. >>So those teams have to be empowered to make decisions because you can't have a program level meeting of six or seven teams and one large hall and say, here's the lay of the land. Here's what we're going to do here are our processes. And here are our guardrails. Those teams have to make decisions much more quickly that developers are actually developing code in smaller chunks of flow. They have to be able to take two hours here or 50 minutes there and do something useful. And so the tools that support us have to become tolerant of the reality of, of, of, of how we're working. So if they work in a way that it allows the team together to take as much autonomy as they can handle, um, to, uh, allow them to communicate in a way that, that, that delivers shared purpose and allows them to adapt and master new technologies, then they're in the zone in their spiritual, they'll get spiritually connected. I hope that makes sense. >>It does. I think we all could use some of that, but, you know, you talked about in the beginning and I've, I've talked to numerous companies during the pandemic on the cube about the productivity, or rather the number of hours of work has gone way up for many roles, you know, and, and, and times that they normally late at night on the weekends. So, but it's a cultural, it's a mind shift to your point about dev ops focused on velocity, sprints, sprints, sprints, and now we have to, so that cultural shift is not an easy one for developers. And even at this folks to flip so quickly, what have you seen in terms of the velocity at which businesses are able to get more of that balance between the velocity, the sprint and the agility? >>I think, I think at the core, this really comes down to management sensitivity. Um, when everybody was in the office, you could kind of see the mental health of development teams by, by watching how they work. You know, you call it management by walking around, right. We can't do that. Managers have to, um, to, to be more aware of what their teams are doing, because they're not going to see that, that developer doing a check-in at 9:00 PM on a Friday, uh, because that's what they had to do, uh, to meet the objectives. And, um, and, and they're going to have to, to, um, to find new ways to measure engagement and also potential burnout. Um, friend of mine once had, uh, had a great metric that he called the parking lot metric. It was helpful as the parking lot at nine. And how full was it at five? >>And that gives you an indication of how engaged your developers are. Um, what's the digital equivalent equivalent to the parking lot metric in the time of COVID it's commit stats, it's commit rates. It's, um, you know, the, uh, the turn rate, uh, that we have in our code. So we have this information, we may not be collecting it, but then the next question becomes, how do we use that information? Do we use that information to say, well, this team isn't delivering as at the same level of productivity as another team, do we weaponize that data or do we use that data to identify impedances in the process? Um, why isn't a team working effectively? Is it because they have higher levels of family obligations and they've got kids that, that are at home? Um, is it because they're working with, um, you know, hardware technology, and guess what, they, it's not easy to get the hardware technology into their home office because it's in the lab at the, uh, at the corporate office, uh, or they're trying to communicate, uh, you know, halfway around the world. >>And, uh, they're communicating with a, with an office lab that is also shut down and, and, and the bandwidth just doesn't enable the, the level of high bandwidth communications. So from a dev ops perspective, managers have to get much more sensitive to the, the exhaust that the dev ops tools are throwing off, but also how they're going to use that in a constructive way to, to prevent burnout. And then they also need to, if they're not already managing or monitoring or measuring the level of developer engagement, they have, they really need to start whether that's surveys around developer satisfaction, um, whether it's, you know, more regular social events, uh, where developers can kind of just get together and drink a beer and talk about what's going on in the project, uh, and monitoring who checks in and who doesn't, uh, they have to, to, um, work harder, I think, than they ever have before. >>Well, and you mentioned burnout, and that's something that I think we've all faced in this time at varying levels and it changes. And it's a real, there's a tension in the air, regardless of where you are. There's a challenge, as you mentioned, people having, you know, coworker, their kids as coworkers and fighting for bandwidth, because everyone is forced in this situation. I'd love to get your perspective on some businesses that are, that have done this well, this adaptation, what can you share in terms of some real-world examples that might inspire the audience? >>Yeah. Uh, I'll start with, uh, stack overflow. Uh, they recently published a piece in the journal of the ACM around some of the things that they had discovered. Um, you know, first of all, just a cultural philosophy. If one person is remote, everybody is remote. And you just think that way from an executive level, um, social spaces. One of the things that they talk about doing is leaving a video conference room open at a team level all day long, and the team members, you know, we'll go on mute, you know, so that they don't have to, that they don't necessarily have to be there with somebody else listening to them. But if they have a question, they can just pop off mute really quickly and ask the question. And if anybody else knows the answer, it's kind of like being in that virtual pod. Uh, if you, uh, if you will, um, even here at Forrester, one of the things that we've done is we've invested in social ceremonies. >>We've actually moved our to our team meetings on, on my analyst team from, from once every two weeks to weekly. And we have built more time in for social Ajay socialization, just so we can see, uh, how, how, how we're doing. Um, I think Microsoft has really made some good, uh, information available in how they've managed things like the onboarding process. I think I'm Amanda silver over there mentioned that a couple of weeks ago when, uh, uh, a presentation they did that, uh, uh, Microsoft onboarded over 150,000 people since the start of COVID, if you don't have good remote onboarding processes, that's going to be a disaster. Now they're not all developers, but if you think about it, um, everything from how you do the interviewing process, uh, to how you get people, their badges, to how they get their equipment. Um, security is a, is another issue that they called out typically, uh, it security, um, the security of, of developers machines ends at, at, at the corporate desktop. >>But, you know, since we're increasingly using our own machines, our own hardware, um, security organizations kind of have to extend their security policies to cover, uh, employee devices, and that's caused them to scramble a little bit. Uh, so, so the examples are out there. It's not a lot of, like, we have to do everything completely differently, but it's a lot of subtle changes that, that have to be made. Um, I'll give you another example. Um, one of the things that, that we are seeing is that, um, more and more organizations to deal with the challenges around agility, with respect to delivering software, embracing low-code tools. In fact, uh, we see about 50% of firms are using low-code tools right now. We predict it's going to be 75% by the end of next year. So figuring out how your dev ops processes support an organization that might be using Mendix or OutSystems, or, you know, the power platform building the front end of an application, like a track and trace application really, really quickly, but then hooking it up to your backend infrastructure. Does that happen completely outside the dev ops investments that you're making and the agile processes that you're making, or do you adapt your organization? Um, our hybrid teams now teams that not just have professional developers, but also have business users that are doing some development with a low-code tool. Those are the kinds of things that we have to be, um, willing to, um, to entertain in order to shift the focus a little bit more toward the agility side, I think >>Lot of obstacles, but also a lot of opportunities for businesses to really learn, pay attention here, pivot and grow, and hopefully some good opportunities for the developers and the business folks to just get better at what they're doing and learning to embrace spiritual co-location Jeffrey, thank you so much for joining us on the program today. Very insightful conversation. >>My pleasure. It's it's, it's an important thing. Just remember if you're going to run that marathon, break it into 26, 10 minute runs, take a walk break in between each and you'll find that you'll get there. >>Digestible components, wise advice. Jeffery Hammond. Thank you so much for joining for Jeffrey I'm Lisa Martin, you're watching Broadcom's dev ops virtual forum >>From around the globe. It's the queue with digital coverage of dev ops virtual forum brought to you by Broadcom, >>Continuing our conversations here at Broadcom's dev ops virtual forum. Lisa Martin here, please. To welcome back to the program, Serge Lucio, the general manager of the enterprise software division at Broadcom. Hey, Serge. Welcome. Thank you. Good to be here. So I know you were just, uh, participating with the biz ops manifesto that just happened recently. I just had the chance to talk with Jeffrey Hammond and he unlocked this really interesting concept, but I wanted to get your thoughts on spiritual co-location as really a necessity for biz ops to succeed in this unusual time in which we're living. What are your thoughts on spiritual colocation in terms of cultural change versus adoption of technologies? >>Yeah, it's a, it's, it's quite interesting, right? When we, when we think about the major impediments for, uh, for dev ops implementation, it's all about culture, right? And swore over the last 20 years, we've been talking about silos. We'd be talking about the paradox for these teams to when it went to align in many ways, it's not so much about these teams aligning, but about being in the same car in the same books, right? It's really about fusing those teams around kind of the common purpose, a common objective. So to me, the, this, this is really about kind of changing this culture where people start to look at a kind of OKR is instead of the key objective, um, that, that drives the entire team. Now, what it means in practice is really that's, uh, we need to change a lot of behaviors, right? It's not about the Yarki, it's not about roles. It's about, you know, who can do what and when, and, uh, you know, driving a bias towards action. It also means that we need, I mean, especially in this school times, it becomes very difficult, right? To drive kind of a kind of collaboration between these teams. And