>> Narrator: Live from Washington D.C., it's theCUBE. Covering .conf2017. Brought to you by Splunk. >> Well welcome back here on theCUBE. We continue our coverage of .conf2017, we're in Washington D.C. Along with Dave Vellante, I'm John Walls. And Dave, you know what time it is, by the way? Just about? >> I don't know, this is the penultimate interview. >> It's almost five o'clock. >> Okay. >> And that means it's almost happy hour time. So I was thinking where might we go tonight, so-- >> There's an app for that. >> There was, and so I looked. It turns out that the Penny Whiskey Cafe is just two tenths of a mile from here. And you know how I knew that? >> How's the ratings on that? >> We got four. >> Four and half with 52. >> 52 reviews? >> Yeah, I feel good about that. >> Yeah, that's pretty good. That's a substantive base. >> I feel very solid with that one. We'll make it 53 in about a half hour. Of course I found it on Yelp. We have a couple of gentlemen from Yelp with us tonight. I don't have to tell you what Yelp does, it does everything for everybody, right. Zach Musgrave, technical lead, and Chris Gordon, software engineer at Yelp. Gentlemen, thanks for being here. And U can join us, by the way, later on, at the Penny Whiskey if you'd like to. First off, what are you doing here, right, at Splunk? What's Yelp and Splunk, what's that intersection all about? Zach, if you would. >> Sure, well Yelp uses Splunk for all sorts of purposes. Operational, intelligence, business metrics, pretty much any sort of analytics from event driven data that you can really think of, Yelp has found a way, and our engineers have found a way to get that into Splunk and derive business value from it. So Chris and I are actually here, we just gave a breakout session at .conf, talking about how we find strong business value and how we quantify that value and mutate our Splunk cluster to really drive that. >> Okay. >> So, so how do you find value then, I mean, what was? >> It's hard. Chris was one of the people who really, really drove this for us. And when we looked at this, you know I once had an engineer who came up to our team, we maintain Splunk amongst other things, and the engineer said can I ingest 10 terabytes of data a day into Splunk and then keep it forever? And I said, um, please don't. And then we talked a bit more about what that engineer was actually trying to do and why they needed this massive amount of data, and we found a better way that was much more efficient. And then where we didn't need to keep all the data forever. So, by being able to have those conversations and to quantify with the data you're already ingesting into Splunk, being able to quanitfy that and actually show how many people were searching this, how's it being used, what's the depth of the search look like, how far back are they looking in time. You can really optimize your Splunk cluster to get a lot more business value than just naively setting it up and turning it on. >> So you weren't taking a brute force approach, you were smarter about that, but you weren't deduping, you were identifying the data that was not necessary to keep, did I get that right? >> Correct. Yeah, we essentially kind of identified what are highest cost per search logs, which we basically just totaled up how many times each log was searched, and then tried to quantify how much each logs was costing us. And then this ended up being a really good metric for figuring out what we'd want to remove or something that was a candidate for dislodging the data somehow. >> So, you guys gave a talk today. We were talking off camera about pricing, that's not something you guys get involved in, but I would categorize this as sort of how do you get the most out of that asset, called Splunk, right. Is that sort of the >> Exactly. >> theme of your talk, right? >> Yeah. We talk a lot about expected value amongst our team, and in the talk we just gave. And we don't ever think about this as, oh do this so that you can spend less money on Splunk or on your infrastructure that's backing Splunk. Think about is more as we have this right now and we can utilize it more effectively. We can get more value out of what we already have. >> Okay, so, I wonder if we could just talk a little bit about your environment. We know you run on AWS. How does that cloud fit in with Splunk, paint a picture for us, if you would. What does it all look like? >> Yeah, so we have two clusters actually. One is the high value, high quality of service cluster, it's the larger generic, we call it generic prod, and then we have another one, where we kind of have our more verbose, maybe slightly less valuable per log cluster. And this runs on a D2, which is just instant storage. And then the higher performance cluster runs all on a GP2. So it's basically just SSDs. And we also do, we also have four copies of each log and we have two searchable copies of each log, so it's pretty well replicated. >> Dave: Okay, so that's how you protect the data. >> Yeah. >> Is to make copies, in what, in different zones, or? >> Yeah, we have two copies of each log in each availability zone, and then one searchable copy of each log in each availability zone. >> And you guys are cloud natives, all cloud, just out of school and graduate school. So you talked about infrastructure as code. You don't do any of that on-prem stuff, you're not like installing gear. And so it's not part of your lexicon, right? >> No. >> Okay. So I want to do a little editorial thing. Kristen Nicole, our managing editor, sent the note around today saying 101s get the best traffic on the website. So I want to do a little DevOps 101, okay. Even though, it's second nature to you, and a lot of people in our audience know what it is. How do you describe DevOps? Give us the 101 on DevOps. >> Okay so, DevOps is a complicated thing, but and occasionally you see it as like a role on like a job board or something. And that always strikes me as odd, because it's not really a role. Like it's a philosophy moreso. The way that I always see it, is it used to be like pre DevOps, was the software developers make a thing, and then they throw it over the fence, and operations just picks it up. And they're like well what do we do with this, and deploy it, okay, good luck. And so with this result in a sort of an us against them mentality, where the developers aren't incentivized to really make it resilient, or really document it well, and operations and the sys admins are not incentivized to really be flexible and to be really hard charging and move quickly, because they're the ones who are going to be on call for whatever the developers made. DevOps is a we, instead of an us verses them. So for example, product teams have an on-call rotation. Operations and sys admins write code. There are still definitely specializations, but it all comes together in a much more holistic manner. >> Okay, and the ops guys will write code, as opposed to hacking code, messing up your code, throwing it back over the fence, and saying hey your code doesn't work. >> Exactly. >> And then you say well it worked when I gave it to you. And then like you said that sort of finger pointing. >> We are totally done with works on my machine, it's over. No more. >> Okay, and the benefits obviously are higher quality, faster time to market, less food fighting. >> Yup, exactly. In the old model you'd have a new deployment of like a website like maybe once a week or maybe even once a month. Yelp deploys multiple times everyday over and over again. And each one of those is going to include changes from a dozen different engineers. So we need to be agile in that manner, just like with our Splunk cluster. >> I mean you guys are relatively new, four years and two years, perspectively. But these days it's a long time. How would you describe your Splunk journey. Where did it start and where do you want to take it? >> I would say it started, you actually had Kris Wehner on here last year, and he talked a lot about it. He was the VP of engineering at SeatMe. And he kind of got Yelp onto the whole Splunk train. And at that point it was used mostly by SeatMe and everyone at Yelp was like oh this is fantastic, we want to use this. And we started basically migrating it to our VPC. And have generally, we're starting to now get everything going, get all the kinks worked out, and really now we're trying to see where we can provide the most value and make things as easy as possible for our developers to add logs and add searches and get what they need out of it. >> So what kind of use cases are you envisioning, and where are you getting value out of it? >> So we have our operations teams get a lot of value out of it when there's some outage happening. And it's really useful for them to be able to just look at the access logs and see what's going on. And Splunk makes that very easy. And we also get a lot of value out of Yelp's application logs. Splunk has been great for figuring out when something's not right. And allowing us to dig in further. >> So yeah, at the end of the day, as consumers, what does this mean to us, ultimately? Like our searches are faster, searches are more refined, searches are more accurate? What does it mean to me at the end of the day that you're enabling what activity through this technology. >> Dave: Yeah, it'll be more secure? >> Yeah, what does it mean? >> As an end user of Yelp? >> Yes. >> So, I'll give you one example that always sticks out in my mind. So I don't know if you all know this, but you can actually do things like order food via Yelp, you can make appointments via Yelp, even with like a dentist. You can beauty appointments, all sorts of personal services. >> Hair salon came up today actually, when I was looking for a bar. >> Absolutely. That's not supposed to happen. >> Dave: Well that was the Penny Whiskey Cafe. >> You never know, but what ever's next door I don't know. >> Can you get a haircut while you drink? >> Hair salons in the District are pretty impressive. >> I wasn't planning on it, no. But anyway, I'm sorry. >> Anyway, so we work with a lot of external partners to enable all these different integrations, right. So you press start order, and then eventually you see the menu, and then you add some stuff to your cart, and then you have to pay. And so if you haven't given us your credit card information yet, then you have to enter that, and that has to go to a payment processor, the order of course has to go out to the partner who's going to fulfill your order, and so on. So there's this pipeline of many different micro services plus the main Yelp application, plus this partner who's actually fulfilling your order, plus the payment processor, and so on, and so on. And it ends up with this really complicated state machine. So the way that actually works under