>>Hello everyone and welcome back to The Cube's Continuing coverage of AWS Reinvent. My name is Savannah Peterson and I am absolutely thrilled for this segment. We are joined by leaders at Cisco App Dynamics, as well as Royal Caribbean. The two have been working together for over five years, leveraging full stack observability. We're gonna dig in, but first of all, please welcome Alice from Royal Caribbean and Greg from Cisco App, app Dynamics to the show. Hey friends. >>Hi. How are you doing? >>I'm excited, clearly. How are you doing, Greg? >>I'm doing fantastic. Thanks for having me on the show today. >>Hey, it's our, it is absolutely our pleasure. Alice, I have to start with you. I don't think there are too many industries that have gotten as much coverage as cruising has over the last couple of years. You've been working with Royal Caribbean for over a decade, so you've seen it through the stormy seas of the pandemic, if you will. What has the last few years and the last few months been like for you? >>You know, it's, it's really been a wild ride. To your point, we were sailing high and then I don't think any other industry experience what we did in Covid, that you walked in one day and then that day the whole industry shut down. So it was a, it was a big challenge for us. And then as soon as we shut down and we weathered the storm with Covid, then we have what we called our healthy and return to service. So as quickly as it stopped, we had to start sailing again. So it's, it's really been a challenge, but we're happy to be back on our feet and heading in the right direction now. >>I, I really hope we can continue the sailing metaphors throughout the course of this interview. And you, you nailed that for a segment. Alice, I'm, I'm, I'm so, I'm so here for it. I, I, I wanna talk about how you've worked together, but I wanna give Greg a second to chime in here. So Greg, you're the executive CTO at Cisco App Dynamics. How, how have you and the team, whether the last two and a half years? >>Well, you, you know, it's interesting, the, the pandemic really brought together an interesting conundrum, right? So on, on one hand, you had, you know, the, the, the consumers, the end users that became very reliant on digital services. They had a function in a way that was very performing, right? So, 84% of the respondents that we had come back through a report called the App Attention Index, came back and said that digital services were, were really instrumental for them to, to get back to some level of normalcy. But the interesting part that came about that is that out of those respondents, 60% of them blame the brand if the, if the application did not work the way they expected it. So they didn't really care about the, it's in the back end, right? So when you look at, yeah, you look at the shift in the IT department, the IT department had to go out and, and quickly innovate, quickly start to introduce new services, which ultimately brought together a, a sprawl in their technology stack. So when you're adding to it, you're not taking things away, you're continuously growing. So finding that that, that the problems or the, the root cause of an application issue became more difficult. So that's where, you know, from an app, Cisco AppDynamics perspective, you know, we're one of the leading observability and app application performance monitoring tools. So we help customers like Ro Caribbean to be able to zero in on root cause and ensure that their end users have that best experience. It's, >>It's, it's, I I'm smiling as someone who was a, a former waitress and I can remember the amount of times I was scolded for something that happened that was far out of my control and the complex layers of the kitchen. And I think that, that anyone who's, who's had a, a poor customer experience while interacting with a brand may or may not intentional, I think it's actually sometimes very unintentional to your point, get frustrated with said brand. I can imagine that is an experience and a priority that you have at Royal Caribbean. Alice, how, how has Full Stack Observability played a role in your, in your team's ability to, to serve the customers and your, and keep your community engaged during this, this very kind of wobbly time? >>Yeah, you know, we have, have really worked hard to improve and remove friction from our guest vacation. And we wanna keep them on vacation and having a great time. You know, we say we don't really sell a cruise. We sell an experience. So we use App AppDynamics to monitor those key applications that our guests are interacting with to ensure that they're having that experience that we expect, you know, we've learned that just because a system or a server says, Hey, I'm up 99% of the time, that doesn't mean that my guests are experiencing that same type of stability, you know? So once again, we really worked well with App Dynamics. They've partnered with us to ensure that, you know, our guests are getting that vacation experience they're looking for. >>Do you think, just a follow up there, do you think that you would have advanced in the ways that you have working with Cisco App Dynamics and across functions over the last few years without this crunch, was necessity the mother of invention for you to any degree? >>You know, I don't, I don't think that the Crunch brought it on cuz we, like I said, we started this journey back in 2017 and we're not unlike a lot of companies where we're on this maturity ride where we wanna go from being reactive, where our guests are telling us something is broken to being preventive. Definitely, you know, COVID played into this because I think we learned to do less, you know, more with less. So, you know, we, you know, it's very hard in the cruise industry. We did take a hit, but we were able to use the app dynamics tools to ensure that our systems were running with having less people also watching those systems. So less eyes on glass, more automation, >>And that's a more, with more, more stability, more credibility, and more transparency is definitely something that we're all looking forward. And, and it's nice to see that implemented, especially at scale when you're dealing with so many customers from all over the world trying to access your service and, and wanting that personalized experience. Greg, what does it feel like for you as a leader to hear someone like Alice say how powerful your tool has been in ensuring that customer experience? >>Yeah, that's, you know, it's absolutely fantastic and especially, you know, Alice is absolutely right. You know, the, the, the cruise industry was really, had a very unique challenge in front of them, and I, I really applaud the folks at Royal Caribbean for stepping up to make sure that when the pandemic eased, so to speak, that they, that the experience to the customer was actually even better, right? So when we were able to work and partner together to make sure that, you know, the, the, the user experience is topnotch, the availability is there, the, the, the, the resiliency of their platform is there. So by, by working with customers like Royal CRI and is really one of the, the, the shining stars that we can talk about that really help make a big difference in, you know, that post pandemic era to be able to really do what's right for the customer. >>How often are you engaging with customers like Alice as a team? How big is that feedback in your product roadmap? >>Oh, personally, I, I'm, I'm engaged with customers on a daily basis and I see it fr across the map from many different industries. And, you know, a lot of folks had different challenges, but the, the ultimate commonality that I've seen across, you know, multiple industries is that, you know, when you, when we're in that pandemic state, digital services were the only way that they, their customers were interacting with, with them. So, you know, when you, when you're looking at a, at a bank or you're looking at a, you know, different types of travel agencies and organizations that, you know, like rural Caribbean as well, that, that really had that opportunity to, to focus on what's the most valuable thing to them, which is user experience. It's a very, very common common trend that we saw. And, you know, you see an expedited path of, of, of digital transformation happen. And really that's where we partner with, you know, customers like Royal Caribbean and, and many others across different industries to make sure that that, that the, the business outcomes were being driven towards the, the proper direction. As well as that, you know, the, the user experience, and I don't think I can emphasize user experience as being so critically important anymore than I've already have, but it's really the, one of the most valuable currencies most organizations have. >>I, one of my favorite lines is, is community is your first defensible asset. And you know, I, you can, you can talk about user experience as much as you want on here. At the end of the day, if people aren't having a positive interaction with your brand or your product, it's probably not going to last super long unless it's legacy. And we won't have to go down that rabbit hole today, >>Especially if I can add there's a lot of competition there. Course, right? There's a lot of competition out there. So if your applications do not perform, or your digital services do not perform, the end user has the quick ability to just quickly delete and move on. And, and the same thing with, with what Alice sees in the, in the cruise industry, you know, you have an opportunity to rise to the top and I, I really applaud them for taking advantage of that, that opportunity. Community. >>Community. Yeah. Well, I'm, I'm here for both of you cheering each other on certainly the, the water level rises together. That's >>Right. Alice, >>What sort of, what sort of challenges are you taking on currently that you're able to disclose? What, what sort of leaps do you think, or doesn't have to be leaps, but what, what kind of experience are you hoping to continue to enhance for Royal Caribbean customers? >>So I think, you know, one of our big challenges that we've, you know, we've announced that we do have a relationship with starlink, so that's going to improve our satellite connectivity, and it really is a game changer for our industry. It's very exciting and, and, but it puts the, it puts the user back in the forefront once again. You know, right now, you know, with our current connectivity, it's all about managing that bandwidth. You know, we're hoping to go to that state where bandwidth isn't at a high cost, so now we're gonna be even able to watch our user interaction more from ship to shore, you know, and you're, and you're, we're maybe moving to that area where we're thinking cloud first from a shift. If you think about it, we've got 50 plus data centers floating around the world, so that connectivity is key. Now we're opening up that bandwidth now I need to see how that, how the transactions are performing as we come off ship. You know, with that, once again, that cloud first mentality, it's a super exciting time for us. And I really see, you know, AppD is gonna play a role in that. >>I, I I, I love that visual just for a second of 50 data centers with also surrounded by people having a very wonderful time on board. What a, what a nice spot. I, I can't say that every data center I've ever been to is, is glamorous, fun or sexy as being on a Royal Caribbean ship. However, I, I hope that we move perhaps in that direction. We were just at super computing a few weeks ago and it was great to see all the hardware there. So you never know. What role do you see yourself in the team and, and Cisco app Dynamics playing in that future for companies like Royal Caribbean, Greg? >>You know, it's really, it's really staying right lockstep with our customers as they move through that digital transformation efforts. The key piece is that we look at it from that full stack view. So we offer full stack observability, which, you know, if you look at the challenges that we want to go after is traditional IT departments were historically siloed pretty significantly between, you know, network and infrastructure security app dev. So ensuring that we can get our customers to, to be able to have that common view that shows what's the real important pieces across all domains. So when they start moving down the path of digital transformation, that's an opportunity to also revamp how their processes are that people interact and the technology that they use to be able to deliver the proper business outcomes. So we talk a lot with our customers around full stack observability, but the key part is business context. >>So if you have a big effort for digital transformation, you're starting to add new services to it, how do you know if it's actually impacting the business in a positive or negative way? So by us implementing the, the business context to ensure that you understand the investments being made that you can show to your business leaders is showing an uptick and the business outcomes you're, you're going after, it's really, really about a strong partnership with our customers, but also ensuring that their business is being positively impacted by our technology to be able to help them really align the teams and be able to have the right desired outcomes. >>I love that Greg and I love that customer first. That community first attitude, it's something that you both share. Final question for the two of you, and I'm gonna start with you, Alice, since I suspect you've probably been on more cruises than Greg and I combined, though I could be making a wild assumption. Where are you cruising to next? >>You know, I just got off the cruise, so next up I wanna revisit the Galapagos. I think the Galapagos is the best place to go, and if you haven't done it, that's absolutely where you should go. >>Oh, it's a beautiful trip. Greg, have you ever done the Galapagos? Is that gonna be your next Royal Caribbean cruise? >>I have never done the Galapagos, but I may just have made it to my list. >>Fantastic. Well, I second Alice's endorsement on that. I, I had the pleasure of going about a decade ago. Very magical place that teaches you a lot about nature, much like the two of you have taught us very extensively about full stack absorbability, how it applies to user experience, customer experience, and the ocean that I am currently staring at here in Pacifica, California. Alice, thank you so much for joining us from Miami Greg to you in Colorado. I hope that you both continue to work in harmony together and that we can all see each other on the friendly sees soon. Thank you all for tuning in to our AWS reinvent coverage. This is the cube. My name's Savannah Peterson, and we look forward to seeing you for our next segment.

(upbeat music) >> Hello, welcome back to theCUBE's coverage of AWS re:Invent 2021. We're here in the studios in Palo Alto, California. Two great guests Linda Tong, general manager of Cisco AppDynamics and Garrick Linn, architect of operations at Match.com. Thanks for joining us. We're talking about AppDynamics, Match.com and customer experience. Mainly around cloud migration. So Linda, great to see you and Garrick, thanks for coming on theCUBE. >> Great to see you again. Thank you for having us. >> Same here. >> Linda, you're a CUBE alumni. we've talked about cloud migration application performance, modern application development, all powered by the Cloud, right? So this is really key and people are relying on the cloud and cloud scale and data to drive the digital transformation, the digital services and applications right now. How has the pandemic affected your customers and their expectations for digital experiences? >> Oh boy, I mean the pandemic has been, it has been rough for our customers, you know, and part of that is what Garrick's going to tell you a little bit more about today, but folks are seeing this increase in expectancy of accelerated speed and delivering innovation, building great applications and iterating on them quickly. And frankly, their customers' demands we're engaging with them through digital services. And that has led to this massive increase in, one, the types of technologies that they're consuming to build and deliver these applications. And two the complexity upon how they actually wrap their arms around it and understand what's going on and deliver these great experiences. And so it's been a rough road for our customers and what we find with AppDynamics and Cisco is our ability to partner with our customers to help them wrap their arms around that complexity. >> John: Garrick, I'd love to get your commentary on this because I'll say, Match.com has been at large-scale for many, many years, and now the pandemic comes in now a new user experience, more accelerated, more action, more things are happening, right? So this is truly the hybrid world coming together. I mean, it is kind of the same game, but kind of new patterns are emerging. What have you seen in the pandemic around the expectations and the services and you guys are providing in the digital experiences? >> Yeah, sure. So as you mentioned, Match has been around for quite some time. We've been here for over 25 years. We have an interesting mix, heterogeneous, technology, some old stuff, some new stuff. A lot of the mentality that we try to bring is to innovate. The pandemic was, it brought a lot of uncertainty. We weren't really sure how people were going to react. Was it going to be everybody kind of hunkers down on dating definitely is something that requires human interaction in multiple levels. And it turned out that people were still very much interested in getting to a place where they can find human connections and you know Match as a premium product tries to make that delightful. And so we had our hands full, especially at the beginning, things like, by checking the video features, how does that work? What are the expectations? Is that going to creep people out? If we try to offer that, are they going to use it? How are they going to date? How are they going to talk? How can we make sure that they're safe? All these kinds of things went into it. And so when we have been using AppDynamics for you know, years now, well before the pandemic, and we use that in order to get a gauge, not just on the type of traffic and load, but also, "Hey, you've got these new features, "how do they fit into this huge complex environment?" And so some of those timelines that maybe were a little bit more relaxed were very much accelerated, And like a lot of companies, we had to figure out how to deliver on that. >> John: Yeah, Linda, I want to get your thoughts. We've talked about in the past, AppDynamics has been a leader in really accelerating the value for customers. Now with the pandemic, you mentioned these new experiences are being pulled in from the physical world, right? So you have things that were happening on digital in the application space. Now you have more experiences coming in because there's no places to meet face to face. Now it's coming together, but people have been seeing the value. Well, if I can't meet in person Match.com are going to do some things, new things, online chat, whatever. This dynamic of old way, new way is changing and cloud is powering that. What are you seeing in terms of your customers' journeys around what was once pre-pandemic and now post-pandemic? >> Well, a big part of that is more and more of these experiences rely on digital services and these amazing sort of ways to connect with each other and in a very digital space, expectations of customers have changed. So not only do you experience applications and you want it to be simple, easy to use, delightful, and it delivers on the needs that you want. But on top of that, you expect it to be performant. You expect it to be secure. You expect there to be frankly, no hiccups whatsoever, because now this is your way to connect with others. This is your way to find dates or go on dates. And the last thing you want, is watching your screen pixelate, as you're trying to have an important conversation. And these kinds of experiences and these challenges as people build more and more of these digital services to build these connections, frankly, require a lot more of folks like Garrick and his team. They now have to deliver amazing experiences with perfect performance, no security risks, no bumps in the night. And that's really tough, right? Expectations have gone through the roof. >> John: Yeah, the whole story on that one point, just to kind of add live in this was that that whole concept of moving fast used to take months, right? I mean, weeks, months, now it's days and hours. So months to weeks, days and hours but Garrick, this is the challenge. This is the opportunity with the cloud. Can you just take us through your cloud journey and your goals and some of the impacts that has had on your transition to the cloud? What does that look like? >> Yeah, so we've had our on-prem data centers for quite some time, and we started putting our toe in, I guess, although it was a kind of intense at the beginning, just trying to get people on board and to say, "Hey, this is possible." We started out with a fairly small SWAT team then managed within a couple of months, working closely with our developers. We have a lot of smart people, you know, with background or overall, just security folks over devs to just demonstrate that we could do it. So we managed to take something like 80% of our front end traffic for most of the day, just kind of spinning that up, learning lessons from that, knowing what we didn't know. AppDynamics, if we didn't have that would have been almost impossible to get a read if for no other reason, then just one little tidbit. We used to have a data center in Virginia. And so physics being what it is, you know, there's just been a flight that we have to contend with. And for a couple, few years, we hadn't had the 30 millisecond or so round trip latency on there. So all of a sudden we're going back to the cloud that reintroduced this latency. So what does that mean? Will you be asked to sort of glide by and absorb it? How do we track it? How can we figure out what the Delta is between, you know, here's how we've done things on-prem. Here's how it looks out here. If you are the cross, you know, calls and, you know, AppDynamics was what we used to be able to get a read and say, "Hey, look, it isn't as good as we know we can make it, but it's something, it's a starting point. Here's why, we can show you the graphs. We can show you the data. Let's do this thing." So we then pulled back and we have focused this year on actually our affinity apps, which is a collection of applications that are also going to be okay just in, and so we've been asked to get those completely migrated over. We're going to be running in hybrid mode for a while. We're going to need to be able to compare apples to apples, apples to orangutans, all that. And this is one of the main things for you, we describe. >> {John] If I can just follow up on that just real quick, because I think this is a good point. You got the data points, you double down on that. You're looking at real data, and then you look at success and you double down, that's the playbook. So, and the other thing is that you guys actually have a real operation that's running full throttled, right? (John laughs) So, yeah, so I can see that nice balance. What does the future look like beyond that? Because when you got a business that's scaling, it's running, it's like changing the airplane engine out at 30,000 feet. You got to continue to push the envelope. >> Yup, so, and no, exactly right. Again, we're a premium product. And so we've got to back that up. And that means, maintaining high availability. And so over the next few years, we're going to be looking at what have we already do? What can we move in piecemeal kind of way where it makes sense? What are the things that we can rethink? We're also using AppDynamics as part of our containerization initiative. You know, we've got lots of virtual infrastructure, but what is it, again, what does it look like on-prem, in a container, go down the list of different things that might be different. And then to be able to compare that to what it looks like, in the cloud. So it's going to be a while yet, but like a lot of companies, when we got into this, we didn't think it was going to be done in six months. Even if we have to deliver those features at a much faster rate, we know that the long haul, we got to make smart decisions and plan the capacity, and, you know, get there. (chuckles) >> John: That's a real pragmatic approach. Linda, you and I both are sports fans. We've talked in the past about sports, and the old adage, what inning are we in growth? It's to use that baseball metaphor. I would say it's a double header, game one won by the cloud, game two is happening now. And the trend is this end-to-end mature, operationally focused customer base. And IT, where IT has shifted to the cloud right now. And they're having this new view of what modern is. End-to-end, understanding different stacks relative to applications. It's not as simple as it was before, but it's relevant. Can you share your views on how that's playing out because, or do you agree with that? And do you see that as an important part of the customer? >> Yeah, I mean, I think it's, that complexity that the IT organizations are seeing now, as they fully adopt the cloud for all their new applications and start to migrate some of their existing applications over. That world is only increasing in complexity. The way that you can virtualize your applications, break them out into millions of services, the dependencies you have on third party applications or SaaS services. These things only add that many more data points that you now have to cover and think about and make sure that those things deliver upon their SLAs, right? And wrapping your arms around that requires a partner to help you separate signal from noise. Because now you're going into a world without simplicity that you just mentioned has gotten to some point where it's beyond what you can actually sort of keep in your mind. Beyond what you can just look at data and sift through and understand, you really need tools and systems that come together, and understand that data for you and start to represent your business to you in a new way and abstract away those layers of complexity. While you do that, because I think, as you talk about those innings, that first inning, second inning, or rather first game, second game in the series, it's not a full migration to the cloud, right? There are going to be some applications that stay on-prem that stay in their traditional environments and may never move. And then some of them are going to go hybrid. Some will keep parts of the applications on-prem, and they're going to start to modularize components of it. And so it's not going to be sort of a mass scale migration. And then we're all in the promised land. And we deal with the cloud complexity. It's going to be ever increasing complexity. As we now introduce so many variants of applications, so many variants of technology, and what people are going to need is someone who can help them cover that entire estate and understand it at scale. >> John: Yeah, I mean, I think it's the enterprise conversion, if you will of cloud operations on-premises because of the reasons. And now you've got the edge. Garrick, this is the whole kind of end-to-end stack conversation view. And by the way, there isn't one tech stack to rule them all because you have different use cases. You might have an application that needs a financial gateway or have other capabilities. So integration's huge. This only increases the point Linda was making about complexity behind the scenes. How does AppDynamics help you with this for Match.com? >> So we have quite a bit of infrastructure, you know, a lot of it is shared, well, most of all, maintaining, sandboxes for user data and that sort of thing. And so now the navigating that space is always interesting. So for instance, one of the new things that we have coming out is Star.com It's out there right now. It's a dating site that's geared towards single parents. It does share some of the infrastructure, but we're realizing what that means, how is that different, how our registration flow is different, how our subscription flow is different. Where are the things that DevOps are actively trying to improve on and rethink? That's one of the things that we try to focus on when we're trying to kind of pick out, like, is this a good candidate to move over to the cloud sooner or later? Is this a good candidate for something that needs to be maybe bake a little bit more? And having established those baselines with the shared infrastructure, and having a pretty good understanding of how they react, how they work really helps us, you know, tee up these new initiatives and in front of those needs in a more efficient way. So yeah, absolutely. >> John: What's some of the activity you guys seen? And what's the peak activity on Match.com these days? >> Yeah, so dating apps in general, but not so particular we use a nested or breast fractal peak, and it's a pattern that, from what they told me back in the old days, took a little while to realize was a thing. And not just like, oh we changed something and then did this and produced that. So every evening is our peak basically. So with taking time zones into account, obviously, in the United States from about five to 10 o'clock at night or so, we get this, growing, burst of traffic. So that can be anywhere from 23% sometimes. It kind of varies. Then we have a weekly peak where every, you know, Sunday and Monday we expect a higher amount of traffic than we would other days. And it kind of makes sense from an Archer psychology kind of standpoint where, you know, you're coming off of dates, you're trying to set dates up. That's where a lot of that activity is. And then we have a yearly peak, which goes from around Christmas to President's day. Believe it or not, it's President's day, it's not Valentine's day. And so the sort of thing where when we're trying to plan for capacity and we do a lot of, what cost squeeze tests, were not quite as I guess, engineering, but hey, what does it look like if we go down in capacity by 50%, what happens? where are the weak points? A January, Monday night is very different from a May, Thursday in June (chuckles). So we have to predict, we can anticipate some of that, but we don't know for sure, a lot can change in a year. So when we're preparing for a yearly peak, we really have to pay attention. We have to prep. We have to plan for that and work with that to figure out how we can get through it and maintain that level of service. >> That's awesome, and AppDynamics to help you to do that. I'd love to get a bot to give me the optimal dating times, to share with my single friends. Great stuff. Linda, thank you for coming. Great to see you. Congratulations on a great case study. Great story. How large-scale applications and are working in the modern cloud. So congratulations on your success. Thanks for coming on theCUBE. Appreciate it. >> Awesome, thank you, so good to be here. >> Okay, CUBE coverage of re:Invent 2021. I'm John Furrier with theCUBE. Thanks for watching. (upbeat music)