so I think there there's a significant role that especially tools can play in terms of providing this complex feedback from teams to, uh, to be in that preface spiritual qualification. >>Well, and it talked about culture being, it's something that, you know, we're so used to talking about dev ops with respect to velocity, all about speed here. But of course this time everything changed so quickly, but going from the physical spaces to everybody being remote really does take it. It's very different than you can't replicate it digitally, but there are collaboration tools that can kind of really be essential to help that cultural shift. Right? >>Yeah. So 2020, we, we touch to talk about collaboration in a very mundane way. Like, of course we can use zoom. We can all get into, into the same room. But the point when I think when Jeff says spiritual, co-location, it's really about, we all share the same objective. Do we, do we have a niece who, for instance, our pipeline, right? When you talk about dev ops, probably we all started thinking about this continuous delivery pipeline that basically drives the automation, the orchestration across the team, but just thinking about a pipeline, right, at the end of the day, it's all about what is the meantime to beat back to these teams. If I'm a developer and a commit code, I don't, does it take where, you know, that code to be processed through pipeline pushy? Can I get feedback if I am a finance person who is funding a product or a project, what is my meantime to beat back? >>And so a lot of, kind of a, when we think about the pipeline, I think what's been really inspiring to me in the last year or so is that there is much more of an adoption of the Dora metrics. There is way more of a focus around value stream management. And to me, this is really when we talk about collaboration, it's really a balance. How do you provide the feedback to the different stakeholders across the life cycle in a very timely matter? And that's what we would need to get to in terms of kind of this, this notion of collaboration. It's not so much about people being in the same physical space. It's about, you know, when I checked in code, you know, to do I guess the system to automatically identify what I'm going to break. If I'm about to release some allegation, how can the system help me reduce my change pillar rates? Because it's, it's able to predict that some issue was introduced in the outpatient or work product. Um, so I think there's, there's a great role of technology and AI candidate Lynch to, to actually provide that new level of collaboration. >>So we'll get to AI in a second, but I'm curious, what are some of the, of the metrics you think that really matter right now is organizations are still in some form of transformation to this new almost 100% remote workforce. >>So I'll just say first, I'm not a big fan of metrics. Um, and the reason being that, you know, you can look at a change killer rate, right, or a lead time or cycle time. And those are, those are interesting metrics, right? The trend on metric is absolutely critical, but what's more important is you get to the root cause what is taught to you lean to that metric to degrade or improve or time. And so I'm much more interested and we, you know, fruit for Broadcom. Are we more interested in understanding what are the patterns that contribute to this? So I'll give you a very mundane example. You know, we know that cycle time is heavily influenced by, um, organizational boundaries. So, you know, we talk a lot about silos, but, uh, we we've worked with many of our customers doing value stream mapping. And oftentimes what you see is that really the boundaries of your organization creates a lot of idle time, right? So to me, it's less about the metrics. I think the door metrics are a pretty, you know, valid set metrics, but what's way more important is to understand what are the antiperspirants, what are the things that we can detect through the data that actually are affecting those metrics. And, uh, I mean, over the last 10, 20 years, we've learned a lot about kind of what are, what are the antiperspirants within our large enterprise customers. And there are plenty of them. >>What are some of the things that you're seeing now with respect to patterns that have developed over the last seven to eight months? >>So I think the two areas which clearly are evolving very quickly are on kind of the front end of the life cycle, where DevOps is more and more embracing value stream management value stream mapping. Um, and I think what's interesting is that in many ways the product is becoming the new silo. Uh, the notion of a product is very difficult by itself to actually define people are starting to recognize that a value stream is not its own little kind of Island. That in reality, when I define a product, this product, oftentimes as dependencies on our products and that in fact, you're looking at kind of a network of value streams, if you will. So, so even on that, and there is clearly kind of a new sets, if you will, of anti-patterns where products are being defined as a set of OTRs, they have interdependencies and you have have a new set of silos on the operands, uh, the Abra key movement to Israel and the SRE space where, um, I think there is a cultural clash while the dev ops side is very much embracing this notion of OTRs and value stream mapping and Belgium management. >>On the other end, you have the it operations teams. We still think business services, right? For them, they think about configure items, think about infrastructure. And so, you know, it's not uncommon to see, you know, teams where, you know, the operations team is still thinking about hundreds of thousands, tens of thousands of business services. And so the, the, there is there's this boundary where, um, I think, well, SRE is being put in place. And there's lots of thinking about what kind of metrics can be fined. I think, you know, going back to culture, I think there's a lot of cultural evolution that's still required for true operations team. >>And that's a hard thing. Cultural transformation in any industry pandemic or not is a challenging thing. You talked about, uh, AI and automation of minutes ago. How do you think those technologies can be leveraged by DevOps leaders to influence their successes and their ability to collaborate, maybe see eye to eye with the SRS? >>Yeah. Um, so th you're kind of too. So even for myself, as a leader of a, you know, 1500 people organization, there's a number of things I don't see right. On a daily basis. And, um, I think the, the, the, the technologies that we have at our disposal today from the AI are able to mind a lot of data and expose a lot of, uh, issues that's as leaders we may not be aware of. And some of the, some of these are pretty kind of easy to understand, right? We all think we're agile. And yet when you, when you start to understand, for instance, uh, what is the, what is the working progress right to during the sprint? Um, when you start to analyze the data you can detect, for instance, that maybe the teams are over committed, that there is too much work in progress. >>You can start to identify kind of, interdepencies either from a technology, from a people point of view, which were hidden, uh, you can start to understand maybe the change filler rates he's he is dragging. So I believe that there is a, there's a fundamental role to be played by the tools to, to expose again, these anti parents, to, to make these things visible to the teams, to be able to even compare teams. Right. One of the things that's, that's, uh, that's amazing is now we have access to tons of data, not just from a given customer, but across a large number of customers. And so we start to compare all of these teams kind of operate, and what's working, what's not working >>Thoughts on AI and automation as, as a facilitator of spiritual co-location. >>Yeah, absolutely. Absolutely. It's um, you know, th there's, uh, the problem we all face is the unknown, right? The, the law city, but volume variety of the data, uh, everyday we don't really necessarily completely appreciate what is the impact of our actions, right? And so, um, AI can really act as a safety net that enables us to, to understand what is the impact of our actions. Um, and so, yeah, in many ways, the ability to be informed in a timely matter to be able to interact with people on the basis of data, um, and collaborate on the data. And the actual matter, I think is, is a, is a very powerful enabler, uh, on, in that respect. I mean, I, I've seen, um, I've seen countless of times that, uh, for instance, at the SRE boundary, um, to basically show that we'll turn the quality attributes, so an incoming release, right. And exposing that to, uh, an operations person and a sorry person, and enabling that collaboration dialogue through data is a very, very powerful tool. >>Do you have any recommendations for how teams can use, you know, the SRE folks, the dev ops says can use AI and automation in the right ways to be successful rather than some ways that aren't going to be nonproductive. >>Yeah. So to me, the th there, there's a part of the question really is when, when we talk about data, there are there different ways you can use data, right? Um, so you can, you can do a lot of an analytics, predictive analytics. So I think there is a, there's a tendency, uh, to look at, let's say a, um, a specific KPI, like a, an availability KPI, or change filler rate, and to basically do a regression analysis and projecting all these things, going to happen in the future. To me, that that's, that's a, that's a bad approach. The reason why I fundamentally think it's a better approach is because we are systems. The way we develop software is, is a, is a non-leader kind of system, right? Software development is not linear nature. And so I think there's a D this is probably the worst approach is to actually focus on metrics on the other end. >>Um, if you, if you start to actually understand at a more granular level, what har, uh, which are the things which are contributing to this, right? So if you start to understand, for instance, that whenever maybe, you know, you affect a specific part of the application that translates into production issues. So we, we have, I've actually, uh, a customer who, uh, identified that, uh, over 50% of their unplanned outages were related to specific components in your architecture. And whenever these components were changed, this resulted in these plant outages. So if you start to be able to basically establish causality, right, cause an effect between kind of data across the last cycle. I think, I think this is the right way to, uh, to, to use AI. And so pharma to be, I think it's way more God could have a classification problem. What are the classes of problems that do exist and affect things as opposed to analytics, predictive, which I don't think is as powerful. >>So I mentioned in the beginning of our conversation, that just came off the biz ops manifesto. You're one of the authors of that. I want to get your thoughts on dev ops and biz ops overlapping, complimenting