the hood, to be very simplistic, is there's a unique order identifier that is assigned to you when you start the order. And then that passed through the whole process. So at every step in this process a bunch of events are emitted out of the various parts of the pipeline and into Splunk, where they're then matched to show that your order is progressing. And the order didn't get stuck. Because you know what's really sad is when you order food and it doesn't show up. So we really have to guard against that. >> Yeah, we hate that. >> Yeah, everybody does. So it's really important that we're able to unify this data, from all these different places, Splunk's really great for that, and to be able to then alert on that and page somebody and say hey, something's not quite right here, we have hungry folks. >> So while I have the smartest guys that we've interviewed all week here, you mentioned, >> Please. You mentioned, aw shucks, I know. You mentioned state machine. Are you playing around with functional programming, so called server lists, probably don't like that word either, but what are you doing there? Are you finding sort of new applications in use cases for so called server lists? >> I would say not so much. I don't know, is anyone at Yelp doing that? >> Yeah, there's some Lambda stuff going on. Like core back end is doing that work right now. A lot of our infrastructure is actually build up before the AWS Lambdas were a thing. So we found other ways to do that, and we have this really cool internal platform as a service, it's a docker, and some scheduling stuff on top of that. So a lot of things, like it's really easy to just launch a batch job in there. And it takes away some of the need for the true server lists. >> Well the reason I ask is because people are saying a lot of the state list IoT apps are going to use that sort of Lambda or homegrown stuff. And I'm not sure what the play is for Yelp in Internet of Things. I would imagine there's actually a play there for you guys though, and I'm curious as to the data angle, and maybe where Splunk might fit in. >> I'm certain that we're going to be using Splunk to read data from all of those different components as they're being launched. I know that there's been a couple early forays into the Lambda space that I've seen go by in code reviews and everything. But of course, with Splunk itself we can get data out of those. So as that happens, like we already have all our pipe lining set up. And it'll be pretty easy for them to analyze their self with Splunk. >> What gets you young folks excited these days? What keeps you enthralled and passionate? What do you look for? >> I don't know I think just in general anything that empowers you to get a lot done without having to fight it constantly. And general DevOps tools have been getting really good at that recently. And yeah, I would say anything that empowers you, gives you the feeling that you can do anything really. >> Yeah, all of the infrastructure is code stuff that's going on right now. So one of the pipelines that we use to get data out of Amazon S3, but it passes notifications through this S3 event notifications to Amazon SNS, to Amazon SQS, to our Splunk forwarders. And so that's a very complicated pipeline. And you have to set it all up, it works really well, but here's the cool part. That's all defined in code. And so this means that if you set up a new integration there's a code review. And we have some verification and validation that it's correct. And furthermore, if anything goes wrong with it, we can just hit a button and it recreates itself. That's what gets me happy. When tools get in my way that's not so good. >> Well and it just leaves more time for higher value activities and that's exciting. the transformation in infrastructure over the last five years has just been mind boggling. So, thanks you guys. >> It does. It does give me a lot of pleasure when something can go catastrophically wrong, and then just like, oh wait, it's self healing, all it can take is give three plays fine. And we're all dandy. >> Well to Dave's point, while I was off camera I did a search on the two smartest guys in the room. And it said one is six feet away the other one is seven feet away, so Yelp works, I mean it really does. But thanks for the time. It's been interesting. Next generation, right? So far over us. >> Yeah, I know. It's kind of depressing, but I love it. (laughing) >> Very good, thanks guys. >> Thank you so much. >> Back with more, here on theCUBE at .conf2017. We are live, Washington D.C. >> Dave: I've kind of had it with millennial. (upbeat music)

>> Announcer: Live from Las Vegas, it's theCube. Covering Veritas Vision 2017. Brought to you by Veritas. >> Welcome back to Las Vegas everybody, this is theCube, the leader in live tech coverage. This is day one of two day coverage of Veritas Vision #VtasVision. My name is Dave Vellante, and I'm here with my co-host Stu Miniman. Zach Bosin is here. He's the director of information governance solutions at Veritas. And Anna Simpson is a distinguished systems engineer at Veritas. Which Anna means you know where all the skeletons are buried and how to put the pieces back together again. Welcome to theCube, thanks for coming on. >> Thank You. >> Thank You. >> Let's start with, we've heard a little bit today about information governance, Zach we'll start with you. It's like every half a decade or so every decade, there's a new thing. And GDPR is now the new thing. What's the state of information governance today? How would you describe it? >> I think the primary problem that organizations are still trying to fight off, is exponential data growth. We release research every year called the Data Genomics Index, and what came back this past year is that data growth has continued to accelerate, as a matter of fact, 49% year over year. So this problem isn't going anywhere and now it's actually being magnified by the fact that data is being stored, not only in the data center on premises, but across the multi-cloud. So information governance, digital compliance is all about trying to understand that data, control that data, put the appropriate policies against it. And that's really what we try to do with helping customers. >> I always wonder how you even measure data. I guess you could measure capacity that leaves the factory. There's so much data that's created that's not even persistent. We don't even know, I think, how fast data is growing. And it feels like, and I wonder if you guys agree or have any data suggestions, it feels like the curve is reshaping. I remember when we were talking to McAfee and Brynjolfsson it feels the curve is just going even more exponential. What's your sense? >> That's typically what we see. And then you have IoT data coming online, faster and faster and it really is a vertical shot up. And all different types and new files types. One of the other really interesting insights, is that unknown file types jumped 30-40%. Things that we don't even recognize with our file analysis tools today, are jumping off the charts. >> It used to be that PST was the little nag, it looks trivial compared to what we face today, Anna. What's your role as a distinguished systems engineer? How do you spend your time? And what are you seeing out there? >> I definitely spend my time dealing with customers around the world. Speaking to them about information governance. Particularly around risk mitigation these day. In terms of the issues we see in information governance, data privacy is a big one. I'm sure you've been hearing about GDPR quite a bit today already. That's definitely a hot topic and something our customers are concerned about. >> Are they ringing you up saying, "Hey, get in here. "I need to talk you about GDPR?" Or is more you going in saying, "You ready for GDPR? How does that conversation go? >> It's definitely a combination between the two. I think there is definitely a lot of denial out there. A lot of people don't understand that it will apply to them. Obviously if they are storing or processing data which belongs to an EU resident, containing their personal data. I think organizations are either in that denial phase or otherwise they're probably too aware, so they've probably started a project, done some assessment, and then they're buried in the panic mode if we have to remediate all these issues before May next year. >> What's the bell curve look like? Let's make it simple. One is, "we got this nailed." That's got to be tiny. The fat middle which is "we get it, we know it's coming, "we got to allocate some budget, let's go." Versus kind of clueless. What's the bell curve look like? >> I would say that there's 2% of companies, maybe, that think they have it nailed. >> Definitely in single digits, a low single digits. >> I think maybe another 30% at least understand the implications and are trying to at least but a plan in place. And the rest, 66% or so, still aren't very aware of what GDPR means for their business. >> Dave: Wow. >> Can you take us inside? what's Veritas's role in helping customers get ready for GDPR? We talked to one of Veritas's consulting partners today and it's a big issue, it crosses five to ten different budget areas. So what's the piece that Veritas leads and what's the part that you need to pull in other partners for? >> Sure thing. So in terms of our approach, we have what we refer to as a wheel. Which sort of attacks different parts of the GDPR, so various articles step you through the processes you need to be compliant. Things like locating personal data, being able to search that data, minimizing what you have, because GDPR is really dictating you can no longer data hoard, because you can only keep data which has business value. Further downstream it's obviously protecting the data that has business value, and then monitoring that over time. From a Veritas approach perspective, we tying those articles obviously to some of our products, some of our solutions. There's also definitely a services component around that as well. When you think about e-discovery of regulatory requirements, when the regulators come in, generally they're not necessarily going to be questioning the tools, they're going to be questioning how you're using those tools to be compliant. It is sort of a combination between tools and services. And then we're also partnering with other consulting companies on that process piece, as well. Zach, at the keynote this morning, there was a lot of discussion about there's dark data out there, and we need to shine a light on it I have to imagine that's a big piece of this. Why don't you bring us up to speed. What are some of the new products that were announced that help with this whole GDRP problem. >> In to that point, 52% of data is dark, 33% is rot, 15% is mission