>> Narrator: From around the globe, it's theCUBE with digital coverage of AWS re:Invent 2020 sponsored by Intel, AWS and our community partners. >> Hello, welcome back to theCUBE's Virtual Coverage of AWS re:Invent 2020 virtual. Normally we're in person. This year because of the pandemic, we're doing it remote. We're Cube Virtual covering AWS re:Invent Virtual. I'm John for your host. We are theCUBE Virtual, two great guests here Linda Tong a general manager, AppDynamics and Dave McCann vice-president of AWS migration, marketplace and control services. Welcome to theCUBE. >> Thanks so much for having us. >> Good to see you again John. >> Linda we were talking to some AppDynamics folks and some of your customers, obviously we've been following the growth of the marketplace for many years. The confluence of the tailwinds of the innovation going on with COVID and post COVID strategies is about helping customers where they are and they're not in the office anymore. They got to get the job done. This is really important on this cloud migration of getting software in the hands of people to write these modern apps. It's a big theme. What's your perspective on this right now, because you guys are partnered with Amazon, share your vision. >> Yeah, absolutely. And you nailed it. It's with COVID-19 our customers like IT organizations are finding this need to accelerate their migration to the cloud. And what's more important is they're finding that more and more of their customers are engaging through digital experiences and with the influx of people leaning on those digital experiences during COVID, performance issues are becoming more and more apparent. And so we're helping our customers as they migrate to the cloud. And specifically to AWS, it's a big partnership for us because we need to understand how our customers and how they manage performance through these transitions can stay flawless so that they can manage those experiences for their end users. >> Yeah, Dave, I've been watching this discovery observation space, observability, service meshes, Kubernetes, cloud native higher level services have really gotten popularity have gone mainstream. So there's more and more demand for I won't call it point products. That's an old term, but in the cloud, these are just higher level services that people are adopting more of. You're seeing huge pickup in the marketplace of companies who are selling through there and engaging but it's not just selling, you're integrating. What's your vision for all of this? >> So, John, you're absolutely right. Our customers as they migrate more and more applications to the cloud and in some regulated industries they still have applications running on premise. They're really actually standing up a new operating model where they not only want observability of what's going on but I feel what we would call service management framework or a set of tools to manage the application portfolio. And companies around the world are putting together new common instance of AWS native services, such as CloudWatch CloudTrail, Service Catalog, AWS Config, Control Tower with best in class vendors like Cisco AppDynamics. And each company is building their own collection of tools into management framework that allows them to optimally modernize and manage their application portfolio. And it's a rising topic around the world. >> Linda, I want to get back to you on AppDynamics you're the leader of the team as general manager, congratulations. You know a little bit about software in the cloud and CloudScale and your career going back to Google now at AppDynamics you've seen a lot of the changes. What specifically value do you see AppDynamics and Amazon bringing to the market today? Because the world's changed. It's still large scale, there's faster speed but you can't just buy things like anymore, I've got to go in send a ticket request, go to procurement, developers want to integrate immediately. They need to integrate when they see a problem they got to integrate technology. This seems to be a trend. What's your, where is AppDynamics bringing the value of AWS to the market? >> Absolutely I think it's threefold. One it's for a lot of these developers, as they start to migrate their applications and modernize them with AWS and all the great services that are available we can partner to help them with that modernization effort while giving them visibility into the performance of those applications to make sure that they don't miss a beat as they deploy those on these new sets of services over AWS. The second thing is, for those customers that are leveraging AWS for that migration, we have a seamless integration between AppDynamics and AWS. So you can buy our service directly through AWS marketplace. So that becomes a really easy procurement. And then on top of that, as, a lot of developers have to manage hybrid employments, so new modern applications has done AWS as well as some of their traditional applications that are talking to each other. They can get that full end to end visibility leveraging AppDynamics so that they can understand what's going on across the entirety of their business as they start to lead these transformations across our organization. >> Dave, just comment on if you can, 'cause I know a little bit about some of the things you put in place, the enterprise I forget development or sales program where at the prices can be more friendly. I think this is kind of a use case where this is proving enterprises can get what they need in the marketplace that not only is it successful but you have traction with this. What's you take on... >> There's a number of motions that we're doing there John, to help large companies around the world who may have, dozens, hundreds and in comes cases with fortune 100 they're thousands of applications. And so you actually have to solve multiple challenges that the company has. On the procurement side, we're obviously working with AppDynamics to publish as a service right in AWS marketplace. And we have over 300,000 customers worldwide only AWS marketplace who are subscribing to software and provisioning out to hundreds and thousands of developers, all of whom are using their own AWS accounts. So on that provisioning and subscription experience we work deeply with the AppDynamics team to meet that a really seamless experience from discovery to provision to meter and billing. On the interoperability front, as Linda mentioned, our customers want these best in class tools like AppDynamics to work well with the other AWS services so that they can really have a very modern DevOps pipeline for those applications that are moving to more of a CICD model. And for people who are still running in a bit more of an Intel, ITSM model, they've still got to manage and monitor applications that haven't quite got there in the full modernization stack. So this is actually happening not just with the customer, the enterprise or with the ISV AppDynamics, this transitions' also working with all the consulting firms. And a lot of the large software resellers around the world, the computer centers of Europe the right spaces, the presidios of North America. The DXEs of Asia Pacific. These consulting partners are also using tools such as AppDynamics so to become a managed service provider. And in some cases on that journey to the cloud no join the customer saying I'm really busy I'm modernizing applications. Hey consulting partner, can you manage some part of my infrastructure, some part of my stack? And tools like AppDynamics and Kubernetes and AWS become really central tool kits to the new emerging managed service providers that are all around the world. >> Yeah, and I talked about this years ago with Andy Jassy and I think we were riffing on this run this new set of category creations of services and companies. Linda this appears to be one of those cases where, there's a category with existing spend and existing customers. So what he just said is interesting. And I want to get your thoughts because these are these points of these new areas where AppDynamics can potentially help enterprises. What are some of the areas that you see AppDynamics helping enterprises in their cloud adoption journey 'cause they want some cloud native we see Hybrid and all the announcements, Outpost, now Edge it's a distributed computer. You need to have software at every piece of the puzzle. So what's your, what areas can you share specifically? >> Absolutely and so, like Dave was just saying it's, as these organizations start to make these major cloud migrations, one, their applications are getting actually significantly more complex than they've ever been. And they're now spanning a much broader ecosystem than they've ever spanned before. So that the kind of coverage that IT organizations and DevOps needs to cover not only is seeing this explosion of data but it's also now spanning areas of control that some of these folks have never had to think about before. And so the value of AppDynamics is our ability to be able to ingest data from your cloud native applications your traditional applications, all different sources of domain data that you want to get including things like security data. So we can start to correlate that in a meaningful way and then tie that back to business insights. And so the way that AppDynamics is actually bringing value to the table is not only helping our customers get visibility across the entire stack, but actually only surfacing the most meaningful insights to help them act on that those performance issues that they might see and more meaningfully manage their businesses. >> Linda I think you guys are onto something really big not just on the wave and just the positioning but one of the trends that we're reporting and we're going to be teasing out all week three weeks here is automation is great but that's just baseline. Everything is a service really speaks to some of the things that you guys have to put in place 'cause the mandate is everything should be a service. Now, I mean, I'm overgeneralizing but that's generally the ivory tower C suite message. Make it as a service cloud scale is beautiful, but then you when you pass it down to the teams, that's like that's not easy boss. It's not easy to do. That's really kind of what you're getting at here. It's not just automation and DevOps. It's the business model. >> Absolutely it's the intelligence it's once you create thousands and thousands of services, how do you manage them effectively and know what matters and what doesn't? >> Dave your final word here on on this point is when you think about that if you believe that to be true, then I'm just going to be downloading services whenever I need them. So it's almost like quasi self service managed services kind of coming together in real time or with my off base there. What's your take on that? >> No, we're actually working together with that dynamic and so all these kinds of things. So as we proliferate services, John and, AWS has got over 175 services and application is made up of many components. So how do you actually correlate an associate all the resources that make up that application? And if you think about dynamics name is the application and dynamics what's going on with the application. So we actually just launched today service catalog application registry, which is a new API surface for the AWS service catalog that allows you to define NGS on all the AWS resources from a cloud formation stack set all the way down into an easy to instance and associate that's an application known. And so the higher level of abstraction is what we talked about is management of the application. And what customers want to do, CIO's want to manage the application all the resources associated through the application whether the application is running well, is it secure? Is it on budget? Whether it's actually running? So application management is kind of where people are going even though their application is made up of dozens of associated services. So this is the next frontier. >> Well you guys are just great to have on world-class partnership two leaders, AppDynamics, story history they continue to do well. And even now with the world going on, Dave congratulations on your success. Final question for both of you is, where's the partnership go from here? I think it's a great success story. What's in the store for the future? >> Linda. >> Yeah to the moon. It's look AWS is an amazing partner. And Dave is a great guy to work with and where we are going is to help our customers build world-class applications and be able to manage them and modernize those effectively. And there's no way we could do that without partners at AWS. So it's a, there's a long-term relationship here. >> Well, congratulations, Linda Tong general manager AppDynamics. Thanks for coming on, and virtually at least we'll see you on the Interwebs during the next couple of weeks here, Virtual re:Invent Dave McCann. Of course, we'll see you again and great to watch you continue to grow. Is there any new title is going to add to your thing marketplace now it's migration, control services come on. >> With innovation culture we keep innovating. >> Great to have you guys on. Thanks for, thanks for sharing, appreciate it. >> John, Linda thank you very much. >> Thanks. >> Thanks for that great insight. Really appreciate it. I'm John from theCUBE you're watching coverage of re:Invent 2020. This is theCUBE virtual. (upbeat music)

(upbeat music) >> From around the globe, it's the CUBE. With digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Hello, and welcome back to the CUBE's coverage. Virtual coverage of AWS reinvent 2020. It's three weeks we're going on, we're on the ground here in Palo Alto. Doing the remote CUBE, CUBE virtual. We are virtual CUBE here. Wall-to-wall coverage over the three weeks. Got a great segment here, Steven Long regional CTO for AppDynamics and Ron Teeter chief architect with Jobvite. Gentlemen, thank you for joining me on the segment. Appreciate it. Thanks for coming on the CUBE Virtual. >> Thanks for having us. >> Great to be here. >> I wish we were in person. Normally we are, but with the pandemic, it's hard. Steven at AppDynamics. I want to ask you, you've got a customer here. We're going to dig into the use cases of the transformation journey, multiple wave transformation which I'm excited to talk about. But talk about AppDynamics. What's the big story for you guys at re:Invent, quickly get 10 seconds to explain. >> Yeah, sure. AppDynamics is the number one world's leading APM vendor and we're there to be the full stack observability platform. And in that we're talking today about our deep code insights, really to gain that visibility into production, securely capture data and really get that context through a dynamic application. So that you can find the problem and fix it right the first time. >> Great. Thanks. Thanks for that insight. Ron, I want to get into you're the chief architect which means you get the keys to the kingdom at Jobvite. You got to look over the landscape. You got to have the 20 mile stare out to the future but you also got to deal with the reality present here. And it's a tough one. When you go back, this is a terrible year a lot of weirdness, a lot of craziness but everyone's hurting, but they're retooling or they have a tailwind behind their back. So they're either accelerating faster or they're retooling. What does transformation mean to you these days? >> Yeah, so for Jobvite we had a distributed workforce prior to the pandemic shutdown. And what it did for us is it actually forced us to go all in on why can't we work remote all the time? Why do we care where we have facilities? And so we've gotten really good at scaling our organization and being productive remote. Now we actually can hire anywhere we want to, right? And that gives us more leverage and opportunities to scale our DMS going into '21. >> Awesome. Now from a technology standpoint, I'm hearing a couple of different stories, there's two extremes is the... I'll say airlines or those kinds of markets where there's not a lot of business happening, but they're retooling. And then you got obviously video or anything virtual modern applications. It's a surge in business so you have to move faster. Speed is critical. How do you retool in an environment where you've got remote which is totally productive, get that. But now I got more teams. I got to coordinate, I got to communicate. I got to make decisions, architectural decisions. They're big ones. And cloud certainly is here. You've got hybrid and you got the edge big themes this week. How do you look at that? >> The way we look at it, Jobvite has the longevity to remember what it was like from 2008 to 2013. we took that economic recession to build two additional products and launch them into the market in 2013 so that we could ride that wave of growth to drive our business objectives. And we're doing the same thing now. Hiring is a fluid market and this year hiring was way down, right? We saw a 60% drop in open requisitions on our platform alone. And you could see it just dive in March but it started coming back in August and September. And so at this point, we're now post pandemic. So the hiring rates right now are higher than they've been all year. They're very close to where they were last year for the same time. And we expect that to continue to climb as businesses continue to evaluate whether or not it's safe to scale. For us, this lull means we've got an opportunity to make changes to our infrastructure, that aren't going to be disruptive to our customers. But also allow us to get out in front of that so that we can go into '21 with a very strong product focus by taking care of some of the technical debt now. That's exactly what we've been doing is investing in ourselves so that we can operate faster with more agility next year. >> That's worth calling out and mentioning. That's great insight. It really is. You got to come out of the pandemic with a growth strategy. I hear all the CXOs and CSOs in particular dealing with all the security uses but they've got to have the growth strategy. Steven, this is where I think the cloud speed scale the operating model of software networks compute. You're seeing that now get back into the swing of things. That's always been the holy trinity, if you will, of technology, network compute, and storage. Now it's got the cloud and you've got an operating model. We're back to kind of a groove swing here. How does AppDynamics and the Amazon all fit together into this kind of journey? >> Yeah, and if we really look at AppDynamics, we focus on that digital experience. And I think when the pandemic hit we saw 95% of customers that we surveyed in our agents of transformation COVID survey that their priorities shifted. And 95% of those said, within that shift the digital experience became front and center. And so when you're operating in the cloud and you want to have that full stack observability not just from the end user and not just from your application perspective but also from your business perspective. And in any given business the application is the north star of the business. So placing the emphasis on that AppDynamics and surfacing what's actually happening at eliminating blind spots during this pandemic where it's more important than ever to have the best digital experience because that's the brand loyalty really, is that digital experience. >> Ron, I want to ask you, you mentioned something earlier you were talking about how you seized on the opportunity to virtual at home and you retool. But also you mentioned some of the macro conditions in the market, jobs are down, the other on the backup on the upswing. But the geographic hiring is a huge deal. I can almost imagine that's kind of an unforeseen use case where, I mean, it's kind of like working at home. Yeah, X percentage of people be working at home. We plan for that in our disaster recovery or disruption management whatever they do, now 100% people work at home. Now, 100% people looking for jobs. You probably need to rethink the use case because when you have a platform, you've got to think, okay how do I serve my customers who might have a need to recruit from more geographical places? That's a coding thing. So how do you do that stuff? Take us through the mindset of what goes on in your world. >> Yeah, so one of the nice things about building Jobvite as a hiring platform and a sourcing engine is, we use it, right? We now need to solve the same kinds of problems internally that our customers are facing, right? And so we control the software, we understand the problem. And so it's just a matter of deciding these are the things that we're going to prioritize next. We saw a very active summer of social justice outrage, and a lot of that stems from the lack of diversity and inclusive in hiring. And we're already responding to that by delivering features into the product line to help our customers address that in their places. And the key to this is speed. I think you mentioned it and Steve's talked about it as well, right? The ability to move quickly, safely it's the grail that everybody's looking for. And you have to have the right partners to make that successful. >> So I got to ask you then, what are the main benefits you see as you've got working at AppDynamics obviously you're a good customer there. As we're talking through it, you've got a great environment. You're a leader, and how to take advantage of these opportunities and code and shift. What's the benefits of AppDynamics in that equation? >> The key there that we see with AppDynamic's Cisco is the scale and the amount of innovation that they can drive through their product line. One of the things that Steve and I were talking about earlier this year during their transform event, was this deep code insights component which is really production runtime debugging. So imagine I can knock out my meantime to repair, my zero trust and my accelerated solutions of early detection in one solution, right? I can take something that would normally take hours, if not days, into minutes to resolve. The impact on an organization of just one simple feature like that is tremendous when people understand what it can do for them. And it's been invaluable for us. >> Well, you got the speed and the scale with the cloud. So take me through that impact. Because one of the things that's being discussed heavily here at re:Invent and in the industry is the new normal and the new realities we're living in, post pandemic as well. What's going to come out of it. And that is the expectations of the users and is going to drive the new experiences. That's kind of the theme. So the question is whether that's developers or end users or consumers or business users. That's huge, for applications to know what the user experience may be because we don't know what they expect and you don't have the right security (laughs). It kind of all crashes. So what's your... I mean you're nodding your head, weigh in, please. >> Yeah, so I heard a comment earlier from one of my peers in the industry, that is basically saying that nine months ago he had 400 facilities and now he has 18,000. Trying to imagine securing that environment For us, the way we think about it is, work is where you're at. And so we solve the access problems and the tooling problems a long time ago for Jobvite. But we'd been doing for our customers is delivering mobile recruiting solutions. So imagine I don't even need my desktop to complete the hiring process. I can work through the negotiations with a recruiter. I can talk to the candidate, I can text them. One of the big things that we released in early access last month was our new intelligent messaging platform. So that recruiters and hiring managers can have a much more rich conversation with candidates on the mobile device where the candidate is, right? And that's how we're trying to bring this new reality to the marketplace and say, "I can't assume that somebody has a browser and an email client anymore," right? Texting-- >> I mean that's a huge point. I mean, the joke Steven is, it's just distributed computing again 'cause there's really no cloud, there's no... If you think about the edge it's everything is the operating environment. Edge is the data center, edge is the cloud, edge is someone else's place. So if you're thinking about what Ron just said, 18,000 facilities, their homes or wherever, everything has to be looked, that's distributed computing we've been there before, right? I mean. >> Yeah and I think the way Ron, I think describes it, is highly accurate in his company, obviously, but in many companies where, if you've got those 18,000 end points in distributed computing you need to be able to gain visibility into production. And production could be a piece of code living anywhere. And if you can gain that and do that in a secure way which what we do AppDynamics, with our deep code insights, then you can look at data on demand and you can begin to understand the context of what's happening for that end user experience. And you can line up a watch point to watch the code that's executing. And then if it's not working you can actually see how it's not working, recreate that and actually fix it right the first time because you can actually see the code and production in the cloud in this distributed environment. And really be it's more powerful way to operate to reduce time when something happens that you need to fix. >> I was talking to a friend yesterday about this. We weren't on camera. I wish the cameras were rolling. But I'd love to get you guys' reaction to this, because we were saying... I remember when I broke into the business as a young CS major in the late '80s. We had to install everything by hand the software, you install stuff on a server. Or had stuff on a machine and then you put it on a server, you put it in a data center, all those things, right? The young kids then come in and saying, "Okay, I just use the cloud." The next generation and they never installed anything. They don't even know what an installation pack is. Now the next generation's not going to have versions. So you start to get into this notion of evolution with software, because if it's software operated you don't know what version you're running. It shouldn't be disruptive. And the point is this is where I think you guys are getting to here is, the holy grail is there's no disruption. You're running your software at home. Your reaction to that kind of evolution. >> Yeah, you want to take that Steve first? >> Yeah, sure. I mean, it's like you said, the way that code has gone to be delivered and executed is it explodes and disappears. And if there is no way to track that and trace that and understand it, the generation we're in of code, that's a femoral. What's it going to be next? And where's it going to go? And will it ever live anywhere that's alive? The technologies are really being pushed and that's the exciting part. And that's why from an AppDynamics perspective, we're investing in open telemetry is distributed tracing. So as you got distributed computing, we do distributed tracing. And we really look at the problem and provide solutions for our customers. >> Awesome. Ron, your time. I mean, observability, if you can't observe it, you can't measure it. You don't understand, it opens up a lot of things. You got to have the observation space and that's everything. It's hard. >> Yeah. Yeah. And especially as we transition from visual physical servers to virtual hosts, to virtual processes, to virtual functions, right? At some point it's the, I don't even know how to measure capacity for a function in the cloud, right? Let alone try to understand well, what's the cost going to be before I actually deploy it and measure what it's going to cost, right? So these are some of the areas where I think a lot of companies are struggling in understanding how do I move something I'm traditionally very comfortable with. This, I know how much a host costs and I can put my software on there and I can run the CPU at 100% and then I know what I'm getting. But as you start moving into virtual processes and virtual functions, it makes it so much more difficult to think about how you do that capacity planning and budgeting exercise in advance. One of the things that we do with observability is we can test it and we can measure it. And then based on that measure we can make predictions about, okay, this is what it looks like in Def, let's extrapolate what that looks like in production, just by scaling the load. And in areas where you've taken IO and network out of the equation that kind of extrapolation works very well. >> That's awesome. Congratulations on a great a use case, Ron. Thanks for sharing your story, Steven. >> Of course. >> Thanks for coming along and highlighting this great use case and congratulations on having a killer product with observability of AppDynamics. We've been following your work as a company and now at Cisco. So yeah, it's killer software. >> Thanks. Modern software is upon us again the next levels here, gentlemen, thank you for your time. Appreciate the insight >> It been a pleasure. >> Welcome. Thank you for the opportunity. >> Okay, This is the CUBE's virtual covers. We are the CUBE virtual. This is what we do now. We're not in person, but we're remote. When we get back to real life, we'll be back on the scene. We're still doing the interviews. Thanks for watching re:Invent coverage 2020 virtual. (soft music)

>>Fly from Barcelona, Spain. It's the cube covering Cisco live 2020 route to you by Cisco and its ecosystem partners. >>Hello everyone. Welcome back to the cubes live coverage. Four days here in Barcelona, Spain for Cisco live 2020 kicking off the year. Great event. I'm Jafar way my co Stu Miniman, our next guest, Danny Winokur, general manager of app dynamics, part of Cisco and special keynoter headlining the event, the networking show headlining by the app development story. Any welcome to the cube. Thanks for joining us. Thank you. It's good to be here. So one of the big signals, I think it was a shot across the bow to the industry, but also internally within Cisco has been the multi-year movement around getting API APIs built into the products. You start to see dev ops become network ops. Now with app dynamics, digging down into the infrastructure provide great value, but in a DevOps way. This is, this is the top story in my mind. You've led the keynote, which was very unusual for Cisco. Was it planned that way? Tell us some of the background. >>Well, it was planned that way. And I think part of what we're recognizing is that in the world that we're now living in where applications have moved to become the center of the business, you have business initiatives encoded in applications and that's what actually drives the use of technology in the organization. So it really starts with the application. And Cisco of course recognizes that and that has implications for the way we think about the entire technology stack. And so we see it as an opportunity to actually make the infrastructure and the people that actually buy and work with the infrastructure, the infrastructure engineers and operations teams, network engineers and network operations teams, they become much more relevant by actually looking at how the technologies and the work that they do are actually placed within the context of the application and how that application and the experiences within it are delivering a business result to the larger organization. >>Yeah, and one of the big trends, how she's doing, I were early days in the cloud, watch Amazon rise up. No one kind of saw that common. Most of the insiders did, but API APIs were key, but the word dev ops was started around that time. Infrastructure as code makes a lot of sense. Programmable infrastructure. That's right. You guys picked up on that. We've been covering that for now for a four years around programmable networking and you guys have been just goes, been shifting the products, but during the keynote you mentioned biz dev ops, which I thought was a very fascinating stake in the ground. Could you explain what you meant by that? Because if I think what you're saying is true, this is now another layer of opportunity that takes advantage of all the scale. The agility. Efficiency. >>Yeah, that's right. That's right. So I mean, what's what's going on is companies that now say, okay, my business is now in my app. The app has become the business. They have to now figure out how do they iterate very, very quickly on that application. And in order to iterate very quickly, the business team, the development team and the operations teams need to work together in a closed loop operating model. Because if they don't work together closely, they have two big problems, right? One is the business initiatives which move very quickly, can't get encoded quickly enough in the application and the application falls behind and the business suffers. Number two, they can't produce winning experiences because executives like us sitting in a conference room with an idea for an experience are almost always wrong about what's going to work for the end-users. The way it works in the modern world and what we know from digital native organizations that have pioneered this is that you actually have to form user research and a hypothesis from it and it in your application and get it quickly in front of your users with real time measurement and telemetry and then you use that to inform yourself in real time around what's working and what's not. >>You reform your hypothesis, make that adjustment reimplementing code, get it back out and iterate and iterate and the more shots on goal that you're able to take with the velocity of iteration, the more likely you are to get to the winning experience. So biz dev ops is really around getting those three teams, the business team, the development team, and the operations team working together with velocity in a new operating model that allows you to actually gain the competitive advantage that's necessary in an experience driven application centric world where the infrastructure and development team and the business are now all working together in tandem, in lockstep. >>The antennae had really interesting stuff as we all know that the organizational construct in the silos often slow down that that innovation and growth we watched for years developers, they find their tools, they do their thing, but as you said, it's got to be connected with the business. I want to make sure I understand. We've seen somewhat places where some of the tooling actually is getting people together because they have common data. You give the business people things in their colors and languages as opposed to the developers. They need different things out of it, but it's a, it's a backbone or back plane buildings together. So are those business product owners or business leaders actually coming into and seeing things? Is it at that level, the >>really important point, right? The problem that we've seen in the traditional operating model is not only are the teams siloed, but the technologies and the data that they rely upon keep them siloed. And so as the changes in the market are pushing them to work together for the reasons I said, they need common tooling and common data sets. And so what we're actually doing at Cisco is connecting app dynamics to the tools that are beneath it in the stack. Like what we announced yesterday with the inner site inner site workload optimizer and what we've previously done with ACI for the software defined data center networking fabric so that you can actually have each team, each persona use a tool that they're comfortable with that's specialized for their domain, but the datasets are now connected. So it gives them a single source of truth that allows them, instead of finger-pointing when something goes wrong or they need to optimize, they're able to actually have a shared source of truth and they can say, okay, I understand my domain here, I understand my domain here, but they're telling me the same thing, and that makes it easier for them to collaborate in this closed loop, the operating model. >>Whereas it was harder to do that when they were looking at their separate tools and separate data. One of the things I want to get your thoughts on, Danny, is as coming from the app dynamics side now at Cisco, you've seen a lot of modern used the word modern applications. The modern architecture is evolving. People see the picture, they know what to do. Most enterprises outside of the the pioneers, they're like, okay, I love the idea of biz dev ops, but Hey, I'm just trying to figure out which cloud I'm going to use. Right. Okay. So take me through how you engage with that because you're kind of, you might be ahead of the curve on the thought process, but I'm just trying to crop the cloud and it's impacted me as a notarized. What do you say to that? What's that? What's your answer to that? >>I mean, what we see going on right now is that in almost every single organization that has their business now running in the apps, those apps are hybrid multi-cloud apps, right? They recognize that in order to iterate quickly on the front end of the application, they probably need to use some of the latest cloud based technologies, either in the public cloud or in a private cloud on premise us. But they also have other components of their architecture that are going to be using something more like web technologies or client server technologies or in some organizations still mainframe technologies for backend data access. And so you end up with this sort of diverse array of layered tech stacks across different deployment environments in a multi-cloud world. And they have to work together seamlessly. And so part of what we've done is innovate lenses within app dynamics that actually give you a view through that complexity so that you can focus on what really matters most. >>And that was yesterday's announcement of the experience journey map that we have from app dynamics, right? It compliments what we've done before with business transactions and business IQ and adds a new lens that is focused on the screens that the end users are actually seeing in their browser or on their mobile device. And it automatically uses AI and ML technology to map a screen by screen journey flow through the application that the user's actually seen and experienced seeing and experiencing. And within that screen-based view, it gives you business data like abandonment rate and it correlates it down to the technical performance of what's actually being served to the user on that screen so that you can quickly determine where are the technology issues across this broad hybrid multi-cloud estate. Where are they actually surfacing issues or not on the screens that your users are seeing. >>So you can now prioritize the warnings on the back end based on what your users really need you to address right away. So if I hear you correctly, what you're saying is essentially cause instrumentation. You mentioned that earlier data is critical. So what you're saying is you could have abandonment rates say's an app or whatever and say maybe there's a DDoS attack on, on a switch or a firewall. So I might want to scale that up with policy. So you're seeing, you're coordinating technical remedies or architectural changes based upon what you know, the business logic, is that what you're kind of getting at? That's exactly right. So we know from data that we have from our app attention index, that 50% of users are willing to pay more for a competitor's product if it performs and gives them a better experience. And worst yet 63% of users and the app potential index have told us that if they get a subpar digital experience, they're going to go out and actually not only leave but bad mouth, the experience that they had and spread ill will about your application. >>So what has to happen in that world is you have to actually relate your business performance data to the user experience within the screen, through the experience journey map into the backend application components, which is the business transaction and then down through intersite into the layers of the infrastructure where you can actually get into the chassies, the blades, the fans, the Dems and the network. So essentially it's like auto scale and concept that will, you know, in cloud that's right. Fly to the app level and a feature by feature basis. That's right. And you can do it exactly. You can do it within the context of the key experiences that have been prioritized as the ones that contribute the greatest impact of your business results. And you can work load optimize and scale infrastructure dynamically and automatically. Final, final point on this cause a good thread here. >>So final question is, okay, now prove it to me. How much money did I make? Can you guys tie that to actual dollars? Because then on the client's side, do they have to program then? No. So you can within app dynamics, through our business IQ capabilities, tell us through the interface of their product, what are the pieces of business data that are the key measures of your business success. It could be dollars, it could be cents, it could be skews, it could be a product ID, it could be an abandonment rate or a funnel conversion through your funnel. You tell us what are those metrics that you need and we will actually introspect, pull them out and give you a real time ROI. It is. That's what it is. So, so Denny, the thing I've been trying to chomp at the bid here, I'm agreeing with a lot of what you're saying. >>There was a trend that was all over everywhere that we went in 2019 that I heard and haven't heard you use a certain word. It's observability. Certain people are like one of the biggest trends of 2020 help us understand your viewpoint on observability what you're hearing from customers because much of the language you're talking about of that systems view resonates as what we're talking about. Observability so just not fond of the word or none. Not trying to jump on that bandwagon. It's a buzzword. What I'm talking about is full stack observability. That's exactly what it is. You can go from the business to the end user experience, the application, the compute infrastructure, the network infrastructure and the security domain that wraps at all and you can actually now see with telemetry that we're pulling in from each of those layers whether it's using app dynamics or using some of the instrumentation that Cisco has across those other infrastructure layers and security layers of the stack. >>We pull that all together with AI and ML produce insights and then provide an API that allows integration with systems for automation and action that is not only full stack observability it's full stack observability paired with the ability to implement an AI ops operating model that then supports a biz dev ops way of working for the company. You might want to throw in horizontal observability too because you know with cloud you've got horizontal scalable across deployment. Exactly across your deployment environment and from an application standpoint, everything from kind of traditional model is through microservices. Do things with serverless do are absolutely we have, we have agent technologies that take care of the very latest serverless technologies. We have things for Kubernetes cluster monitoring, we have support for CloudWatch and then going all the way back to the other side. Of course, traditional job applications.net applications back to mainframes IIB. >>We monitor and support all of that. It's the broadest array of visibility of what you're going to cabbage in the company working for you, the all the cool stuff. Cloud native Coobernetti's we've tried, we let, we like to be the cool kids. Magic questions. So I got to ask you, since you've got a good view up and down the stack and across multiple domains and workloads and clouds, what do you think, going into 2020 with this show and beyond, what is the most important story you think that people are talking about and what's the most important story that you think people should be talking about? I think the most important thing that's going on right now is figuring out how to connect across the different technologies and the different layers, right? We're coming from a place where there's naturally been a specialization within each of the domains. >>The whole point now is about multi domain and actually connecting the different layers of the technology stack to produce insights that allow for movement in this lock step higher velocity model. Because what we know from all of the data and all of the experience with customers is that the winners and an experience driven world are those that can actually implement with velocity, not break things and deliver well-designed, beautiful experiences. And in order to do that, you need to be able to connect these different technologies and get the teams that traditionally run them working together in a much more collaborative, what are people missing? What should we be people be focused on. Outside of that, what other areas that either the media or customers, what are the, what are some of the hidden gems out there that people should really pay attention to? Well, I think, I mean I think there's a lot of exciting innovation that is going on in some of the new cloud native technologies in the cloud native architectures. >>The other thing that I think is a little bit of a hidden thing that a lot of people haven't realized is that the cloud is great for some of the really high velocity, fast moving things, but it's not always the most efficient or the least, sorry, the most cost effective way, least least costly way of running everything and so we actually do see some recoil back to these hybrid environments where people are actually now running some cloud technologies on premise us and so I think that's an area to watch as we see some of the public cloud players, obviously out of the traditional players bringing cloud innovation, but running that on premises in a way that connects seamlessly to elastic scalable public cloud resources that work together in tandem. I guess last >>question I had for you, I think it was in your keynote, I heard you talk about customers using app D as being agents of transformation. Just what advice do you give them? You know, where are some of the stumbling blocks that if they don't have a conversation or understand a certain architecture that they're going to run into some issues? >>Yeah. So for us, an agent of transformation is the sort of notion of a change agent in the organization that recognizes the things we've been talking about where the world is going and is seeking to be that disruptive force of change inside the company. And in order to do that, what we have found is they're most successful when they get their hands on hard cold data, right? That's how you convince an organization. You show them the data and you connect the data and the technology to a business result. And so the most effective change agents have been able to go into the depths of the technology. They've been able to correlate data sets up and down the stack and then walk into the board room at the executive level and show in an undeniable evidence based way that these layers of technology are producing this business result and the organization needs to invest to accelerate that. And that's >>jail model too. You just get the data and iterate. Double down on absolutely what you want. It brings it all the way up to the boardroom. Danny, thanks so much for taking the time to share that. Great insights. I'll give you a minute to get a plug in for app dynamics. What do you guys got going on? Which shows you're going to be at the coming year, actually Cisco live in America. Any other event you going to be there? Any investment areas? Give a quick plug for what's going on. >>Yeah, no, I appreciate it. The next big one for us is on February the 20th we're running a global virtual event called app dynamics transform 2020 which is our annual showcase where we bring together all of the latest and greatest innovations that app dynamics has across what we're doing with AI and ML. Everything that we're doing around new experiences, cloud native technologies, the AI ops operating model, our vision for the central nervous system for it, and we're going to showcase all of that demo and talk about our roadmap. So it's a global live virtual event. Come to our website, aptdynamics.com and please tune it. Right. Well, congratulations for your success and thank you. Love to have you come into our studio. Talk about what you're doing with video because that's a hard, hard problem. We talked to Sri about that. Thanks for coming. I really appreciate it. Thank you guys. Yeah, appreciate it. We're here in the cube AptDynamics headlining the keynote at Cisco systems. A networking company turned into a data company, a video company, an instrumentation company. Application can be all now in one. Just the cube bringing you all the data here in Barcelona. I'm John. We'll be back with more live coverage after this short break.