each other, what, from a, the biz ops perspective, what does it mean to the future of dev ops? >>Yeah, so, so it's interesting, right? If you think about DevOps, um, there's no felony document, right? Can we, we can refer to the Phoenix project. I mean, there are a set of documents which have been written, but in many ways, there's no clear definition of what dev ops is. Uh, if you go to the dev ops Institute today, you'll see that they are specific, um, trainings for instance, on value management on SRE. And so in many ways, the problem we have as an industry is that, um, there are set practices between agile dev ops, SRE Valley should management. I told, right. And we all basically talk about the same things, right. We all talk about essentially, um, accelerating in the meantime fee to feedback, but yet we don't have the common framework to talk about that. The other key thing is that we add to wait, uh, for, uh, for jeans, Jean Kim's Lascaux, um, to, uh, to really start to get into the business aspect, right? >>And for value stream mapping to start to emerge for us to start as an industry, right. It, to start to think about what is our connection with the business aspect, what's our purpose, right? And ultimately it's all about driving these business outcomes. And so to me, these ops is really about kind of, uh, putting a lens on this critical element that it's not business and it, that we in fact need to fuse business 19 that I need needs to transform itself to recognize that it's, it's this value generator, right. It's not a cost center. And so the relationship to me, it's more than BizOps provides kind of this Oliver or kind of framework, if you will. That set the context for what is the reason, uh, for it to exist. What's part of the core values and principles that it needs to embrace to, again, change from a cost center to a value center. And then we need to start to use this as a way to start to unify some of the, again, the core practices, whether it's agile, DevOps value, stream mapping SRE. Um, so, so I think over time, my hope is that we start to optimize a lot of our practices, language, um, and, uh, and cultural elements. >>Last question surgeon, the last few seconds we have here talking about this, the relation between biz ops and dev ops, um, what do you think as DevOps evolves? And as you talked to circle some of your insights, what should our audience keep their eyes on in the next six to 12 months? >>So to me, the key, the key, um, challenge for, for the industry is really around. So we were seeing a very rapid shift towards kind of, uh, product to product, right. Which we don't want to do is to recreate kind of these new silos, these hard silos. Um, so that, that's one of the big changes, uh, that I think we need to be, uh, to be really careful about, um, because it is ultimately, it is about culture. It's not about, uh, it's not about, um, kind of how we segment the work, right. And, uh, any true culture that we can overcome kind of silos. So back to, I guess, with Jeffrey's concept of, um, kind of the spiritual co-location, I think it's, it's really about that too. It's really about kind of, uh, uh, focusing on the business outcomes on kind of aligning on driving engagement across the teams, but, but not for create a, kind of a new set of silos, which instead of being vertical are going to be these horizontal products >>Crazy by surge that looking at culture as kind of a way of really, uh, uh, addressing and helping to, uh, re re reduce, replace challenges. We thank you so much for sharing your insights and your time at today's DevOps virtual forum. >>Thank you. Thanks for your time. >>I'll be right back >>From around the globe it's the cube with digital coverage of devops virtual forum brought to you by Broadcom. >>Welcome to Broadcom's DevOps virtual forum, I'm Lisa Martin, and I'm joined by another Martin, very socially distanced from me all the way coming from Birmingham, England is Glynn Martin, the head of QA transformation at BT. Glynn, it's great to have you on the program. Thank you, Lisa. I'm looking forward to it. As we said before, we went live to Martins for the person one in one segment. So this is going to be an interesting segment guys, what we're going to do is Glynn's going to give us a really kind of deep inside out view of devops from an evolution perspective. So Glynn, let's start. Transformation is at the heart of what you do. It's obviously been a very transformative year. How have the events of this year affected the >> transformation that you are still responsible for driving? Yeah. Thank you, Lisa. I mean, yeah, it has been a difficult year. >>Um, and although working for BT, which is a global telecommunications company, um, I'm relatively resilient, I suppose, as a, an industry, um, through COVID obviously still has been affected and has got its challenges. And if anything, it's actually caused us to accelerate our transformation journey. Um, you know, we had to do some great things during this time around, um, you know, in the UK for our emergency and, um, health workers give them unlimited data and for vulnerable people to support them. And that's spent that we've had to deliver changes quickly. Um, but what we want to be able to do is deliver those kinds of changes quickly, but sustainably for everything that we do, not just because there's an emergency. Um, so we were already on the kind of journey to agile, but ever more important now that we are, we are able to do those, that kind of work, do it more quickly. >>Um, and that it works because the, the implications of it not working is, can be terrible in terms of you know, we've been supporting testing centers,  new hospitals to treat COVID patients. So we need to get it right. And then therefore the coverage of what we do, the quality of what we do and how quickly we do it really has taken on a new scale and what was already a very competitive market within the telco industry within the UK. Um, you know, what I would say is that, you know, we are under pressure to deliver more value, but we have small cost challenges. We have to obviously, um, deal with the fact that, you know, COVID 19 has hit most industries kind of revenues and profits. So we've got this kind of paradox between having less costs, but having to deliver more value quicker and  to higher quality. So yeah, certainly the finances is, um, on our minds and that's why we need flexible models, cost models that allow us to kind of do growth, but we get that growth by showing that we're delivering value. Um, especially in these times when there are financial challenges on companies. So one of the things that I want to ask you about, I'm again, looking at DevOps from the inside >>Out and the evolution that you've seen, you talked about the speed of things really accelerating in this last nine months or so. When we think dev ops, we think speed. But one of the things I'd love to get your perspective on is we've talked about in a number of the segments that we've done for this event is cultural change. What are some of the things that you've seen there as, as needing to get, as you said, get things right, but done so quickly to support essential businesses, essential workers. How have you seen that cultural shift? >>Yeah, I think, you know, before test teams for themselves at this part of the software delivery cycle, um, and actually now really our customers are expecting that quality and to deliver for our customers what they want, quality has to be ingrained throughout the life cycle. Obviously, you know, there's lots of buzzwords like shift left. Um, how do we do shift left testing? Um, but for me, that's really instilling quality and given capabilities shared capabilities throughout the life cycle that drive automation, drive improvements. I always say that, you know, you're only as good as your lowest common denominator. And one thing that we were finding on our dev ops journey was that we  would be trying to do certain things quick, we had automated build, automated tests. But if we were taking a weeks to create test scripts, or we were taking weeks to manually craft data, and even then when we had taken so long to do it, that the coverage was quite poor and that led to lots of defects later on in the life cycle, or even in our production environment, we just couldn't afford to do that. >>And actually, focusing on continuous testing over the last nine to 12 months has really given us the ability to deliver quickly across the whole life cycle. And therefore actually go from doing a kind of semi agile kind of thing, where we did the user stories, we did a few of the kind of agile ceremonies, but we weren't really deploying any quicker into production because our stakeholders were scared that we didn't have the same control that we had when we had more waterfall releases. And, you know, when we didn't think of ourselves. So we've done a lot of work on every aspect, um, especially from a testing point of view, every aspect of every activity, rather than just looking at automated tests, you know, whether it is actually creating the test in the first place, whether it's doing security testing earlier in the lot and performance testing in the life cycle, et cetera. So, yeah,  it's been a real key thing that for CT, for us to drive DevOps, >>Talk to me a little bit about your team. What are some of the shifts in terms of expectations that you're experiencing and how your team interacts with the internal folks from pipeline through life cycle? >>Yeah, we've done a lot of work on this. Um, you know, there's a thing that I think people will probably call it a customer experience gap, and it reminds me of a Gilbert cartoon, where we start with the requirements here and you're almost like a Chinese whisper effects and what we deliver is completely different. So we think the testing team or the delivery teams, um, know in our teeth has done a great job. This is what it said in the acceptance criteria, but then our customers are saying, well, actually that's not working this isn't working and there's this kind of gap. Um, we had a great launch this year of agile requirements, it's one of the Broadcom tools. And that was the first time in, ever since I remember actually working within BT, I had customers saying to me, wow, you know, we want more of this. >>We want more projects to have extra requirements design on it because it allowed us to actually work with the business collaboratively. I mean, we talk about collaboration, but how do we actually, you know, do that and have something that both the business and technical people can understand. And we've actually been working with the business , using agile requirements designer to really look at what the requirements are, tease out requirements we hadn't even thought of and making sure that we've got high levels of test coverage. And what we actually deliver at the end of it, not only have we been able to generate tests more quickly, but we've got much higher test coverage and also can more smartly, using the kind of AI within the tool and then some of the other kinds of pipeline