>>Hey, everyone, welcome back to the cubes on the ground. Coverage of Pedro Duty Summit 22. I'm your host, Lisa Martin. I'm very excited to be joined by Manjula Toleration, the S VP and chief customer officer at page duty. Welcome to the programme. >>Thank you, Lisa. It's great to have chatted with you this morning as well, >>isn't it? I have had the great fortune of watching her fireside chat. That Mandela did, um, with is the logic monitor that was >>she of logic. >>And I thought, She's got great energy. We're gonna have a great conversation. So let's talk about the customer experience these days. One of the things I think that's been very, very short supply in the pandemic is patience. I know it's been in short supply with me and, of course, in our consumer lives in our business lives. The customer experience, though, has been something that every company needs to really pin their businesses on. Because if it's not a good customer experience, that customer goes right to social media. They churn. They leave, but they take others down with them. Talk to me about how the customer experience fits into this year's summit. Especially for this, we have to be ready for everything in a digital world environment. >>I love this question, and I reason I love this question is I even look at my own behaviour. But before we get into that, let's talk about data. I'm just reading an article. Mackenzie did a survey. Did you know that from pre covid to today customer interactions that have moved to digital are from 41% to 65%? That's exponential. That's huge. And guess what? We've all got impatient. You become like our kids, and I think about myself as an individual. If I need tied right now to do my laundry, I need it right now. So if I go to Costco website to order it so that it can get delivered in the next hour, and even if there's a second glitch on it, I'll swap over to Amazon and I'll swap over to target. That's what's happening in real world, whether it be to see or it's b to B, and why is it important to the points we are making in terms of ready for anything in the world of digital everything. It's important because customers are impatient. It's a digital world. I don't walk into the store to do any interactions anymore. And the reality of all of this is it's grounded on trust. Customers have to trust you and the window of choice not only in the B two b, but a lot in the enterprise and the B to B world. It's about trust, right? And what does pager duty do? Pager duty is at the heart of this pager. Duty is at the heart of making every second matter, and every second is equal to money. Absolutely. And it's about customer experience. And it isn't about just the experience where of an employee who may not sleep at night because they got a disruption due to an incident which is also super important during the mass resignation. But it is also about the CEO agenda and the boardroom, because how our CEO s driving customer trust in order to keep customers and drive this new era of digital everything as digital transformation is occurring. Well, >>I know patriarchy was doing that. I had the chance to watch um, CEO Jennifer to, uh, fireside chat, her keynote, and then her fireside chat with the CEO of Doc, You Sign And you. The Storey was very bidirectional, very symbiotic in terms of the trust that he has in Houston and Austin has and Pedro duty. But talk to me as the chief customer officer. What is it that's unique about how patriarchy works with its customers? 21,000 plus now to build and maintain that trust, especially in such volatile times? >>You know what is really cool? I joined page duty a little less than two years ago. In the next few days, it'll be two years now. What do I find exciting as a chief customer officer and the go to market teams differentiation versus other customers? We had a born SAS company and what do we have access to form our customers? We have access to their operations data and that combination of our core values that is championing the customer and the data science that we have about how customers are using our data is a differentiation. That's the magic. So if you think about why pager duty is bringing this level of trust to the customers, it's because we know how many and let's take an example. Employee retention, mass resignation. We know which employee was called. How many times at night during an outage. Can we give that guidance to managers and leaders in order to drive that trust? Absolutely. And on the other hand, we are driving amazing return on investment at the executive levels for the customer experience that they are driving. So Peter Duty is becoming the trusted advisor all the way from practitioners, where we are improving their work life balance to the executive levels, >>improving work. Life balance is so critical. There was a stat that Sean Scott shared this morning that that was looking at the amount of work volume from 2020 compared to 2021 42% of people said, I am working more hours. I don't think I've ever heard anyone say, Can I work more? Please? No. That work life balance is critical, but also the ability to deliver that seamless digital customer experience that we all expect, Um, and and to get it right the first time is critical. But using that customer data as you're saying, empowering the organisations, not just the customer support folks or the SRS or the develops folks but all the way up to the C suite to ensure that their brand reputation is valuable, it's maintained, and that trust is really bidirectional. That's the secret sauce. >>You're absolutely right. You know, there's a different dimension to this as well. We think about how we're using customer data in order to achieve the results. We want three vectors here. Number one is we'll use customer data to really understand what is best in class on up time. What is the best in class to reduce noise during alert, what is best in best in class for customer service operations? And because we have customer data, we can benchmark we can benchmark. What industry? What's happening in the financial services industry? What's happening in the technology industry? What's happening in the retail industry. Our customers love that, so we will share with them. The customer success organisation, especially the customer success managers, will go in and meet with the customers and say This is where you stand in reference to your peers and customers love here about that. This is the differentiated value proposition, right? The second thing that our customer success managers do is share with the customers This is where you are in reference to your peers in your vertical other vertical. But let me tell you how you can improve your deployment, the performance of our technology and you're all operating model. As a result of the data we've got, >>there's the proactive nous. That's another differentiator of of what I was hearing today from pager duty. That you're enabling those CSM is to be proactive when so often many are reactive, and it's the customer that's found the problem first. >>Yes, I'll even talk more about the reactive to proactive. We build a methodology, and I'm sure Shaun Scott covered it as well, which is a maturity curve moving from reactive to proactive because so many of our customers are saying we are reacting when we have a disruption on our digital platform, but 30% of the times