critical. Today we announced 23 new connectors for the Veritas information map. This is our immersive visual data mapping tool, that really highlights where you're stale, and orphaned, and non-business critical data is across the entire enterprise. New connectors with Microsoft as your Google Cloud storage, Oracle databases, so forth and so on, there's quite a number that we're adding into the fold. That really gives organizations better visibility into where risk may be hiding, and allows you to shine that light and interrogate that data in ways you couldn't do previously because you didn't have those types of insights. >> Also we heard about Risk Analyzer? >> Yes, that's right. We just recently announced the Veritas Risk Analyzer, this is a free online tool, where anyone can go to Veritas.com/riskanalyzer, take a folder of their data, and try out our brand new integrated classification engine. We've got preset policies for GDPR, so you drop in your files, and we'll run the classification in record speed, and it will come back with where PII is, how risky that folder was, tons of great insights. >> So it's identifying the PII, and how much there is, and how siloed it is? Are you measuring that? What are you actually measuring there? >> We're actually giving you a risk score. When we're analyzing risk, you might find one individual piece of PII, or you might find much more dense PII. So depending on the number of files, and the types of files, we'll actually give you a different risk tolerance. What we're doing with the Risk Analyzer is giving you a preview, or just a snapshot of the types of capabilities that Veritas can bring to that discussion. >> Who do you typically talk to? Is it the GC, is it the head of compliance, chief risk officer, all of the above? >> Yeah, it's definitely all of the above-- >> Some person who has a combination of those responsibilities, right? >> Yeah, exactly. It's usually, if we're talking GDPR specifically, it's usually information security, compliance, legal, and particularly in organizations now, we're definitely seeing more data privacy officers. And they're the ones that truly understand what these issues are; GDPR or other personal data privacy regulations. >> Let's say I'm the head of compliance security risk information governance, I wear that hat. Say I'm new to the job, and I call you guys in and say, "I need help." Where do I start? Obviously you're going to start with some kind of assessment Maybe you have a partner to help you do that, I can run my little risk analyzer, sort of leech in machine, and that's good but that's just scratching the surface. I know I have a problem. Where do we start? What are the critical elements? And how long is it going to take me to get me where I need to be? >> I think visibility is obviously the first step, which Zach already spoke to. You really have to be able to understand what you have to then be able to make some educated decisions about that. Generally that's where we see the gap in most organizations today. And that's particularly around unstructured data. Because if it's structured, generally you have some sort of search tools that you can quickly identify what is within there. >> To add on to that, you actually have 24 hours. We can bring back one hundred million items using the information map, so you get a really clean snapshot in just one day to start to understand where some of that risk may be hiding. >> Let's unpack that a little bit. You're surveying all my data stores, and that's because you see that because you've got the back-up data, is that right? >> The backup data is one portion of it. The rest is really coming from these 23 new connectors into those different data stores and extracting and sweeping out that metadata, which allows us to make more impactful decisions about where we think personal data may be, and then you can take further downstream actions using the rest of our tool kit. >> And what about distributed data on laptops, mobile devices, IoT devices, is that part of the scope, or is that coming down the road, or is it a problem to be solved? >> It's a little out of scope for what we do. On the laptop/desktop side of things, we do have e-discovery platform, formally known as Clearwell, which does have the ability to go out and search those types of devices and then you could be doing some downstream review of that data, or potentially moving it elsewhere. It's definitely a place we don't really play right now. I don't know if you had other comments? >> You got to start somewhere. Start within your enterprise. This has always been a challenge. We were talking off camera about FRCP and email archiving. I always thought the backup ... The back company was in a good spot. They analyzed that data. But then there's the but. Even these are backed up, kind of, laptops and mobile devices. Do you see the risk and exposures in PII really at the corporate level, or are attorneys going to go after the processes around distributed data, and devices, and the like? >> I think anything is probably fair game at this point given that GDPR isn't being enforced yet. We'll have to see how that plays out. I think the biggest gap right now, or the biggest pain point for organizations, is on structured data. It kind of becomes a dumping ground and people come and go from organizations, and you just have no visibility into the data that's being stored there. And generally people like to store things on corporate networks because it gets backed up, because it doesn't get deleted, and it's usually things that probably should not be stored there. >> If I think back to 2006, 2007 time frame with Federal Rules of Civil Procedure, which basically said that electronic information is now admissible. And it was a high profile case, I don't want to name the name because I'll get it wrong, but they couldn't produce the data in court, the judge penalized them, but then they came back and said, "We found some more data. "We found some more data. "We found some more data." Just an embarrassment. It was one hundred million dollar fine. That hit the press. So what organizations did, and I'm sure Anna you could fill in the gaps, they basically said, "Listen, "it's an impossible problem so we're going to go after "email archiving. "We're going to put the finger in the dyke there, "and try to figure the rest of this stuff out later." What happened is plaintiff's attorney's would go after their processes and procedures, and attack those. And if you didn't have those in place, you were really in big trouble. So what people did is try to put those in place. With GDPR, I'm not sure that's going to fly. It's almost binary. If somebody says, "I want you to delete my data," you can't prove it, I guess that's process-wise, you're in trouble, in theory. We'll see how it holds up and what the fines look like, but it sounds like it's substantially more onerous, from what we understand. Is that right? >> Yes, I would 100% agree. From an e-discovery standpoint, there's proportionality and what's reasonable relative to the cost of the discovery and things like that. I actually don't think that that is going to come into play with GDPR because the fines are so substantial. I don't know what would be considered unreasonable to go out and locate data. >> Zach you have to help us end this on an up note. (group laughs) >> Dave: Wait, I wanted to keep going in to the abyss. (group laughs) We've talk about the exponential growth of data, and big data was supposed to be that bit-flip ... of turned it for, "Oh my God, I need to store it "and do everything, I need to be able to harness it "and take advantage of it" Is GDPR an opportunity for customers, to not only get their arms around information, but extract new value from it? >> Absolutely. It's all about good data hygiene. It's about good information governance. It's about understanding where your most valuable assets are, focusing on those assets, and getting the most value you can from them. Get rid of the junk, you don't need that. It's just going to get you into trouble and that's what Veritas can help you do. >> So a lot of unknowns. I guess the message is, get your house in order, call some experts. I'd call a lot of experts, obviously Veritas. We had PWC on earlier today, and a number of folks in your ecosystem I'm sure can help. Guys, thanks very much for coming on theCube and scaring the crap out of us. (group laughs) >> Thanks a lot. >> Alright, keep it right there buddy, we'll be back for our wrap, right after this short break. (light electronic music)

>>From around the globe. If the cube with digital coverage of AWS reinvent 20, 20 special coverage sponsored by AWS worldwide public sector. >>Okay. Welcome back everyone. To the cubes, virtual coverage of AWS reinvent 2020, this is the cube virtual. I'm your host John farrier with the cube. The cube normally is there in person this year. It's all virtual. This is the cube virtual. We're doing the remote interviews and we're bringing in commentary and discussion around the themes of re-invent. And this today is public sector, worldwide public sector day. And the theme from Teresa Carlson, who heads up the entire team is to think big and look at the data. And I wanted to bring in a special cube alumni and special guests. Alan Cohen. Who's a partner at data collective venture capital or DCVC, um, which we've known for many, many years, founders, Matt OCO and Zachary Bogue, who started the firm, um, to over at about 10 years ago. We're on the really the big data wave and have grown into a really big firm thought big data, data, collective big ideas. That's the whole purpose of your firm. Alan. You're now a partner retired, retired, I mean a venture capitalist over at being a collective. Great to see you. Thanks for coming on. >>Great to see you as well. John, thanks for being so honest this morning. >>I love to joke about being retired because the VC game, it's not, um, a retirement for you. You guys made, you made some investments. Data collective has a unique, um, philosophy because you guys invest in essentially moonshots or big ideas, hard problems. And if I look at what's going on with Amazon, specifically in the public sector, genome sequencing now available in what they call the open data registry. You've got healthcare expanding, huge, you got huge demand and education, real societal benefits, uh, cybersecurity contested in space, more contention and congestion and space. Um, there's a lot of really hard science problems that are going on at the cloud. And AI are enabling, you're investing in entrepreneurs that are trying to solve these problems. What's your view of the big ideas? What are people missing? >>Well, I don't know if they're missing, but I think what I'd say, John, is that we're starting to see a shift. So