tools, actually deliver to choose the right tasks, and actually doing a risk based testing approach. So that's been a great launch this year, but just the start of many kinds of things that we're doing >>Well, what I hear in that, Glynn is a lot of positives that have come out of a very challenging situation. Talk to me about it. And I liked that perspective. This is a very challenging time for everybody in the world, but it sounds like from a collaboration perspective you're right, we talk about that a lot critical with devops. But those challenges there, you guys were able to overcome those pretty quickly. What other challenges did you face and figure out quickly enough to be able to pivot so fast? >>I mean, you talked about culture. You know, BT is like most companies  So it's very siloed. You know we're still trying to work to become closer as a company. So I think there's a lot of challenges around how would you integrate with other tools? How would you integrate with the various different technologies. And BT, we have 58 different IT stacks. That's not systems, that's stacks, all of those stacks can have hundreds of systems. And we're trying to, we've got a drive at the moment, a simplified program where we're trying to you know, reduce that number to 14 stacks. And even then there'll be complexity behind the scenes that we will be challenged more and more as we go forward. How do we actually highlight that to our users? And as an it organization, how do we make ourselves leaner, so that even when we've still got some of that legacy, and we'll never fully get rid of it and that's the kind of trade off that we have to make, how do we actually deal with that and hide that from our users and drive those programs, so we can, as I say, accelerate change,  reduce that kind of waste and that kind of legacy costs out of our business. You know, the other thing as well, I'm sure telecoms is probably no different to insurance or finance. When you take the number of products that we do, and then you combine them, the permutations are tens and hundreds of thousands of products. So we, as a business are trying to simplify, we are trying to do that in an agile way. >>And haven't tried to do agile in the proper way and really actually work at pace, really deliver value. So I think what we're looking more and more at the moment is actually  more value focused. Before we used to deliver changes sometimes into production. Someone had a great idea, or it was a great idea nine months ago or 12 months ago, but actually then we ended up deploying it and then we'd look at the users, the usage of that product or that application or whatever it is, and it's not being used for six months. So we haven't got, you know, the cost of the last 12 months. We certainly haven't gotten room for that kind of waste and, you know, for not really understanding the value of changes that we are doing. So I think that's the most important thing of the moment, it's really taking that waste out. You know, there's lots of focus on things like flow management, what bits of our process are actually taking too long. And we've started on that journey, but we've got a hell of a long way to go. But that involves looking at every aspect of the software delivery cycle. >> Going from, what 58 IT stacks down to 14 or whatever it's going to be, simplifying sounds magical to everybody. It's a big challenge. What are some of the core technology capabilities that you see really as kind of essential for enabling that with this new way that you're working? >>Yeah. I mean, I think we were started on a continuous testing journey, and I think that's just the start. I mean as I say, looking at every aspect of, you know, from a QA point of view is every aspect of what we do. And it's also looking at, you know, we've started to branch into more like AI, uh, AI ops and, you know, really the full life cycle. Um, and you know, that's just a stepping stone to, you know, I think autonomics is the way forward, right. You know, all of this kind of stuff that happens, um, you know, monitoring, uh, you know, watching the systems what's happening in production, how do we feed that back? How'd you get to a point where actually we think about change and then suddenly it's in production safely, or if it's not going to safety, it's automatically backing out. So, you know, it's a very, very long journey, but if we want to, you know, in a world where the pace is in ever-increasing and the demands for the team, and, you know, with the pressures on, at the moment where we're being asked to do things, uh, you know, more efficiently and as lean as possible, we need to be thinking about every part of the process and how we put the kind of stepping stones in place to lead us to a more automated kind of, um, you know, um, the future. >>Do you feel that that planned outcomes are starting to align with what's delivered, given this massive shift that you're experiencing? >>I think it's starting to, and I think, you know, as I say, as we look at more of a value based approach, um, and, um, you know, as I say, print, this was a kind of flow management. I think that that will become ever, uh, ever more important. So, um, I think it starting to people certainly realize that, you know, teams need to work together, you know, the kind of the cousin between business and it, especially as we go to more kind of SAS based solutions, low code solutions, you know, there's not such a gap anymore, actually, some of our business partners that expense to be much more tech savvy. Um, so I think, you know, this is what we have to kind of appreciate what is its role, how do we give the capabilities, um, become more of a centers of excellence rather than actually doing mounds amounts of work. And for me, and from a testing point of view, you know, mounds and mounds of testing, actually, how do we automate that? How do we actually generate that instead of, um, create it? I think that's the kind of challenge going forward. >>What are some, as we look forward, what are some of the things that you would like to see implemented or deployed in the next, say six to 12 months as we hopefully round a corner with this pandemic? >>Yeah, I think, um, you know, certainly for, for where we are as a company from a QA perspective, we are, um, you let's start in bits that we do well, you know, we've started creating, um, continuous delivery and DevOps pipelines. Um, there's still manual aspects of that. So, you know, certainly for me, I I've challenged my team with saying how do we do an automated journey? So if I put a requirement in JIRA or rally or wherever it is and why then click a button and, you know, with either zero touch for one such, then put that into production and have confidence that, that has been done safely and that it works and what happens if it doesn't work. So, you know, that's, that's the next, um, the next few months, that's what our concentration, um, is, is about. But it's also about decision-making, you know, how do you actually understand those value judgments? >>And I think there's lots of the things dev ops, AI ops, kind of that always ask aspects of business operations. I think it's about having the information in one place to make those kinds of decisions. How does it all try and tie it together? As I say, even still with kind of dev ops, we've still got elements within my company where we've got lots of different organizations doing some, doing similar kinds of things, but they're all kind of working in silos. So I think having AI ops as it comes more and more to the fore as we go to cloud, and that's what we need to, you know, we're still very early on in our cloud journey, you know, so we need to make sure the technologies work with cloud as well as you can have, um, legacy systems, but it's about bringing that all together and having a full, visible pipeline, um, that everybody can see and make decisions. >>You said the word confidence, which jumped out at me right away, because absolutely you've got to have be able to have confidence in what your team is delivering and how it's impacting the business and those customers. Last question then for you is how would you advise your peers in a similar situation to leverage technology automation, for example, dev ops, to be able to gain the confidence that they're making the right decisions for their business? >>I think the, the, the, the, the approach that we've taken actually is not started with technology. Um, we've actually taken a human centered design, uh, as a core principle of what we do, um, within the it part of BT. So by using human centered design, that means we talk to our customers, we understand their pain points, we map out their current processes. Um, and then when we mapped out what this process does, it also understand their aspirations as well, you know? Um, and where do they want to be in six months? You know, do they want it to be, um, more agile and, you know, or do they want to, you know, is, is this a part of their business that they want to do one better? We actually then looked at why that's not running well, and then see what, what solutions are out there. >>We've been lucky that, you know, with our partnership, with Broadcom within the payer line, lots of the tools and the PLA have directly answered some of the business's problems. But I think by having those conversations and actually engaging with the business, um, you know, especially if the business hold the purse strings, which in, in, uh, you know, in some companies include not as they do there is that kind of, you know, almost by understanding their, their pain points and then starting, this is how we can solve your problem. Um, is we've, we've tended to be much more successful than trying to impose something and say, well, here's the technology that they don't quite understand. It doesn't really understand how it kind of resonates with their problems. So I think that's the heart of it. It's really about, you know, getting, looking at the data, looking at the processes, looking at where the kind of waste is. >>And then actually then looking at the right solutions. Then, as I say, continuous testing is massive for us. We've also got a good relationship with Apple towards looking at visual AI. And actually there's a common theme through that. And I mean, AI is becoming more and more prevalent. And I know, you know, sometimes what is AI and people have kind of this semantics of, is it true AI or not, but it's certainly, you know, AI machine learning is becoming more and more prevalent in the way that we work. And it's allowing us to be much more effective, be quicker in what we do and be more accurate. And, you know, whether it's finding defects running the right tests or, um, you know, being able to anticipate problems before they're happening in a production environment. >>Well, thank you so much for giving us this sort of insight outlook at dev ops sharing the successes that you're having, taking those challenges, converting them to opportunities and forgiving folks who might be in your shoes, or maybe slightly behind advice enter. They appreciate it. We appreciate