we are hearing from customers before we are hearing from ourselves. So how do we become proactive? And how does that data signs actually start showing the signs when a potential disruption could occur? And that is about moving reactive to overall proactive. I'd also like to add one more dimension to this, you know, when customers are doing really well. They're optimised on our platform. They don't want to hear from our post sales organisation all the time. They want a human touch when they need it. They want a digital touch when they need it. By using our data and our data science, we are becoming one of the best world class customer success organisations in the world and you ask why? The reason is because we are using data science in order to build and we have built the early warning system. The early warning system tells us how every single of our customers is doing in terms of both their growth as well as the risk that they may leave us. So if a customer is very healthy on a scale of 1 200 if we have a healthy customer, we will engage with them potentially just digitally and engage with them with our services are customer success team and our entire post sales organisation, when there is an optimisation and when they really need us. So data scientists being used not only in terms of giving customer the right information to grow them, but how we interact with them as well, >>that's brilliant. And there's so many organisations that I talked to across industries that cannot get that right. >>And >>so customers are being contacted too frequently. They may have said. I opted out, I don't want and then suddenly that that the first responders, the incident responders, is marketing. But that happens so frequently, you think. But there's an opportunity there. It's not rocket science, but it's about leveraging that data in an optimal, smart way. But you guys are light years ahead of a lot of other companies that haven't figured that >>out. No, we are leading edge and we are leading edge because we had a born SAS company and we've got effective operations data of the customer, and we have some of the best data scientists and the analysts within my organisation. Looking at this, engaging with the customer and only optimising the magic is data science and humans coming together to engage with customers and drive customer success for the customer and ultimately building their customer experience for their customers. >>Let's talk about some of the numbers Mandela, because they are really impressive. I was looking at some stats. You're paid your duties renewal rates are over 95%. Your growth is incredible, just coming off the biggest quarter ever, but also the gross annual benefit from customers. Talk to me about that alone. That can be up to $10 million. These read these tangible business outcomes that pager duty is delivering to customers are significant, >>and again, it's based on data science. This is not making you know what traditional companies do. Traditional companies will go to the customer and say, Tell me your business imperatives. Tell me your what are the business problems you're solving are because we have the data science. We have our oi arranging from 309 100% very impressive within a couple of months. We think about it if we are able to drive incidents that are very, very significant. And I know you've got the numbers in terms of growing our reducing the workload on very expensive engineering. Uh, individuals within the organisation from, I believe, 3200 and 25,000, and I know you have those numbers think about If 30% of your organisation focuses just on innovation and product development, worse is on an incident, and they work, life balance, the quality of life increases, the retention of the employees, and yet the company's only driving their growth. That is why our customers love us. That is why our renewal rates are greater than 95%. That's why a net retention scores are greater than 100 and 2020% over five quarters. And that is why we have more than 30% growth year over year, quarter over quarter. >>When I saw that stat Manville about you know, the number of incidents reduced, >>that >>translates to employee productivity and and looking at it in terms of FTE. From a quantity perspective, that's the first time I've seen a company and I interview a lot of companies actually put it in that perspective, and I thought, That is huge. That's how organisations should be talking about that rather than reducing feeds are going. We are victims of the great resignation is look at the impact that can be made here by using data science by using the right mix of human and automation together. It's that's the first time. So congratulations to you and Pedro duty for the first time I've seen that and I think everybody needs to be working to be able to explain it that way, especially the fact that we're still in a volatile environment. >>Absolutely. It's about customer experience, but it is just as much employee experience. There is so much that the industry is talking about. That's top of mind for board levels. That's top of mind from CEO S. How do I retain my employees and drive greater operational efficiency? And now, with the macro economic challenges that are occurring in terms of inflation and in and the cost to serve and increasing the profits are customers are making. Operational efficiency is becoming even more important so that the employees are focusing more on innovation rather than downtime or disruptions. And it's actually about growing the business rather than just running the business. And if we can optimise running the business growth is what our customers are looking >>for, right? I always think, and we're almost out of time here. But I always think the employee experience and the customer experience are like this, and they should be. But it's critical to optimise both. How do you when you talk to some of those big and our price customers. We have Doc Watson on the main stage this morning, but I was looking at the website and three that jumped out to me that I use peloton, salesforce and slack. How do you advise them? You have this wealthiest gold of information on customers. This is how you need to leverage it in the right way to grow your business. What are some of the top three things you recommend those customers do, for example, >>that so let me talk about a couple of customers as an example. There are some customers of ours in the retail business, or it is a telecommunication company that is trying to increase their, um, up time from 98.7% to 3 nines as an example, or a tech company that doesn't even know that they were down for six hours in one small part of their business. And we're trying to figure out how do we solve for that as customers are overall complaining. So for us as a organisation, the magic is again bringing data together employee engagement, and what we do is we use the data to engage with their customers to ultimately understand what is their business value proposition. If you don't do it in isolation, you do it in. What is the customer trying to achieve? Are they trying to achieve the best in class website? Are they trying to achieve increased operational efficiency? What are their metrics? What are their numbers? And we take our data, our people, to marry all of that together. And that's the magic. >>I love it. I wish we had more time. Angela. We