>> Live from San Diego, California It's the queue covering Sisqo live US 2019 Tio by Cisco and its ecosystem. Barker's >> Welcome Back. We're here at the San Diego Convention Center for Sisqo Live 2019 30th year The show. 28,000 in attendance. I'm stupid, and we're actually at the midpoint of three days of life water wall coverage here and happy to bring back to the program to Cube alumni first. To my right is Ben I, who is the CEO of Turban on Mick. And sitting next to him is Thomas wide, who's the chief marketing and strategy officer of AP Dynamics or APD? Ia's everybody calls them here at the show. Gentlemen, thanks so much for joining us. Thank you. All right, So, Thomas, first of all, we had you on it, reinvent like soon after the acquisition of AP ti Bisys. Go. It's been about two years, and I believe it's been about two years that turban Onyx been partnering with Cisco. So let's start with you. And you know what? What changed in those two years? >> Yeah, it's been amazing. Two years ago, we were on the doorstep of an I P O and it's been a rocketship ride ever since. You know AP Dynamics. After the last two years, the businesses more than doubled team sizes more than doubled, and today we're really happy to be the largest and fastest growing provider of application for miss monitoring in the market. But the reason why, that is, is because our customers are embarking on the sigil transformation, and the application has really become the foundation of their modern day business. That's the way brands are engaging with their users. And but now more than ever, and then the application landscape has gotten way more complex, with micro services and multiple clouds and all of the threats that go on in the infrastructure. And so what Hap Dynamics has been doing is just really providing that really time business and application performance that our customers need to ensure business outcomes. We think of ourselves as Thie Marie for the application or the infrastructure. >> That's awesome. So then, you know it's been interesting to watch in the networking space the last few years. For the most part, applications used to be That's just this thing that ran through the pipes every once in a while, I need to, you know, think about performance. I need to make sure I got buffer credits or, you know, it's now going East West rather the north south and the like. But it was solutions like turban on IQ that sat on top of it and helped understand and help people manage their application. Of course. AP ti pulling that story together even tighter. So, you know, give us the latest we've talked to you. It's just go live before an important partnership. What was the latest in your world, >> boy? The well, so one of the things we're doing is we're building an actual bundle together without D. And if you think about a PM, you're getting the application topology as well as response time and use a response time, which is critical to maintaining the brand and the digital economy that we're talking about. What when you look at every one of those hops and the application of there's a entire application stack that sits underneath a resource ing stack and what we're doing is we're bringing in a R M, which is application re sourcing management with a I so that they're automatically adjusting the resource is in all times continuously in order to support the performance needs that Abdi is showing us when you put together a PM plus a r m. You have total application performance and that customers air really, uh, queuing to so much so that we've actually decided to put this bundle officially together in the marketplace. We just became the first ap TI re sell software product, and now we're taking not to market as C one plus happy. >> Well, congratulations on that is harder ship, Thomas. Bring us inside the customers a little bit. What does this mean for them? You know what that journey we talk about, you know, for, you know, last 10 15 years, you gotta break down those silos. It's not just the networking team, you know, tossing over some band within Leighton, see and write them coming back. And I need some more. No, no, we're not going. You know, we're not going to give you any service level agreement or anything like that, because that's not our job. To what? We'll just set this up and you use what you got. So what would happen in >> trend that we're seeing is a move toward this concept of a iob, which is the really the consolidation of bringing and user application network and infrastructure monitoring closer together and tying that together with a base insights to Dr Automation and Action and very similar to what turbo gnomic specializes in here. And so what we're seeing is, you know, the combination of Cisco plus APP Dynamics. Plus, companies like Turbo is beginning to build that self healing, self learning environment where developers and environments need to be able to drive automation on that. Automation ultimately gets tomb or innovation when you can reduce the mundane tasks, really take a lot of our developers time. And so we're really excited about some of the work we're doing together when you think about the ability to take really time business insights from the application and reprogrammed the network based on the needs of the AP or change out the workloads and move them around on different servers, depending on the needs of the AP, these are all things that combination of Turbo, Cisco and epidemics are doing together. >> Yeah, actually, I did a whole show down in D. C a couple months ago, Cisco Partner. We're focused on a I ops. And, you know, we understand customers had a lot of tools that they have to deal with. We need to simplify this environment, allow them tow, you know, focus on their business, not managing this complex environment of all these tools. How does that whole concept of II ops and, you know, automating this environment managing my workloads? You know what? What do you sing with your customers? >> I think all the customers are saying, Look, there's too many tools today. They don't need another resource monitor, et cetera. What they need is they need to understand, through the lens of the application, all the resource dependencies. So instead of looking at a field of servers and saying, I have five nines availability or storage or whatever, what they really want to see is whatever the servers and storage and resource is dependent on this specific up that runs the bank or the CPD company of the manufacturer. And can I make sure that those re sources are supporting performance of the application? And that's is this total application performance concept, much more so than than whether I have five nines availability and all my other host accents? >> Yeah, absolutely. Did you have a comment on other Guy's >> gonna say We're seeing so many different customers in different verticals, Whether it's retail, hospitality, automakers, they're all benefitting from the cloud migration. And now that they have the cloud migration, the ability to have that elasticity of their workloads, they're scaling in and out based on the application demands. This is becoming critical. This is no longer a luxury for the most cloud eight of companies in the world. Enterprises with mission critical systems are all becoming dependent on these more modern technologies. And I think they need partners like ours more than ever. >> Yeah, One of the questions we've had is you talk to customers today and they are multi cloud. But that multiyear hybrid cloud is a bunch of pieces and one of our premises. We ask, from a research standpoint, how can this some of those pieces be more valuable than just the independent pieces alone, you know, kind of one plus one with, you know, an extra factor talk a little bit about the customers. And also, you know, what does this combination do that I couldn't just, you know, grab these pieces together and kind of make it work in my portfolio of those, you know, dozens of tools that I have. >> What glad. But I think the customers one of things this needed. We literally announced his partnership publicly two weeks ago and already have closed the 1st 2 just out of momentum that that folks are realizing the need to be able to say, Look, I can host my applications on Prem with a number of different vendors, I can host my applications off Prem with a number of different vendors. But the real question is, where am I going to get the most performance? Where can I do it in a compliant way with all my policies and how can I make sure that I'm doing it cost effectively? And when there's a multiplicity of tradeoffs where I can choose, then it's incumbent upon each of those vendors, strategic as they are to be able to offer the best service, the best performance, the best compliance and resource ing, and that's what we're bringing to him. And I think that's why you're seeing that a pipeline is built to several double digit millions and already deals are closing everything I'd >> add to that Is that, you know, going back to the point around a ops in the evolution of a lot of these modern ing and automation technologies. >> A lot of our >> customers have a hybrid environment of different tools and providers that they leverage. And so one of the things that were really focused on is an open ecosystem where you'd be able to ingest data sources from various different players. Some of them can be Cisco, Turman, Onyx and Abdi. But some of them can be other providers that are also have very good products in very specific domains. I think the key is that being ableto be ableto bring that data together, Dr Cross domain correlation in a more automated way than ever before, leveraging some of the more modern AI ai capabilities, which drives the action ing that people really need. And that is really the automation step is where customers start to see the benefits. But I think the better and more valuable the data that you have, the better automation you could do because your predictability of your algorithms are much better at that >> point. All right, been your customers that have rolled out that this solution I know the joint solutions brand new. But what? What is then the key metrics? Howto they define success how today they know you know that they they've reached that success. >> So first and foremost, the line of business. Who's the customer to central it? Whether it's hosted or not, they care the most. That performance does not degrade and is always improving. Okay, But when they do that and they can show that, then a ll the decision that the rest of central takes down in fromthe container layer to the pods that a virtual to the cloud I asked on Prem in off those become acceptable choices for central i t. To make because fundamentally, Lina businesses saying, Yep, we're good, right? So that's where we're seeing the value of being able to see the response time and bridging the application performance to the application resource ing that frankly hasn't ever been solved in five decades of it. And I think it goes back to a Thomas was just saying It's the quality of the analytics that comes from a iob. I don't think people need more tools to capture more data. There's a lot of data out there. The question is, can you make it actionable? And are your analytics correct? And, frankly, are they the best? And I think we see that that's been a big parcel of what we've done during the two years Cisco's told us on multiple occasions it's the fastest software O AM they've had by bringing it through, starting with the data center team and growing up through traditional Cisco and then with their purchase of Abdi two years ago. That combination makes a ton of sense, and now you've got the top all the way to the bottom. And that's a pretty special spot, I think un replicated by any other strategic today. Yeah, the other thing, >> I just added, That is the importance of being able to monitor the business in real time as well. And so a lot of what we've talked about are the technology analytics, the operational analytics that we run our business on, but being able to correlate the business transactions running through the application, so users what their journey looks like, they're, you know, abandonment, rates, revenues, you know, the ability to engage with the users, tying that back to the specific infrastructure in a way that's used to be a bit of black box before. Now that all comes a life by the combination of these technologies. >> So Thomas big trends we see at this show. So a Cisco's transformation towards a software company and the world of multi cloud abdi plays a pretty important piece of that. You know, discussion. Talk a little bit about kind of where you are and you know where do you see Cisco moving along that journey and then, you know, help tie in where turban Ah, Mick Fitz. >> Yeah. So I think it really goes back to the fact that as our customers are making this digital transformation, they're really looking at a variety of infrastructures. You know, cloud providers to be able to offer these applications. And what Appdynamics has done is really created this monitoring fabric that sits across any infrastructure and it tightly ties to the business value of the application. So if you combine that with a lot of what Cisco's doing around connectivity securing the clouds, securing the infrastructure around it and tying that Teo where we're strong and networking and bringing all that together, I think fundamentally, we've got a lot of the pieces of the puzzle to truly enable a i ops, but we don't have them all. And I think that's what's important, that we partner with people like Ben because it brings together a set of automation capability around application resource ing that we don't have and our customers are better suited working with with Ben and team on that. So how do we integrate those things in a frictionless way and make that part of our sales process? That's really what this partnerships all about. >> All right, then where do we see the partnership going down the road? >> I think it's going to get more exciting. So right now we're pulling unit Election Lee from Abdi. I think we're going to go right back the other way. That Thomas referred to, which is one of my favorite parts of Abdi. Is the business like you? Yeah, it's where you say, What is the cost of the late and see in anyone? Hop and where do the Bandon rates? Abandonment rates happen from consumers on that application right now, we can price for the first time what's the cost of the late sea in that one tear and across the across the application overall. And then, more importantly, what do we do about it? Well, that's the resource ing and the digestion is being resolved in real time. And so I think, the ability look att, the resiliency of applications both across and up and down the a p m plus the a r m and being able to guarantee or assure performance, total application performance. That's a big message. >> All right, what would I give you both? Just fun. A word here, you know, about halfway through the conference here in San Diego. Thomas, >> I would just say that the energy that we're seeing, the feedback we're getting from customers in the business insights part of the world of solutions been phenomenal. I think there's so many more developer oriented, application developer oriented individuals that's just go live than ever before. And I think that serves both of our business is quite well. >> Look, I think this has been a great show, but one of the things you're going to see is all of these vendors who have had global presence for in this case, 30 years. Sisqo live 30 years long But now being able to think through how do I become that much more application relevant? You know, if you think about transformation of application is going to come top down, not bottom up. And so, while we have all the evolution and, frankly disruption happening, digital disruption happening across it, the way to know which of the ones that are going to stick, they're going to come top down. And I think the moves that they're making all the way through buying happy all the way through partnering with C warmer turban Ah, Mick has been emblematic of what that opportunity is in the marketplace on the realization that customers care about their applications, their applications run their business. And you've got to look at the topology and you gotta look and response time and you gotta look at the resource ing. But that's a really fun spot for us to be in together. >> Bennett Thomas Congratulations on the expanded partnership and thanks again for joining us on the Cube. Thanks to you. All right, we're here in the Definite zone. Three days, Walter Wall coverage. Arms to Minuteman, David Long days in the house. Lisa Martin's here to we'll be back with lots more coverage. Thanks for watching the Cube

>> Live from Las Vegas, it's theCUBE, covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> And welcome back to Las Vegas. We are at AWS re:Invent, along with Rebecca Knight, I'm John Walls. A lot of energy still behind us here. >> It's amazing. >> Have you noticed that? >> This is day three, people, wow. >> And again, I know a lot of you watching, you come to shows, you attend these things, and you realize that day three sometimes can be a little bit >> Sleepy, yeah. >> Slower, yeah. Not so here, this place is still very much alive. >> Sin City. >> Yeah. Easy, easy now. (group chuckles) We're joined by a couple of gentlemen right now to join us here, Prathap Dendi, who is the General Manager of Growth Initiatives and Commercialization at AppDynamics. Prathap, thank you for being with us. >> Oh, great to be here. >> And Emmanuel Offiong, who is Vice President of Enterprise at Wyndham Hotels. Emmanuel, now usually the conversation in here is, hey, how ya doin', where are you staying? We don't have to ask you that. (group chuckles) We know, right. >> Right. >> So you're good to go at Wyndham. So, first off, let's just talk about, I'd like to get your ideas, we've talked about the show, I mean, how do you feel? You're probably around here quite a bit, Prathap, at various shows and what have ya, your thoughts about what you're seeing here at AWS re:Invent 2018? >> For starters, I think you guys need at least 10 more Cubes because I've been watching the activity here. It's just, you know, crazy, right? A lot of high energy here, a lot of cloud stories, multi-cloud stories, really feed on that, a lot of innovation that's being announced here. >> Alright, and Emmanuel, we hear this a lot, right, customers who are making that big digital jump, you're making that leap, and, in some cases, it's a bit of a leap of faith, right, in some respects. Let's go back to before that, the genesis of your decision, what was the impetus and what were your reservations, and what are your reservations still, for that matter, going forward? >> Sure, so I actually joined Wyndham about three years ago when we were trying to undertake this digital journey, and what we realized was that there was a lot of competition with our online travel agents, and we weren't really bringing in customers the way we thought we could, and so we realized that our digital platforms were antiquated. They weren't speaking to our customers in terms of increased loyalty and such, and so we knew that we had to make a change. We knew that in today's economy, in order to attract customers, we had to be more digital friendly. We had to provide a seamless experience, and we had to make sure that, on all of our platforms, that customers were able to check-in and check-out on their mobile platforms very easily. >> You mentioned online travel agents, but just talk a little bit about this era of hoteling. Has it become so much more competitive, particularly with the rise of Airbnb and other VRBOs? >> It has, it really has, so the Expedias, the Airbnbs of the world, they've really embraced technology, more so than maybe the traditional hospitality companies have, and so that's why you'll see companies like ourselves starting to make investments in technology, making investments into digital transformation. >> So you have your aha moment, we need to move forward, we need a digital transformation so you begin to look for partners. What were you looking for? >> Couple of things, so we were looking at transformation on three levels, for digital, infrastructure management, and data, and so, in terms of a partner, what we wanted to do is we were looking for someone to help us ease that journey. We knew the journey was going to be rough, especially from where we started, so we were looking for a partner like AWS that was going to help us sort of make that scale into modern-day technology very quickly. >> Alright, so when you talk about a digital journey, I just want to back up a little bit. What exactly does that encompass in your case? I mean, I'm thinking you've got your website, you've got your reservation, you know, you've got all these microservices running on your site, you know, it's all good, it's all fine. What weren't you doing specifically germane to your business that AppDynamics is now getting you back up to speed and getting you into the 21st century, if you will? >> Sure, so let me give you some context then. When we talk about customers, we talk about two sets of customers. There are guests who walk in through the door, and then there are franchisees. We're a franchise-based company so let's speak to our guests. In regards to our guests, our check-in/check-out process wasn't as seamless as it could be, right. It wasn't very mobile friendly at the time so those were the things that we were looking to change, and in regards to our franchisees, their ultimate goal is they want to be able to check revenue. They want to be able to check rates, change rates. They want to be able to see what their competitors are doing, and they want to be able to do that very seamlessly and on a mobile platform, and we didn't have those capabilities available to them at the time. >> If I may say something? >> Please. >> It's interesting when we see leaders like Emmanuel talk about digital transformation, they're not talking about I.T. transformation, they're not talking about servers going away, infrastructure. It's really refreshing to see customers talk about business model changes. What I see, you know, Scott and Emmanuel, their team has done a great job about focusing on what is it about the business model that needs to change, and really getting that end-user experience journey, like you asked, right from the time they log-in to requesting a service or changing some reservation, all of that is what they're capturing, and it's really complex, and I know he's quite humble to say, oh, we've done it at scale, but this is hard stuff, to make it simple for the end-user passes the complexity down to the systems, and that's what the team at Wyndham was able to do and we're lucky, AppDynamics, to be part of that journey that monitors the end-to-end performance of the end-user journeys, and then importantly correlate that to business outcomes. You know, do we actually have more partners coming in? Is the full journey faster now, now that we've gone to AWS, is it really impacting the business or is it just I.T. spin? So that's really a good caller to see that digital transformation is really a business model change not just an I.T. change. >> So the business model, so walk us through exactly what you did for this transformation and this cloud migration too. >> Sure, so the first step was realizing that we had to start to migrate some workloads to the cloud, and the reason why we knew we had to go to the cloud was, like I said before, we wanted to get out of the business of managing infrastructure, right, so we said we're going to take our workloads to the cloud. Well, going to the cloud, especially with the type of workloads we were looking at, is often a very complicated and complex adventure, and that's where AppDynamics came in for us, right. We knew we needed something that was going to allow us to see end to end where we started from, and when we migrate to the cloud, have that same level of visibility to ensure that we didn't do two things, right. We're protecting the brand, and we want to make sure we protect our customer experience. Those are the two things that were most important to us as a part of this journey. >> From a security standpoint, huge concern, right? I mean, it has been for a while, but when you go public and what exposure there might be, how have you two kind of dealt with that because, obviously, you're dealing with financial information, with customer information, there's a lot of proprietary stuff that you're getting from your folks that you have to protect, and, obviously, internally as well. So talk about the security component. >> Yeah, happy to go first. It used to be just about five, six years ago, application was seen as a separate silo or a separate layer, and security was different and experience was different. What we're now seeing is every business function is getting really melded into that one concept of end-user experience so security becomes, not an afterthought, but actually is part of the design construct, right, and what we've seen with customers like Wyndham is they have gotten so much better at measuring right from the click stream of from reservation to fulfillment, and looking for anomalies in that data, right, so security correlation to the application data is out of the box now so that's the pre-design for architecture groups like Emmanuel's. >> Sure, yeah, so I (chuckles) I think you said it very well. >> I'll say what he said, right? (group chuckles) >> Well, when you're thinking about this migration, which began in, when did this journey begin? >> Couple years ago. >> Couple of years ago. So, now, was there resistance to it? As you said, you were really at this tipping point where you said we got to do something different here. We've got a lot of different competition coming at us from different angles. >> Yeah, so there was some level of internal concern, I would say, but we worked through that, right. It's really about, at the end of the day, we migrated 8,400 hotels across 18 brands onto this new platform, right, so it's not insignificant so you can imagine, right, the amount of internal conversations that needed to happen to get something like that accomplished. >> And what haven't you done? Obviously, this is a multi-year process. You can't snap your fingers and it's going to be done. I assume you're in a still a nascent stage of this, and you have much more work to do. >> Yep, now we're focused on data, right. Now, we're focused on grabbing insights from the data that we've put into the cloud. We've migrated most of what we were looking to migrate over the last two years, if you will, and now we're lookin' at how do we get more insights from the data that's available to us? >> Alright, and is that something that your company can play with as well? >> And Amazon and AWS themselves so I think over the years what I've seen, you know, I've been an engineer in this career, now in the business side, you co-system around application stack has gotten so transparent, right, so customers like Wyndham are able to purchase best of breed solutions like AppDynamics on AWS marketplace, click of a button. There's no long cycles of value so you quickly get to the value, and then once the journey starts, it's really all about the customer. They're generating trillions of data set every day across their business. Our goal is to see how can we bubble up the impact of that investment to their line of business? How quickly are the customers getting on board, making their decisions versus having to worry about the servers and the infrastructure. That's what we're seeing in a big way. >> Well, and as you said before, this is a business model change. It wasn't just a technology change so how have your customers seen this? How are they reacting? What are your franchisees seeing? How has the business changed? >> From our perspective, the customers love it, and we can measure that in terms of our bookings. We're up 75% in terms of mobile bookings as a result of some of these changes that we've made. Our customers have given us feedback that the experience is much more seamless. Our franchisees have given us feedback that, you know what, it's easier to use our services. >> Yeah, all I want is the best rate. (group laughs) Just give me the best rate, Emmanuel, alright, and I'm a happy camper. >> The statistic that he shared is phenomenal, right, being able to see 75% jump in mobile booking is significant. >> That's extraordinary. >> That's real ROI. >> Yeah, and there are others too. Scott, their CIO, recently wrote in a blog about how and why the CIOs are sleeping better, right. They're actually getting sleep back, and I think that's really the result of the transformation where systems like AppDynamics, systems like applications they wrote, they'll become a lot more seamless now, and being able to show, when I invest a dollar into an application, how is that yielding to line of business, real time is what they have as power now. >> The boss is happy. >> Yeah. >> Yes. >> Well, if they're sleeping well, we're all sleeping well. I know how that goes. Gentlemen, thanks for sharing this story. >> Thank you. >> Thank you, thank you for having us. >> Appreciate your time here. >> Appreciate it. >> Appreciate it. >> You bet, back with more here from AWS re:Invent. You're watching this live from Las Vegas, and we're on theCUBE. (techno music)