your time. >>Well, it's been an absolute pleasure, really. Thank you for inviting me. I have a extremely enjoyed it. So thank you ever so much. >>Excellent. Me too. I've learned a lot for Glenn Martin. I'm Lisa Martin. You're watching the cube >>Driving revenue today means getting better, more valuable software features into the hands of your customers. If you don't do it quickly, your competitors as well, but going faster without quality creates risks that can damage your brand destroy customer loyalty and cost millions to fix dev ops from Broadcom is a complete solution for balancing speed and risk, allowing you to accelerate the flow of value while minimizing the risk and severity of critical issues with Broadcom quality becomes integrated across the entire DevOps pipeline from planning to production, actionable insights, including our unique readiness score, provide a three 60 degree view of software quality giving you visibility into potential issues before they become disasters. Dev ops leaders can manage these risks with tools like Canary deployments tested on a small subset of users, or immediately roll back to limit the impact of defects for subsequent cycles. Dev ops from Broadcom makes innovation improvement easier with integrated planning and continuous testing tools that accelerate the flow of value product requirements are used to automatically generate tests to ensure complete quality coverage and tests are easily updated. >>As requirements change developers can perform unit testing without ever leaving their preferred environment, improving efficiency and productivity for the ultimate in shift left testing the platform also integrates virtual services and test data on demand. Eliminating two common roadblocks to fast and complete continuous testing. When software is ready for the CIC CD pipeline, only DevOps from Broadcom uses AI to prioritize the most critical and relevant tests dramatically improving feedback speed with no decrease in quality. This release is ready to go wherever you are in your DevOps journey. Broadcom helps maximize innovation velocity while managing risk. So you can deploy ideas into production faster and release with more confidence from around the globe. It's the queue with digital coverage of dev ops virtual forum brought to you by Broadcom. >>Hi guys. Welcome back. So we have discussed the current state and the near future state of dev ops and how it's going to evolve from three unique perspectives. In this last segment, we're going to open up the floor and see if we can come to a shared understanding of where dev ops needs to go in order to be successful next year. So our guests today are, you've seen them all before Jeffrey Hammond is here. The VP and principal analyst serving CIO is at Forester. We've also Serge Lucio, the GM of Broadcom's enterprise software division and Glenn Martin, the head of QA transformation at BT guys. Welcome back. Great to have you all three together >>To be here. >>All right. So we're very, we're all very socially distanced as we've talked about before. Great to have this conversation. So let's, let's start with one of the topics that we kicked off the forum with Jeff. We're going to start with you spiritual co-location that's a really interesting topic that we've we've uncovered, but how much of the challenge is truly cultural and what can we solve through technology? Jeff, we'll start with you then search then Glen Jeff, take it away. >>Yeah, I think fundamentally you can have all the technology in the world and if you don't make the right investments in the cultural practices in your development organization, you still won't be effective. Um, almost 10 years ago, I wrote a piece, um, where I did a bunch of research around what made high-performance teams, software delivery teams, high performance. And one of the things that came out as part of that was that these teams have a high level of autonomy. And that's one of the things that you see coming out of the agile manifesto. Let's take that to today where developers are on their own in their own offices. If you've got teams where the team itself had a high level of autonomy, um, and they know how to work, they can make decisions. They can move forward. They're not waiting for management to tell them what to do. >>And so what we have seen is that organizations that embraced autonomy, uh, and got their teams in the right place and their teams had the information that they needed to make the right decisions have actually been able to operate pretty well, even as they've been remote. And it's turned out to be things like, well, how do we actually push the software that we've created into production that would become the challenge is not, are we writing the right software? And that's why I think the term spiritual co-location is so important because even though we may be physically distant, we're on the same plane, we're connected from a, from, from a, a shared purpose. Um, you know, surgeon, I worked together a long, long time ago. So it's been what almost 15, 16 years since we were at the same place. And yet I would say there's probably still a certain level of spiritual co-location between us, uh, because of the shared purposes that we've had in the past and what we've seen in the industry. And that's a really powerful tool, uh, to build on. So what do tools play as part of that, to the extent that tools make information available, to build shared purpose on to the extent that they enable communication so that we can build that spiritual co-location to the extent that they reinforce the culture that we want to put in place, they can be incredibly valuable, especially when, when we don't have the luxury of physical locate physical co-location. Okay. That makes sense. >>It does. I shouldn't have introduced us. This last segment is we're all spiritually co-located or it's a surge, clearly you're still spiritually co located with jump. Talk to me about what your thoughts are about spiritual of co-location the cultural impact and how technology can move it forward. >>Yeah. So I think, well, I'm going to sound very similar to Jeff in that respect. I think, you know, it starts with kind of a shared purpose and the other understanding, Oh, individuals teams, uh, contributed to kind of a business outcome, what is our shared goal or shared vision? What's what is it we're trying to achieve collectively and keeping it kind of aligned to that? Um, and so, so it's really starts with that now, now the big challenge, always these over the last 20 years, especially in large organization, there's been specialization of roles and functions. And so we, we all that started to basically measure which we do, uh, on a daily basis using metrics, which oftentimes are completely disconnected from kind of a business outcome or purpose. We, we kind of reverted back to, okay, what is my database all the time? What is my cycle time? >>Right. And, and I think, you know, which we can do or where we really should be focused as an industry is to start to basically provide a lens or these different stakeholders to look at what they're doing in the context of kind of these business outcomes. So, um, you know, probably one of my, um, favorites experience was to actually weakness at one of a large financial institution. Um, you know, Tuesday Golder's unquote development and operations staring at the same data, right. Which was related to, you know, in calming changes, um, test execution results, you know, Coverity coverage, um, official liabilities and all the all ran. It could have a direction level links. And that's when you start to put these things in context and represent that to you in a way that these different stakeholders can, can look at from their different lens. And, uh, and it can start to basically communicate and, and understand have they joined our company to, uh, to, to that kind of common view or objective. >>And Glen, we talked a lot about transformation with you last time. What are your thoughts on spiritual colocation and the cultural part, the technology impact? >>Yeah, I mean, I agree with Jeffrey that, you know, um, the people and culture, the most important thing, actually, that's why it's really important when you're transforming to have partners who have the same vision as you, um, who, who you can work with, have the same end goal in mind. And w I've certainly found that with our, um, you know, continuing relationship with Broadcom, what it also does though, is although, you know, tools can accelerate what you're doing and can join consistency. You know, we've seen within simplify, which is BTS flagship transformation program, where we're trying to, as it can, it says simplify the number of systems stacks that we have, the number of products that we have actually at the moment, we've got different value streams within that program who have got organizational silos. We were trying to rewrite, rewrite the wheel, um, who are still doing things manually. >>So in order to try and bring that consistency, we need the right tools that actually are at an enterprise grade, which can be flexible to work with in BT, which is such a complex and very dev, uh, different environments, depending on what area of BT you're in, whether it's a consumer, whether it's a mobile area, whether it's large global or government organizations, you know, we found that we need tools that can, um, drive that consistency, but also flex to Greenfield brownfield kind of technologies as well. So it's really important that as I say, for a number of different aspects, that you have the right partner, um, to drive the right culture, I've got the same vision, but also who have the tool sets to help you accelerate. They can't do that on their own, but they can help accelerate what it is you're trying to do in it. >>And a really good example of that is we're trying to shift left, which is probably a, quite a bit of a buzz phrase in their kind of testing world at the moment. But, you know, I could talk about things like continuous delivery direct to when a ball comes tools and it has many different features to it, but very simply on its own, it allows us to give the visibility of what the teams are doing. And once we have that visibility, then we can talk to the teams, um, around, you know, could they be doing better component testing? Could they be using some virtualized services here or there? And that's not even the main purpose of continuous delivery director, but it's just a reason that tools themselves can just give greater visibility of have much more intuitive and insightful conversations with other teams and reduce those organizational silos. >>Thanks, Ben. So we'd kind of sum it up, autonomy collaboration tools that facilitate that. So let's talk now about metrics from your perspectives. What are the metrics that matter? Jeff, >>I'm going to go right back to what Glenn said about data that provides visibility that enables us to, to make decisions, um, with shared purpose. And so business value has to be one of the first things that we look at. Um, how do we assess whether we have built something that is valuable, you