are out of time but talking about the value of the customer experience, the impact that is possible to be made leveraging technologies like pager duty. It's It's revolutionising operations. It's revolutionising customers 21,000 plus one million plus users at a time. It's awesome. You have to come back so we can talk more because I can. No, we're just scratching the surface here. >>Yes, we are. This is a very, very exciting area right now, and it is a great opportunities for chief customer officers on really rallying the whole company on championing the customers because whether it's a product, our capabilities, it's really a major transformation happening in the in the industry, and we need to stay very close to it? >>Absolutely. Thank you so much for joining me today. It's been such a pleasure talking to you. I look forward to seeing you again. >>Real pleasure, Lisa, To get to know you. And the gun was she was awesome. >>Good. Thank you for Manjula. Televisa. I'm Lisa Martin. You're watching the cubes on the ground. Coverage of pager duty. Summit 22 from San Francisco. Thanks for watching. And bye for now. Mm mm. Mm mm.

>>Hello, everyone. Welcome to this cube conversation. I'm here in Palo Alto, California. I'm John furrier, host of the cube, and we have a great guest here. Barack Shuster. Who's in Tel-Aviv senior director of chief architect at bridge crew, a part of Palo Alto networks. He was formerly the co-founder of the company, then sold to Palo Alto networks Brock. Thanks for coming on this cube conversation. >>Thanks John. Great to be here. >>So one of the things I love about open source, and you're seeing a lot more of the trend now that talking about, you know, people doing incubators all over the world, having open source and having a builder, people who are starting companies, it's coming more and more, you you're one of them. And you've been part of this security open source cloud infrastructure infrastructure as code going back a while, and you guys had a lot of success. Now, open source infrastructure as code has moved up to the stack, certainly lot going down at the network layer, but developers just want to build security from day one, right? They don't want to have to get into the, the, the waiting game of slowing down their pipelining of code in the CIC D they want to move faster. And this has been one of the core conversations this year is how to make developers more productive and not just a cliche, but actually more productive and not have to wait to implement cloud native. Right. So you're in the middle of it. And you've got you're in, tell us, tell us what you guys are dealing with that, >>Right? Yeah. So I hear these needles working fast, having a large velocity of releases from many of my friends, the SRAs, the DevOps, and the security practitioners in different companies. And the thing that we asked ourselves three years ago was how can we simplify the process and make the security teams an enabler instead of a gatekeeper that blocks the releases? And the thing that we've done, then we understood that we should do is not only doing runtime scanning of the cloud infrastructure and the cloud native clusters, but also shift left the findings and fixings the remediation of security issues to the level of the code. So we started doing infrastructure is good. We Terraform Kubernetes manifests cloud formation, server less, and the list goes on and we created an open source product around it, named checkup, which has an amazing community of hundreds of contributors. Not all of them are Palo Alto employees. Most of them are community users from various companies. And we tried to and succeeded to the democratic side is the creation of policy as code the ability to inspect your infrastructure as code and tell you, Hey, this is the best practice that you should use consider using it before applying a misconfigured S3 bucket into production, or before applying a misconfigured Kubernetes cluster into your production or dev environment. And the goal, >>The goal, >>The goal is to do that from the ID from the moment that you write code and also to inspect your configuration in CGI and CD and in runtime. And also understand that if there is any drift out there and the ability to fix that in the source code, in the blueprint itself. >>So what I hear you saying is really two problems you're solving. One is the organizational policies around how things were done in a environment before all the old way. You know, the security teams do a review, you send a ticket, things are waiting, stop, wait, hurry up and wait kind of thing. And then there's the technical piece of it, right? Is that there's two pieces to that. >>Yeah, I think that one thing is the change of the methodologies. We understood that we should just work differently than what we used to do. Tickets are slow. They have priorities. You have a bottleneck, which is a small team of security practitioners. And honestly, a lot of the work is repetitive and can be democratized into the engineering teams. They should be able to understand, Hey, I wrote the code piece that provision this instance, I am the most suitable person as a developer to fix that piece of code and reapply it to the runtime environment. >>And then it also sets the table for our automation. It sets the table for policies, things that make things more efficient scaling. Cause you mentioned SRS are a big part of this to dev ops and SRE. Those, those folks are, are trying to move as fast as possible at scale, huge scale challenge. How does that impact the scale piece become into here? >>So both themes Esri's and security teams are about a link to deploying application, but new application releases into the production environment. And the thing that you can do is you can inspect all kinds of best practices, not only security, best practices, but also make sure that you have provision concurrencies on your serverless functions or the amount of auto-scaling groups is what you expect it to be. And you can scan all of those things in the level of your code before applying it to production. >>That's awesome. So good, good benefits scales a security team. It sounds like too as well. You could get that policy out there. So great stuff. I want to really quickly ask you about the event. You're hosting code two cloud summit. What are we going to see there? I'm going to host a panel. Of course, I'm looking forward to that as well. You get a lot of experts coming in there. Why are you having this event and what topics will be covered? >>So we wanted to talk on all of the shifts, left movement and all of the changes that have happened in the cloud security market since inception till today. And we brought in great people and great practitioners from both the dev ops side, the chaos engineering and the security practitioners, and everybody are having their opinion on what's the current status state, how things should be implemented in a mature environment and what the future might hold for the code and cloud security markets. The thing that we're going to focus on is all of the supply chain from securing the CCD itself, making sure your actions are not vulnerable to a shut injection or making sure your version control system are configured correctly with single sign-on MFA and having branch protection rules, but also open source security like SCA software composition