if you look at the last, I don't know, forever 40, 50 years in the it and the tech industry, we took a lot of atoms. We built networks and data warehouses and server farms, and we, we kind of created software with it. So we took Adam's and we turned them into bets. Now we're seeing things move in the other direction where we're targeting bits, software, artificial intelligence, massive amount of compute power, which you can get from companies like, like AWS. And now we're creating better atoms. That means better met medicines and vaccines we're investor, um, and a company called abs Celera, which is the therapeutic treatment that J and J has, um, taken to market. Uh, people are actually spaces, a commercial business. >>If it's not a science fiction, novel we're investors in planet labs and rocket labs and compel a space so people can see right out. So you're sitting on your terrorists of your backyard from a satellite that was launched by a private company without any government money. Um, you talked about gene sequencing, uh, folding of proteins. Um, so I think the big ideas are we can look at some of the world's most intractable issues and problems, and we can go after them and turn them into commercial opportunities. Uh, and we would have been able to do that before, without the advent of big data and obviously the processing capabilities and on now artificial intelligence that are available from things like AWS. So, um, it's kind of, it's kind of payback from the physical world to the physical world, from the virtual world. Okay. >>Pella space was featured in the keynote by Teresa Carlson. Um, great to tie that in great tie in there, but this is the kind of hard problems. And I want to get your take because entrepreneurs, you know, it reminds me of the old days where, you know, when you didn't go back to the.com, when that bubble was going on, and then you got the different cycles and the different waves, um, the consumer always got the best kind of valuations and got the most attention. And now B to B's hot, you got the enterprise is super hot, mainly because of Amazon >>Sure. Into the Jordash IPO. Obviously this morning, >>Jordache IPO, I didn't get a phone call for friends and family and one of their top customers. They started in Palo Alto. We know them since the carton Jordache, these are companies that are getting massive, uh, zoom. Um, the post pandemic is coming. It's going to be a hybrid world. I think there's clear recognition that this some economic values are digital being digitally enabled and using cloud and AI for efficiencies and philosophy of new things. But it's going to get back to the real world. What's your, it's still hard problems out there. I mean, all the valuations, >>Well, there's always hard problems, but what's different now. And from a perspective of venture and, and investors is that you can go after really hard problems with venture scale level of investments. Uh, traditionally you think about these things as like a division of a company like J and J or general electric or some very massive global corporation, and because of the capabilities that are available, um, in the computing world, um, as well as kind of great scientific research and we fund more PhDs probably than any other, uh, any other type of background, uh, for, for founders, they can go after these things, they can create. Uh, we, uh, we have a company called pivot bio, uh, and I think I've spoken to you about them in the past, Sean, they have created a series of microbes that actually do a process called nitrogen fixation. Um, so it attaches the nitrogen to the roots of corn, sorghum and wheat. >>So you don't have to use chemical fertilizer. Well, those microbes were all created through an enormous amount of machine learning. And where did that machine learning come from? So what does that mean? That means climate change. That means more profitable farmers. Uh, that means water and air management, all major issues in our society where if we didn't have the computing capabilities we have today, we wouldn't have been able to do that. We clearly would have not been able to do that, um, as a venture level of investments to get it started. So I think what's missing for a lot of people is a paucity of imagination. And you have to actually, you know, you actually have to take these intractable problems and say, how can I solve them and then tear it apart to its actual molecules, just the little inside joke, right? And, and then move that through. >>And, you know, this means that you have to be able to invest in work on things. You know, these companies don't happen in two or three years or five years. They take sometimes seven, 10, 15 years. So it's life work for people. Um, but though, but we're seeing that, uh, you know, that everywhere, I mean, rocket lab, a company of ours out of New Zealand and now out of DC, which we actually launched the last couple of space, um, satellites, they print their rocket engines with a 3d printer, a metal printer. So think about that. How did all that, that come to bear? Um, and it started as a dangerous scale style of investments. So, you know, Peter Beck, the founder of that company had a dream to basically launch a rocket, you know, once a year, once a month, once a week, and eventually to once a day. So he's effectively creating a huge, um, huge upswing in the ability of people to commercialize space. And then what does space do? It gives you better observability on the planet from a, not just from a security point of view, but from a weather and a commerce point of view. So all kinds of other things that looked like they were very difficult to go after it now starts to become enabled. Yeah. >>I love the, uh, your investment in Capella space because I think that speaks volumes. And one of the things that the founder was talking about was getting the data down is the hard part. He he's up, he's up there now. He can see everything, but now I've got to get the data down because say, say the wildfires in California, or whether, um, things happening around the globe now that you have the, uh, the observation space, you got to get the data down there. This is the huge scale challenge. >>Well, let me, let me, let me give you something. That's also, so w you know, we are in a fairly difficult time in this country, right? Because of the covert virus, uh, we are going to maybe as quickly as next week, start to deliver, even though not as many as we'd like vaccines and therapeutics into this virus situation, literally in a year, how did all these things, I mean, obviously one of the worst public health crisis of our lifetimes, and maybe, you know, uh, of the past century, uh, how did that happen? How did it all day? Well, you know, some, I mean, the ability to use, um, computing power in, in assistance, in laboratory, in, in, uh, in, um, development of, of pharmaceutical and therapeutics is a huge change. So something that is an intractable problem, because the traditional methods of creating vaccines that take anywhere from three to seven years, we would have a much worse public health crisis. I'm not saying that this one is over, right. We're in a really difficult situation, but our ability to start to address it, the worst public health crisis in our lifetime is being addressed because of the ability of people to apply technology and to accelerate the ability to create vaccines. So great points, absolutely amazing. >>Let's just, let's just pause that let's double down on that and just unpack that, think about that for a second. If you didn't, and then the Amazon highlight is on Andy Jesse's keynote carrier, which makes air conditioning. They also do refrigeration and transport. So one IOT application leveraging their cloud is they may call it cold chain managing the value chain of the transport, making sure food. And in this case vaccine, they saw huge value to reduce carbon emissions because of it does the waste involved in food alone was a problem, but the vaccine, they had the cold, the cold, cold, cold chain. Can you hear me? >>Maybe this year, the cold chain is more valuable than the blockchain. Yeah. >>Cold don't think he was cold chain. Sounds like a band called play. Um, um, I had to get that in and Linda loves Coldplay. Um, but if you think about like where we are to your point, imagine if this hit 15 years ago or 20 years ago, um, you know, YouTube was just hitting the scene 20 years ago, 15 years ago, you know, so, you know, that kind of culture, we didn't have zoom education would be where we would be Skyping. Um, there's no bandwidth. So, I mean, you, you know, the, the bandwidth Wars you would live through those and your career, you had no bandwidth. You had no video conferencing, no real IOT, no real supply chain management and therapeutics would have taken what years. What's your reaction to, to that and compare and contrast that to what's on full display in the real world stage right now on digital enablement, digital transformation. >>Well, look, I mean, ultimately I'm an optimist because of what this technology allows you to do. I'm a realist that, you know, you know, we're gonna lose a lot of people because of this virus, but we're also going to be able to reduce a lot of, um, uh, pain for people and potentially death because of the ability to accelerate, um, these abilities to react. I think the biggest and the, the thing that I look for and I hope for, so when Theresa says, how do you think big, the biggest lesson I think we're going to we've learned in the last year is how to build resilience. So all kinds of parts of our economy, our healthcare systems, our personal lives, our education, our children, even our leisure time have been tested from a resilience point of view and the ability of technology to step in and become an enabler for that of resilience. >>Like there isn't like people don't love zoom school, but without zoom school, what we're going to do, there is no school, right? So, which is why zoom has become an indispensable utility of our lives, whether you're on a too much, or you've got zoom fatigue, does it really matter the concept? What we're going to do, call into a conference call and listen to your teacher, um, right in, you know, so how are you going to, you're going to do that, the ability to repurpose, um, our supply chain and, you know, uh, we, we, we see this, we're going to see a lot of change in the, in the global supply chain. You're going to see, uh, whether it's re domestication of manufacturing or tightening of that up, uh, because we're never going to go without PPE again, and other vital elements. We've seen entire industries repurposed from B2B to B to C and their ability to package, deliver and service customers. That is, those are forms of resilience. >>And, and, and, and taking that to the next