know, that could be sales revenue, it could be net promoter score. Uh, if you're not selling what you've built, it could even be what the level of reuse is within your organization or other teams picking up the services, uh, that you've created. Um, one of the things that I've begun to see organizations do is to align value streams with customer journeys and then to align teams with those value streams. So that's one of the ways that you get to a shared purpose, cause we're all trying to deliver around that customer journey, the value with it. >>And we're all measured on that. Um, there are flow metrics which are really important. How long does it take us to get a new feature out from the time that we conceive it to the time that we can run our first experiments with it? There are quality metrics, um, you know, some of the classics or maybe things like defect, density, or meantime to response. Um, one of my favorites came from a, um, a company called ultimate software where they looked at the ratio of defects found in production to defects found in pre production and their developers were in fact measured on that ratio. It told them that guess what quality is your job to not just the test, uh, departments, a group, the fourth level that I think is really important, uh, in, in the current, uh, situation that we're in is the level of engagement in your development organization. >>We used to joke that we measured this with the parking lot metric helpful was the parking lot at nine. And how full was it at five o'clock. I can't do that anymore since we're not physically co-located, but what you can do is you can look at how folks are delivering. You can look at your metrics in your SCM environment. You can look at, uh, the relative rates of churn. Uh, you can look at things like, well, are our developers delivering, uh, during longer periods earlier in the morning, later in the evening, are they delivering, uh, you know, on the weekends as well? Are those signs that we might be heading toward a burnout because folks are still running at sprint levels instead of marathon levels. Uh, so all of those in combination, uh, business value, uh, flow engagement in quality, I think form the backbone of any sort of, of metrics, uh, a program. >>The second thing that I think you need to look at is what are we going to do with the data and the philosophy behind the data is critical. Um, unfortunately I see organizations where they weaponize the data and that's completely the wrong way to look at it. What you need to do is you need to say, you need to say, how is this data helping us to identify the blockers? The things that aren't allowing us to provide the right context for people to do the right thing. And then what do we do to remove those blockers, uh, to make sure that we're giving these autonomous teams the context that they need to do their job, uh, in a way that creates the most value for the customers. >>Great advice stuff, Glenn, over to your metrics that matter to you that really make a big impact. And, and, and also how do you measure quality kind of following onto the advice that Jeff provided? >>That's some great advice. Actually, he talks about value. He talks about flow. Both of those things are very much on my mind at the moment. Um, but there was this, I listened to a speaker, uh, called me Kirsten a couple of months ago. It taught very much around how important flow management is and removing, you know, and using that to remove waste, to understand in terms of, you know, making software changes, um, what is it that's causing us to do it longer than we need to. So where are those areas where it takes long? So I think that's a very important thing for us. It's even more basic than that at the moment, we're on a journey from moving from kind of a waterfall to agile. Um, and the problem with moving from waterfall to agile is with waterfall, the, the business had a kind of comfort that, you know, everything was tested together and therefore it's safer. >>Um, and with agile, there's that kind of, you know, how do we make sure that, you know, if we're doing things quick and we're getting stuff out the door that we give that confidence, um, that that's ready to go, or if there's a risk that we're able to truly articulate what that risk is. So there's a bit about release confidence, um, and some of the metrics around that and how, how healthy those releases are, and actually saying, you know, we spend a lot of money, um, um, an investment setting up our teams, training our teams, are we actually seeing them deliver more quickly and are we actually seeing them deliver more value quickly? So yeah, those are the two main things for me at the moment, but I think it's also about, you know, generally bringing it all together, the dev ops, you know, we've got the kind of value ops AI ops, how do we actually bring that together to so we can make quick decisions and making sure that we are, um, delivering the biggest bang for our buck, absolutely biggest bang for the buck, surge, your thoughts. >>Yeah. So I think we all agree, right? It starts with business metrics, flow metrics. Um, these are kind of the most important metrics. And ultimately, I mean, one of the things that's very common across a highly functional teams is engagements, right? When, when you see a team that's highly functioning, that's agile, that practices DevOps every day, they are highly engaged. Um, that that's, that's definitely true. Now the, you know, back to, I think, uh, Jeff's point on weaponization of metrics. One of the key challenges we see is that, um, organizations traditionally have been kind of, uh, you know, setting up benchmarks, right? So what is a good cycle time? What is a good lead time? What is a good meantime to repair? The, the problem is that this is very contextual, right? It varies. It's going to vary quite a bit, depending on the nature of application and system. >>And so one of the things that we really need to evolve, um, as an industry is to understand that it's not so much about those flow metrics is about our, these four metrics ultimately contribute to the business metric to the business outcome. So that's one thing. The second aspect, I think that's oftentimes misunderstood is that, you know, when you have a bad cycle time or, or, or what you perceive as being a buy cycle time or better quality, the problem is oftentimes like all, do you go and explore why, right. What is the root cause of this? And I think one of the key challenges is that we tend to focus a lot of time on metrics and not on the eye type patterns, which are pretty common across the industry. Um, you know, if you look at, for instance, things like lead time, for instance, it's very common that, uh, organizational boundaries are going to be a key contributor to badly time. >>And so I think that there is, you know, the only the metrics there is, I think a lot of work that we need to do in terms of classifying, descend type patterns, um, you know, back to you, Jeff, I think you're one of the cool offers of waterscrumfall as a, as, as a key pattern, the industry or anti-spatter. Um, but waterscrumfall right is a key one, right? And you will detect that through kind of a defect arrival rates. That's where that looks like an S-curve. And so I think it's beyond kind of the, the metrics is what do you do with those metrics? >>Right? I'll tell you a search. One of the things that is really interesting to me in that space is I think those of us had been in industry for a long time. We know the anti-patterns cause we've seen them in our career maybe in multiple times. And one of the things that I think you could see tooling do is perhaps provide some notification of anti-patterns based on the telemetry that comes in. I think it would be a really interesting place to apply, uh, machine learning and reinforcement learning techniques. Um, so hopefully something that we'd see in the future with dev ops tools, because, you know, as a manager that, that, you know, may be only a 10 year veteran or 15 year veteran, you may be seeing these anti-patterns for the first time. And it would sure be nice to know what to do, uh, when they start to pop up, >>That would right. Insight, always helpful. All right, guys, I would like to get your final thoughts on this. The one thing that you believe our audience really needs to be on the lookout for and to put on our agendas for the next 12 months, Jeff will go back to you. Okay. >>I would say look for the opportunities that this disruption presents. And there are a couple that I see, first of all, uh, as we shift to remote central working, uh, we're unlocking new pools of talent, uh, we're, it's possible to implement, uh, more geographic diversity. So, so look to that as part of your strategy. Number two, look for new types of tools. We've seen a lot of interest in usage of low-code tools to very quickly develop applications. That's potentially part of a mainstream strategy as we go into 2021. Finally, make sure that you embrace this idea that you are supporting creative workers that agile and dev ops are the peanut butter and chocolate to support creative, uh, workers with algorithmic capabilities, >>Peanut butter and chocolate Glen, where do we go from there? What are, what's the one silver bullet that you think folks to be on the lookout for now? I, I certainly agree that, um, low, low code is, uh, next year. We'll see much more low code we'd already started going, moving towards a more of a SAS based world, but low code also. Um, I think as well for me, um, we've still got one foot in the kind of cow camp. Um, you know, we'll be fully trying to explore what that means going into the next year and exploiting the capabilities of cloud. But I think the last, um, the last thing for me is how do you really instill quality throughout the kind of, um, the, the life cycle, um, where, when I heard the word scrum fall, it kind of made me shut it because I know that's a problem. That's where we're at with some of our things at the moment we need to get beyond that. We need >>To be releasing, um, changes more frequently into production and actually being a bit more brave and having the confidence to actually do more testing in production and go straight to production itself. So expect to see much more of that next year. Um, yeah. Thank you. I haven't got any food analogies. Unfortunately we all need some peanut butter and chocolate. All right. It starts to take us home. That's what's that nugget you think everyone needs to have on their agendas? >>That's interesting. Right. So a couple of days ago we had kind of a latest state of the DevOps report, right? And if you read through the report, it's all about the lost city, but it's all about sweet. We still are receiving DevOps as being all about speed. And so to me, the key advice is in order to create kind of a spiritual collocation in order to foster engagement, we have to go back to what is it we're trying to do collectively. We have to go back to tie everything to the business outcome. And so for me, it's absolutely imperative for organizations to start to plot their value streams, to understand how they're delivering value into aligning everything they do from a metrics to deliver it, to flow to those metrics. And only with that, I think, are we going to be able to actually start to really start to align kind of all these roles across the organizations and drive, not just speed, but business outcomes, >>All about business outcomes. I think you guys, the three of you could write a book together. So I'll give you that as food for thought. Thank you all so much for joining me today and our guests. I think this was an incredibly valuable fruitful conversation, and we appreciate all of you taking the time to spiritually co-located with us today, guys. Thank you. Thank you, Lisa. Thank you. Thank you for Jeff Hammond serves Lucio and Glen Martin. I'm Lisa Martin. Thank you for watching the broad cops Broadcom dev ops virtual forum.