analysis infrastructure as code security. Obviously Ron thinks security drifts and Kubernetes security. So we're going to talk on all of those different aspects and how each and every team is mitigating. The different risks that come with. >>You know, one of the things that you bring up when you hear you talking is that's the range of, of infrastructure as code. How has infrastructure as code changed? Cause you're, you know, there's dev ops and SRS now application developers, you still have to have programmable infrastructure. I mean, if infrastructure code is real realize up and down the stack, all aspects need to be programmable, which means you got to have the data, you got to have the ability to automate. How would you summarize kind of the state of infrastructure as code? >>So a few years ago, we started with physical servers where you carried the infrastructure on our back. I, I mounted them on the rack myself a few years ago and connected all of the different cables then came the revolution of BMS. We didn't do that anymore. We had one beefy appliance and we had 60 virtual servers running on one appliance. So we didn't have to carry new servers every time into the data center then came the cloud and made everything API first. And they bill and enabled us to write the best scripts to provision those resources. But it was not enough because he wanted to have a reproducible environment. The is written either in declarative language like Terraform or CloudFormation or imperative like CDK or polluted, but having a consistent way to deploy your application to multiple environments. And the stage after that is having some kind of a service catalog that will allow application developer to get the new releases up and running. >>And the way that it has evolved mass adoption of infrastructure as code is already happening. But that introduces the ability for velocity in deployment, but also new kinds of risks that we haven't thought about before as security practitioners, for example, you should vet all of the open source Terraform modules that you're using because you might have a leakage. Our form has a lot of access to secrets in your environment. And the state really contains sensitive objects like passwords. The other thing that has changed is we today we rely a lot on cloud infrastructure and on the past year we've seen the law for shell attack, for example, and also cloud providers have disclosed that they were vulnerable to log for shell attack. So we understand today that when we talk about cloud security, it's not only about the infrastructure itself, but it's also about is the infrastructure that we're using is using an open source package that is vulnerable. Are we using an open source package that is vulnerable, is our development pipeline is configured and the list goes on. So it's really a new approach of analyzing the entire software bill of material also called Asbell and understanding the different risks there. >>You know, I think this is a really great point and great insight because new opera, new solutions for new problems are new opportunities, right? So open source growth has been phenomenal. And you mentioned some of those Terraform and one of the projects and you started one checkoff, they're all good, but there's some holes in there and it's open source, it's free, everyone's building on it. So, you know, you have, and that's what it's for. And I think now is open source goes to the next level again, another generational inflection point it's it's, there's more contributors there's companies are involved. People are using it more. It becomes a really strong integration opportunity. So, so it's all free and it's how you use it. So this is a new kind of extension of how open source is used. And if you can factor in some of the things like, like threat vectors, you have to know the code. >>So there's no way to know it all. So you guys are scanning it doing things, but it's also huge system. It's not just one piece of code. You talking about cloud is becoming an operating system. It's a distributed computing environment, so whole new area of problem space to solve. So I love that. Love that piece. Where are you guys at on this now? How do you feel in terms of where you are in the progress bar of the solution? Because the supply chain is usually a hardware concept. People can relate to, but when you bring in software, how you source software is like sourcing a chip or, or a piece of hardware, you got to watch where it came from and you gotta track track that. So, or scan it and validate it, right? So these are new, new things. Where are we with? >>So you're, you're you're right. We have a lot of moving parts. And really the supply chain terms of came from the automobile industry. You have a car, you have an engine engine might be created by a different vendor. You have the wheels, they might be created by a different vendor. So when you buy your next Chevy or Ford, you might have a wheels from continental or other than the first. And actually software is very similar. When we build software, we host it on a cloud provider like AWS, GCP, Azure, not on our own infrastructure anymore. And when we're building software, we're using open-source packages that are maintained in the other half of the war. And we don't always know in person, the people who've created that piece. And we do not have a vetting process, even a human vetting process on these, everything that we've created was really made by us or by a trusted source. >>And this is where we come in. We help you empower you, the engineer, we tools to analyze all of the dependency tree of your software, bill of materials. We will scan your infrastructure code, your application packages that you're using from package managers like NPM or PI. And we scan those open source dependencies. We would verify that your CIC is secure. Your version control system is secure. And the thing that we will always focus on is making a fixed accessible to you. So let's say that you're using a misconfigured backup. We have a bot that will fix the code for you. And let's say that you have a, a vulnerable open-source package and it was fixed in a later version. We will bump the version for you to make your code secure. And we will also have the same process on your run time environment. So we will understand that your environment is secure from code to cloud, or if there are any three out there that your engineering team should look at, >>That's a great service. And I think this is cutting edge from a technology perspective. What's what are some of the new cloud native technologies that you see in emerging fast, that's getting traction and ultimately having a product market fit in, in this area because I've seen Cooper. And you mentioned Kubernetes, that's one of the areas that have a lot more work to do or being worked on now that customers are paying attention to. >>Yeah, so definitely Kubernetes is, has started in growth companies and now it's existing every fortune 100 companies. So you can find anything, every large growler scale organization and also serverless functions are, are getting into a higher adoption rate. I think that the thing that we seeing the most massive adoption off is actually infrastructure as code during COVID. A lot of organization went through a digital transformation and in that process, they have