level. If you think about what's actually happening on full display, and again, on my one-on-one with Andy Jassy prior to the event, and he laid this out on stage, he kind of talks about this, every vertical being disrupted, and then Dr. Matt wood, who's the machine learning lead there in Swami says, Hey, you know, cloud compute with chips now, and with AI and machine learning, every industry, vertical global industry is going to be disrupted. And so, you know, I get that. We've been saying that in the queue for a long time, that that's just going to happen. So we've been kind of on this wave of horizontal, scalability and vertical specialization with data and modern applications with machine learning, making customization really high-fidelity decisions. Or as you say, down to the molecule level or atomic level, but this is clear what, what I found interesting. And I want to get your thoughts because you have one been there, done that through many ways of innovation and now investor leading investor >>Investor, and you made up a word. I like it. Okay. >>Jesse talks about leadership to invent and reinvent. Can't fight gravity. You've got to get talent hungry for invention, solve real-world problems. Speed. Don't complexify. That's his message. I said to him, in my interview, you need a wartime conciliary cause he's a big movie buff. I quote the godfather. Yeah. Don't you don't want to be the Tom Hagen. You don't want to be that guy, right? You're not a wartime. Conciliary this is a time there's times in companies' histories where there's peace and there's wartime, wartime being the startup, trying to find its way. And then they get product market fit and you're growing and scaling. You're operating, you're hiring people to operate. Then you get into a pivot or a competitive situation. And then you got to get out there and, and, and get dirty and reinvent or re-imagine. And then you're back to peace. Having the right personnel is critical. So one of the themes this year is if you're in the way, get out of the way, you know, and some people don't want to hold on to hold onto the past. That's the way we did it before I built this system. Therefore it has to work this way. Otherwise the new ways, terrible, the mainframe, we've got to keep the mainframe. So you have a kind of a, um, an accelerated leadership, uh, thin man mantra happening. What is your take on this? Because, >>Sorry. So if you're going to have your F R R, if you're going to, if you are going to use, um, mob related better for is I'll share one with you from the final season of the Soprano's, where Tony's Prado is being hit over the head with a bunch of nostalgia from one of his associates. And he goes, remember, when is the lowest form of conversation and which is iconic. I think what you're talking about and what Andy is talking about is that the thing that makes great leadership, and what I look for is that when you invest in somebody or you put somebody in a leadership position to build something, 50% of their experience is really important. And 50% of it is not applicable in the new situation. And the hard leadership initiative has to understand which 50 matters in which 50 doesn't matter. >>So I think the issue is that, yeah, I think it is, you know, lead follow or get out of the way, but it's also, what am I doing? Am I following a pattern for a, for a, for an, a, for a technology, a market, a customer base, or a set of people are managing that doesn't really exist anymore, that the world has moved on. And I think that we're going to be kind of permanent war time on some level we're going to, we're going to be co we're because I think the economy is going to shift. We're going to have other shocks to the economy and we don't get back to a traditional normal any time soon. Yep. So I, I think that is the part that leadership in, in technology really has to, would adopt. And it's like, I mean, uh, you know, the first great CEO of Intel reminded us, right. Then only the paranoid survive. Right. Is that it's you, some things work and some things don't work and that's, that's the hard part on how you parse it. So I always like to say that you always have to have a crisis, and if there is no crisis, you create the crisis. Yeah. And, you know, >>Sam said, don't let a good crisis go to waste. You know? Um, as a manager, you take advantage of the crisis. >>Yeah. I mean, look, it wouldn't have been bad to be in the Peloton business this year. Right, too. Right. Which is like, when people stayed home and like that, you know, you know, th that will fade. People will get back on their bikes and go outside. I'm a cyclist, but you know, a lot more people are going to look at that as an alternative way to exercise or exercising, then when it's dark or when the weather is inclement. So what I think is that you see these things, they go in waves, they crest, they come back, but they never come back all the way to where they were. And as a manager, and then as a builder in the technology industry, you may not get like, like, like, okay, maybe we will not spend as much time on zoom, um, in a year from now, but we're going to still spend a lot of time on zoom and it's going to still be very important. >>Um, what I, what I would say, for example, and I, and looking at the COVID crisis and from my own personal investments, when I look at one thing is clear, we're going to get our arms around this virus. But if you look at the history of airborne illnesses, they are accelerating and they're coming every couple of years. So being able to be in that position to, to more react, more rapidly, create vaccines, the ability to foster trials more quickly to be able to use that information, to make decisions. And so the duration when people are not covered by therapeutics or vaccines, um, short, and this, that is going to be really important. So that form of resilience and that kind of speed is going to happen again and again, in healthcare, right. There's going to be in, you know, in increasing pressure across that in part of the segment food supply, right. I mean, the biggest problem in our food supply today is actually the lack of labor. Um, and so you have far, I mean, you know, farmers have had a repurpose, they don't sell to their traditional, like, so you're going to see increased amount of optimization automation and mechanization. >>Lauren was on the, um, keynote today talking about how their marketplaces collected as a collective, you know, um, people were working together, um, given that, given the big ideas. Well, let's, let's just, as we end the segment here, let's connect big ideas. And the democratization of, I mean, you know, the old expression Silicon Valley go big or go home. Well, I think now we're at a time where you can actually go big and stay and, and, and be big and get to be big at your own pace because the, the mantra has been thinking big in years, execute plan in months and execute weekly and month daily, you know, you can plan around, there's a management technique potentially to leverage cloud and AI to really think about bit the big idea. Uh, if I'm a manager, whether I'm in public sector or commercial or any vertical industry, I can still have that big idea that North star and then work backwards and figure that out. >>That sounds to the Amazon way. What's your take on how people should be. What's the right way to think about executing down that path so that someone who's say trying to re-imagine education. And I know a, some people that I've talked to here in California are looking at it and saying, Hey, I don't need to have silos students, faculty, alumni, and community. I can unify them together. That's an idea. I mean, execution of that is, you know, move all these events. So they've been supplying siloed systems to them. Um, I mean, cause people want to interact online. The Peloton is a great example of health and fitness. So there's, there's everyone is out there waiting for this playbook. >>Yeah. Unfortunately I, I had the playbook. I'd mail it to you. Uh, but you know, I think there's a couple of things that are really important to do. Maybe good to help the bed is one where is there structural change in an industry or a segment or something like that. And sorry to just people I'm home today, right? It's, everybody's running out of the door. Um, and you know, so I talked about this structural change and you, we talked about the structural change in healthcare. We talked about kind of maybe some of the structural change that's coming to agriculture. There's a change in people's expectations and how they're willing to work and what they're willing to do. Um, you, as you pointed out the traditional silos, right, since we have so much information at our fingertips, um, you know, people's responsibility as opposed to having products and services to deliver them, what they're willing to do on their own is really changed. >>Um, I think the other thing is that, uh, leadership is ultimately the most important aspect. And we have built a lot of companies in the industry based on forms of structural relations industry, um, background, I'm a product manager, I'm a sales person, I'm a CEO, I'm a finance person. And what we're starting to see is more whole thinking. Um, uh, particularly in early stage investors where they think less functionally about what people's jobs are and more about what the company is trying to get done, what the market is like. And it's infusing a lot more, how people do that. So ultimately most of this comes down to leadership. Um, uh, and, and that's what people have to do. They have to see themselves as a leader in their company, in their, in the business. They're trying to build, um, not just in their function, but in the market they're trying to win, which means you go out and you talk to a lot more people. >>You do a lot, you take a lot fewer things for granted. Um, you read less textbooks on how to build companies and you spend more time talking to your customers and your engineers, and you start to look at enabling. So the, we have made between machine learning, computer vision, and the amount of processing power that's available from things like AWS, including the services that you could just click box in places like the Amazon store. You actually have to be much more expansive in how you think about what you can get done without having to build a lot of things. Cause it's actually right there at your fingertips. Hopefully that kind of gets a little bit to what you were asking. >>Well, Alan, it's always great to have you on and great insight and, uh, always a pleasure to talk candidly. Um, normally we're a little bit more boisterous, but given how terrible the situation is with COVID while working at home, I'm usually in person, but you've been great. Take a minute to give a plug for