>> Announcer: Live from Las Vegas, it's theCUBE covering AWS re:Invent 2017, presented by AWS, intel, and our ecosystem of partners. >> Welcome back everyone, live here in Las Vegas. This is theCUBE's exclusive coverage of AWS re:Invent Amazon Web Services annual conference, forty-five thousand people here. Huge event. This is the industry bellwether for Cloud computing now, soon to be IT public sector, IOT, AI, as Amazon sets the trends. TheCUBE's got the coverage. I'm John Furrier with Stu Miniman. Our next two guests is Barry Russell, general manager and (mumbles) for Amazon Web Services Marketplace, hot and on fire, growing, and Thomas Wyatt, chief strategy officer at App Dynamics, partner of AWS. Welcome to theCUBE. >> It's great to be here guys. >> Thank you. >> Partner central, lot of love going on in the partnerships because Amazon has an enabling platform. They lower the costs, increase the value, and increase the wealth creation flowing around. You guys are taking advantage of that. >> Absolutely, so with AppDynamics, we're helping customers with their Cloud migration to Amazon. You know, applications really are becoming the foundation of the modern business and understanding the performance of those applications, the users, the application, the business metrics themselves is critical, as this really signifies the brand for most companies. So as they are moving their workloads over to Amazon, it's critical they really understand how things are performing and make sure that they perform well in that new environment. And so the relationship we've had together has been phenomenal in helping that happen. >> (mumbles) done a lot of work, though, on the app side. And it's interesting, and the hottest trend right now that we're seeing, certainly in this Cloud conversion, IT in particular, as well as other markets, I mentioned IOT and AI, obviously hot as hell as well, is the instrumentation of the data is super critical. >> Yes, yes. >> And that is not new to you guys. But it's now becoming apparent that it's easier to do in the Cloud than it was before. >> Sure. >> What do you see? I mean you must look at the Cloud and be like, man this is so awesome, horizontally scalable, but all the goodness of having that instrumentation. What's your take on that? >> Right so it really starts with that. Instrumentation provides you the insights in real time necessary to take advantage of the optimizations that Cloud provides you, so the ability to scale up, scale down. If you know how your application is performing in real time, you take that guesswork out. And I think that's really what, leveling AppDynamics with Amazon really gives you that capability, the best of both worlds. >> Yeah, Barry, the application monitoring space, you have a number of really good partners here. Amazon also has some of their own pieces. How do you balance that sort of engagement? We've seen, you know the partner summit I saw some really good slides up there. We've interviewed a number of the partners of this space, but want to get your viewpoint. Well, first, AppDynamics makes their software available as SaaS, which is a pretty quickly growing trend, with all sorts of customers, you know, particularly enterprise customers wanting to move to that model. And then we work with AppDynamics to come up with a specific use case for the workloads that are migrating over, particularly with customers that are migrating large amount of workloads as they're shutting down data centers. And we make those available to those customers and provide them with a choice. And once we document that technical use case we can put that in the hands of our SAs, our solution architects, Proserv teams, and consulting partners like 2nd Watch and Slalom, Accenture, and Deloitte, to help advise the customer on which third-party software meets those workload needs best. >> Thomas, you know, Cisco's got a pretty sizable presence at this show. I was mentioning, you know, this is the second recently acquired company of Cisco that we've had on the program this week. I mean, they spent billions of dollars on AppDynamics, bunch of others. Cisco has always been an acquisitive company, but, you know, what is the kind of acceleration of Cloud, mean for Cisco. How are companies like AppDynamics helping along that shift for Cisco's business? >> Yeah, that's a great question. I think the way to think about it is, Cisco's really been helping our customers with their networking, their data center, security, but it was a critical missing component for us was really understanding application intelligence and how end users and businesses are impacted by the infrastructure. And so, bringing AppDynamics into part of Cisco, which we're running it fairly autonomously, but having the ability to connect to other infrastructure-related products to provide more real-time intelligence is a key part of the strategy. So bringing those things together and then complementing that with our Cloud partners, and the marketplace has really made that super easy for us now, from the context of making it easier to buy AppDynamics with AWS. That combination has been super powerful. >> Talk about the marketplace dynamics that you're trying to create, Barry, because you obviously got a good thing going. What are you doing to create the incentives, to create a frictionless environment? Because obviously you don't want any friction, but you got growth. >> Barry: We do. >> What are some of the speed bumps you're hitting? How are you addressing it? How are you with AppDynamics of the world? Is there incentive programs? Is there joint selling? How should partners think about that? And then I'd love to get your reaction to Amazon's programs. >> Well there's one key thing that we launched a couple of weeks ago. It's called seller private offers. And what it enabled us to do, and it was kind of a missing piece, was for a seller to work with a customer, so AppDynamics working with a customer, to negotiate on best price and terms for a longer period of duration of use, one, two, or three year subscription. That enabled the customer to get the best terms and price to run the software on AWS, and it also enabled sales teams, for example, working with Cisco and AppDynamics, to sell in a way that they were more accustomed to once a customer was familiar with the software. And then we announced... >> Renewals' a recurring revenue. >> Right. >> Right. >> They're smiling over there. >> And then we paired it with enterprise contract that we launched on Tuesday. Which was a negotiated set of terms to remove a ton of friction around legal negotiation of standard contract terms between software vendors and enterprise buyers, and so we're trying to innovate between both the buyer and the seller at all times. >> So until you can actually voice order product, you're gonna always be chippin' away at the friction? >> Barry: Always. >> Thomas: Right. >> All right, your reaction to Amazon, how are they a partner? You can tell the truth even though he's standing right there. >> Thomas: No absolutely. >> Come on... >> I mean, here's the key thing. We've been a marketplace partner for several quarters now. We're seeing huge transactions flow through that, and as part of that, the two key things that we're finding. The first one is the deal sizes are expanding, and largely because there's a lot of comfort from the end customers at the combination of AppDynamics working closely with AWS, ensuring those systems are integrated, that they work well together, they can be procured together, there's common bill. Those kind of capabilities have really helped us. The second thing is, we're proving that we can help accelerate the pace of Cloud migration. So, we're seeing on average our enterprise customers are getting through the Cloud 30% faster by using the two solutions together. >> So they like the buying methodology. >> Thomas: That's right. >> And speed of deployment. >> The speed of deployment and the fact that when they get there, they know their environment's going to be very stable. They have that additional assurance because they've got the performance monitoring metrics before they make the move, and then once they get there they have it. Because the AppDynamics really provides you that visibility across both. So, thinking about it from... >> So I saw the announcement, it was one click was it Andy who put up one click something? Was that a marketplace deal? I saw it on the keynote yesterday. It might have been one click (mumbles), I don't know. >> I don't think it was associated with the marketplace. We do still have that feature. Yeah, so. >> So things are going good? You're happy? >> Yeah, I mean a great example, NASDAQ spoke yesterday with Barry, Heather Abbott, and talked about their experience about moving their workloads over to AWS and how AppDynamics was instrumental to help them understand the dependencies of their environment before they made that transition. There are so many great examples of that, and that's why we think... >> All right, so final question for you, then I know Stu wants to jump in, Andy Jassy told me when I interviewed him last week for the event, customers vote with their workloads. What are the workloads that you're seeing moving over? What kinds of workloads fit into this new style, this new guard model of... >> I would say a couple years ago it was primarily new apps, building from the ground up. Now it's the mission critical stuff. It's the important things that people are running their businesses on, moving those over, and I think that's part of the reason why AppD is becoming more integrated into that, is because AppD instruments generally the most critical applications, not necessarily the third and fourth tier. So the typical workloads that impact revenue, impact customer engagements, are ones that are now being... >> So you're at the center of all the migrations? >> Thomas: Yeah. >> Awesome. >> So the one, can't let you go without asking, beyond just getting to the Cloud, I'm wondering what you're seeing from customers and how you're working with them on moving along from just instances to containerization and even serverless. >> Yeah, in the enterprise space we're definitely seeing the phase one was just move the existing VMs over. Now it's refactoring and reestablishing the products and the architectures based on the modern technologies like Lamba and Serverless, and other things. It's all great. It's a really exciting time. >> Thomas Wyatt, chief strategy officer AppDynamics, happy partner obviously (mumbles) workloads are moving to the Cloud. Barry Russell, general manager of the place making it happen. >> Congratulations, Barry, on your success. >> Thank you. >> And AppDynamics >> Thank you. >> Congratulations on your acquisition with Cisco. Big deal. You guys are driving a big part of their transformation. >> Barry: Yes. Congratulations to you guys as well. >> Thank you. >> Of course, Amazon's taking no prisoners here at re:Invent, 45,000 people. I'm John Furrier (mumbles) more live coverage from day 3 after this short break.

(relaxing music) >> Hello everyone and welcome back to theCUBE's continuing coverage of AWS re:Invent. My name is Savannah Peterson and I am absolutely thrilled for this segment. We are joined by leaders at Cisco AppDynamics as well as Royal Caribbean. The two have been working together for over five years, leveraging full stack observability. We're going to dig in, but first of all please welcome Alice from Royal Caribbean and Greg from Cisco AppDynamics to the show. Hey friends. >> Hi. How are you doing? >> I'm excited, clearly. How are you doing, Greg? >> I'm doing fantastic. Thanks for having me on the show today. >> Hey, it's our, it is absolutely our pleasure. Alice, I have to start with you. I don't think there are too many industries that have gotten as much coverage as cruising has over the last couple of years. You've been working with Royal Caribbean for over a decade so you've seen it through the stormy seas of the pandemic, if you will. What has the last few years and the last few months been like for you? >> You know, it's really been a wild ride. To your point, we were sailing high, and then I don't think any other industry experienced what we did in COVID, that you walked in one day and then that day the whole industry shut down. So it was a big challenge for us. And then as soon as we shut down and we weathered the storm with COVID, then we had what we called our healthy return to service. So as quickly as it stopped, we had to start sailing again. So it's really been a challenge but we're happy to be back on our feet and heading in the right direction now. >> I really hope we can continue the sailing metaphors throughout the course of this interview. And you nailed that for a segment, Alice, I'm so here for it. I want to talk about how you've worked together but I want to give Greg a second to chime in here. So, Greg, you're the executive CTO at Cisco AppDynamics. How have you and the team weathered the last two and a half years? >> Well, you know, it's interesting, the pandemic really brought together an interesting conundrum, right? So on one hand, you had, you know, the consumers, the end users that became very reliant on digital services. They had a function in a way that was very performing, right? So, 84% of the respondents that we had come back through a report called the App Attention Index, came back and said that digital services were really instrumental for them to get back to some level of normalcy. But the interesting part that came about that is that out of those respondents, 60% of them blamed the brand if the application did not work the way they expected it. So they didn't really care about the complex- >> Wow. >> In the back end, right? So when you look at- >> Yeah. >> You look at the shift in the IT department, the IT department had to go out and quickly innovate. Quickly start to introduce new services, which ultimately brought together a sprawl in their technology stack. So, when you're adding to it you're not taking things away, you're continuously growing. So finding that the problems or the root cause of an application issue became more difficult. So that's where, you know, from a Cisco AppDynamics perspective, you know we're one of the leading observability and application performance monitoring tools. So, we help customers like Royal Caribbean to be able to zero in on root cause and ensure that their end users have that best experience. >> It's, I'm smiling as someone who was a former waitress and I can remember the amount of times I was scolded for something that happened that was far out of my control in the complex layers of the kitchen. (Greg laughs) And I think that anyone who's had a poor customer experience while interacting with a brand may or may not intentionally, you know, I think it's actually sometimes very unintentional to your point, get frustrated with said brand. I can imagine that is an experience and a priority that you have at Royal Caribbean, Alice. How has full stack observability played a role in your team's ability to serve the customers and keep your community engaged during this very kind of wobbly time? >> Yeah, you know, we have really worked hard to improve and remove friction from our guest vacation. And we want to keep them on vacation and having a great time. You know, we say we don't really sell a cruise. We sell an experience. So we use AppDynamics to monitor those key applications that our guests are interacting with to ensure that they're having that experience that we expect. You know, we've learned that just because a system or a server says, hey I'm up 99% of the time, that doesn't mean that my guests are experiencing that same type of stability, you know? So once again, we really worked well with AppDynamics. They've partnered with us to ensure that, you know, our guests are getting that vacation experience they're looking for. >> Do you think, just a follow up there, do you think that you would have advanced in the ways that you have working with Cisco AppDynamics and across functions over the last few years, without this crunch? Was necessity the mother of invention for you to any degree? >> You know, I don't think that the crunch brought it on 'cause we, like I said, we started this journey back in 2017. And we're not unlike a lot of companies where we're on this maturity ride where we want to go from being reactive, where our guests are telling us something is broken, to being preventive. Definitely, you know, COVID played into this because I think we learned to do less, you know, more with less. So, you know, it's very hard in the cruise industry. We did take a hit but we were able to use the AppDynamics tools to ensure that our systems were running with having less people also watching those systems. So less eyes on glass, more automation. >> And that's more stability, more credibility, and more transparency is definitely something that we're all looking forward. And it's nice to see that implemented, especially at scale when you're dealing with so many customers from all over the world trying to access your service and wanting that personalized experience. Greg, what does it feel like for you as a leader to hear someone like Alice say how powerful your tool has been in ensuring that customer experience? >> Yeah, that's, you know, it's absolutely fantastic. And especially, you know, Alice is absolutely right. You know, the cruise industry was really, had a very unique challenge in front of them. And I really applaud the folks at Royal Caribbean for stepping up to make sure that when the pandemic eased, so to speak, that the experience to the customer was actually even better, right? So when we were able to work and partner together to make sure that, you know, the user experience is topnotch, the availability's there, the resiliency of their platform is there. So, by working with customers like Royal Caribbean is really one of the shining stars that we can talk about that really helped make a big difference in, you know that post pandemic era to be able to really do what's right for the customer. >> How often are you engaging with customers like Alice as a team? How big is that feedback in your product roadmap? >> Oh, personally, I'm engaged with customers on a daily basis. And I see it across the map from many different industries. And, you know, a lot of folks had different challenges, but the ultimate commonality that I've seen across, you know, multiple industries is that, you know, when we're in that pandemic state, digital services were the only way that their customers were interacting with them. So, you know, when you're looking at a bank or you're looking at, you know, different types of travel agencies and organizations that, you know like Royal Caribbean as well, that really had that opportunity to focus on what's the most valuable thing to them which is user experience. It's a very, very common trend that we saw. And, you know, you see an expedited path of digital transformation happen. And really that's where we partner with, you know, customers like Royal Caribbean and many others across different industries to make sure that the business outcomes were being driven towards the proper direction as well as that, you know, the user experience. And I don't think I can emphasize user experience as being so critically important, anymore than I already have. But it's really one of the most valuable currencies most organizations have. >> One of my favorite lines is community is your first defensible asset. And you know, you can talk about user experience as much as you want on here, at the end of the day. If people aren't having a positive interaction with your brand or your product, it's probably not going to last super long unless it's legacy. And we don't have to go down that rabbit hole today. >> Especially if I can add, there's a lot of competition there. >> Of course. >> Right? There's a lot of competition out there. So if your applications do not perform or your digital services do not perform the end user has the quick ability to just quickly delete and move on. And the same thing with what Alice sees in the cruise industry, you know. You have an opportunity to rise to the top and I really applaud them for taking advantage of that opportunity. >> Yeah. Well, I'm here for both of you cheering each other on. Certainly, the water level rises together. >> That's right. >> Alice, what sort of challenges are you taking on currently that you're able to disclose? What sort of leaps do you think or it doesn't have to be leaps, but what kind of experience are you hoping to continue to enhance for Royal Caribbean customers? >> You know, right now, you know with our current connectivity it's all about managing that bandwidth. You know, we're hoping to go to that state where bandwidth isn't at a high cost. So now we're going to be even able to watch our user interaction more from ship to shore. You know, and we're maybe moving to that area where we're thinking cloud first from a shift. If you think about it, we've got 50 plus data centers floating around the world. So that connectivity is key. Now we're opening up that bandwidth. Now I need to see how the transactions are performing as we come off ship. You know, with that, once again, that cloud first mentality. It's a super exciting time for us. And I really see, you know, AppD is going to play a role in that. >> I love that visual just for a second of 50 data centers with also, surrounded by people having a very wonderful time on board. What a nice thought. I can't say that every data center I've ever been to is as glamorous, fun or sexy as being on a Royal Caribbean ship. However, I hope that we move perhaps in that direction. We were just at Super Computing a few weeks ago and it was great to see all the hardware there. So you never know. What role do you see yourself and the team and Cisco AppDynamics playing in that future for companies like Royal Caribbean, Greg? >> You know, it's really, it's really staying right lockstep with our customers as they move through that digital transformation efforts. The key piece is that we look at it from that full stack view. So we offer full stack observability, which, you know, if you look at the challenges that we want to go after. Traditional IT departments were historically siloed pretty significantly between, you know network and infrastructure, security, app dev. So I mean, ensuring that we can get our customers to be able to have that common view that shows what's the real important pieces across all domains. So when they start moving down the path of digital transformation, that's an opportunity to also revamp how their processes are, the people interact and the technology that they use to be able to deliver the proper business outcomes. So we talk a lot with our customers around full stack observability, but the key part is business context. So if you have a big effort for digital transformation, you're starting to add new services to it. How do you know if it's actually impacting the business in a positive or negative way? So by us implementing the business context to ensure that you understand the investments being made, that you can show to your business leaders, is showing an uptake in the business outcomes you're going after. It's really, really about a strong partnership with our customers. But also ensuring that their business is being positively impacted by our technology to be able to help them really align the teams and be able to have the right desired outcomes. >> I love that Greg and I love that customer first, that community first attitude. It's something that you both share. Final question for the two of you. And I'm going to start with you, Alice, since I suspect you've probably been on more cruises than Greg and I combined. Though I could be making a wild assumption. Where are you cruising to next? >> You know, I just got off a cruise. So next stop, I want to revisit the Galapagos. I think the Galapagos is the best place to go. And if you haven't done it that's absolutely where you should go. >> Oh, it's a beautiful trip. Greg, have you ever done the Galapagos? Is that going to be your next Royal Caribbean cruise? >> I have never done the Galapagos, but that may just have made it to my list. >> Fantastic. Well, I second Alice's endorsement on that. I had the pleasure of going about a decade ago. Very magical place that teaches you a lot about nature. Much like the two of you have taught us very extensively about full stack observability, how it applies to user experience, customer experience and the ocean that I am currently staring at here in Pacifica, California. Alice, thank you so much for joining us from Miami. Greg, to you in Colorado. I hope that you both continue to work in harmony together and that we can all see each other on the friendly seas soon. Thank you all for tuning in to our AWS re:Invent coverage. This is theCUBE. My name's Savannah Peterson. And we look forward to seeing you for our next segment. (relaxing music)