started to work remotely and have agreed on migrating to a new infrastructure, not the data center, but the cloud provider. So at other teams that were not experienced with those clouds are now getting familiar with it and getting exposed to new capabilities. And with that also new risks. >>Well, great stuff. Great to chat with you. I want to ask you while you're here, you mentioned depth infrastructure as code for the folks that get it right. There's some significant benefits. We don't get it. Right. We know what that looks like. What are some of the benefits that can you share personally, or for the folks watching out there, if you get it for sure. Cause code, right? What does the future look like? What does success look like? What's that path look like when you get it right versus not doing it or getting it wrong? >>I think that every engineer dream is wanting to be impactful, to work fast and learn new things and not to get a PagerDuty on a Friday night. So if you get infrastructure ride, you have a process where everything is declarative and is peer reviewed both by you and automated frameworks like bridge and checkoff. And also you have the ability to understand that, Hey, once I re I read it once, and from that point forward, it's reproducible and it also have a status. So only changes will be applied and it will enable myself and my team to work faster and collaborate in a better way on the cloud infrastructure. Let's say that you'd done doing infrastructure as code. You have one resource change by one team member and another resource change by another team member. And the different dependencies between those resources are getting fragmented and broken. You cannot change your database without your application being aware of that. You cannot change your load Bonser without the obligation being aware of that. So infrastructure skullduggery enables you to do those changes in a, in a mature fashion that will foes Le less outages. >>Yeah. A lot of people getting PagerDuty's on Friday, Saturday, and Sunday, and on the old way, new way, new, you don't want to break up your Friday night after a nice dinner, either rock, do you know? Well, thanks for coming in all the way from Tel-Aviv really appreciate it. I wish you guys, everything the best over there in Delhi, we will see you at the event that's coming up. We're looking forward to the code to cloud summit and all the great insight you guys will have. Thanks for coming on and sharing the story. Looking forward to talking more with you Brock thanks for all the insight on security infrastructures code and all the cool things you're doing at bridge crew. >>Thank you, John. >>Okay. This is the cube conversation here at Palo Alto, California. I'm John furrier hosted the cube. Thanks for watching.

>>Welcome to the cube conversation here. I'm Sean ferry with the cube in Palo Alto, California. We've got two great guests here featuring armory who has with them Patrion open-source and talking open source and the enterprise. I'm your host, John ferry with the cube. Thanks for watching guys. Thanks for coming on. Really appreciate. I've got two great guests, Ben mapping, and SVP, a strategic partner in the armory and Ian Della horn, S staff SRE at Patrion gentlemen, you know, open source and enterprise is here and we wouldn't talk about thanks for coming. I appreciate it. >>Yeah. Thank you, John. Really happy to be here. Thank you to the Cuban and your whole crew. I'll start with a quick intro. My name is Ben Mappin, farmers founders, lead strategic partnerships. As John mentioned, you know, it all, it really starts with a premise that traditional businesses, such as hotels, banks, car manufacturers are now acting and behaving much more like software companies than they did in the past. And so if you believe that that's true. What does it mean? It means that these businesses need to get great at delivering their software and specifically to the cloud, like AWS. And that's exactly what armory aims to do for our customers. We're based on opensource Spinnaker, which is a continuous delivery platform. And, and I'm very happy that Ian from Patrion is here to talk about our journey together >>And introduce yourself what you do at Patriot and when Patrion does, and then why you guys together here? What's the, what's the story? >>Absolutely. Hi, John and Ben. Thanks for, thanks for having me. So I am Ian. I am a site reliability engineer at Patrion and Patrion is a membership platform for creators. And what we're our mission is to get creators paid, changing the way the art is valued so that creators can make money by having a membership relationship with, with fans. And we are, we're built on top of AWS and we are using Spinnaker with armory to deploy our applications that, you know, help, help creators get paid. Basically >>Talk about the original story of Ben. How are you guys together? What brought you together? Obviously patron is well-known in the creator circles. Congratulations, by the way, all your success. You've done a great service for the industry and have changed the game you were doing creators before it was fashionable. And also you got some cutting-edge decentralization business models as well. So again, we'll come back to that in a minute, but Ben, talk about how this all comes together. Yeah, >>Yeah. So Ian's got a great kind of origin story on our relationship together. I'll give him a lead in which is, you know, what we've learned over the years from our large customers is that in order to get great at deploying software, it really comes down to three things or at least three things. The first being velocity, you have to ship your software with velocity. So if you're deploying your software once a quarter or even once a year, that does no good to your customers or to your business, like just code sitting in a feature branch on a shelf, more or less not creating any business value. So you have to ship with speed. Second, you have to ship with reliability. So invariably there will be bugs. There will be some outages, but you know, one of the things that armory provides with Spinnaker open sources, the ability to create hardened deployment pipeline so that you're testing the right things at the right times with the right folks involved to do reviews. >>And if there is hopefully not, but if there is a problem in production, you're isolating that problem to a small group of users. And then we call this the progressive deployment or Canary deployment where you're deploying to a small number of users. You measure the results, make sure it's good, expand it and expand it. And so I think, you know, preventing outages is incredibly incredibly important. And then the last thing is being able to deploy multi target multi-cloud. And so in the AWS ecosystem, we're talking about ECS, EKS Lambda. And so I think that these pieces of value or kind of the, the pain points that, that enterprises face can resonate with a lot of companies out there, including ENN Patriot. And so I'll, I'll, I'll let you tell the story. >>Yeah, go ahead. Absolutely. Thanks. Thanks for the intro, man. So background background of our partnership with armory as back in the backend, February of 2019, we had a payments payments slowed down for payments processing, and we were risking not getting creators paid on time, which is a doc great for creators because they rely