the data collective venture capital firm. DCVC you guys have a really unique investment thesis you're in applied AI, computational biology, um, computational care, um, enterprise enablement. Geospatial is about space and Capella, which was featured carbon health, smart agriculture transportation. These are kind of like not on these are off the beaten path of like traditional herd mentality of venture capital. You guys are going after big problems. Give us an update on the firm. I know that firm has gotten bigger lately. You guys have >>No, I mean the further firm has gotten bigger, I guess since Matt, Zach started about a decade ago. So we have about $2.3 billion under management. We also have bio fund, uh, kind of a sister fund. That's part of that. I mean, obviously we are, uh, traditionally an early stage investor, but we have gone much longer now with these additional, um, um, investment funds and, and the confidence of our LPs. Uh, we are looking for bears. You said John, really large intractable, um, industry problems and transitions. Uh, we tend to back very technical founders and work with them very early in the creation of their business. Um, and we have a huge network of some of the leading people in our industry who work with us. Uh, we, uh, it's a little bit of our secret weapon. We call it our equity partner network. Many of them have been on the cube. >>Um, and these are people that work with us in the create, uh, you know, the creation of this. Uh, we've never been more excited because there's never been more opportunity. And you'll start to see, you know, you're starting to hear more and more about them, uh, will probably be a couple of years of report. We're a household name. Um, but you know, we've, we we're, we're washing deal flow. And the good news is I think more people want to invest in and build the things that we've. So we're less than itchy where people want to do what we're doing. And I think some of the large exits that starting to come our way or we'll attract more, more great entrepreneurs in that space. >>I really saw the data models, data, data trend early, you saw a Realty impacted, and I'll say that's front and center on Amazon web services reinvent this year. You guys were early super important firm. I'm really glad you guys exist. And you guys will be soon a household name if not already. Thanks for coming on. Right, >>Alan. Thanks. Thank you. Appreciate >>It. Take care. I'm John ferry with the cube. You're watching a reinvent coverage. This is the cube live portion of the coverage. Three weeks wall to wall. Check out the cube.net. Also go to the queue page on the Amazon event page, there's a little click through the bottom and the metadata is Mainstage tons of video on demand and live programming there too. Thanks for watching.

>>Live from Las Vegas. It's the cube covering splunk.com 19 brought to you by Splunk. >>Okay. Welcome back. Everyone live in Las Vegas. We're here for Splunk's dot com I'm John ferry with the Q, this our seventh year covering.com but.com 10th year of their end user conference, their customer conference. That's been exciting to watch the evolution of Splunk and how a lot of it's because of their great products. We have our next guest Pang, senior director of product line management for Splunk business flow. Welcome to the cube. Well I'm glad to have you. One of the successes of Splunk has been great products. They never deviate off the core, kept building on it a year in the senior director of product land for you know, business flows, analytics. All I see everywhere is dashboards and visualizations. It looks so easy. Tell us about what your products are doing. >>Yeah, definitely and you know, I think one of the places to start is just how we moved into this area and start the new product. A lot of people know us for it and security use cases, but a lot of our customers are also using it to address business needs. So what they really saw was the value of Splunk to pull data from across different silos. Um, so in a business sense it could be, I have different systems for maybe my leads sales and closing the books, right? Those are all disparate. It's really hard to pull it together. And so they came to us saying like, we'd love a way to stitch this together and be able to visualize it. And that was really where Splunk business flow was born from. So we actually simplify it by connecting all these disparate data points, creating a full journey view or a process view that you can graphically see what's happening and then point and click and drill in. So it's really opening up a whole new set of users for us with that. And a whole new set of use cases that way. Surely. Yes. So if you think about, we have tons of data, it's tens of events. If you know a common thread like a user and how they might go to the store and then do something online and really understand the customer experience. If you could actually thread that all together, who would knows so much more about their customer experience and that's what we're able to do and we do it seamlessly for them. >>Well the database guy in me from the old eighties college saying, I gotta write a schema for that. I got to store the data. I mean in the old way it was really hard to compare like the pain or even capability >>we're hitting. Exactly the pain point. Right. That's why it's been so hard to do that because it was so rigid. The beauty of Splunk is the scheme on raid aspect of it. So because we store all the data and then we can distract it as needed, we do the search on demand and that's how we're able to actually stitch it together. Yeah. Yeah. And I think like one of the things has been the struggle of, well people have made a lot of probably more conservative decisions earlier on in their data and that's why they weren't able to get the information. And so part the main pain point we always heard was I got one piece of data, but now that I look into it, crap, I need to know what else there is. And then you have, it's another three week cycle, right, to pull that data in, bring it all in. Well now that's all in Splunk. You can just pull it as you need it on. >>It's a use case. Then from an operations standpoint, they're pretty comfortable with handling slug. They know what it means to Splunk, the data. >>Exactly. And we really see it as a partnership between the Splunk admin as well as the business users. The Splunk admin helps to get it all set up and then the business user can actually investigate on their own and they don't need to know SPL or anything like that to be able to use the product. Exactly. That's a great question. So it's a premium solution. So you do need Splunk enterprise or Splunk cloud. And then this is stacks essentially on top of it. Um, and so it uses the underlying Splunk data, but then it's also doing the additional work of doing the correlation across it, stitching it together, providing the visualizations. And then from there you can do things like AB comparison mode. You can see conversion rates, you can drag it, you can drill down all the way into the actual event. So the beauty of it is being able to see the holistic picture but then go down into the individual Avenger. >>It's definitely the business analyst and I think there is some crossover with it and security as well. So we actually had a session here where our own it internal it use focus flow to monitor their ticketing system and look for black hole tickets. So have you, I don't know if you've ever, you know, submit an it ticket. You never hear anything back because it's gotten lost. But yeah, exactly. But what are those, what are those? Zachary, you're very fortunate, but it was one of those problems where you hear a lot of it departments, you know, you might've, because you're outsourcing certain portions, you lose some of those tickets. You don't know what happened. So they were actually able to use the product to see that. But it also applies to people within. Um, one example we have, sorry, I'm thinking of some public customers that we have. So Domino's is a public customer. Um, that was a beta customer that used it for payment processing on, on, um, Superbowl. So like that's another great, >>yeah, the obviously scale is huge there. The data. So I gotta ask the cloud question. Since we brought up cloud, is this service cloud enabled in the sense of, is it on an on premise thing or is it, does the workflow kicked into the analytics? How's the cloud play? >>Yes. So it sits on top of both. Um, so it works either with the Splunk enterprise or Splunk cloud enterprise license essentially. And then the actual architecture of it is a hybrid environment. So we have a hybrid component that's in our own host of cloud that feeds the UI. And the great thing about that is that we're able to update the product very quickly and push out updates to the customers very easily though. So, um, we first announced it back in may of this year and have added additional functionality as part of COF and it did come out of customers and then seeing the opportunity with the machine data. So, um, there are a lot of great stories that we've had historically. I think Dubai airports, you can see some different stories of for pupil piece, the journey together. And so out of those conversations bore was the idea was >>every product line has a list that didn't make the cut on the product is called the roadmap is also new things. What are some of the things that you see big picture areas that you're going to focus in on to extend out the capabilities and value of the product? >>You really see the product evolving the same way that you see a lot of the portfolio for all. So Doug has talked a lot about investigate, monitoring and analyzing and act, right. And so those same concepts apply into how you think about a process as well. So right now we're really helping the investigation and monitoring, but we'll also continue to extend across that spectrum of time. Yeah, definitely in how we've built the product. But also, um, I think it can sit alongside some of the other things that you're also seeing in that realm. >>Final question for you. For people that are watching that couldn't make the conference, what's the biggest, biggest story here for dotcom this year? How would you, >>I mean overall I really think it is our data to everything message that we're discussing. Um, I think today you can really see how we apply in all of these vast areas and really the power of being able to have access and make that data actionable and do something with it. Thank you so much. It's so nice to be with you today. >>John Barry here in the cube coverage here in Las Vegas with dotcom Splunk's annual conference. It's their 10th year, March 7th year covering them. We'll be right back with more day to coverage after this show. >>Right.