(upbeat music) >> Full stack observability is all the rage today. As businesses lean into digital, customer experience becomes ever more important. Why? Well, it's obvious, fickle consumers can switch brands in the blink of an eye or the click of a mouse. Technology companies have sprung into action and the observability space is getting pretty crowded in an effort to simplify the process of figuring out the root cause of application performance problems without an army of PhDs and lab coats, also known as endlessly digging through logs, for example. We see decades old software companies that have traditionally done monitoring or log analytics and or application performance management stepping up their game. These established players, you know, they typically have deep feature sets and sometimes purpose-built tools that attack one particular segment of the marketplace. And now they're pivoting through M&A and some organic development trying to fill gaps in their portfolio. And then, you got all these new entrants coming to the market, claiming end to end visibility across the so-called modern cloud and now edge native stacks. Meanwhile, cloud players are gaining traction and participating through a combination of native tooling combined with strong ecosystems to address this problem. But, you know, recent survey research from ETR confirms our thesis that no one company has it all. Here's the thing. Customers just want to figure out the root cause as quickly and as efficiently as possible. It's one thing to observe the stack end to end, but the question is who is automating the observers? And that's why we're here today. Hello, my name is Dave Vellante and welcome to this special Cube presentation where we dig into root cause analysis, and specifically, how one company, Zebrium, is using unsupervised machine learning to detect anomalies and pinpoint root causes and delivering it as an automated service. And in this session, we have two deep dives. First, we're going to dig into this exciting new field of RCaaS, Root Cause As A Service with two of the founders and technical experts behind Zebrium. And then we bring in two technical experts from Cisco, an early Zebrium customer who ran a POC with Zebrium's service, automating and identifying root cause problems within four very well established and well known Cisco product lines, including WebEx Client and UCS. I was pretty amazed at the results and I think you'll be impressed as well. So thanks for being here. Let's get started. With me right now is Larry Lancaster, who's a founder and CTO of Zebrium. And he's joined by Rod Bagg, who's the founder and vice president of engineering at the company. Gents, welcome. Thanks for coming on. >> Thanks. >> Okay. >> It's good to be here. >> It's good to be here >> All right Rod, talk to me. Talk to me about software downtime, what root cause means, all the buzzwords in your domain, MTTR and SLO. What do we need to know? >> Yeah, I mean, it's like you said. I mean, it's extremely important to our customers and to most businesses out there to drive uptime and avoid as much downtime as possible. So, you know, when you think about it, all of these businesses, most companies nowadays, either their product is software and it's running, you know, running on the web and that's how you get a point click. Or the business depends on, you know, internal systems to drive their business and to run it. When that is down, that is hugely impacting to them. So if you take a look, you know, way back, you know, 20, 30 years ago, software was simple. You know, there wasn't much to it. It was pretty monolithic and maybe it took a couple of people to maintain it and keep it running. There wasn't really anything complicated about it. It was a single tenant piece of software. Today's software is so complicated, often running, you know, maybe hundreds of services to keep that or to actually implement what that software is doing. So as you point out, you know, enter the sort of observability space and the tools that are now in use to help monitor that software and make sure when something goes wrong, they know about it But there's kind of an interesting stat around the observability space. So when you look at observability in the context or through the lens of the cost of downtime, it's really interesting. So observability tools are about a $20 billion market, okay? But the cost of downtime, even with that in place, is still hundreds of billions of dollars. So you're not taking much of a bite out of what the real problem is. You have to solve root cause and get to that fast. So it's all great to know that something went wrong but you got to know why. And it's our contention here that, you know, really, when you take a look at the observability space, you have metrics, that's a great tool. I mean, there's lots of great tools out there, you know, around metrics monitoring that's going to tell you when something went wrong. It's very rarely it's going to tell you why. Similarly for tracing, it's going to point you to where the issue is. It's going to take you through that stack and probably pinpoint where you're being, you know where it's happening or where something is running slow, potentially. So that's great. But again, the root cause of why it's happening is going to be buried in log files. And I can expand on that a little bit more but you know, when you're a software developer and you're writing your software, those log files are a wealth of information. It's just a set of breadcrumbs that are littered with facts about how the software is behaving and why it's doing what it's doing, or why it went wrong. And it's that that really gets you to the root cause very fast. And that's our contention, is that these software systems are so complex nowadays and that the root cause is lying in those logs. So how do you get there fast? You know, we would contend that you better automate that or you are just doomed for failure. And that's where we come in. >> Great. >> Getting to that root cause. >> Thank you, Rod. You know, it's interesting you talk about the $20 billion market. There's an analogy with security, right? We spend 80, $100 billion a year on securing our infrastructure, and yet we lose probably closer to a trillion dollars a year in breaches. And there's a similar analogy here. 20 billion could be 5X in downtime impacts or more. Okay, let's go to Larry. Tell us a little bit more about Zebrium. I'm interested always to ask a founder why you started the company. Rod touched on that a little bit. You guys have invented this concept of RCaaS. What does it mean? What problems does it solve, and how does it solve the problem? Let's get into it. >> Yeah. Hey, thanks, Dave. So I think when you said, you know, who's automating the observer, that that's a great way to think about it because what observability really means is it's a property of a system that means you can see into it. You can observe the internal state and that makes it easier to troubleshoot, right? But the problem is if it's too complicated, you just push the bottleneck up to your eyeball. There's only so much a person can filter through manually, right? And I love the way you put that. So that's a great way to think about it is automating the observer. Now, of course, it means that, you know, you reduce your MTTR, you meet your service level objectives, all that stuff, you improve customer experience. That's all true, but it's important to step back and realize like we have cracked a real nut here. People have been trying to figure out how to automate this part of sort of the troubleshooting experience, this human part of finding the root cause indicators for a long time. And until Zebrium came along, I would argue, no one's really done it right. So, you know, I think it's also important you know, as we step back, we can probably look forward five to 10 years and say, everyone's going to look back and say how did we do all this manually? You're going to see this sort of last mile of observability and troubleshooting is going to be automated everywhere because otherwise, you know, people are just... They're not going to be able to scale their business. So, you know, I think one more thing that's important to point out is, you know, I think Zebrium, you know, it's one thing to have the technology but we've learned we need to deliver it right where people are today. You can't just expect people to dive into a new tool. So, you know, we're looking at, you know, if you look at Zebrium, you'll put us on your dashboard and we don't care what kind of a dashboard it is. It could be, you know Datadog, New Relic, Elastic, Dynatrace, Grafana AppDynamics, ScienceLogic, we don't care. You know, they're all our friends. So we're more interested in getting to that root cause than trying to fight, you know, these incumbents and all that stuff. Yep. >> Yeah. So, interesting. Again, another analogy I think about. You know, you talked about automation. If we're to look back and say this is what... We're never going to do this again, it's like provisioning loans. Nobody provisions loans anymore, it's all automated. >> Larry: (chuckling) That's right. >> So Larry, I'll stay with you, then the skeptic in me says, this sounds amazing, but if I, you know... It might be too good to be true. Tell us how it works. >> Larry: (chuckling) Yeah. So that's interesting. So Cisco came along and they were equally skeptical. So what they did was they took a couple of months and they did a very detailed study. And they got together 192 incidents across four product lines, where they knew that the root cause was in the logs. And they knew what that root cause was because they had had their best engineers, you know work on those cases and take detailed notes of the incidents that had taken place. And so they ran that data through the Zebrium software. And what they found was that in more than 95% of those incidents, Zebrium reflected the correct root cause indicators at the correct time. Like that blew us away. When we saw that kind of evidence, Dave, I have to tell you, everyone was just jumping up and down. It was like, you know, it was like the Apollo command center, you know when they finally, you know, touchdown on the moon kind of thing. So, you know, it's really an exciting point in time to be at the company, like just seeing everything finally being proven out according to this vision. I'm going to tell you one more story which is actually one of my favorites, because we got a chance to work with Seagate Lyve Cloud. So they're, you know, a hyper modern, you know, SaaS business, they're an S3 competitor. Zoom has their files stored on Lyve Cloud, you know, to let you know who they are. So essentially, what happened was they were in alpha, their early access, and they had an outage, and it was pretty bad. I mean, it went on for longer than a day, actually, before they were completely restored. And it was, you know, fortunately for them, it was early access. So no one was expecting, you know, uptime, you know, service level objectives and so on. But they were scared, because they realized, if something like this happens in production, you know, they're screwed. So what they did was they saw Zebrium. They went and did some research, they saw Zebrium. They went in a staging environment, recreated the exact (indistinct) that they had had. And what they saw was immediately, Zebrium pops up a root cause report that tells them exactly the root cause that they took over a day to find. These are the kind of stories that let us know we're onto something transformational. >> Dave: Yeah. That's great. I mean, you guys are jumping up and down, I'm sure. We're going to hear from Cisco later. I bet you, they were jumping up and down too because they didn't have to do all that heavy lifting anymore. So Rod, Larry's just sort of implying that, or actually, you guys both talked about that your tool is agnostic. So how does one actually use the service? How do I deploy it? >> Yeah. So let me step back. So when we talk about logs right? Like, you know, all these bread crumbs being in logs and everything else? So, you know, they are a great wealth of you know, information, but people hate dealing with them. I mean, they hate having to go in and figure out what log to look at. In fact, you know, we had one of our... Or we've heard from several of our customers now prior to using Zebrium, when they, you know, have some issue, and they know there's something wrong, something on their dashboard has told them that something's wrong, maybe a metric has, you know, taken a blip or something's happened that they know there's a problem. We've heard from them that it can take like a number of hours just to get to the right set of logs, like figuring out over these hundreds of services where the logs are, to get to them, maybe searching in a log manager. Just to get into the right context, even, can take hours. So, you know, that's obviously the problem we solve but, you know, we don't want them just looking at logs. I mean, you know, we don't want to put them back in the thing they don't like doing because people don't do that. They don't like doing it. So we put it up on the dashboard. So if something is going wrong with your metrics and that's the indicator, or maybe it's something with tracing that you're sort of digging through that you know something's wrong, we will be right on that same dashboard. So we're deployed as a SaaS service. You send us your logs, you click on one of our integrations and we integrate with all these tools that Larry's talked about. And when we detect anything that is a root cause report, it will show up on your dashboard in the same timeline as those blips in your metrics. So when you see something going wrong and you know there's an issue, take a look at the portion of your dashboard that is us, and we're going to tell you why. We're going to get you to the why that went wrong. No other work could be... You can, you know, also click down and click through to us so that you land up in our portal, if you want to do some more digging around, if you need to or whatever, maybe to get some context what have you, but it's fair that if you ever need to do that, the answer should be right there on your dashboard. And that that's how we expect people to use it. We don't want them digging in logs and going through things, we want it to be right in their workflow. >> Great. Thank you, Larry. So Rod, we talked about Cisco. We're going to hear more from them in a moment in Seagate. I would think this is like a perfect solution for a SaaS provider, anybody doing AI ops. Do you have some examples of those types of firms leaning into this? >> Rod: Yeah, a couple of great ones. Well, I mean, we've got many of them, but a couple that I'll touch on. We have an actual AI ops company that was looking for, you know, sort of some complimentary technology and so on. And so they decided to just put us through our paces by having one of their own SREs sign up for our service in our SaaS environment, and send the logs from their system to us, you know, and just see how we did. So it turned out we ended up talking back to this SRE like a week after he had installed the product, you know signed up and then, you know, started sending us logs. And, you know, he was hewing and hawing, saying that he was busy, like every SRE is, and that he didn't have a chance to really do much with us yet. And, you know, we were just, you know, having this conversation on the phone, and he comes to tell us that, yeah I've been busy because we had this, you know, terrible outage, like, you know, five days ago. And we said like, "Okay did you actually look on the Zebrium dashboard?" (chuckles) And he goes, "You know what? I didn't even think to do it yet. I mean, I'd just been so busy and frazzled." So we have an integration with that company, he hadn't put that integration in, so it wasn't in his dashboard yet, but it was certainly on ours. So he went there, and he looks and he looks on the day, you know, on the time range of when he had had this incident. And right at the very top of the page on our portal was that incident with that root cause. And he was flabbergasted. It literally would've saved him hours and hours and hours. They had this issue going on for over 24 hours. And we had the answer right there in five minutes, and it was crazy. And we get that kind of stories. It's just like the Seagate one. If you use us and you have a problem, we're going to detect it. And you're going to hear from Cisco how successful we are at detecting things. I mean, it'll be there when you have a problem. In SaaS companies, you know, one of our customers is Alchera. They do cost optimizations for cloud properties, you know, for AWS optimization, Google, Google cloud, and so on. But they use our software, and they have a lot of interaction, obviously with these cloud vendors and the APIs of those cloud vendors. So, you know, in order to figure out your costing at AWS, they're using all those APIs. So it turned out, you know, they had some issue where their services were breaking. And we had that root cause report right on the screen, again within five minutes, that was pointing to an API problem with Google. And they had changed one of their APIs and Alchera was not aware of it. So their stuff was breaking because of a change downstream that we had caught. And I'll just tell you one last one because it's somewhat related to one of these cloud vendors. You know, it was a big cloud vendor who had an outage a couple of months ago. And it's interesting because, you know, a lot of our customers will set up shared Slack channels with us, where we're monitoring or seeing their incidents as well as they are. So we get a little Slack representation of the incident that we detected for them or the root cause that we detected for them, and that's in a shared community channel. So we could see this happening when that AWS outage happened. We could see our customers getting impacted by that AWS outage, and the root cause of what was going on there in AWS that was impacting our customers that was showing up in our incidents. Now we didn't obviously, you know, have the very root cause of what was going on in AWS, per se but we were getting to the root cause of why our customer's applications were failing. And that was because of issues going on at AWS. >> Very interesting. I mean, I think one of your biggest challenges is going to be getting people's attention because these SREs are so busy, their hair's on fire. >> Rod: That's it. Right. (chuckling). You know, when you say, hey, (indistinct). >> I tell you, if you get their attention, they love it. I mean, this AI ops company, I didn't even tell you the punchline there, but, you know, they had this incident that occurred that we found. And quite literally, the next week, they ended up signing up as a paid customer. So... >> Dave: that's great. And Larry, to give you the last word. I mean, you know, Rod was talking about, you know, changes in APIs and you know, there's still a lot of scripts out there. You guys, if I understand it correctly, run both as a service in the cloud and you can run on-prem, which is important because there's a lot of sensitive information in logs that people are trying not to leave. >> Larry: That's right. Absolutely. >> Dave: But close it out here. >> Yeah. I mean, that's right, you can run it on-prem. Just like we run it in our cloud, you can run it in your cloud or on your own infrastructure. Now that's all true. You know, I think the one hurdle now that we have left as a company is getting the word out and getting people to believe that this is actually possible and try it for themselves. You don't believe it, do a POC, try it yourself. And you know, people have become so jaded by the lack of, you know, real, sort of, innovation in the software industry for the last 10 years that it's hard to get people to... But guys, you got to give it a shot, I'm telling you. I'm telling you right now, it works. And you'll hear more about that from one of our customers in a minute. >> All right guys, thanks so much. Great story. Really appreciate you sharing. >> Thank you. >> Yeah. Thanks Dave. Appreciate the time. >> Okay. In a moment, we're going to hear from Cisco who is the customer in this case example and a company that has... Look, they have quite an impressive suite of observability tooling, and they've done a pretty compelling proof of concept with Zebrium using real data on some Cisco products that you've heard of, like WebEx. So stay tuned and learn about how you can really take advantage of this new technology called Root Cause As A Service. You're watching theCube, the leader in enterprise and emerging tech coverage. (upbeat music)

(bright intro music) >> Full stack observability is all the rage today. As businesses lean in to digital, customer experience becomes ever more important, why? Well, it's obvious. Fickle consumers can switch brands in the blink of an eye or the click of a mouse. Technology companies have sprung into action, and the observability space is getting pretty crowded in an effort to simplify the process of figuring out the root cause of application performance problems without an army of PhDs and lab coats, also known as endlessly digging through logs, for example. We see decades-old software companies that have traditionally done monitoring or log analytics and/or application performance management stepping up their game. These established players, you know, they typically have deep feature sets and sometimes purpose built tools that attack one particular segment of the marketplace, and now, they're pivoting through M&A and some organic development trying to fill gaps in their portfolio, and then you got all these new entrants coming to the market claiming end to end visibility across the so-called modern cloud and now edge-native stacks. Meanwhile, cloud players are gaining traction and participating through a combination of native tooling combined with strong ecosystems to address this problem, but, you know, recent survey research from ETR confirms our thesis that no one company has at all. Here's the thing. Customers just want to figure out the root cause as quickly and efficiently as possible. It's one thing to observe the stack end to end, but the question is who is automating the observers? And that's why we're here today. Hello, my name is Dave Vellante, and welcome to this special "CUBE" presentation where we dig into root cause analysis and, specifically, how one company, Zebrium, is using unsupervised machine learning to detect anomalies and pinpoint root causes and delivering it as an automated service. In this session, we have two deep dives. First, we're going to dig into this exciting new field of RCA, root cause as a service, with two of the founders and technical experts behind Zebrium, and then we bring in two technical experts from Cisco, an early Zebrium customer who ran a POC with Zebrium's service, automating and identifying root cause problems within four very well established and well-known Cisco product lines including Webex client and UCS. I was pretty amazed at the results, and I think you'll be impressed as well. So thanks for being here. Let's get started with me right now is Larry Lancaster who's a founder and CTO of Zebrium, and he's joined by Rod Bagg who's a founder and Vice-President of Engineering at the company. Gents, welcome, thanks for coming on. >> Thanks. >> (indistinct). >> To be here. >> Great to be here. >> All right, Rod, talk to me. Talk to me about software downtime, what root cause means, all the buzzwords in your domain, MTTR and SLO, what do we need to know? >> Yeah, I mean, it's like you said. I mean, it's extremely important to our customers and to most businesses out there to drive up time and avoid as much downtime as possible. So, you know, when you think about it, all of these businesses, most companies nowadays, either their product is software and it's running, you know, running on the web, and that that's how you get a point click or their business depends on it and, you know, internal systems to drive their business and to run it. Now, when that is down, that is hugely impacting to them. So if you take a look, you know, way back, you know, 20, 30 years ago, software was simple. You know, there wasn't much to it. It was pretty monolithic, and maybe it took a couple of people to maintain it and keep it running. It wasn't really anything complicated about it. It was a single tenant piece of software. Today's software is so complicated, often running, you know, maybe hundreds of services to keep that or to actually implement what that software is doing. So as you point out, you know, enter the sort of observability space and the tools that are now in use to help monitor that software and make sure when something goes wrong, they know about it, but there's kind of an interesting stat around the observability space. So when you look at observability in the context or through the lens of the cost of downtime, it's really interesting. So observability tools are about a $20 billion market, okay? But the cost of downtime, even with that in place, is still hundreds of billions of dollars. So you're not taking much of a bite out of what the real problem is. You have to solve root cause and get to that fast. So it's all great to know that something went wrong, but you got to know why, and it it's our contention here that, you know, really, when you take a look at the observability space, you have metrics. That's a great tool. I mean, there's lots of great tools out there, you know, around metrics monitoring that's going to tell you when something went wrong. It's very rarely it's going to tell you why. Similarly for tracing, it's going to point you to where the issue is. It's going to take you through that stack and probably pinpoint where you're being, you know, where it's happening or where something is running slow potentially. So that's great, but again, the root cause of why it's happening is going to be buried in log files, and I can expand on that a little bit more, but, you know, when you're a software developer, and you're writing your software, those log files are a wealth of information. It's just a set of breadcrumbs that are littered with facts about how the software is behaving and why it's doing what it's doing or why it went wrong, and it's that that really gets you to the root cause very fast, and that's, our contention is that these software systems are so complex nowadays, and that the root cause is lying in those logs. So how do you get there fast? You know, we would contend that you better automate that or you're just doomed for failure, and that's where we come in. >> Great. >> Getting to that request. >> Thank you, Rod. You know, it's interesting. You talk about the $20 billion market. There's an analogy with security, right? We spend 80, $100 billion a year on securing our infrastructure, and yet we lose, probably, closer to a trillion dollars a year in breaches, and there's a similar analogy here. 20 billion could be 5x in downtime impacts or more. Okay, let's go to Larry. Tell us a little bit more about Zebrium. I'm interested always to ask a founder why you started the company. Rod touched on that a little bit. You guys have invented this concept of RCAs. What does it mean? What problems does it solve? And how does it solve the problem? Let's get into it. >> Yeah, hey, thanks, Dave. So I think when you said, you know, who's automating the observer? That's a great way to think about it because what observability really means is it's a property of a system that means you can see into it. You can observe the internal state, and that makes it easier to troubleshoot, right? But the problem is if it's too complicated, you just push the bottleneck up to your eyeball. There's only so much a person can filter through manually, right? And I love the way you put that. So that's a great way to think about it is automating the observer. Now, of course, it means that, you know, you reduce your MTTR, you meet your service level objectives, all that stuff, you improve customer experience, that's all true, but it's important to step back and realize like we have cracked a real nut here. People have been trying to figure out how to automate this part of sort of the troubleshooting experience, this human part of finding the root cause indicators for a long time, and until Zebrium came along, I would argue no one's really done it right. So, you know, I think it's also important, you know, as we step back, we can probably look forward five to 10 years and say, "Everyone's going to look back and say, 'How did we do all this manually?'" You're going to see this sort of last mile of observability and troubleshooting is going to be automated everywhere because otherwise, you know, people are just, they're not going to be able to scale their business. So, you know, I think one more thing that's important to point out is, you know, I think Zebrium, you know, it's one thing to have the technology, but we've learned we need to deliver it right where people are today. You can't just expect people to dive into a new tool. So, you know, we're looking at, you know, if you look at Zebrium, you'll put us on your dashboard, and we don't care what kind of a dashboard it is. It could be, you know, Datadog, New Relic, Elastic, Dynatrace, Grafana, AppDynamics, ScienceLogic, we don't care. You know, they're all our friends. So we're more interested in getting to that root cause than trying to fight, you know, these incumbents and all that stuff, yeah. >> Yeah, so interesting. Again, another analogy I think about, you know, you talked about automation, where to look back, and say, "This is what- We're never going to do this again." It's like provisioning LANs. Nobody provisioned LANs anymore. It's all automated. >> That's correct. >> So, Larry, stay with you. The skeptic in me says, "This sounds amazing," but if, you know, it probably too good to be true. Tell us how it works. >> Yeah, so that's interesting. So Cisco came along and they were equally skeptical. So what they did was they took a couple of months, and they did a very detailed study, and they got together 192 incidents across four product lines where they knew that the root cause was in the logs, and they knew what that root cause was because they'd had their best engineers, you know, work on those cases and take detailed notes of the incidents that had taken place, and so they ran that data through the Zebrium software, and what they found was that in more than 95% of those incidents, Zebrium reflected the correct root cause indicators at the correct time. Like that blew us away. When we saw that kind of evidence, Dave, I have to tell you, everyone was just jumping up and down. It was like, you know, it was like the Apollo Command Center, you know, when they finally, (Dave laughs) you know, touchdown on the moon kind of thing. So, you know, it's really exciting at a point in time to be at the company, like just seeing everything finally being proven out according to this vision. I'm going to tell you one more story, which is actually one of my favorites, because we got a chance to work with Seagate Lyve Cloud. So they're, you know, a hyper modern, you know, SaaS business. They're an S3 competitor. Zoom has their files stored on Lyve Cloud to give, you know, to let you know who they are. So, essentially, what happened was they were in alpha, in their early access, and they had an outage, and it was pretty bad. I mean, it went on for longer than a day, actually, before they were completely restored, and it was, you know, fortunately, for them, it was early access. So no one was expecting, you know, uptime, you know, service level objectives and so on, but they were scared because they realized if something like this happens in production, you know, they're screwed. So what they did was they saw Zebrium, they did some research, they saw Zebrium. They went in a staging environment, recreated the exact (indistinct) that they'd had, and what they saw was, immediately, Zebrium pops up a root cause report that tells them exactly the root cause that they took over a day to find. These are the kind of stories that let us know we're onto something transformational. >> Yeah, that's great. I mean, you guys are jumping up and down. I'm sure, we're going to hear from Cisco later. I bet you, they were jumping up and down, too, 'cause they didn't have to do all that heavy lifting anymore. So Rod, Larry's just sort of implying that or, actually, you guys both talked about that your tool's agnostic. So how does one actually use the service? How do I deploy it? >> Yeah, so let me step back. So when we talk about logs, right? Like, you know, all these red crumbs being in logs and everything else. So, you know, they are a great wealth of, you know, information, but people hate dealing with them. I mean, they hate having to go in and figure out what log to look at. In fact, you know, we had one of our, or we've heard from several of our customers now prior to using Zebrium, but when they're, you know, have some issue, and they know there's something wrong, something on their dashboard has told them that something's wrong, maybe a metrics is, you know, taken a blip or something's happened that they know there's a problem, we've heard from them that it can take like a number of hours just to get to the right set of logs, like figuring out over these hundreds of services where the logs are to get to them, maybe searching in a log manager, just to get into the right context even can take hours. So, you know, that's obviously the problem we solve, but, you know, we don't want them just looking at logs. I mean, you know, we don't want to put 'em back in the thing they don't like doing 'cause people don't do what they don't like doing. So we put it up on the dashboard. So if something is going wrong with your metrics, and that's the indicator or maybe it's something with tracing that you're sort of digging through now that you know something's wrong, we will be right on that same dashboard. So we're deployed as a SaaS service. You send us your logs. You click on one of our integrations, and we integrate with all these tools that Larry's talked about, and when we detect anything that is a root cause report, it will show up on your dashboard in the same timeline as those blips in your metrics. So when you see something going wrong, and you know there's an issue, take a look at the portion of your dashboard that is us, and we're going to tell you why. We're going to get you to the why that went wrong. Not no other work could be- You can, you know, also click down and click through to us so that you land up in our portal if you want to do some more digging around if you need to or whatever, maybe to get some context, what have you, but it's fair that you ever need to do that. The answer should be right there on your dashboard, and that's how we expect people to use it. We don't want them digging in logs and going through things. We want it to be right in their workflow. >> Great, thank you, Larry. So Rod, we talked about Cisco. We're going to hear more from them in a moment and Seagate. I would think this is like a perfect solution for a SaaS provider, anybody doing AIOps, do you have some examples of those types of firms leaning into this? >> Yeah, a couple of great, well, I mean, we got many of them, but couple that I'll touch on. We have an actual AIOps company that was looking for, you know, sort of some complimentary technology and so on, and so they decided to just put us through our paces by having one of their own SREs sign up for our service in our SaaS environment and send the logs from their system to us, you know, and just see how we did. So it turned out we ended up talking back to this SRE like a week after he had installed the product, you know, signed up, and then, you know, started sending us logs, and, you know, he was hemming and hawing saying that he was busy like, you know, like every SRE is, and that he didn't have a chance to really do much with us yet, and, you know, we just, you know, having this conversation on the phone, and he comes to tell us that, "Yeah, I've been busy because we had this, you know, terrible outage like, you know, five days ago," and we said like, "Okay, did you actually look on the Zebrium dashboard?" (laughs) And he goes, "You know what? I didn't even think to do it yet. I mean, I'd just been so busy and frazzled." So we have an integration with that company. He hadn't put that integration in so it wasn't in his dashboard yet, but it was certainly on ours. So he went there and he looks on the day like, you know, on the time range of when he had this incident, and right at the very top of the page on our portal was the incident with the root cause, and he was flabbergasted. It literally would've saved him hours and hours and hours. They had this issue going on for over 24 hours, and we had the answer right there in five minutes, and it was crazy, and we get that kind of story. It's just like the Seagate one. If you use us and you have a problem, we're going to detect it, and you're going to hear from Cisco how successful we are at detecting things. I mean, it'll be there when you have a problem. In SaaS companies, you know, one of our customers is Archera. They do cost optimizations for cloud properties, you know, for AWS optimization, Google cloud, and so on, but they use our software, and they have a lot of interaction, obviously, with these cloud vendors and the APIs of those cloud vendors. So, you know, in order to figure out you're costing at AWS, they're using all those APIs. So it turned out, you know, they had some issue where their services were breaking and we had that root cause report right on the screen, again, within five minutes that was pointing to an API problem with Google, and they had changed one of their APIs, and Archera was not aware of it. So their stuff was breaking because of a change downstream that we had caught, and I'll just tell you one last one because it's somewhat related to one of these cloud vendors of, you know, big cloud vendor who had an outage couple of months ago, and it's interesting because, you know, lot of our customers will set up shared Slack channels with us where we're monitoring or seeing their incidents as well as they are. So we get a little Slack representation of the incident that we detected for them or the root cause that we've detected for them, and that's in a shared community channel. So we could see this happening when that AWS outage happened. We could see our customers getting impacted by that AWS outage and the root cause of what was going on there in AWS that was impacting our customers, that was showing up in our incidents. Now, we didn't obviously, you know, have the very root cause of what was going on in AWS per se, but we were getting to the root cause of why our customer's applications were failing, and that was because of issues going on at AWS. >> Very interesting. I mean, I think one of your biggest challenge is going to be getting people's attention because these SREs is so busy, their hair's on fire. (all laughs) You know, he's like, "Hey, chap, I'm going to show you, look at this." >> I tell you. You get their attention, they love it. I mean, this AIOps company, I didn't even tell you the punchline there, but, you know, they had this incident that occurred that we found and, quite literally, the next week, they ended up signing up as a paid customer, so. >> That's great, and Larry, give you the last word. I mean, you know, Rod was talking about, you know, changes in APIs, and, you know, there's still a lot of scripts out there. You guys, if I understand it correctly, run both as a service in the cloud and you can run on-prem, which is important because there's a lot of sensitive information in logs and people don't want to leave. >> That's right, absolutely. >> But, yeah, close it out here. >> Yeah, I mean, you can, that's right, you can run it on-prem, just like we run it in our cloud. You can run it in your cloud or on your own infrastructure. Now, that's all true. You know, I think the one hurdle now that we have left as a company is getting the word out and getting people to believe that this is actually possible and try it for themselves. You don't believe it? Do a POC, try it yourself. And, you know, people have become so jaded by the lack of, you know, real sort of innovation in the software industry for the last 10 years that it's hard to get people to... But guys, you got to give it a shot. I'm telling you. I'm telling you right now, it works, and you'll hear more about that from one of our customers in a minute. >> Alright guys, thanks so much. Great story, really appreciate you sharing. >> Thank you. >> Yeah, thanks, Dave. Appreciate the time. >> Okay, in a moment, we're going to hear from Cisco who is the customer in this case example, and a company that is... Look, they have quite an impressive suite of observability tooling, and they've done a pretty compelling proof of concept with Zebrium using real data on some Cisco products that you've heard of like Webex. So stay tuned and learn about how you can really take advantage of this new technology called root cause as a service. You're watching "theCUBE", the leader in enterprise and emerging tech coverage. (bright outro music)