on us for income to be able to pay themselves, pay their rent or mortgage, but also pay staff because they have video editors, website admins, people that nature work with them. And there were, they're a very, there's a very many root causes to this, to this incident, all kind of culminate at once. One of the things that we saw was that deploying D point fixes to remediate. This took too long or taking at least 45 minutes to deploy a new version of the application. And so we've had continuous delivery before using a custom custom home built, rolling deploy. >>We needed to get that time down. We also needed to be secure in our knowledge of like that deploy was stable. So we had had to place a break in the middle due to various factors that that can happen during the deploy previously, I had used a Spinnaker at previous employers. I have been set it up myself and introduced it. And I knew about, I knew like, oh, this is something we could, this would be great. But the Patriot team, the patron SRE team at that time was two people. So I don't have the ability to manage Spinnaker on my own. It's a complex open-source product. It can do a lot of things. There's a lot of knobs to tweak a lot of various settings and stuff you need to know about tangentially. One of the co-founders of, of armory had been, had to hit, had hit me up earlier. I was like, Hey, have you heard of armory? We're doing this thing, opens our Spinnaker, we're packaging this and managing it, check us out if you want. I kind of like filed it away. Like, okay, well that might be something we can use later. And then like two weeks later, I was like, oh wait, this company that does Spinnaker, I know of them. We should probably have a conversation with them and engage with them. >>And so you hit him up and said, Hey, too many knobs and buttons to push what's the deal. >>Yeah, exactly. Yeah. So I was, I was like, Hey, so by the way, I about that thing, how, how soon can you get someone get someone over here? >>So Ben take us through the progression. Cause that really is how things work in the open source. Open source is really one of those things where a lot of community outreach, a lot of people are literally a one degree or two separation from someone who either wrote the project or is involved in the project. Here's a great example. He saw the need for Spinnaker. The business model was there for him to solve. Okay. Fixes rolling deployments, homegrown all the things, pick your pick, your use case, but he wanted to make it easier. This tends to, this is kind of a pattern. What did you guys do? What's the next step? How did this go from here? >>Yeah. You know, Spinnaker being source is critical to armory's success. Many companies, not just pastry on open source software, I think is not really debatable anymore in terms of being applicable to enterprise companies. But the thing with selling open source software to large companies is that they need a backstop. They need not just enterprise support, but they need features and functionality that enable them to use that software at scale and safely. And so those are really the things that, that we focus on and we use open source as a really, it's a great community to collaborate and to contribute fixes that other companies can use. Other companies contribute fixes and functionality that we then use. But it's, it's really a great place to get feedback and to find new customers that perhaps need that enhanced level of functionality and support. And, and I'm very, very happy that Patrion was one of those companies. >>Okay. So let's talk about the Patrion. Okay. Obviously scaling is a big part of it. You're an SRE site, reliability engineers with folks who don't know what that is, is your, your job is essentially, you know, managing scale. Some say you the dev ops manager, but that's not really right answer. What is the SRE role at patriotics share with folks out there who are either having an SRE. They don't even know it yet or need to have SRS because this is a huge transition that, and new, new and emerging must have role in companies, >>Right? Yeah. We're the history of Patrion covers a lot. We cover a wide swath of a wide swath of, of, of things that we work with and, and areas that we consider to be our, our purview. Not only are we working on working with our AWS environment, but we also are involved in how can we make the site more reliable or performance so that, so that creators fans have a good experience. So we work with our content delivery numbers or caching strategies for caching caching assets. We work inside the application itself for doing performance performance, a hassle. This is also in proving observability with distributed tracing and metrics on a lot of that stuff, but also on the build and deploy side, if we can, if we can get that deploy time faster, like give engineers faster feedback on features that they're working on or bug fixes and also being secure and knowing that the, the code that they're working on it gets delivered reliably. >>Yeah. I think I, you have the continuous delivery is always the, the, the killer killer workflow as both the Spinnaker question here. Well, how has Spinnaker, well, what, how, how does Spinnaker being an open source project help you guys? I mean, obviously open source code is great. How has that been significant and beneficial for both armory and Patrion? >>Yeah, I'll take the first stab at this one. And it starts at the beginning. Spinnaker was created by Netflix and since Netflix open source that four or five years ago, there have been countless and significant contributions from many other companies, including armory, including AWS and those contributions collectively push the industry forward and allow the, the companies that, you know, that use open-source Spinnaker or armory, they can now benefit from all of the collective effort together. So just that community aspect working together is huge. Absolutely huge. And, you know, open source, I guess on the go-to-market side is a big driver for us. You know, there's many, many companies using open-source Spinnaker in production that are not our customers yet. And we, we survey them. We want to know how they're using open-source Spinnaker so that we can then improve open-source Spinnaker, but also build features that are critical for large companies to run at scale, deploy at scale, deploy with velocity and with reliability. >>Yeah. What's your take on, on the benefits of Spinnaker being open source? >>A lot of what Ben, it's been really beneficial to be able to like, be able to go in and look at the source code for components. I've been wondering something like, why is this thing working like this? Or how did they solve this? It's also been useful for, I can go ask the community for, for advice on things. If armory doesn't has the, it doesn't have the time or bandwidth to work on some things I've been able to ask the special interest groups in the source community. Like, can we, can we help improve this or something like that. And I've also been able to commit simple bug fixes for features that I've, that I've needed. I was like, well, I don't need to, I don't need to go engage are very on this. I can just like, I can just write up a simple patch on and have that out for review. >>You know, that's the beautiful thing about open sources. You get the source code and