>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Run. Welcome back to the Cubes live coverage here in San Francisco. Mosconi North while you're here as part of our exclusive covers. The Cube for IBM think twenty nineteen, their annual conference of customers and employees coming together to set the agenda for the next year. For IBM and its ecosystem. I'm John for a student. Um, in day. Volonte and Lisa Martin co hosting all week This week. Four days of wall to wall coverage. Day two of our kind Really Day one of the show Kickoff. We're here ending out that day and just had the CEO's keynote, and we're going to a review and analysis. David's do. We had a lot of interviews. Coming up to this theme is pretty clear. It's a I cloud and everything else going underneath that classic development application. Developers, developers in general, making applications That's classic, but eyes the big story. And, like like Always Cloud and the promise of Where That's Going, which is hybrid and multi cloud Dave, You set on the keynote. Any surprises from Ginny Rometty? >> I wouldn't say there were any surprises. First of all, I like Jenny. I think she she's a great presenter. I'd like to hang out with their like we were kids. That was what I wanted to hang out with us. He's a time person. I think I would feel comfortable talking to, you know, sports or business. She looked good. She had a really nice, sharp white suit on. She's self deprecating. She was drinking Starbucks. You know, they're obviously a client of IBM. I got the best moment was when Jim White hearse came on stage. He said, It's great to be here So he was like, Yeah, given thirty four billion reasons why it's great to be here kind of thing, So that was pretty funny. And she had. She made the comment. We've been dating Red Hat for twenty years before we decided to get married. She was trying to make a case You normally in Jenny's presentation, she she makes a really solid, puts forth the solid premise and then sort of backs it up with her guests. Today, I thought her premise, which was we're entering Chapter two. It's all about scaling and embedding a I everywhere. It's about hybrid. It's about bringing mission critical APS, you know, move those forward. And she had a number of other lessons learned. I thought she laid it out, but I think it sort of missed the back end. I don't think they punctuated the tail end of Jenny's talk. The guests were great and they had guys on from Kaiser Permanente E. T. And they were very solid. Well, think they made the case as strong as the premises that she put forward. And you know, we could talk more about that. >> And Stewart see red hat on stage. We've been commenting. We've been analyzing the acquisition of Red Hat, big number, thirty four billion dollars critical point you guys talk about in your opening on day one, the leverage they need to get out of that. This is the Alamo for them with the cloud. In my opinion, IBM is a lot to bring to the bear in the cloud. They I anywhere telegraphs that they wanna have their stuff with containers and multiple clouds. They want to be positioned as a multi cloud company but still have their cloud, providing the power for the workload. That makes sense, right? Bm. This is their last stand. This is like, you know, the Alamo for them. They They need to make cloud work right now. Watson, move from a product or brand ballistically open step. Is it tied together? Stew your thoughts on open stack and how this fits into their narrative. >> So I think you mean open shift, right, John s o from red hat standpoint. Absolutely what they're doing. They are involved in open stack, but open stack. You got a small, >> but they're one of the few that are sanguine on Open, Zachary read. >> I mean, read had open shift. My bad >> way it absolutely. And it is complicated in the multi cloud world and lots of different pieces. We've had a number of conversations with the IBM people that have worked with side by side, red hat in the open source communities, IBM, no stranger to open source and a CZ we talked about in our open on yesterday. It's the developers is really what where IBM needs to go and where Red Hat has a bevy of them on DH John. What you said about Multi Cloud? Absolutely. It's if IBM thinks that buying Red hat will make them the Goebel Global player in Cloud. I think that's wrong, and I don't think that's what they're doing. When I wrote a block post when it came, and I said, Is this move going to radically change the cloud landscape? No. Can this acquisition radically change IBM and change the trajectory of where they fit into Multi cloud? Absolutely. So there's cultural differences. We had Ah, Stephanie sheriffs on who's a longtime IBM er who now runs the biggest business inside of Red Hat. And she talked about the passion of open source. This is not lip service. I've many friends that have worked for it. Had I've, you know, worked with them, partner with them and cover them for most of those twenty years on DH? Absolutely. You've got over ten thousand people that are passionate involved in communities on DH. When you talk about the developer world, you talk about the cloud native world. This is what you know. Really. Red Hat moment has been waiting. >> It was interesting. John and I would like one if you could comment on this is you hearing IBM? Jenny talked about Chapter two. She took a digital reinvention. Here's yet another company using the reinvent terminology. I think that's what sort of pointed she talked. About forty percent of the world is going to be private. Sixty percent is going to be public Cloud. The sort of that's the first time I've heard those that she said It's flipped if you're ah, regulated industry. But what do your thoughts on people essentially using and Amazons narrative on reinvention? >> Everyone's using Amazons narrative. Here's the bottom line. Amazon is winning impact large margins. I think the numbers airway skewed in the favor of the people trying to catch up. I think that's more of a game. If vacation by the analyst firms, Amazon is absolutely blowing away the competition when it comes to public loud. The only game at the table right now for the Oracle's, IBM, Sze and Microsoft and Google is the slow down the adoption of Amazon. And you see the cloud adoption of Amazon, whether it's in the government sector, which I think is more acute. And Mohr illustrative, the Jet I contract a ten billion dollar contract. That is a quote sole source deal. But it was bid as a multi source deal means anyone could bid on it. Well, guess what? That is a going to be an award and probably to Amazon as the sole winner because IBM doesn't have the certification. Nor does Microsoft notice Oracle. Nobody's got Amazons winning that, and that begs the argument. Can you use one cloud? And the answer is Yes, you can. If the APP worked, Load works best for it, and procurement does not decide output for the cloud. For example, if it's a Jet I contract, it's a military application. So, like a video game, would you want to play a video game and be lagging? Would you want our military to be lagging? Certainly, the D O d. Says no. So one cloud makes sense. If you're running office three sixty five, you want to use azure. So Microsoft has taken that, and their earnings have been phenomenal by specialising around their workloads. That makes sense for Azure, and they're catching up. IBM has an opportunity to do the same for their workload. The business workload. So aye, aye, anywhere is interesting to me. So I think this is a good bet. If they can pull it off, that's the strategy, and the world will go multi cloud, where certain clouds will be sold for the apple sole source for the workloads. That makes sense for those workload. So this is where the market's going, right? So this whole notion of there won't be multi class. It's going to be multi cloud and it's gonna winner, winner take most. And the game right now is to stop ama's. That is clearly the case, and you're seeing it in the bids you see in the customer base. And IBM is catching Oppa's fast as they can. They got the people and the technology. The question is, how much do they catch up and level up? Tamas on? >> Well, stew despite Jenny, you know, invoking the reinvent terminology, they're her. Kino was starkly different than what you would expect from an Amazon Kino. They may. She mentioned a couple of the announcements, Watson anywhere, which, by the way, is about time. It's about time that Watson ran on other people's clouds of it, which should have been a while ago and in hyper protect is the world's most secure cloud. But we don't have any really details on that. And then I'd be in business automation with Watson, and that was really it. I think it was by design not to give a big product pitch, you know, very non Steve jobs. Like very done, Andy Jazzy like which is all product product product. I mean, kind of surprising in a big show with all these customers. You think they'd be pitching, but I think their intent was to really be more content. Orient >> Well, So Dave, you know, goes back at the core. What is IBM's biggest business? IBM biggest businesses. So services. So I've done a number of interviews this week already talking about how IBM is helping with digital transformation, how they're helping people move to more agile and development for environments. You know, the multi cloud world. How