>>from around the globe. It's the Cube with digital coverage of biz ops Manifesto unveiled Brought to you by Biz Ops Coalition >>Hey, welcome back, everybody. Jeffrey here with the Q. Come to you from our Palo Alto studios today for a big big reveal. We're excited to be here. It's the biz. Opps manifesto, unveiling things been in the works for a while and we're excited. Have our next guest one of the really the powers behind this whole effort. And he's joining us from Boston. It's surge Lucio, the vice president and general manager Enterprise software division that Broadcom Serge, Great to see you. >>Good to see. Oh, absolutely. So you've been >>in this business for a very long time? You've seen a lot of changes in technology. What is the biz Ops manifesto? What is this coalition all about? Why do we need this today in in 2020? >>Yeah, so? So I've been in this business for close to 25 years, writes about 25 years ago, the agile manifesto was created, and the goal of the actual manifesto was was really to address the uncertainty around software development and the inability to predict the effort to build software. And if you if you roll that kind of 20 years later and if you look at the current state of the industry, the Product Project Management Institute estimates that we're wasting about a million dollars every 20 seconds in digital transformation initiatives that do not deliver on business results. In fact, we we recently served, uh, the number of executives in partnership with Harvard Business Review and 77% off. Those executives think that one of the key challenges that they have is really at the collaboration between business and I t. And that that's been kind of a case for almost 20 years now. Eso the key challenge we're faced with is really that we need a new approach. And many of the players in the industry, including ourselves, have been using different terms. Right? Some are. We are talking about value stream management. Some are talking about software delivery management. If you look at the site reliability engineering movement, in many ways it embodies a lot of this kind of concepts and principles. So we believe that it became really imperative for us to crystallize around kind of one concept and so In many ways, the Bezos concept and the bazaars manifesto are out, bringing together a number of ideas which have been emerging in the last five years or so and defining the key values and principles to finally helped these organizations truly transform and become digital businesses. And so the hope is that by joining our forces and defining kind of key principles and values, we can help kind of the industry not just by, you know, providing them with support, but also tools and consulting that is required for them to truly achieve that kind of transformation, that everybody's >>right, right? So co vid Now we're six months into it, approximately seven months into it. Um, a lot of pain, a lot of bad stuff still happening. We've got a ways to go. But one of the things that on the positive side, right and you've seen all the memes and social media is a driver of digital transformation and a driver of change. Because we have this light switch moment in the middle of March and there was no more planning, there was no more conversation. You suddenly got remote. Workforce is everybody's working from home, and you gotta go, right, So the reliance on these tools increases dramatically. But I'm curious, you know, kind of short of the beginnings of this effort and short of kind of covert, which, you know, came along unexpectedly. I mean, what were those inhibitors? Because we've been making software for a very long time. Write the software development community has has adopted kind of rapid change and and iterative delivery and and sprints what was holding back the connection with the business side to make sure that those investments were properly aligned with outcomes. >>Well, so So that you have to understand that I ts is kind of its own silos. And traditionally it has been treated as a cost center within large organizations and not as a value center. And so as a result, kind of the traditional dynamic between the I t. And the business is basically one of a kind of supplier to to kind of a business on. Do you know if you could go back? Thio? I think Elon Musk a few years ago, basically, at these concepts, off the machines to build the machines and you went as far as saying that the machines or the production line is actually the product, so meaning that the core of the innovation is really about building kind of the engine to deliver on the value. And so, in many ways, way have missed on this shift from, um, kind of I t becoming this kind of value center within the enterprises and any told about culture now culture is is the sum total of behaviors and the realities that if you look at the i t, especially in the last decade with the agile with develops with hybrid infrastructures, it's it's way more volatile today than it was 10 years ago. And so the when you start to look at the velocity of the data, the volume of data, the variety of data to analyze kind of the system, um, it's very challenging for I t. To actually even understand and optimize its own processes, let alone to actually include business as kind of an integral part of kind of a delivery chain. And so it's both kind of a combination off culture which is required a za well as tools, right to be able to start to bring together all these data together and then given the volume variety velocity of the data. We have to apply some core technologies which have only really, truly emerging last 5 to 10 years around machine learning and knowledge. And so it's really kind of a combination of those freaks which are coming together today. Truly, organizations get to the next level, >>right? Right. So let's talk about the manifesto. Let's talk about the coalition, the Biz Ops Coalition. I just like that you put down these really simple you know, kind of straightforward core values. You guys have four core values that you're highlighting, you know, business outcomes over individual projects and outputs, trust and collaboration over side load teams and organizations, data driven decisions. What you just talked about, you know, over opinions and judgment on learned, responded Pivot. I mean, surgery sounds like pretty basic stuff, right? I mean, aren't isn't everyone working to these values already? And I think you touched on it on culture, right? Trust and collaboration, data driven decisions. I mean, these air fundamental ways that people must run their business today or the person that's across the street that's doing it is gonna knock him right off the block. >>Yeah, so that's very true. But so I'll mention the novel survey. We need, uh, think about six months ago and twist in partnership with an industry analyst, and we serve it again. The number of 80 executives to understand how many were tracking business outcomes somebody you have, the software executives I T executives were tracking business outcomes, and the there were. Less than 15% of these executives were actually tracking the outcomes of the software delivery. And you see that every day, right? So in my own teams, for instance, we've bean adopting a lot of these core principles in the last year or so, and we've uncovered that 16% of our resource is we're basically aligned around initiatives which were not strategic for us. I take, you know, another example. For instance, one of our customers in the airline industry uncovered, for instance, that a number of that they had software issues that led to people searching for flights and not returning any kind of availability. And yet, you know, the I T teams whether its operations software involvement were completely oblivious to that because they were completely blindsided to it. And so the connectivity between the in words metrics that Turkey is using, whether it's database I, time cycle, time or whatever metric we use in I t are typically completely divorced from the business metrics. And so at its core, it's really about starting to align the business metrics with with the the software delivered change. Right, this, uh, this system, which is really a core differentiator for these organizations. It's about connecting those two things and and starting Thio infuse some of the actual culture and principles. Um, that's emerged from the software side into the business side. Of course, the lien movement and over movements have started to change some of these dynamics on the business side. And and so I think this thesis is the moment where we were starting to see kind of the imperative to transform. Now Cuvee the obviously has been a key driver for that. The the technology is right to start to be able to leave data together and really kind of also the cultural shifts through agile fruit develops through the SRE movement, fueling business transformation. All of these things are coming together and that are really creating kind of conditions. For the Bezos Manifesto to exist. >>So, uh, Clayton Christensen, great hard professor innovator's dilemma might still my all time favorite business books, you know, talks about how difficult it is for in comments to react to to disruptive change, right, because they're always working on incremental change because that's what their customers are asking for. And there's a good our ally when you talk about, you know, companies not measuring the right thing. I mean, clearly, I t has some portion of their budget that has to go to keeping the lights on, right, that that's always the case. But hopefully that's a an ever decreasing percentage of their total activity. So, you know what should people be measuring? I mean, what are kind of the new metrics? Um, in biz ops that drive people to be looking at the right things, measuring the right things and subsequently making the right decisions investment decisions on whether they should do, you know, move Project a along or Project B. >>So there are really two things, right? So So I think what you are talking about this portfolio management, investment management, right and which, which is a key challenge, right in my own experience, right driving strategy or large scale kind of software organization for years. It's very difficult