that's, and some people just think it's so easy, Ben, you know, just, Hey, just give me the open source. I'll code it. I got an unlimited resource team. Not, not always the case. So I gotta ask you guys on Patrion. Why use a company like armory, if you have the open source code and armory, why did you build a business on the open source project? Like Spinnaker? >>Yeah. Like I see. Absolutely. Yeah. Like I, like I said earlier, the atrium, the Patrion SRE team was wasn't is fairly small. There's two people. Now we're six. People are still people down. We're six people now. So being sure we could run a Spinnaker on our own if we, if we wanted to. And, but then we'd have no time to do anything else basically. And that's not the best use of our, of our creators money. Our fans, the fans being the creators artists. We have obviously take a percentage on top of that. And we, we need to spend our, that money well, and having armory who's dedicated to the Spinnaker is dedicated, involved the open source project. But also there are experts on this Sunday. It was something that would take me like a week of stumbling around trying to find documentation on how to set this thing up. They done this like 15, 20 times and they can just go, oh yeah, this is what we do for this. And let me go fix it for you >>At score. You know, you've got a teammate. I think that's where, what you're getting at. I got to ask you what other things is that free you up? Because this is the classic business model of life. You know, you have a partner you're moving fast, it slows you down to get into it. Sure. You can do it yourself, but why it's faster to go with it, go together with a partner and a wing man as we will. What things did does that free you up to work on as an SRE? >>Oh, that's freed me up to work on a bigger parts of our build and deploy pipeline. It's freed me up to work on moving from a usage based deploys onto a containerization strategy. It's freed me up to work on more broader observability issues instead of just being laser-focused on running an operating spending. >>Yeah. And that really kind of highlights. I'm glad you said that because it highlights what's going on. You had a lot of speed and velocity. You've got scale, you've got security and you've got new challenges you got to fix in and move fast. It's a whole new world. So again, this is why I love cloud native. Right? So you got open source, you got scale and you guys are applying directly to the, to the infrastructure of the business. So Ben, I got to ask you armory. Co-founder why did you guys build your business on an open source project? Like Spinnaker? What was the mindset? How did you attack this? What did you guys do? Take us through that piece because this is truly a great entrepreneurial story about open source. >>Yeah. Yeah. I'll give you the abridged version, which is that my co-founders and I, we solved the same problem, which is CD at a previous company, but we did it kind of the old fashioned way we home role. We handled it ourselves. We built it on top of Jenkins and it was great for that company, but, and that was kind of the inspiration for us to then ask questions. Hey, is this bigger? We, when at the time we found that Spinnaker had just been, you know, dog food inside of Netflix and they were open sourcing it. And we thought it was a great opportunity for us to partner. But the bigger reason is that Spinnaker is a platform that deploys to other platforms like AWS and Kubernetes and the sheer amount of surface area that's required to build a great product is enormous. And I actually believe that the only way to be successful in this space is to be open source, to have a community of large companies and passionate developers that contribute the roads if you will, to deploy into various targets. >>And so that's the reason, number one for it being open source and us wanting to build our business on top of open source. And then the second reason is because we focus almost exclusively on solving enterprise scale problems. We have a platform that needs to be extensible and open source is by definition extensible. So our customers, I mean, Ian just had a great example, right? Like he needed to fix something he was able to do so solve it in open source. And then, you know, shortly thereafter that that fix in mainline gets into the armory official build and then he can consume his fix. So we see a lot of that from our other customers. And then even, you know, take a very, very large company. They may have custom off that they need to integrate with, but that doesn't, that's not in open-source Spinnaker, but they can go and build that themselves. >>Yeah, it's real. It really is the new modern way to develop. And I, you know, last 80 with startup showcase last season, Emily Freeman gave a talk on, you know, you know, retiring, I call it killing the software, SDLC, the lifecycle of how software was developed in the past. And I got to ask you guys, and, and this cube conversation is that this is kind of like the, the kind of the big wave we're on now is cloud scale, open source, cloud, native data security, all being built in on this in the pipelines to your point is SRS enabling a new infrastructure and a new environment for people to build essentially SAS. So I got to ask you guys as, and you mentioned it Ben, the old way you hand rolled something, Netflix, open source, something, you got to look at Lyft with Envoy. I mean, large-scale comes, are donating their stuff into open source and people getting on top of it and building it. So the world's changed. So we've got to ask you, what's the difference between standing up a SAS application today versus say five to eight years ago, because we all see salesforce.com. You know, they're out there, they built their own data center. Cloud skills changed the dynamics of how software is being built. And with open-source accelerating every quarter, you're seeing more growth in software. How has building a platform for applications changed and how has that changed? How people build SAS applications, Ben, what's your take on this? It's kind of a thought exercise here. >>Yeah. I mean, I wouldn't even call it a thought exercise. We're seeing it firsthand from our customers. And then I'll, you know, I'll, I'll give my answer and you can weigh in on like practical, like what you're actually doing at Patrion with SAS, but the, the costs and the kind of entry fee, if you will, for building a SAS application has tremendously dropped. You don't need to buy servers and put them inside data centers anymore. You just spin up a VM or Kubernetes cluster with AWS. AWS has led the way in public cloud to make this incredible easy. And the tool sets being built around cloud native, like armory and like many other companies in the space are making it even easier. So we're just seeing the proliferation of, of software being developed and, and hopefully, you know, armory is playing a role in, in making it easier and better. >>So before we get to Unum for a second, I just want to just double down on it because there's great conversation that implies that there's going to be a new migration of apps everywhere, right. As tsunami of clutter good or bad, is that good or bad or is it all open source? Is it all good then? >>Absolutely good. For sure. There will be, you know, good stuff developed and not so good stuff