(bright music) >> Hello everyone and welcome back to theCUBE's live coverage here in San Francisco, California for AWS Summit 2022. I'm John Furrier, your host of theCUBE. Two days of coverage, AWS Summit 2022 in New York city's coming up this summer, we'll be there as well. Events are back. theCUBE is back. Of course, with theCUBE virtual, CUBE hybrid, the cube.net. Check it out, a lot of content this year more than ever. A lot more cloud data, cloud native, modern applications, all happening. Got a great guest here. Jeremy Burton, CUBE alumni, CEO of Observe, Inc. in the middle of all the cloud scale, big data, observability. Jeremy, great to see you. Thanks for coming on. >> Always great to come and talk to you on theCUBE man. It's been a few years. >> Well, you got your hands. You're in the trenches with great startup, good funding, great board, great people involved in the observability space, hot area, but also you've been a senior executive. President of Dell, EMC, 11 years ago you had a vision and you actually had an event called cloud meets big data. >> Jeremy: Yeah. >> And it's here. You predicted it 11 years ago. Look around, it's cloud meets big data. >> Yeah, the cloud thing I think was probably already a thing, but the big data thing I do claim credit for sort of catching that bus early, We were on the bus early and I think it was only inevitable. Like if you could bring the economics and the compute of cloud to big data, you could find out things you could never possibly imagine. >> So you're close to a lot of companies that we've been covering deeply. Snowflake obviously are involved. The board level, the founders, the people there, cloud, Amazon, what's going on here? You're doing a startup as the CEO at the helm, chief of Observe, Inc., which is an observability, which is to me in the center of this confluence of data, engineering, large scale integrations, data as code, integrating into applications. It's a whole another world developing, like you see with Snowflake, it means Snowflake is super cloud as we call it. So a whole nother wave is here. What's this wave we're on? How would you describe the wave? >> Well, a couple of things. People are, I think, riding more software than ever before. Why? Because they've realized that if you don't take your business online and offer a service, then you become largely irrelevant. And so you you've got a whole set of new applications. I think more applications now than any point, not just ever, but the mid nineties. I always looked at as the golden age of application development. Now, back then people were building for Windows. Well now they're building for things like, AWS is now the platform. So you've got all of that going on. And then at the same time, the side effect of these applications is they generate data and lots of data and the transactions, what you bought today or something like that. But then there's what we do, which is all the telemetry data, all the exhaust fumes. And I think people really are realizing that their differentiation is not so much their application. It's their understanding of the data. Can I understand who my best customers are? What I sell today? If people came to my website and didn't buy, then why not? Where did they drop off? All of that they want to analyze. And the answers are all in the data. The question is, can you understand it? >> In our last startup showcase, we featured data as code. One of the insights that we got out of that, and I want to get your opinion on or reaction to is, is that data used to be put into a data lake and turns into a data swamp or throw into the data warehouse, and then we'll do some queries, maybe a report once in a while. And so data, once it was done, unless it was real time, even real time was not good anymore after real time. That was the old way. Now you're seeing more and more effort to say, let's go look at the data, 'cause now machine learning is getting better. Not just train once, they're iterating. This notion of iterating and then pivoting, iterating and pivoting That's a Silicon Valley story. That's like how startups were, but now you're seeing data being treated the same way. So now you have this data concept that's now part of a new way to create more value for the apps. So this whole new cycle of data being reused and repurposed, then figure it out. >> Yeah, yeah, I'm a big fan of, years ago, just an amazing guy, Andy McAfee, at the MIT labs. I spent time with and he had this line, which still sticks to me this day, which is look, he said, I'm part of a body, which believes that everything is a matter of data. Like if you have enough data, you can answer any question. And this has going back 10 years when he was saying these kind of things and certainly, research is on the forefront. But I think starting to see that mindset of the MIT research be mainstream in enterprises. They're realizing that, yeah, it is about the data. If I can better understand my data better than competitor, then I've got an advantage. And so the question is how? What technologies and what skills do I need in my organization to allow me to do that? >> So let's talk about Observe, Inc. You're the CEO. Given you've seen the waves before, you're in the front lines of observability, which again is in the center of all this action. What's going on with the company? Give a quick minute to explain Observe for the folks who don't know what you guys do. What's the company doing? What's the funding status? What's the product status? And what's the customer status? >> Yeah, so we realized, a handful of years ago, let's say five years ago. Look, the way people are building applications is different. They're way more functional. They change every day. But in some respects there are a lot more complicated. They're distributed, microservices architectures. And when something goes wrong, the old way of troubleshooting and solving problems was not going to fly because you had so much change going into production on a daily basis. It was hard to tell like where the problem was. And so we thought, okay, it's about time. Somebody looks at the exhaust fumes from this application and all the telemetry data and helps people troubleshoot and make sense of the problems that they're seeing. So that's observability. It's actually a term that goes back to the 1960s. It was, a guy called, like everything in tech, it's a reinvention of something from years gone by, but there's a guy called Rudy Coleman in 1960s, kind of term. And the term was been able to determine the state of a system by looking at its external outputs. And so we've been going on this for the best part of four years now. It took us three years just to build the product. I think what people don't appreciate these days often is the barrier to entry in a lot of these markets is quite high. You need a lot of functionality to have something that's credible with a customer. So yeah, this last year, we did our first year selling. We've got about 40 customers now. We got great investors Sutter Hill Ventures. Mike Speiser who was really the first guy in the Snowflake and the initial investor. We're fortunate enough to have Mike on our board. And part of the Observe story is closely knit with Snowflake because all of that telemetry data, we store in there. >> So I want to pivot to that. Mike Speiser, Snowflake, Jeremy Burton, theCUBE kind of same thinking. This idea of a super cloud or what Snowflake became. >> Jeremy: Yeah. >> Snowflake is massively successful on top of AWS. And now you're seeing startups and companies build on top of Snowflake. >> Jeremy: Yeah. >> So that's become an entrepreneurial story that we think that to go big in the cloud, you can have a cloud on a cloud, like as Jerry Chen in Greylock calls it, castles in the cloud where there are moats in the cloud. So you're close to it. I know you're doing some stuff with Snowflake's. So as a startup, what's your view on building on top of say a Snowflake or an AWS, because again, you got to go where the data is. You need all the data. >> Jeremy: Yeah. >> What's your take on that? >> Having enough gray hair now. Again, in tech, I think if you want to predict the future, look at the past. And 20 years ago, 25 years ago, I was at a smaller company called Oracle. And an Oracle was the database company and their ambition was to manage all of the world's transactional data. And they built on a platform or a couple of platforms. One, Windows, and the other main one was Solaris. And so at that time, the operating system was the platform. And then that was the ecosystem that you would compete on top of. And then there were companies like SAP that built applications on top of Oracle. So then wind the clock forward 25 years, gray hairs, the platform isn't the operating system anymore. The platform is AWS, Google cloud. I probably look around if I say that in. >> It's okay. But Hyperscale. >> Yeah. >> CapEx built out. >> That is the new platform. And then Snowflake comes along. Well, their aspiration is to manage all of the, not just human generated data, but machine generated data in the world of cloud. And I think they they've done an amazing job doing for the, I'd say the big data world, what Oracle did for the relational data world way back 25 years ago. And then there are folks like us come along and of course my ambition would be, look, if we can be as successful as an SAP building on top of Snowflake, as they were on top of Oracle, then we'd probably be quite happy. >> So you're building on top of Snowflake? >> We're building on top of Snowflake a hundred percent. And I've had folks say to me, well, aren't you worried about that? Isn't that a risk? It's like, well, that's a risk. >> Are you still on the board? >> Yeah, I'm still on the board. Yeah. That's a risk I'm prepared to take. I am long on Snowflake. >> It sounds, well, you're in a good spot. Stay on the board then you'll know as going on. Okay, seriously, this is a real dynamic. >> Jeremy: It is. >> It's not a one off. >> Well, and I do believe as well that the platform that you see now with AWS, if you look at the revenues of AWS, it is an order of magnitude more than Microsoft was 25 years ago with windows. And so I believe the opportunity for folks like Snowflake and folks like Observe, it's an order magnitude more than it was for the Oracle and the SAPs of the old world. >> Yeah, and I think this is something that this next generation of entrepreneurship is the go big scenario is you got to be on a platform. >> Yeah and it's quite easy. >> Or be the platform, but it's hard. There's only like how many seats are at that table left. >> Well, value migrates up over time. So when the cloud thing got going, there were probably 10, 20, 30, rack space and there's 1,000,001 infrastructure for service, platform as a service. My old employee EMC, we had Pivotal. Pivotal was a platform as a service. You don't hear so much about it these days, but initially there's a lot of players and then it consolidates. And then to extract a real business, you got to move up, you got to add value, you got to build databases, then you got to build applications. >> It's interesting. Moving from the data center to the cloud was a dream for starters 'cause they didn't have to provision the CapEx. Now the CapEx is in the cloud. Then you build on top of that, you got Snowflake. Now you got on top of that. >> The assumption is almost that compute and storage is free. I know it's not quite free. >> Yeah, it's almost free. >> But as an application vendor, you think, well, what can I do if I assume compute and storage is free, that's the mindset you've got to get into. >> And I think the platform enablement to value. So if I'm an entrepreneur, I'm going to get a serious multiple of value in what I'm paying. Most people don't even blink at their AWS bills unless they're like massively huge. Then it's a repatriation question or whatever discount question. But for most startups or any growing company, the Amazon bill should be a small factor. >> Yeah, a lot of people ask me like, look, you're building on Snowflake. You're going to be paying their money. How does that work with your business model? If you're paying them money, do you have a viable business? And it's like, well, okay. We could build a database as well in Observe, but then I've got half the development team working on something that will never be as good as Snowflake. And so we made the call early on that, no, we want to innovate above the database. Snowflake are doing a great job of innovating on the database and the same is true with something like Amazon, like Snowflake could have built their own cloud and their own platform, but they didn't. >> Yeah and what's interesting is that Dave Vellante and I have been pointing this out and he's obviously more on Snowflake. I've been looking at Databricks and the same dynamics happening. The proof is the ecosystem. >> Yeah. >> If you look at Snowflake's ecosystem right now and Databricks, it's exploding. The shows are selling out. This floor space is booked. That's the old days at VMware. The old days at AWS. >> One and for Snowflake and any platform provider, it's a beautiful thing because we build on Snowflake and we pay their money. They don't have to sell to us. And we do a lot of the support. And so the economics work out really, really well if you're a platform provider and you've got a lot of ecosystems. >> And then also you get a trajectory of economies of scale with the institutional knowledge of Snowflake, integrations, new products, you're scaling and step function with them. >> Yeah, we manage 10 petabytes of data right now. When I arrived at EMC in 2010, we had one petabyte customer. And so at Observe, we've been only selling the product for a year. We have 10 petabytes of data under management. And so being able to rely on a platform that can manage that is invaluable. >> Well, Jeremy, great conversation. Thanks for sharing your insights on the industry. We got a couple minutes left, put a plug in for Observe. What do you guys do? You got some good funding, great partners. I don't know if you can talk about your POC customers, but you got a lot of high ends folks that are working with you. You get in traction. >> Yeah >> Scales around the corner sounds like. Is that where you at? Pre-scale? >> We've got a big announcement coming up in two or three weeks. We've got new funding, which is always great. The product is really, really close. I think, as a startup, you always strive for market fit, at which point can you just start hiring salespeople and the revenue keeps going. We're getting pretty close to that right now. We've got about 40 SaaS companies that run on the platform. They're almost all AWS Kubernetes, which is our sweet spot to begin with, but we're starting to get some really interesting enterprise type customers. We're F5 networks. We're POC in right now with Capital One. We've got some interesting news around Capital One coming up. I can't share too much, but it's going to be exciting. And like I said, Sutter Hill continue to stick. >> And I think Capital One's a big Snowflake customer as well, right? >> They were early and one of the things that attracted me to Capital One was they were very, very good with Snowflake early on and they put Snowflake in a position in the bank where they thought that snowflake could be successful. And today that is one of Snowflake's biggest accounts. >> Capital One, very innovative cloud. Obviously, AWS customer and very innovative. certainly in the CISO and CIO. On another point on where you're at. So you're pre-scale meaning you're about to scale. >> Jeremy: Right. >> So you got POCs. What's that trajectory look like? And you see around the corner, what's going on? What's around the corner that you're going to hit the straight and narrow and gas it fast? >> Yeah, the key thing for us is we got to get the product right. The nice thing about having a guy like Mike Speiser on the board is he doesn't obsess about revenue at this stage. His questions at the board are always about like, is the product right? Is the product right? Have you got the product right? 'Cause we know when the product's right, we can then scale the sales team and the revenue will take care of itself. So right now all the attention is on the product. This year, the exciting thing is we're adding all the tracing visualizations. So people will be able to the kind of things that back in the day you could do with the New Relics and AppDynamics, the last generation of APM tools. You're going to be able to do that within Observe. And we've already got the logs and the metrics capability in there. So for us this year is a big one 'cause we complete the trifecta, the logs. >> What's the secret sauce of observe if you put it into a sentence, what's the secret sauce? >> I think, an amazing founding engineering team, number one. At the end of the day, you have to build an amazing product and you have to solve a problem in a different way and we've got great long term investors. And the biggest thing our investors give is, actually it's not just money, it gives us time to get the product right. Because if we get the product right, then we can get the growth. >> Got it. Final question while I got you here. You've been on the enterprise business for a long time. What's the buyer landscape out there? You got people doing POCs, Capital One scale. So we know that goes on. What's the appetite at the buyer side for startups and what are their requirements that you're seeing? Obviously, we're seeing people go in and dip into the startup pool because new ways to refactor their business, restructure. So a lot of happening in cloud. What's the criteria? How are enterprises engaging in with startups? >> Yeah, enterprises, they know they've got to spend money transforming the business. I almost feel like my old Dell or EMC self there, but what we were saying five years ago is happening. Everybody needs to figure out a way to take their business to this digital world. Everybody has to do it. So the nice thing from a startup standpoint is they know at times they need to risk or take a bet on new technology in order to help them do that. So I think you've got buyers that A, have money, B, are prepared to take risks, and it's a race against time to get their offerings in this new digital footprint. >> Final, final question. What's the state of AWS? Where do you see them going next? Obviously, they're continuing to be successful. How does cloud 3.0? Or they always say it's day one, but it's maybe more like day 10, but what's next for AWS? Where do they go from here? Obviously, they're doing well and they're getting bigger and bigger. >> Yeah, it's an amazing story. We are on AWS as well. And so I think if they keep nurturing the builders and the ecosystem, then that is their superpower. They have an early leads. And if you look at where, maybe the likes of Microsoft lost the plot in the late nineties, it was they stopped really caring about developers and the folks who are building on top of their ecosystem. In fact, they started buying up their ecosystem and competing with people in their ecosystem. And I see with AWS, they have an amazing head start. And if they did more, if they do more than that, that's what's going to keep this juggernaut rolling for many years to come. >> They got the Silicon and they got the Stack developing. Jeremy Burton inside theCUBE, great resource for commentary, but also founding with the CEO of a company called Observe, Inc. In the middle of all the action and the board of Snowflake as well. Great startup. Thanks for coming on theCUBE. >> Always a pleasure. >> Live from San Francisco's theCUBE. I'm John Furrier, your host. Stay with us. More coverage from San Francisco, California after the short break. (soft music)

(bright upbeat music) >> The adoption of container orchestration platforms is accelerating at a rate as fast or faster than any category in enterprise IT. Survey data from Enterprise Technology Research shows Kubernetes specifically leads the pack into both spending velocity and market share. Now like virtualization in its early days, containers bring many new performance and tuning challenges in particular insuring consistent and predictable application performance is tricky especially because containers, they're so flexible and they enable portability. Things are constantly changing. DevOps pros have to way through a sea of observability data and tuning the environment becomes a continuous exercise of trial and error. This endless cycle taxes resources and kills operational efficiency. So teams often just capitulate and simply dial up and throw unnecessary resources at the problem. StormForge is a company founded mid last decade that is attacking these issues with a combination of machine learning and data analysis. And with me to talk about a new offering that directly addresses these concerns is Matt Provo, founder and CEO of StormForge. Matt, welcome to theCUBE. Good to see you. >> Good to see you. Thanks for having me. >> Yeah, so we saw you guys at a KubeCon sort of first introduce you to our community but add a little color to my intro there if you will. >> Yeah, well, Semi stole my thunder but I'm okay with that. Absolutely agree with everything you said in the intro. You know, the problem that we have set out to solve which is tailor made for the use of real machine learning not machine learning kind of as a marketing tag is connected to how workloads on Kubernetes are really managed from a resource efficiency standpoint. And so a number of years ago, we built the core machine learning engine and have now turned that into a platform around how Kubernetes resources are managed at scale. And so organizations today as they're moving more workloads over, sort of drink the Kool-Aid of the flexibility that comes with Kubernetes and how many knobs you can turn. And developers in many ways love it. Once they start to operationalize the use of Kubernetes and move workloads from pre-production into production, they run into a pretty significant complexity wall. And this is where StormForge comes in to try to help them manage those resources more effectively in ensuring and implementing the right kind of automation that empowers developers into the process ultimately does not automate them out of it. >> So you've got news. You had launch coming to further address these problems. Tell us about that. >> Yeah, so historically, you know, like any machine learning engine, we think about data inputs and what kind of data is going to feed our system to be able to draw the appropriate insights out for the user. And so historically we've kind of been single threaded on load and performance tests in a pre-production environment. And there's been a lot of adoption of that, a lot of excitement around it and frankly amazing results. My vision has been for us to be able to close the loop, however, between data coming out of pre-production and the associated optimizations and data coming out of production environment and our ability to optimize that. A lot of our users along the way have said these results in pre-production are fantastic. How do I know they reflect reality of what my application is going to experience in a production environment? And so we're super excited to announce kind of the a second core module for our platform called Optimize Live. The data input for that is observability and telemetry data coming out of APM platforms and other data sources. >> So this is like Nirvana. So I wonder if we could talk a little bit more about the challenges that this addresses. I mean, I've been around a while and it really have observed... And I used to ask, you know, technology companies all the time. Okay, so you're telling me beforehand what the optimal configuration should be and resource allocation. What happens if something changes? >> Yeah. >> And then it's always, always a pause. >> Yeah. >> And Kubernetes is more of a rapidly changing environment than anything we've ever seen. So specifically the problem you're addressing. Maybe talk about that a little bit. >> Yeah, so we view what happens in pre-production as sort of the experimentation phase. And our machine learning is allowing the user to experiment in scenario plan. What we're doing with Optimize Live and adding the the production piece is what we kind of also call kind of our observation phase. And so you need to be able to run the appropriate checks and balances between those two environments to ensure that what you're actually deploying and monitoring from an application performance, from a cost standpoint is with your SLOs and your SLAs as well as your business objectives. And so that's the entire point of this edition is to allow our users to experience hopefully the Nirvana associated with that because it's an exciting opportunity for them and really something that no else is doing from the standpoint of closing that loop. >> So you said front machine learning not as a marketing tag. So I want you to sort of double click on that. What's different than how other companies approach this problem? >> Yeah, I mean, part of it is a bias for me and a frustration as a founder of the reason I started the company in the first place. I think machine learning or AI gets tagged to a lot of stuff. It's very buzzwordy. It looks good. I'm fortunate to have found a number of folks from the outset of the company with, you know, PhDs in Applied Mathematics and a focus on actually building real AI at the core that is connected to solving the right kind of actual business problems. And so, you know, for the first three or four years of the company's history, we really operated as a lab. And that was our focus. We then decided, we're trying to connect a fantastic team with differentiated technology to the right market timing. And when we saw all these pain points around how fast the adoption of containers and Kubernetes have taken place but the pain that the developers are running into, we actually found for ourselves that this was the perfect use case. >> So how specifically does Optimize Live work? Can you add a little detail on that? >> Yes, so when you... Many organizations today have an existing monitoring APM observability suite really in place. They've also got a metric source. So this could be something like Datadog or Prometheus. And once that data starts flowing, there's an out of the box or kind of a piece of Kubernetes that ships with it called the VPA or the Vertical Pod Autoscaler. And less than, really than 1% of Kubernetes users take advantage of the VPA mostly because it's really challenging to configure and it's not super compatible with the the tool set or, you know, the ecosystem of tools in a Kubernetes environment. And so our biggest competitor is the VPA. And what's happening in this environment or in this world for developers is they're having to make decisions on a number of different metrics or resource elements typically things like memory and CPU. And they have to decide what are the requests I'm going to allow application and what are the limits? So what are those thresholds that I'm going to be okay with so that I can, again, try to hit my business objectives and keep in line with my SLAs? And to your earlier point in the intro, it's often guesswork. You know, they either have to rely on out of the box recommendations that ship with the databases and other services that they are using or it's a super manual process to go through and try to configure and tune this. And so with Optimize Live, we're making that one click. And so we're continuously and consistently observing and watching the data that's flowing through these tools and we're serving back recommendations for the user. They can choose to let those recommendations automatically patch and deploy or they can retain some semblance of control over are the recommendations and manually deploy them into their environment themselves. And we, again, really believe that the user knows their application. They know the goals that they have and we don't. But we have a system that's smart enough to align with the business objectives and ultimately provide the relevant recommendations at that point. >> So the business objectives are an input from the application team? >> Yep. >> And then your system is smart enough to adapt and address those. >> Application over application, right? And so the thresholds in any given organization across their different ecosystem of apps or environment could be different. The business objectives could be different. And so we don't want to predefine that for people. We want to give them the opportunity to build those thresholds in and then allow the machine learning to learn and to send recommendations within those bounds. >> And we're going to hear later from a customer who's hosting a Drupal, one of the largest Drupal hosts. So it's all do it yourself across thousands of customers so it's, you know, very unpredictable. I want to make something clear though as to where you fit in the ecosystem. You're not an observability platform, you leverage observability platforms, right? So talk about that and where you fit into the ecosystem. >> Yeah, so it's a great point. We're also, you know, a series B startup and growing. We've the choice to be very intentionally focused on the problems that we've solve. And we've chosen to partner or integrate otherwise. And so we do get put into the APM category from time to time. We are really an intelligence platform. And that intelligence and insights that we're able to draw is because of the core machine learning we've built over the years. And we also don't want organizations or users to have to switch from tools and investments that they've already made. And so we were never going to catch up to to Datadog or Dynatrace or Splunk or AppDynamics or some of the other. And we're totally fine with that. They've got great market share and penetration. They do solve real problems. Instead, we felt like users would want a seamless integration into the tools they're already using. And so we view ourselves as kind of the Intel inside for that kind of a scenario. And it takes observability and APM data and insights that were somewhat reactive. They're visualized and somewhat reactive. And we add that proactive nature onto it, the insights and ultimately the appropriate level of automation. >> So when I think, Matt, about cloud native and I go back to the sort of origins of CNCF who's a, you know, handful of companies. And now you look at the participants it'll, you know, make your eyes bleed. How do you address dealing with all those companies and what is the partnership strategy? >> Yeah, it's so interesting because it's just that even that CNCF landscape has exploded. It was not too long ago where it was as small or smaller than the FinOps landscape today which by the way, the FinOps piece is also on a a neck breaking, you know, growth curve. We, I do see, although there are a lot of companies and a lot of tools, we're starting to see a significant amount of consistency or hardening of the tool chain, you know, with our customers and users. And so we've made strategic and intentional decisions on deep partnerships in some cases like OEM uses of our technology and certainly, you know, intelligent and seamless integrations into a few. So, you know, we'll be announcing a really exciting partnership with AWS and that specifically what they're doing with EKS, their Kubernetes distribution and services. We've got a deep partnership and integration with Datadog and then with Prometheus and specifically a few other cloud providers that are operating, manage Prometheus environments. >> Okay, so where do you want to take this thing? You're not taking the observability guys head on, smart move. So many of those even entering the market now. But what is the vision? >> Yeah, so we've had this debate a lot as well 'cause it's super difficult to create a category. You know, on one hand, you know, I have a lot of respect for founders and companies that do that. On the other hand from a market timing standpoint, you know we fit into AIOps, that's really where we fit. You know, we've made a bet on the future of Kubernetes and what that's going to look like. And so from a containers and Kubernetes standpoint, that's our bet. But we're an AIOps platform. You know, we'll continue getting better at the problems we solve with machine learning and we'll continue adding data inputs. So we'll go, you know, we'll go beyond the application layer which is really where we play now. We'll add, you know, kind of whole cluster optimization capabilities across the full stack. And the way we will get there is by continuing to add different data inputs that make sense across the different layers of the stack. And it's exciting. We can stay vertically oriented on the problems that we're really good at solving but we can become more applicable and compatible over time. >> So that's your next concentric circle. As the observability vendors expand their observation space, you can just play right into that. >> Yeah. >> The more data you get because your purpose built to solving these types of problems. >> Yeah, so you can imagine a world right now out of observability, we're taking things like telemetry data pretty quickly. You can imagine a world where we take traces and logs and other data inputs as that ecosystem continues to grow, it just feeds our own, you know, we are reliant on data. >> Excellent, Matt, thank you so much. >> Thanks for having me. >> Appreciate for coming on. Okay, keep it right there in a moment. We're going to hear from a customer with a highly diverse and constantly changing environment that I mentioned earlier. They went through a major replatforming with Kubernetes on AWS. You're watching theCUBE, you are leader in enterprise tech coverage. (bright upbeat music)