to even get kind of a base data as to who is doing what. Uh, I mean, some of our largest customers were engaged with right now are simply trying to get a very simple answer, which is how many people do I have, and that specific initiative at any point in time and just tracking that information is extremely difficult. So and and again, back to Product Project Management Institute, they have estimated that on average, I two organizations have anywhere between 10 to 20% of their resource is focused on initiatives which are not strategically aligned. So so that's one dimensional portfolio management. I think the key aspect, though that we are we're really keen on is really around kind of the alignment of the business metrics to the ICTY metrics eso I'll use kind of two simple examples, right and my background is around quality and I have always believed that fitness for purpose is really kind of a key, um, a philosophy, if you will. And so if you start to think about quality is fitness for purpose, you start to look at it from a customer point of view, right? And fitness for purpose for core banking application or mobile application are different, right? So the definition of a business value that you're trying to achieve is different on DSO the And yet if you look at our I t operations are operating there are using kind of the same type of kind of inward metrics like a database off time or a cycle time or what is my point? Velocity, right? And s o the challenge really is this inward facing metrics that the I t. Is using which are divorced from ultimately the outcome. And so, you know, if I'm if I'm trying to build a poor banking application, my core metric is likely going to be up time, right? If I'm if I'm trying to build a mobile application or maybe a social mobile app, it's probably going to be engagement. And so what you want is for everybody across I t to look at these metric and what part of the metrics withing the software delivery chain which ultimately contribute to that business metric in some cases, cycle time, maybe completely relevant. Right again. My core banking up. Maybe I don't care about cycle time. And so it's really about aligning those metrics and be able to start to differentiate. Um, the key challenge you mentioned around the around the disruption that we see is or the investors is. Dilemma now is really around the fact that many idea organizations are essentially applying the same approaches for innovation right for basically scrap work, Then they would apply to kind of over more traditional projects. And so, you know, there's been a lot of talk about to speed I t. And yes, it exists. But in reality are are really organizations truly differentiating out of the operate their their projects and products based on the outcomes that they're trying to achieve? And and this is really where bizarre is trying to affect. >>I love that. You know, again, it doesn't seem like brain surgery, but focus on the outcomes right and and it's horses for courses. As you said this project, you know what you're measuring and how you define success isn't necessarily the same as it is on this other project. So let's talk about some of the principles we talked about the values, but you know I think it's interesting that that that the bishops coalition, you know, just basically took the time to write these things down, and they don't seem all that super insightful. But I guess you just got to get him down and have them on paper and have it in front of your face. But I want to talk about, you know, one of the key ones which you just talked about, which is changing requirements right and working in a dynamic situation, which is really what's driven. You know this, the software to change and software development because, you know, if you're in a game app and your competitors comes out with a new blue sword, you've got to come out with a new blue swords. So whether you have that on your compound wall, we're not. So it's It's really this embracing of the speed of change and and and making that you know the rule, not the exception. I think that's a phenomenon. And the other one you talked about his data right and that today's organizations generate more data than humans can process. So informed decisions must be generated by machine learning and ai and you know and the big data thing with a dupe you know, started years ago. But we are seeing more and more that people are finally figuring it out that it's not just big data on It's not even generic machine learning artificial intelligence. But it's applying those particular data sets and that particular types of algorithms to a specific problem to your point, to try to actually reach an objective. Whether that's, you know, increasing the your average ticket or, you know, increasing your check out rate with with with shopping carts that don't get left behind and these types of things. So it's a really different way to think about the world in the good old days, probably when you got started, when we had big Giant you know, M R D s and P R. D s and sat down and coded for two years and and came out with a product release and hopefully not too many patches subsequently to that. Yeah, >>it's interesting right again, back to one of these service that we did with about 600 the ICTY executives and we we purposely designed those questions to be pretty open. Andi and one of them was really wrong requirements, and it was really around. Kind of. What is the best approach? What is your preferred approach towards requirements? And if I remember correctly, Over 80% of the ICTY executives said that the best approach their preferred approach is for requires to be completely defined before self for the bombing starts, let me pause there. We're 20 years after the agile manifesto, right, and for 80% of these idea executives to basically claimed that the best approach is for requires to be fully baked before solved before software development starts basically shows that we still have a very major issue again. Our apotheosis in working with many organizations is that the key challenges really the boundary between business and I t. Which is still very much contract based. If you look at the business side, they basically are expecting for I t deliver on time on budget, Right? But what is the incentive for I t to actually deliver on the business outcomes, right? How often is I t measured on the business outcomes and not on S L. A or on a budget secretary, and so that that's really the fundamental shift that we need to. We really need to drive up to send industry andi way. Talk about kind of this dis imperative for organizations to operate. That's one. And back to the, you know, various doors still, Um, no. The key difference between these large organization is really kind of a. If you look at the amount of capital investment that they can put into pretty much anything, why are they losing compared Thio? You know, startups. What? Why is it that more than 40% off personal loans today are issued not by your traditional brick and mortar banks, but by start ups? Well, the reason, Yes, it's the traditional culture of doing incremental changes, not disrupting ourselves, which Christenson covered at length. But it's also the inability to really fundamentally change kind of dynamic between business I t and partner, right, to to deliver on a specific business. All >>right, I love that. That's a great That's a great summary and in fact, getting ready for this interview. I saw you mentioning another thing where you know the problem with the agile development is that you're actually now getting mawr silos because you have all these autonomous people working you know, kind of independently. So it's even harder challenge for for the business leaders toe, as you said to know what's actually going on. But But, sir, I want to close um, and talk about the coalition eso clearly These are all great concepts, these air concepts. You want to apply to your business every day. Why the coalition? Why, you know, take these concepts out to a broader audience, including your competition and the broader industry to say, Hey, we as a group need to put a stamp of approval on these concepts. These values these principles. It's >>so first, I think we we want everybody to realize that we are all talking about the same things, the same concepts e think we were all from our own different vantage point, realizing that things have to change and again back to you know, whether it's value stream management or site reliability, engineering or biz Opps we're all kind of using slightly different languages on DSO. I think one of the important aspects of these apps is for us, all of us, whether we're talking about consulting actual transformation experts, whether we're talking about vendors right to provide sort of tools and technologies or these larger enterprises to transform for all of us to basically have kind of a reference that lets us speak around kind of in a much more consistent way. The second aspect is for to me is for these concepts to start to be embraced not just by us or trying or vendors, um, system integrators, consulting firms, educators, spot leaders but also for some of our own customers to start to become evangelists of their own in the industry. So we are. Our objective with the coalition is to be pretty, pretty broad, Um, and our hope is by by starting to basically educate our joint customers or our partners that we can start to really foster disbelievers and and start to really change some of dynamics. So we're very pleased that if you look at what some of the companies which have joined the the manifesto eso, we have vendors such as stashed up or advance or pager duty, for instance, or even planned you one of my direct competitors but also fought leaders like Tom Davenport or or Cap Gemini or smaller firms like Business Agility Institute or Agility Elf on DSO our goal really is to start to bring together. For three years, people have bean LP. Large organizations do digital transformation. Vendors were providing the technologies that many of these organizations used to deliver all these digital transformation and for all of us to start to provide the kind of education, support and tools that the industry need. >>That's great search. And, you know, congratulations to you and the team. I know this has been going on for a while putting all this together, getting people to sign onto the manifesto of putting the coalition together and finally today getting to unveil it to the world in a little bit more of a public opportunity. So again, you know, really good values, really simple principles, something that that shouldn't have to be written down. But it's nice because it is. And now you can print it out and stick it on your wall. So thank you for for sharing the story. And again, congrats to you on the team. >>Thank you. Thank you. Appreciate it. >>My pleasure. Alright, He surge If you wanna learn more about the bizarre manifesto goto biz Opps manifesto dot or greed it and you can sign it and you can stay here from or coverage on. The Cube of the bizarre manifesto unveiled. Thanks for watching. See you next time.