do they know IBM has a long history with C. S, P s and M s peace? So they have large constituencies And sure, they have products. You know, great stuff talking about, You know, how do they have the best infrastructure to run your workloads and the strength that they haven't supercomputing in HPC. And how they can leverage that? Because IBM knows a thing or two about scale. But, you know, Dave, one of the questions I have for you is we've seen the big services organizations go through radical downsizing. You know, HP spun off their business. Del got rid of the Perot business. You know, IBM still is, you know, services. At its core, it is IBM built for the multi cloud cloud native. You know, Ai ai world, Or do they still need to go through some massive changes? >> Well, multi Cloud is complicated and complex. IBM does complicated services, you know, deal with complexity, but I still can't help but feel like, >> Well, I well, I thought, wouldn't comment on them. I think the services. If the Manual Services Professional Services dropped down, IBM has a great opportunity to move them to cloud based services, meaning I can write software. And this is where I think they have an advantage. They could really nail the business applications, which will become services, whether its domain expertise in a vertical. And I think this is their cloud opportunity. IBM could capture that they could take entirely new category of applications. Business applications and services, automate them with machine learning, automate them with cloud scale their cloud scale while making them portable on multiple clouds. So the notion of services will be the professional services classic your grandfather's services, too. Cloud based services at scale. >> Yeah, well, I think you're right. Look, that's one. IBM is biggest strengths, and Jenny did that acquisition. By the way. The PwC acquisition is one hundred thousand. People instantly brought IBM into that deep vertical industry expertise, and they're not going to give that up any time soon. And this so many opportunities to code. If I those services or that song you know, through software and make them repeatable services, I mean, they're at as a service. Business is one of the fastest growing parts of IBM, you know, revenue stream. So I don't see that going. Wait. All I do think there was a missed opportunity and maybe they can't talk about it for was some regulatory reason. They're just paranoid. But you had white hearse up on the stage. You just spent thirty four billion dollars. I would have liked to hurt Mohr about the rationale, even though we've heard it before. They did. You know, Jim and Jeannie did a tour there on all the big TV shows You're on Kramer. But I would have liked to heard sort of six months on what that rationale is and how they're going to help transform with this in this new chapter and what that role that red hat was going play, I thought it was a missed opportunity. >> Well, speculate on that. I think of things. Probably. They probably don't have their answer yet. IBM is very good on messaging. You know, they're pretty tight, but I think Arvin Krishna talked to assert this morning. On our first interview. He brought up the container ization and Coburn Eddie's trend. I think that's where red hat fits and melons and give them cloud Native developers in Enterprise Fortune one thousand. They also got the cloud native ecosystem behind that the C in C F etcetera. But Containers does for Legacy Container ization, and Cooper daddies really preserves legacy. It allows developers to essentially keep the old while bringing in the new and managing the life cycle of those applications, not a ribbon replace. This is an opportunity for IBM, and if I think the messaging folks and the product dies or probably figure out okay, how do we take the red hat and open shift and be cloud native and take all the goodness that comes in with cloud Native the new developers, the Devil Infrastructures code, make under the covers infrastructure programmable and is Rob Thomas pointed out, having horizontal data layer that enables new kinds of business services. So to me, container ization, it's kind of nerdy Cooper netease. But this is really a new linchpin to what could be a sea change for IBM in terms of revenue. Keeping the Legacy customs happy because then the pressure to move to Amazon goes away because I can say, Whoa, wait. If the question is, why adopt if customs have an answer for that that gives IBM time, This is what they want otherwise, cloud native worlds could move very, very fast. We've seen the velocity of the momentum, and I think that's a key move. >> I think your point about slowing down the Amazon momentum is a good one, and I want to talk about five things that Ginny said that lessons learned, she said. One. You can approach the world from outside in and focus on customer experience. Or you could do inside out, identify new ways to work and new work flows, you know, kind of driving change. The third lesson learned was You need a business platform fueled by data with invented A I. The fourth is you need an ai ai platform. And in the fifth is Rob Thomas is you can't have a eye without a word that you needed information, architecture, which, by the way, I believe it to be true. So those are business oriented discussions. It's not something that you necessarily here from Amazon there kind of chewy. There's the services component to all that. The big question I have is Well, Watson, be that ai ai platform. >> Yeah, I mean something, You know, I look at is why Doe I choose a platform and a partner. So we understand Amazon, you know, they want to be the leader and everything. They have a lot more services in anyone. But, you know, if I want data services, first cloud that comes to mind to me is Google. You know, Google has a real strength there, You know. Where does IBM have a leadership compared to Google business productivity? IBM has a lot of strength there, but Microsoft also has a place so you know, customers. If they're going to live, Multi cloud, they're going Teo in many ways go backto best of breed on DH. Therefore, where will IBM differentiate themselves from some of those? >> We have visibility down. It's clear now that the industry the fog is lifting, starting to see Cem clear lines of sight and a few major trends. And it's pretty clear on where the industry's going for the next ten years. Application developers at the top of the stack gonna build APS The infrastructures cloud cloud something multi cloud cloud, native infrastructures, code and data. And a I see that Amazon reinvent sage maker. You're seeing all the major innovations happening around APS using data power advice, cloud scale, that's it. Everything else to me is glue or some sort of fabric component. Or a piece of that distributed architecture and its cloud. Aye, aye, and an apple. >> A CZ. Dave is often said, it's the innovation sandwich of today. >> Yeah, well, so I guess the things I want to mention it because of me. There's been some high profile failed failures with Watson, But watching was trying to do some things that were not, you know, voice response to Alexa, you know, solve cancer, you know, world problems and so I think IBM is actually earned the right to be in the discussion, and the Red had acquisition gives IBM instant credibility in this game, especially in this a multi cloud game. >> Well, they got me. They have the right to be the zillions of customers. They have a lot of a lot of business model innovations with that that their customers are innovating on. And if they keep the cloud innovate, they gotta match the specs. Specs of the cloud. They gotta be there with Cloud. If they don't make the cloud work, they're going to be subservient to the other clouds. They have to make it in the top three. This is clear. Hey, I think I think we're working a lot of experience and data. I think Watson kind of finding his home is a brand's natural fit. Got a portfolio of data? I think IBM will do very well in the data front. It's the cloud game that they got a really sure up. They got to make sure that IBM cloud conserved. They're custom, >> but the good news is there is there. In the game we saw HPD tried to get into HPD, tried to get the cloud it failed. Cisco, for a while, was trying to get with Sawyer. AMC make of numerous attempts. VM were made, made numerous attempts. IBM spent two billion dollars in software. They they they've got a cloud. You know, they've transformed what was essentially a bare metal hosting platform, you know, into a cloud. They've jammed all there as a service products in there. They're SAS portfolio. So there, at least in the game and, you know, again, I've said often, I think they're very Oracle like it's not the biggest cloud. It's not going to scale to the Amazon levels, but they've got a cloud, and it's a key part of the strategy. >> Innovation Sandwich applications Cloud What data? In the middle of a I. That's the formula, David said on the Q beer. All right day to coverage for the Cuba. Four days were here in the lobby of Mosconi North, part of the new refurbished Mosconi Center in San Francisco. Howard Street's closed. It feels like Salesforce. Dreamforce event. Big event in San Francisco. I'm John First Amendment Dave along. They were here for four days Day, two of four days of coverage for IBM think back tomorrow. Thanks for watching.