(bright upbeat music) >> The adoption of container orchestration platforms is accelerating at a rate as fast or faster than any category in enterprise IT. Survey data from Enterprise Technology Research shows Kubernetes specifically leads the pack in both spending velocity and market share. Now like virtualization in its early days, containers bring many new performance and tuning challenges. In particular, ensuring consistent and predictable application performance is tricky especially because containers they're so flexible and the enabled portability things are constantly changing. DevOps pros have to wade through a sea of observability data and tuning the environment becomes a continuous exercise of trial and error. This endless cycle taxes, resources, and kills operational efficiencies so teams often just capitulate and simply dial up and throw unnecessary resources at the problem. StormForge is a company founded in mid last decade that is attacking these issues with a combination of machine learning and data analysis. And with me to talk about a new offering that directly addresses these concerns, is Matt Provo, founder and CEO of StormForge. Matt, welcome to thecube. Good to see you. >> Good to see you, thanks for having me. >> Yeah. So we saw you guys at CubeCon, sort of first introduce you to our community but add a little color to my intro if you will. >> Yeah, well you semi stole my thunder but I'm okay with that. Absolutely agree with everything you said in the intro. You know, the problem that we have set out to solve which is tailor made for the use of real machine learning not machine learning kind of as a marketing tag is connected to how workloads on Kubernetes are really managed from a resource efficiency standpoint. And so a number of years ago we built the core machine learning engine and have now turned that into a platform around how Kubernetes resources are managed at scale. And so organizations today as they're moving more workloads over sort of drink the Kool-Aid of the flexibility that comes with Kubernetes and how many knobs you can turn and developers in many ways love it. Once they start to operationalize the use of Kubernetes and move workloads from pre-production into production, they run into a pretty significant complexity wall. And this is where StormForge comes in to try to help them manage those resources more effectively in ensuring and implementing the right kind of automation that empowers developers into the process ultimately does not automate them out of it. >> So you've got news, your hard launch coming in to further address these problems. Tell us about that. >> Yeah so historically, you know, like any machine learning engine, we think about data inputs and what kind of data is going to feed our system to be able to draw the appropriate insights out for the user. And so historically we are, we've kind of been single-threaded on load and performance tests in a pre-production environment. And there's been a lot of adoption of that, a lot of excitement around it and frankly, amazing results. My vision has been for us to be able to close the loop however between data coming out of pre-production and the associated optimizations and data coming out of production, a production environment, and our ability to optimize that. A lot of our users along the way have said these results in pre-production are fantastic. How do I know they reflect reality of what my application is going to experience in a production environment? And so we're super excited to announce kind of the second core module for our platform called Optimize Live. The data input for that is observability and telemetry data coming out of APM platforms and other data sources. >> So this is like Nirvana. So I wonder if we could talk a little bit more about the challenges that this addresses. I mean, I've been around a while and it really have observed and I used to ask technology companies all the time, okay, so you're telling me beforehand what the optimal configuration should be in resource allocation, what happens if something changes? And then it's always a pause. And Kubernetes is more of a rapidly changing environment than anything we've ever seen. So this is specifically the problem you're addressing. Maybe talk about that a little bit. >> Yeah so we view what happens in pre-production as sort of the experimentation phase and our machine learning is allowing the user to experiment and scenario plan. What we're doing with Optimize Live and adding the production piece is what we kind of also call kind of our observation phase. And so you need to be able to run the appropriate checks and balances between those two environments to ensure that what you're actually deploying and monitoring from an application performance, from a cost standpoint, is aligning with your SLOs and your SLAs as well as your business objectives. And so that's the entire point of this addition is to allow our users to experience hopefully the Nirvana associated with that because it's an exciting opportunity for them and really something that nobody else is doing from the standpoint of closing that loop. >> So you said upfront machine learning not as a marketing tag. So I want you to sort of double click on that. What's different than how other companies approach this problem? >> Yeah I mean, part of it is a bias for me and a frustration as a founder of the reason I started the company in the first place. I think machine learning our AI gets tagged to a lot of stuff. It's very buzzwordy, it looks good. I'm fortunate to have found a number of folks from the outset of the company with, you know, PhDs in Applied Mathematics and a focus on actually building real AI at the core that is connected to solving the right kind of actual business problems. And so, you know, for the first three or four years of the company's history, we really operated as a lab and that was our focus. We then decided we're trying to connect a fantastic team with differentiated technology to the right market timing. And when we saw all of these pain points around how fast the adoption of containers and Kubernetes have taken place but the pain that the developers are running into, we found it, we actually found for ourselves that this was the perfect use case. >> So how specifically does Optimize Live work? Can you add a little detail on that? >> Yeah so when you, many organizations today have an existing monitoring APM observability suite really in place. They've also got, they've also got a metric source, so this could be something like Datadog or Prometheus. And once that data starts flowing, there's an out of the box or kind of a piece of Kubernetes that ships with it called the VPA or the Vertical Pod Autoscaler. And less than really less than 1% of Kubernetes users take advantage of the VPA mostly because it's really challenging to configure and it's not super compatible with the tool set or the, you know, the ecosystem of tools in a Kubernetes environment. And so our biggest competitor is the VPA. And what's happening in this environment or in this world for developers is they're having to make decisions on a number of different metrics or resource elements typically things like memory and CPU. And they have to decide what are the, what are the requests I'm going to allow for this application and what are the limits? So what are those thresholds that I'm going to be okay with? So that I can again try to hit my business objectives and keep in line with my SLAs. And to your earlier point in the intro, it's often guesswork. You know, they either have to rely on out of the box recommendations that ship with the databases and other services that they are using or it's a super manual process to go through and try to configure and tune this. And so with Optimize Live, we're making that one-click. And so we're continuously and consistently observing and watching the data that's flowing through these tools and we're serving back recommendations for the user. They can choose to let those recommendations automatically patch and deploy or they can retain some semblance of control over the recommendations and manually deploy them into their environment themselves. And we again, really believe that the user knows their application, they know the goals that they have, we don't. But we have a system that's smart enough to align with the business objectives and ultimately provide the relevant recommendations at that point. >> So the business objectives are an input from the application team and then your system is smart enough to adapt and adjust those. >> Application over application, right? And so the thresholds in any given organization across their different ecosystem of apps or environment could be different. The business objectives could be different. And so we don't want to predefine that for people. We want to give them the opportunity to build those thresholds in and then allow the machine learning to learn and to send recommendations within those bounds. >> And we're going to hear later from a customer who is hosting a Drupal, one of the largest Drupal host, is it? So it's all do it yourself across thousands of customers so it's very unpredictable. I want to make something clear though, as to where you fit in the ecosystem. You're not an observability platform, you leverage observability platforms, right? So talk about that and where you fit in into the ecosystem. >> Yeah so it's a great point. We, we're also you know, a series B startup and growing. We've made the choice to be very intentionally focused on the problems that we've solve and we've chosen to partner or integrate otherwise. And so we do get put into the APM category from time to time. We're really an intelligence platform. And that intelligence and insights that we're able to draw is because we, because of the core machine learning we've built over the years. And we also don't want organizations or users to have to switch from tools and investments that they've already made. And so we were never going to catch up to Datadog or Dynatrace or Splunk or AppDynamics or some of the other, and we're totally fine with that. They've got great market share and penetration and they do solve real problems. Instead, we felt like users would want a seamless integration into the tools they're already using. And so we view ourselves as kind of the Intel inside for that kind of a scenario. And it takes observability and APM data and insights that were somewhat reactive, they're visualized and somewhat reactive and we make those, we add that proactive nature onto it, the insights and ultimately the appropriate level of automation. >> So when I think Matt about cloud native and I go back to the sort of origins of CNCF, it was a, you know, handful of companies, and now you look at the participants, you know, make your eyes bleed. How do you address dealing with all those companies and what's the partnership strategy? >> Yeah it's so interesting because it's just that even at CNCF landscape has exploded. It was not too long ago where it was as smaller than the finOps Landscape today which by the way the FinOps pieces is also on a neck breaking, you know, growth curve. We, I do see although there are a lot of companies and a lot of tools, we're starting to see a significant amount of consistency or hardening of the tool chain with our customers and users. And so we've made strategic and intentional decisions on deep partnerships in some cases like OEM users of our technology and certainly, you know, intelligent and seamless integrations into a few. So, you know, we'll be announcing a really exciting partnership with AWS and specifically what they're doing with EKS, their Kubernetes distribution and services. We've got a deep partnership and integration with Datadog and then with Prometheus and specifically cloud provider, a few other cloud providers that are operating manage Prometheus environments. >> Okay so where do you want to take this thing? If it's not, you're not taking the observability guys head on, smart move, so many of those even entering the market now, but what is the vision? >> Yeah so we've had this debate a lot as well because it's super difficult to create a category. You know, on one hand, I have a lot of respect for founders and companies that do that, on the other hand from a market timing standpoint, you know, we fit into AIOps. That's really where we fit. You know we are, we've made a bet on the future of Kubernetes and what that's going to look like. And so from a containers and Kubernetes standpoint that's our bet. But we're an AIOps platform, we'll continue getting better at what, at the problems we solve with machine learning and we'll continue adding data inputs so we'll go beyond the application layer which is really where we play now. We'll add kind of whole cluster optimization capabilities across the full stack. And the way we'll get there is by continuing to add different data inputs that make sense across the different layers of the stack and it's exciting. We can stay vertically oriented on the problems that we're really good at solving but we become more applicable and compatible over time. >> So that's your next concentric circle. As the observability vendors expand their observation space you can just play right into that. The more data you get could be because you're purpose built to solving these types of problems. >> Yeah so you can imagine a world right now out of observability, we're taking things like telemetry data pretty quickly. You can imagine a world where we take traces and logs and other data inputs as that ecosystem continues to grow, it just feeds our own, you know, we are reliant on data. So. >> Excellent. Matt, thank you so much. Thanks for hoping on. >> Yeah, appreciate it. >> Okay. Keep it right there. In a moment, We're going to hear from a customer with a highly diverse and constantly changing environment that I mentioned earlier, they went through a major re-platforming with Kubernetes on AWS. You're watching theCube, your a leader in enterprise tech coverage. (bright music)

(upbeat music) >> Hello and welcome to this CUBE conversation here presenting the "AWS Startup Showcase: "New Breakthroughs in DevOps, Data Analytics "and Cloud Management Tools" featuring Opsani for the cloud management and migration track here today, I'm your host John Furrier. Today, we're joined by Patrick Conte, Chief Commercial Officer, Opsani. Thanks for coming on. Appreciate you coming on. Future of AI operations. >> Thanks, John. Great to be here. Appreciate being with you. >> So congratulations on all your success being showcased here as part of the Startups Showcase, future of AI operations. You've got the cloud scale happening. A lot of new transitions in this quote digital transformation as cloud scales goes next generation. DevOps revolution as Emily Freeman pointed out in her keynote. What's the problem statement that you guys are focused on? Obviously, AI involves a lot of automation. I can imagine there's a data problem in there somewhere. What's the core problem that you guys are focused on? >> Yeah, it's interesting because there are a lot of companies that focus on trying to help other companies optimize what they're doing in the cloud, whether it's cost or whether it's performance or something else. We felt very strongly that AI was the way to do that. I've got a slide prepared, and maybe we can take a quick look at that, and that'll talk about the three elements or dimensions of the problem. So we think about cloud services and the challenge of delivering cloud services. You've really got three things that customers are trying to solve for. They're trying to solve for performance, they're trying to solve for the best performance, and, ultimately, scalability. I mean, applications are growing really quickly especially in this current timeframe with cloud services and whatnot. They're trying to keep costs under control because certainly, it can get way out of control in the cloud since you don't own the infrastructure, and more importantly than anything else which is why it's at the bottom sort of at the foundation of all this, is they want their applications to be a really a good experience for their customers. So our customer's customer is actually who we're trying to solve this problem for. So what we've done is we've built a platform that uses AI and machine learning to optimize, meaning tune, all of the key parameters of a cloud application. So those are things like the CPU usage, the memory usage, the number of replicas in a Kubernetes or container environment, those kinds of things. It seems like it would be simple just to grab some values and plug 'em in, but it's not. It's actually the combination of them has to be right. Otherwise, you get delays or faults or other problems with the application. >> Andrew, if you can bring that slide back up for a second. I want to just ask one quick question on the problem statement. You got expenditures, performance, customer experience kind of on the sides there. Do you see this tip a certain way depending upon use cases? I mean, is there one thing that jumps out at you, Patrick, from your customer's customer's standpoint? Obviously, customer experience is the outcome. That's the app, whatever. That's whatever we got going on there. >> Sure. >> But is there patterns 'cause you can have good performance, but then budget overruns. Or all of them could be failing. Talk about this dynamic with this triangle. >> Well, without AI, without machine learning, you can solve for one of these, only one, right? So if you want to solve for performance like you said, your costs may overrun, and you're probably not going to have control of the customer experience. If you want to solve for one of the others, you're going to have to sacrifice the other two. With machine learning though, we can actually balance that, and it isn't a perfect balance, and the question you asked is really a great one. Sometimes, you want to over-correct on something. Sometimes, scalability is more important than cost, but what we're going to do because of our machine learning capability, we're going to always make sure that you're never spending more than you should spend, so we're always going to make sure that you have the best cost for whatever the performance and reliability factors that you you want to have are. >> Yeah, I can imagine. Some people leave services on. Happened to us one time. An intern left one of the services on, and like where did that bill come from? So kind of looked back, we had to kind of fix that. There's a ton of action, but I got to ask you, what are customers looking for with you guys? I mean, as they look at Opsani, what you guys are offering, what's different than what other people might be proposing with optimization solutions? >> Sure. Well, why don't we bring up the second slide, and this'll illustrate some of the differences, and we can talk through some of this stuff as well. So really, the area that we play in is called AIOps, and that's sort of a new area, if you will, over the last few years, and really what it means is applying intelligence to your cloud operations, and those cloud operations could be development operations, or they could be production operations. And what this slide is really representing is in the upper slide, that's sort of the way customers experience their DevOps model today. Somebody says we need an application or we need a feature, the developers pull down something from get. They hack an early version of it. They run through some tests. They size it whatever way they know that it won't fail, and then they throw it over to the SREs to try to tune it before they shove it out into production, but nobody really sizes it properly. It's not optimized, and so it's not tuned either. When it goes into production, it's just the first combination of settings that work. So what happens is undoubtedly, there's some type of a problem, a fault or a delay, or you push new code, or there's a change in traffic. Something happens, and then, you've got to figure out what the heck. So what happens then is you use your tools. First thing you do is you over-provision everything. That's what everybody does, they over-provision and try to soak up the problem. But that doesn't solve it because now, your costs are going crazy. You've got to go back and find out and try as best you can to get root cause. You go back to the tests, and you're trying to find something in the test phase that might be an indicator. Eventually your developers have to hack a hot fix, and the conveyor belt sort of keeps on going. We've tested this model on every single customer that we've spoken to, and they've all said this is what they experience on a day-to-day basis. Now, if we can go back to the side, let's talk about the second part which is what we do and what makes us different. So on the bottom of this slide, you'll see it's really a shift-left model. What we do is we plug in in the production phase, and as I mentioned earlier, what we're doing is we're tuning all those cloud parameters. We're tuning the CPU, the memory, the Replicas, all those kinds of things. We're tuning them all in concert, and we're doing it at machine speed, so that's how the customer gets the best performance, the best reliability at the best cost. That's the way we're able to achieve that is because we're iterating this thing in machine speed, but there's one other place where we plug in and we help the whole concept of AIOps and DevOps, and that is we can plug in in the test phase as well. And so if you think about it, the DevOps guy can actually not have to over-provision before he throws it over to the SREs. He can actually optimize and find the right size of the application before he sends it through to the SREs, and what this does is collapses the timeframe because it means the SREs don't have to hunt for a working set of parameters. They get one from the DevOps guys when they send it over, and this is how the future of AIOps is being really affected by optimization and what we call autonomous optimization which means that it's happening without humans having to press a button on it. >> John: Andrew, bring that slide back up. I want to just ask another question. Tuning in concert thing is very interesting to me. So how does that work? Are you telegraphing information to the developer from the autonomous workload tuning engine piece? I mean, how does the developer know the right knobs or where does it get that provisioning information? I see the performance lag. I see where you're solving that problem. >> Sure. >> How does that work? >> Yeah, so actually, if we go to the next slide, I'll show you exactly how it works. Okay, so this slide represents the architecture of a typical application environment that we would find ourselves in, and inside the dotted line is the customer's application namespace. That's where the app is. And so, it's got a bunch of pods. It's got a horizontal pod. It's got something for replication, probably an HPA. And so, what we do is we install inside that namespace two small instances. One is a tuning pod which some people call a canary, and that tuning pod joins the rest of the pods, but it's not part of the application. It's actually separate, but it gets the same traffic. We also install somebody we call Servo which is basically an action engine. What Servo does is Servo takes the metrics from whatever the metric system is is collecting all those different settings and whatnot from the working application. It could be something like Prometheus. It could be an Envoy Sidecar, or more likely, it's something like AppDynamics, or we can even collect metrics off of Nginx which is at the front of the service. We can plug into anywhere where those metrics are. We can pull the metrics forward. Once we see the metrics, we send them to our backend. The Opsani SaaS service is our machine learning backend. That's where all the magic happens, and what happens then is that service sees the settings, sends a recommendation to Servo, Servo sends it to the tuning pod, and we tune until we find optimal. And so, that iteration typically takes about 20 steps. It depends on how big the application is and whatnot, how fast those steps take. It could be anywhere from seconds to minutes to 10 to 20 minutes per step, but typically within about 20 steps, we can find optimal, and then we'll come back and we'll say, "Here's optimal, and do you want to "promote this to production," and the customer says, "Yes, I want to promote it to production "because I'm saving a lot of money or because I've gotten "better performance or better reliability." Then, all he has to do is press a button, and all that stuff gets sent right to the production pods, and all of those settings get put into production, and now he's now he's actually saving the money. So that's basically how it works. >> It's kind of like when I want to go to the beach, I look at the weather.com, I check the forecast, and I decide whether I want to go or not. You're getting the data, so you're getting a good look at the information, and then putting that into a policy standpoint. I get that, makes total sense. Can I ask you, if you don't mind, expanding on the performance and reliability and the cost advantage? You mentioned cost. How is that impacting? Give us an example of some performance impact, reliability, and cost impacts. >> Well, let's talk about what those things mean because like a lot of people might have different ideas about what they think those mean. So from a cost standpoint, we're talking about cloud spend ultimately, but it's represented by the settings themselves, so I'm not talking about what deal you cut with AWS or Azure or Google. I'm talking about whatever deal you cut, we're going to save you 30, 50, 70% off of that. So it doesn't really matter what cost you negotiated. What we're talking about is right-sizing the settings for CPU and memory, Replica. Could be Java. It could be garbage collection, time ratios, or heap sizes or things like that. Those are all the kinds of things that we can tune. The thing is most of those settings have an unlimited number of values, and this is why machine learning is important because, if you think about it, even if they only had eight settings or eight values per setting, now you're talking about literally billions of combinations. So to find optimal, you've got to have machine speed to be able to do it, and you have to iterate very, very quickly to make it happen. So that's basically the thing, and that's really one of the things that makes us different from anybody else, and if you put that last slide back up, the architecture slide, for just a second, there's a couple of key words at the bottom of it that I want to want to focus on, continuous. So continuous really means that we're on all the time. We're not plug us in one time, make a change, and then walk away. We're actually always measuring and adjusting, and the reason why this is important is in the modern DevOps world, your traffic level is going to change. You're going to push new code. Things are going to happen that are going to change the basic nature of the software, and you have to be able to tune for those changes. So continuous is very important. Second thing is autonomous. This is designed to take pressure off of the SREs. It's not designed to replace them, but to take the pressure off of them having to check pager all the time and run in and make adjustments, or try to divine or find an adjustment that might be very, very difficult for them to do so. So we're doing it for them, and that scale means that we can solve this for, let's say, one big monolithic application, or we can solve it for literally hundreds of applications and thousands of microservices that make up those applications and tune them all at the same time. So the same platform can be used for all of those. You originally asked about the parameters and the settings. Did I answer the question there? >> You totally did. I mean, the tuning in concert. You mentioned early as a key point. I mean, you're basically tuning the engine. It's not so much negotiating a purchase SaaS discount. It's essentially cost overruns by the engine, either over burning or heating or whatever you want to call it. I mean, basically inefficiency. You're tuning the core engine. >> Exactly so. So the cost thing is I mentioned is due to right-sizing the settings and the number of Replicas. The performance is typically measured via latency, and the reliability is typically measured via error rates. And there's some other measures as well. We have a whole list of them that are in the application itself, but those are the kinds of things that we look for as results. When we do our tuning, we look for reducing error rates, or we look for holding error rates at zero, for example, even if we improve the performance or we improve the cost. So we're looking for the best result, the best combination result, and then a customer can decide if they want to do so to actually over-correct on something. We have the whole concept of guard rail, so if performance is the most important thing, or maybe some customers, cost is the most important thing, they can actually say, "Well, give us the best cost, "and give us the best performance and the best reliability, "but at this cost," and we can then use that as a service-level objective and tune around it. >> Yeah, it reminds me back in the old days when you had filtering white lists of black lists of addresses that can go through, say, a firewall or a device. You have billions of combinations now with machine learning. It's essentially scaling the same concept to unbelievable. These guardrails are now in place, and that's super cool and I think really relevant call-out point, Patrick, to kind of highlight that. At this kind of scale, you need machine learning, you need the AI to essentially identify quickly the patterns or combinations that are actually happening so a human doesn't have to waste their time that can be filled by basically a bot at that point. >> So John, there's just one other thing I want to mention around this, and that is one of the things that makes us different from other companies that do optimization. Basically, every other company in the optimization space creates a static recommendation, basically their recommendation engines, and what you get out of that is, let's say it's a manifest of changes, and you hand that to the SREs, and they put it into effect. Well, the fact of the matter is is that the traffic could have changed then. It could have spiked up, or it could have dropped below normal. You could have introduced a new feature or some other code change, and at that point in time, you've already instituted these changes. They may be completely out of date. That's why the continuous nature of what we do is important and different. >> It's funny, even the language that we're using here: network, garbage collection. I mean, you're talking about tuning an engine, am operating system. You're talking about stuff that's moving up the stack to the application layer, hence this new kind of eliminating of these kind of siloed waterfall, as you pointed out in your second slide, is kind of one integrated kind of operating environment. So when you have that or think about the data coming in, and you have to think about the automation just like self-correcting, error-correcting, tuning, garbage collection. These are words that we've kind of kicking around, but at the end of the day, it's an operating system. >> Well in the old days of automobiles, which I remember cause I'm I'm an old guy, if you wanted to tune your engine, you would probably rebuild your carburetor and turn some dials to get the air-oxygen-gas mix right. You'd re-gap your spark plugs. You'd probably make sure your points were right. There'd be four or five key things that you would do. You couldn't do them at the same time unless you had a magic wand. So we're the magic wand that basically, or in modern world, we're sort of that thing you plug in that tunes everything at once within that engine which is all now electronically controlled. So that's the big differences as you think about what we used to do manually, and now, can be done with automation. It can be done much, much faster without humans having to get their fingernails greasy, let's say. >> And I think the dynamic versus static is an interesting point. I want to bring up the SRE which has become a role that's becoming very prominent in the DevOps kind of plus world that's happening. You're seeing this new revolution. The role of the SRE is not just to be there to hold down and do the manual configuration. They had a scale. They're a developer, too. So I think this notion of offloading the SRE from doing manual tasks is another big, important point. Can you just react to that and share more about why the SRE role is so important and why automating that away through when you guys have is important? >> The SRE role is becoming more and more important, just as you said, and the reason is because somebody has to get that application ready for production. The DevOps guys don't do it. That's not their job. Their job is to get the code finished and send it through, and the SREs then have to make sure that that code will work, so they have to find a set of settings that will actually work in production. Once they find that set of settings, the first one they find that works, they'll push it through. It's not optimized at that point in time because they don't have time to try to find optimal, and if you think about it, the difference between a machine learning backend and an army of SREs that work 24-by-seven, we're talking about being able to do the work of many, many SREs that never get tired, that never need to go play video games, to unstress or whatever. We're working all the time. We're always measuring, adjusting. A lot of the companies we talked to do a once-a-month adjustment on their software. So they put an application out, and then they send in their SREs once a month to try to tune the application, and maybe they're using some of these other tools, or maybe they're using just their smarts, but they'll do that once a month. Well, gosh, they've pushed code probably four times during the month, and they probably had a bunch of different spikes and drops in traffic and other things that have happened. So we just want to help them spend their time on making sure that the application is ready for production. Want to make sure that all the other parts of the application are where they should be, and let us worry about tuning CPU, memory, Replica, job instances, and things like that so that they can work on making sure that application gets out and that it can scale, which is really important for them, for their companies to make money is for the apps to scale. >> Well, that's a great insight, Patrick. You mentioned you have a lot of great customers, and certainly if you have your customer base are early adopters, pioneers, and grow big companies because they have DevOps. They know that they're seeing a DevOps engineer and an SRE. Some of the other enterprises that are transforming think the DevOps engineer is the SRE person 'cause they're having to get transformed. So you guys are at the high end and getting now the new enterprises as they come on board to cloud scale. You have a huge uptake in Kubernetes, starting to see the standardization of microservices. People are getting it, so I got to ask you can you give us some examples of your customers, how they're organized, some case studies, who uses you guys, and why they love you? >> Sure. Well, let's bring up the next slide. We've got some customer examples here, and your viewers, our viewers, can probably figure out who these guys are. I can't tell them, but if they go on our website, they can sort of put two and two together, but the first one there is a major financial application SaaS provider, and in this particular case, they were having problems that they couldn't diagnose within the stack. Ultimately, they had to apply automation to it, and what we were able to do for them was give them a huge jump in reliability which was actually the biggest problem that they were having. We gave them 5,000 hours back a month in terms of the application. They were they're having pager duty alerts going off all the time. We actually gave them better performance. We gave them a 10% performance boost, and we dropped their cloud spend for that application by 72%. So in fact, it was an 80-plus % price performance or cost performance improvement that we gave them, and essentially, we helped them tune the entire stack. This was a hybrid environment, so this included VMs as well as more modern architecture. Today, I would say the overwhelming majority of our customers have moved off of the VMs and are in a containerized environment, and even more to the point, Kubernetes which we find just a very, very high percentage of our customers have moved to. So most of the work we're doing today with new customers is around that, and if we look at the second and third examples here, those are examples of that. In the second example, that's a company that develops websites. It's one of the big ones out in the marketplace that, let's say, if you were starting a new business and you wanted a website, they would develop that website for you. So their internal infrastructure is all brand new stuff. It's all Kubernetes, and what we were able to do for them is they were actually getting decent performance. We held their performance at their SLO. We achieved a 100% error-free scenario for them at runtime, and we dropped their cost by 80%. So for them, they needed us to hold-serve, if you will, on performance and reliability and get their costs under control because everything in that, that's a cloud native company. Everything there is cloud cost. So the interesting thing is it took us nine steps because nine of our iterations to actually get to optimal. So it was very, very quick, and there was no integration required. In the first case, we actually had to do a custom integration for an underlying platform that was used for CICD, but with the- >> John: Because of the hybrid, right? >> Patrick: Sorry? >> John: Because it was hybrid, right? >> Patrick: Yes, because it was hybrid, exactly. But within the second one, we just plugged right in, and we were able to tune the Kubernetes environment just as I showed in that architecture slide, and then the third one is one of the leading application performance monitoring companies on the market. They have a bunch of their own internal applications and those use a lot of cloud spend. They're actually running Kubernetes on top of VMs, but we don't have to worry about the VM layer. We just worry about the Kubernetes layer for them, and what we did for them was we gave them a 48% performance improvement in terms of latency and throughput. We dropped their error rates by 90% which is pretty substantial to say the least, and we gave them a 50% cost delta from where they had been. So this is the perfect example of actually being able to deliver on all three things which you can't always do. It has to be, sort of all applications are not created equal. This was one where we were able to actually deliver on all three of the key objectives. We were able to set them up in about 25 minutes from the time we got started, no extra integration, and needless to say, it was a big, happy moment for the developers to be able to go back to their bosses and say, "Hey, we have better performance, "better reliability. "Oh, by the way, we saved you half." >> So depending on the stack situation, you got VMs and Kubernetes on the one side, cloud-native, all Kubernetes, that's dream scenario obviously. Not many people like that. All the new stuff's going cloud-native, so that's ideal, and then the mixed ones, Kubernetes, but no VMs, right? >> Yeah, exactly. So Kubernetes with no VMs, no problem. Kubernetes on top of VMs, no problem, but we don't manage the VMs. We don't manage the underlay at all, in fact. And the other thing is we don't have to go back to the slide, but I think everybody will remember the slide that had the architecture, and on one side was our cloud instance. The only data that's going between the application and our cloud instance are the settings, so there's never any data. There's never any customer data, nothing for PCI, nothing for HIPPA, nothing for GDPR or any of those things. So no personal data, no health data. Nothing is passing back and forth. Just the settings of the containers. >> Patrick, while I got you here 'cause you're such a great, insightful guest, thank you for coming on and showcasing your company. Kubernetes real quick. How prevalent is this mainstream trend is because you're seeing such great examples of performance improvements. SLAs being met, SLOs being met. How real is Kubernetes for the mainstream enterprise as they're starting to use containers to tip their legacy and get into the cloud-native and certainly hybrid and soon to be multi-cloud environment? >> Yeah, I would not say it's dominant yet. Of container environments, I would say it's dominant now, but for all environments, it's not. I think the larger legacy companies are still going through that digital transformation, and so what we do is we catch them at that transformation point, and we can help them develop because as we remember from the AIOps slide, we can plug in at that test level and help them sort of pre-optimize as they're coming through. So we can actually help them be more efficient as they're transforming. The other side of it is the cloud-native companies. So you've got the legacy companies, brick and mortar, who are desperately trying to move to digitization. Then, you've got the ones that are born in the cloud. Most of them aren't on VMs at all. Most of them are on containers right from the get-go, but you do have some in the middle who have started to make a transition, and what they've done is they've taken their native VM environment and they've put Kubernetes on top of it so that way, they don't have to scuttle everything underneath it. >> Great. >> So I would say it's mixed at this point. >> Great business model, helping customers today, and being a bridge to the future. Real quick, what licensing models, how to buy, promotions you have for Amazon Web Services customers? How do people get involved? How do you guys charge? >> The product is licensed as a service, and the typical service is an annual. We license it by application, so let's just say you have an application, and it has 10 microservices. That would be a standard application. We'd have an annual cost for optimizing that application over the course of the year. We have a large application pack, if you will, for let's say applications of 20 services, something like that, and then we also have a platform, what we call Opsani platform, and that is for environments where the customer might have hundreds of applications and-or thousands of services, and we can plug into their deployment platform, something like a harness or Spinnaker or Jenkins or something like that, or we can plug into their their cloud Kubernetes orchestrator, and then we can actually discover the apps and optimize them. So we've got environments for both single apps and for many, many apps, and with the same platform. And yes, thanks for reminding me. We do have a promotion for for our AWS viewers. If you reference this presentation, and you look at the URL there which is opsani.com/awsstartupshowcase, can't forget that, you will, number one, get a free trial of our software. If you optimize one of your own applications, we're going to give you an Oculus set of goggles, the augmented reality goggles. And we have one other promotion for your viewers and for our joint customers here, and that is if you buy an annual license, you're going to get actually 15 months. So that's what we're putting on the table. It's actually a pretty good deal. The Oculus isn't contingent. That's a promotion. It's contingent on you actually optimizing one of your own services. So it's not a synthetic app. It's got to be one of your own apps, but that's what we've got on the table here, and I think it's a pretty good deal, and I hope your guys take us up on it. >> All right, great. Get Oculus Rift for optimizing one of your apps and 15 months for the price of 12. Patrick, thank you for coming on and sharing the future of AIOps with you guys. Great product, bridge to the future, solving a lot of problems. A lot of use cases there. Congratulations on your success. Thanks for coming on. >> Thank you so much. This has been excellent, and I really appreciate it. >> Hey, thanks for sharing. I'm John Furrier, your host with theCUBE. Thanks for watching. (upbeat music)

>>mhm >>Welcome to this cube conversation here in Palo alto California. I'm john Kerry host of the cube. We've got a great awesome conversation with the Ceo and co founder of harness a hot startup jodi Benson who is the co founder and Ceo but also the co founder of unusual ventures which is a really awesome venture capital firm, doing some great work investment but also they have great content over there for entrepreneurs and for people in the community And of course he's also the founder of big labs, his playground. If you're building out new applications also well known for being the founder of Ap dynamics of super successful billion dollar exit as a startup, Salto, Cisco now doing a lot of things and driving harness, solving big problems. So joe t mouthful intro there, you've done a lot. Congratulations on your an amazing entrepreneur career and now your next uh next next opportunities harness among other things. So congratulations. Thank you for coming. >>Thank you john and glad to be here. >>You guys are solving a big problem in software delivery. Obviously software changing the world. You're seeing open source projects increasing in order of magnitude enterprises jumping on open source in general adoption, large scale with cloud software is being delivered faster than ever before and with cloud scale and now edge this huge challenges around how software deployed, managed maintained. You got, we're talking about space to how do you do break fix in space, all these things are happening at a massive scale across the world. You are solving a big problem. So take a minute to explain what harnesses doing, why you guys exist, why you jumping in into this venture. >>Sure. Yeah. You know what harness mission is to simplify supper delivery and make it uh top notch for everyone. Like if you look at like you know the likes of google and facebook and netflix and amazon these companies are mastered the process of software delivery like and your engineers write code and the code is shipped to the end users and they can do it like multiple times a day at their scale and you know at the complexity that they have but most other business in the world they all want to be software companies but it's extremely, extremely hard for them to get there and I saw this firsthand when I was at epidemics as you know as Ceo last there we're about 12 1300 employees in the company and we had about about 3 50 or so engineers in the company For every 10 or 12 engineers, we had one person whose job was to write automation and scripting and tooling for trying to ships off you know uh you know all kind of scripting kind of stuff. We'll write scripts and chef and puppet and sensible and to deploy in aws and whatnot. And you know one day we're doing the math were like you know we have you know about overall about 30 people whose job was to do devops engineering by writing automation etc to deploy somewhere and I would do the math like you know, one engineer cost is 200 k loaded cost at six million a year that you're spending six million a year just writing deployment, scripting, you know, and even with that we were nowhere close to world class like world class is in like what you would think you could ship every day, we chip on demand, you could, you know, you could deploy software, ship software all of that right? And that was the, you know, I looked at that as a problem inside of dynamics and all they have done with customers, I would talk to like large banks, insurance companies and retailers and telcos and I would hear the same challenge like you know, we hear about devops, we go to the all these devops conferences and events and we see the same 10 companies, you know presenting how the home grew some kind of a devops system for software delivery etc. And you know, I mean that was like, you know, we just, we cannot survive with this like and as the world we need to have uh the right kind of platforms for software delivery and simplify this so that everyone could become as good as a google netflix amazon etcetera that stand of our mission at harness that can we take every business in the world, you know and in a few weeks or a few months, can we get them as sophisticated and good in terms of their dueling for software delivery as a google facebook amazon, those kind of companies would be and that's, that's what we're doing. So >>It's a great ambition and by the way it's a bold move and it's needed. I'll tell you, it's interesting. You mentioned some of those commentary about shipping code at that speed Facebook Google. They had that they had they were forced to do that and again they have all that benefit the mainstream enterprise doesn't. But if you even go back 20 years ago, 15 years ago, that's when Amazon was born. You see two and S three is celebrating their 15th birthday. Software. Yeah, hyper scale has had some good moves there. But the average business went from craft, you know, waterfall QA department go back a little bit slower. I won't say slow motion but manageable now with the speed of shipping and the speed of the scale, that's a huge issue. What kind of pressure do you see that putting on the developer, the individual, not just the system because you got the system of development and the devil and the developers themselves. >>I think the developers have have done quite well to this. I feel like, you know, if you look at the software development part of itself, you know the agile development has been happening for quite some time. So developers have learned how to ship things fast and like in a week sprint or a two week sprint or in in kind of faster cycles. They have moved off from the waterfall kind of models like many years ago now. So that's the suffering development side of things then you have the infrastructure side of things which is the like any province in infrastructure fast. Can you get hardware fast? That's the, you know, the cloud has done that well where the challenges the process, the developers are writing code fast enough these days and you have the, you know, the infrastructure itself could be prov isn't and maintained and and and change fast enough but how do you bring it all together and there is the entire process around it. That's not moving fast enough. So that's where the bottom language. So I feel the, you know, and the process is not good. The developer experience becomes really bad bad because developers are waiting for the process to go and you know, they write some code and the code is sitting on the shelf and they are waiting for things. >>Uh they get all pissed off and mad. What's the holdup? Why what's the process? And then security shifting left, wait a minute to go back and rewrite code. This is huge. I want to just get back and just nail it quickly if you don't mind honing in on the value proposition. What is the harness value proposition? What is the pitch, what are you, what are you offering? What are you solving? Can you nail in on that real quick? >>Sure. So what harness is swallowing is simplifying that software delivery by plane, so developer writes code and that code goes goes through a bunch of steps so a bunch of steps which is uh you know you build the code then you you know test the code, you know, then you do integration tests, then you you know go through your security checks, then you go through a compliance checks, then you go through more dusting, then you're deploying a staging environment, then you go one to do a bunch of things on it. Then you start deploying in production environment but in production you will deploy on like a small part of production, verify everything is working well, it's not working well, you'll roll it back, it's working well then you deploy two more things. This entire process could take like weeks for people to do and this is mostly automated, you know in kind of uh uh you know this kind of random scripts here and there etcetera. So we simplify the entire process that you could describe your process in the language, I just described like you know in a very descriptive declarative kind of way like this is the process I want to achieve and hardness will automatically create your pipelines for this. This kind of process and most of these pipelines have a lot of heavy use of intelligence and um L two, it could go from one step to another, like, so many times, like when you say, you know, deploy the guard and and and 1% of my production environment and see everything is working well and if everything is working well, go to the next 10%. But how do you figure out if everything is working well and that's where the intelligence and um El comes in like, you know, what we learn, what is a normal behavior of your application, how does a normal part of the code works like, you know, there, what's the performance behavior, what is a functional behavior? What errors it is? And if everything is good then you go to the next step so that entire cycle harness automatically, uh you know, uh managers and its automated, you know, if you get governance, you get like, you know, high degree of automation, you get a high degree of, you know, security, you get high degree of like, you know, uh uh you know, quality around him. And so it's it's think of like the, the Ci cd has a lot of developers know and know this process is is ci cd on steroids available to you, Right? So you >>sound like you're making it easier on the Ci cd pipeline process, standing it up, detecting it, prototyping it, if you will, for lack of a better description, get get used to the pipeline and then move it out, roll it out and build your own in a way >>that, is that what is that what you're doing? It's like, you know, a lot of these complex ci city pipelines, what people need, you know, it can take them like three months, six months to to put it uh you know, put it together the harness, it's like an hour, an hour, you could put it together, you know, very, very sophisticated uh Ci cd pipeline and the pipeline is, you know, automated is is, you know, it's it's intelligent around like, you know, what is the normal behavior of your of your applications? Uh It's it's just so phenomenally different than how people have done ci cd before that we simplify the process. Automate the process, you know, and make it manageable and very ready to get involved. >>It's funny you mentioned the three weeks weeks it could take to do the csd pipeline. Of course, that doesn't factor in the what happens when you roll it out, people start complaining, playing with it, breaking it, then you gotta go back and do it again. I mean, that's real and that's a real problem, I mean, can you just going to give a taste of the scar tissue that goes on there. What's some of the what are some of the what some of the pain points that you solve? >>Yeah. So, I think the that is that really becomes the core of the pain point, like, you know, people need, like high amount of dependability, easy to change things, you know, it's we call it like the lack of intelligent automation, you know, and the and this heavy amount of developer toil that the developers have to do so much work around around making all of this work like you know it has to be simplified. So that's that's where our value product comes in like you know, it's it's you know uh you can get like a visual builder and like minutes you can build out the entire process which is your job stability at city pipeline or you could also do like a declarative Yamil interface and just like you know in a few lines just right up whatever process you would want and we would review should be shipped with all kind of integrations with every cloud environment, every monitoring system, every system, every kind of testing process, every kind of security scanning so you can just drag and drop and in minutes eur, europe and running, it just creates so much velocity in this entire process. And also this manageability that people have struggled with >>morale to I mean you can imagine the morale developers go up significantly when you start seeing that the developer productivity has always been a big thing but this intelligent automation conversations huge. Some people have it, some people don't, people say they have it, what is how can you, how can the company figure out uh if someone's really got the real deal when it comes to intelligent automation because again, automation is the is key into devops. >>Yeah, I think I I almost started like you know like if you look at the generational evolution of things like the the first generation was uh you know developer writes code and then it will give you will give it to some some mighty at men who will go and deploy the code, run some commands and do things like tradition to was writing scripts that you're right, a lot of scripts that was automation but it was kind of dumb our dimension and that's how we have, you know that that's where the industry is so actually break now even most of it, the third generation is when the automation is you don't write scripts to you know uh to automate things, you tell our system what you want to achieve and it generates automation for you, right? And that's what we call intelligent automation. Where it's all declarative and all the you don't have to maintain a lot of you know scripts etcetera because they are, you know, they can't keep up with it. You know, you have to change the process all the time and if you change the process, it doesn't work, it becomes completely, you know, uh you know, it becomes very fragile to manage it. So that's that's really where intelligent automation comes in, you know, I look at like, you know, if you can have like uh like you look at like a wrestler, you know, making cars the entire assembly line is automated, but it's, but it's if you want to change something in the assembly line, even that process is automated and it's very simple. Right? So it's and that's what gives them so much uh you know, uh you know, uh let's say control and manageability around the manufacturing process. So the software delivery, uh you know, by assembly line, which is the software software by ci cd piper and really should be a more sophisticated and more intelligent as well now. And that's that's an exhibition, >>jodi. You're also pointing out something that we cover a lot on the cube and we've been writing about is how modern software practices are changing, where this team makeup or whatever its speed is key, but also getting data. Everyone who's successful with cloud and cloud scale and now you got the edge opening up and like I said, even space is going to be programmable, Everything's programmable. And the key is to get the data from the use cases right, get something deployed, look at it, get some data and then double down and make it better. That's a modern approach, not build it and then rebuild it and tear it down and rebuild it, which you're kind of leaning into this idea of let's get some delivery going, let's structure it and then feed it more so that the developers can iterate with with, with the pipeline and this is this again, can scale, can you talk about that? Can you comment on your reaction to that? >>Yeah, definitely. That's exactly how we look at it. Like, you know, you uh you want developers to kind of like say they want to do a, you know, automated process to deploy in their communities infrastructure in matter of minutes, you should be able to get started, but now it's like, you know, there's so much data that comes into it. Like, you know that you have monitoring systems systems like ab dynamics and you're like and data dog and you're logging systems your Splunk and elastic and you know, some logic, you have your, you know, different kind of testing systems here, your security scanning, so there's so much data in it. They're like, you know, terabytes and terabytes of data from it. So when you start doing your deployments, we could also come seem all of the data and see like what was the impact of those deployments or court changes in each of these monitoring, dusting, logging gonna systems and you know, what, how the data changes and then now is that based on that we can learn like, you know, what should be your ideal process and what will break in your process and that's that's the how harness platform works. That's the core of that intelligent automation networks, they're expanding it now to bring a few more of the devops use cases into it Also like the one is cloud cost management because when you, when you, you know, uh you know when we started shipping, there's a lot of people would tell us like, you know, you're you're doing a great job helping us managing the quality, which we always were concerned about like when we're deploying things so you know, security, you know, functionality etcetera. But cloud cost is a big challenge as well. You have your paying like tens and tens of millions of dollars to the cloud providers. And when developers do things in an automated way, it could increase without cost suddenly and we don't know what to do how to manage that. So that's the, you know, we we introduced a new model called cloud cost management to as part of the develops software delivery process that every time you're shipping code and we also figure out like, you know, what with impact on on your on your podcast, you know, can we automate the, you know, uh if there is there is too much impact, can we automate the, you know, the roll back around it, you know, can you get and you can you can we stop the delivery process at that point, can we help you troubleshoot and, you know, reduce the cost down? So that's, you know, that's cost becomes another another another dimension to it. Uh you know, then we recently just added uh you know, the next level that's managing feature Flags. And a lot of the time software developers are adding feature flags to like this feature would be given to this consumer and like, you know, and this feature will be given to this consumer until you test it out through uh test kind of thing and like, you know, what is the impact of, you know, uh turning a feature on versus off, you know, we're bringing that into the same ci cd pipeline. So it's kind of an integrated approach to this uh you know, our intelligently automated biplane instead of these uh small point approaches that just very hard to manage. >>I mean the level of data involved the creature flag for instance, the great is an amazing thing because that allows you to do things that used to be extremely difficult to provision. I mean just picking the color of icon, for instance, this kind of blue, I mean I was just, you hear about this, these kinds of things happening at scale and the date is pretty accurate when it comes in. So I think that's an example of the kind of speed and agility that developers want and the question I want to ask you though on that point because this opens up the whole next conversation, you guys have a modern approach and so much traction and you've recently raised big rounds of funding as you go to the market place, your experienced entrepreneur and uh and Ceo you've seen the waves before. What's the big wave that you're on now? What's the big momentum tailwind for harness? Is it the fact that you're creating value for developers or is it the system that you're integrating into with the intelligence to make things smarter and more scalable? What's the or is it all the above? Can you just share what that that story is? >>Yeah, I think it's, it's, it's really, really both of them. But you know, what are our business case when you go to people who tell them like say, if you're you know, 200 developers. uh, you know, we can give you the world's best software delivery tooling at the cost of half to one developer. Right? So like, you know, so which is like 44, 200 person organization at like 200 to 200 to $300,000 a year. They will get the best software delivery tooling better than a Google Facebook Amazon kind of companies very, very quickly. So our, our entire value prop is built on that like a developer experience gets much better. The productivity gets much better. Developers on an average are spending like 20-30% of the time on deployment, delivery-related toil, like unnecessary stuff that we deal with. So it's only 30% more efficiency gain for the developers. Their quality of life gets better that they don't need to worry about like weekends and nights to babysit your deployments and you know, things breaking and troubleshooting things all the time. Right? So that's that's a that's a big big value. But as a business you get much more velocity your innovation velocity is much higher. You know your risk on your, you know your consumers is much lower because your quality of the of of you know how your ship becomes becomes better. So our business case of like you know at the past of like 1-2 develops engineers will get you the best develops uh you know tooling in the world possible. You know it's not a hard business case for us to make, right? That's that's what we we we look at, it becomes pretty pretty obvious for you know as people try our product, you know the business case >>you don't have to really pass the I. Q. Test to figure this one out, okay everyone's happier and you have more options to scale and make more money in new opportunities not just existing business. I mean the feature flagging these new features you can build a new value and take more territory if you're a business or whatever your objective is so clear value. Can you give an example of some recent successes you've had or or traction points that you think is worth notable that people can get their arms around. >>Yeah definitely like you know we are we're helping a lot of uh you know a lot of customers you know doing uh like completely changing their uh their uh their process of software delivery, you know, 11 recent example, uh nationwide insurance, you know, nationwide insurance, you know, moving from their data center kind of approach to public cloud and to communities and to microservices, like a major cloud native re architecture and in a very ambitious aggressive project to do it, you know, in a in a in a short period of time and harness becomes a platform for them to kind of, you know, uh to remove all the bottom leg around the process, the software delivery process. You know, they obviously they still have to do the developer side of things and they have to do the cloud infrastructure side of things, which is they're doing. But the entire process of how you bring together, you know, harness becomes accelerated around it. So a lot of these kind of stories that we when we kind of create this fundamental transformation for our for our for our customers, you know, uh you know, moving to to a public cloud, you know, moving to microservices, moving to communities, you know, re architect things, but they become much faster. Cloud native higher, you know, a true software company and you know, I would say that's that's something we we we we take a they can take a lot of pride in, I think are always our biggest challenge is uh is to is to is to evangelize and and convince the market that this is possible to do with the product, because historically people have got told like, you know, the only way you can do this kind of software delivery processes and tooling is by engineering it on your own. So everyone wants us on the path of writing their own, you know, and and it's very hard for every, every company in the world to become very good in writing your own software delivery, tooling and processes and systems, etcetera. Right? So it's uh and that's it. So, you know, there is still that that education and evangelism needs to be done, that, you know, there is uh there is no point, you're trying to do it on your own, you can get a platform that can do it all for you and you can focus on the your core business of, you know, what you want to innovate on. >>And I think the Devil's movement hasn't been pioneered and you have to hand roll everything and that's the way it was. But now, as the mainstream market picks this up, you're standing on the shoulders of those pioneers, you are one of them. It's awesome to see this modern approach because it's really playing out in real time again, you've done that before, joe t so it's impressive and, you know, you've seen the movie and developed and the earlier versions pre devops. So, so as cloud native comes and start scaling it's going to be for the rest of us. So, great, great that you're providing the platform and the tools and software. I got to ask you if you don't mind because a lot of people are looking at ways for modern approaches to organizing their teams, how would you define the modern devops movement? You look at devops one point. Oh, we got here. Okay, cloud, cloud native, cloud scale, modern applications, pipe lining. Now, we're looking at a whole another level of confluence of uh of integration and speed. How would you define the modern devops movement? >>Yeah, I think that's a that's a very good question. I think that the core of modern devops, what I would call it develops to point to me is developers self service. It was like the first generation of develops was they create this kind of a devoPS team and then the developers will give all the, you know, delivery related stuff that develops team and the devops team starts to become a bottle, like everywhere now, like in the developed steam job is to build a ci pipeline and the city pipeline and the deployment scripts and you know, do like, you know, you want to do a canary deployment, they have to figure it out how to do it, they have to do, like, you know, you are uh you know, all sort of things that the that needs to be done, you create a central develops team and you give it to them and they become like, you know, uh become a big bottleneck, we look at the modern develops or the next generation and develops has to be done around focusing on the developer experience that and making it all self service for the developers. So you have, you have, let's say you are definitely in for a micro service and it's like, you know 57 engineers, you know, modeling a micro service you want like that, they can go and say this is for our micro service, you know, in a matter of minutes or hours, they can engineer the process without having to lean on a central deVOPS team and to do all the work for them and that's you know, by by maybe a modeler or in some kind of mammal interface or something. That's very easy for them, their experience is so easy that they can manage it themselves without the central deVOPS team have to write it all or cut it all and manage it all. But at the same time the center deVOPS teams, job becomes a bar and governance that can they define the guardrails, that they can define the guardrails on like, you know, you have to have this level of security before something goes into production, you have to have this level of quality before something goes into production, you have to have like, you know, uh this, your cost could not be more than this, right? So you define, so in this instance, instead of the center develops team is doing all the work themselves on writing all the stuff they define the guard rails and it becomes a very easy cell service experience of the developers should do things within those, those guard rails. This is what the modern never actually, >>that's awesome and also accelerate more business value And you're nailing it joe t thank you for coming on and great. Uh, the Ceo on the cube ceo and co founder harness harness dot IO. You guys got free trials, free downloads. You got a great, uh, by as you go model also. Um, you're an entrepreneur at heart. Uh, co founder of unusual ventures, Big Labs appdynamics. Now harness. Congratulations. Thanks for coming on. >>Hey, thank you john. >>Okay, this is a cube conversation. I'm john for here in Palo alto California with the cube. Thanks for watching.