developed, but survival of the fittest will hopefully promote those, the best apps with the highest value to the end user and, and society at large and push us all forward. So, >>And what's your take, obviously, Kubernetes, you seeing things like observability talking about how we're managing stateful and services that are being deployed and tear down in real time, automated, all new things are developing. How does building a true scalable SAS application change today versus say five, eight years ago? >>I mean, like you said, there's a, there's a lot, there's a lot of new, both open source. So SAS products available that you can use to build a scale stuff. Like if you're going to need that to build like secure authentication, instead of having to roll that out and you could go with something like Okta raw zero, you can just pull that off the shelf stuff for like managing push notifications before that was like something really hard to really hard to do. Then Firebase came on the scene and also for manic state and application and stuff like that. And also for like being, being able to deliver before >>You had Jenkins, maybe even for that, you didn't really have anything Jenkins came along. And then now you have open-source products like Spinnaker that you can use to deliver. And then you have companies built around that, that you can just go and say, Hey, can you please help us deliver this? Like you just help us, enable us to be able to build, build our products so that we can focus on delivering value to our creators and fans instead of having to focus on, on other things. >>So bill it builds faster. You can compose stuff faster. You don't have to roll your own code. You can just roll your own modules basically, and then exactly what prietary on top of it. Absolutely. Yeah. And that's why commercial open source is booming. Guys. Thank you so much, Ben, congratulations on armory and great to have you on from Patrion well-known success. So we'll accompany you congratulate. If we don't know patriarch, check it out, they have changed the game on creators and leading the industry. Ben. Great, great shot with armory and Spinnaker. Thanks for coming on. Thank you >>So much. Thank you >>So much. Okay. I'm Sean Ferrer here with the cube conversation with Palo Alto. Thanks for watching.

>>Mhm >>Hello and welcome to this special cube conversation. I'm john furrier here in Palo alto California, host of the cube we're here with Sean Knapp was the Ceo and founder of Ascend dot Io heavily venture backed working on some really cool challenges and solving some big problems around scale data and creating value in a very easy way and companies are struggling to continue to evolve and re factor their business now that they've been re platform with the cloud, you're seeing a lot of new things happening. So Sean great to have you on and and thanks for coming on. >>Thanks for having me john So >>one of the things I've been interesting with your company, not only do you have great pedigree in terms of investors and tech tech staff is that you guys are going after this kind of new scaling challenge um which is not your classic kind of talking points around cloud scale, you know, more servers, more more data more. It's a little bit different. Can you describe what you guys mean around this new scaling challenge? >>Absolutely. The classic sense of scaling, particularly when it comes to the data industry, whether it's big data data science, data engineering has always focused on bits and bytes, how many servers, how big your clusters are and You know, we've watched over the last 5-10 years and those kinds of scaling problems while not entirely solved for most companies are largely solved problems now and the new challenge that is emerging is not how do you store more data or how do you process more data but it's how do you create more data products, how do you drive more value from data? And the challenge that we see many companies today, really struggling to tackle is that data productivity, that data velocity challenge and that's more people problem. It is a how do you get more people able to build more products faster and safely that propelled the business forward? >>You know, that's an interesting topic, We talk about devops and how devops is evolving. Um and you're seeing SRS has become a standard position now in companies site reliability engineers at Google pioneered, which essentially the devops person, but now that you don't need to have a full devops team as you get more automation, That's a big, big part of it. I want to get into that because you're touching on some scale issues around people, the relationships to the machines and the data. It's it's an interesting conversation, but before we do that, can you just take a minute to explain uh what you guys do, what does this send? I o I know you're in Palo alto, it's where I live um and our offices here, what's a sandy all about? >>Absolutely. So what ascend really focuses on is building the software stack on top of modern day, big data infrastructure for data engineers, data scientists, data analyst to self serve and create active data pipelines that feel the rest of their business. Uh And we provide this as a service to a variety of different companies from Australia to Italy finance to IOT uh start ups to large enterprises and really hope elevate their teams, you know, as Bezos said a long time ago, out of the muck of of the underlying infrastructure, we help them do the same thing out of the muck of classic data engineering work, >>that's awesome Andy Jassy now the ceo of amazon who was the sea of avenue too many times over the years and he always has the line undifferentiated heavy lifting. Well, I mean data is actually differentiated and it's also heavy lifting too, but you got, you have differentiation with data but it's super important, it's really you gotta but there's a lot of it now, so there's a lot of heavy lifting, this is where people are struggling, I want to get your thoughts on this because you have an opinion on this around how teams are formed, how teams can scale because we know scales coming on the data side and there's different solutions, you've got data bricks, you've got snowflake yet red shift, there's a zillion other opportunities for companies to deploy data tooling and platforms. >>What's your hands to the >>changes in data? >>Well, I think in the data ecosystem is we're changing very, very quickly uh which makes it for a very exciting industry uh and I do think that we are in this great cycle of continuing to reinvest higher and higher up the stack if you will. Right and in many ways we want to keep elevating our teams or partners or customers or companies out of the non differentiated elements. Uh and this is one of those areas where we see tremendous innovation happening from amazon from data breaks from snowflake, who are solving many of these underlying infrastructure, storage processing and even some application layer challenges proteins. And what we find oftentimes is that teams after having adopted some of these stacks on some of these solutions, then have to start solving the problem of how do we build after, how do we build better? And how do we produce more on top of these incredibly valuable investments that we've made and they're looking for acceleration. There's they're looking for in many ways the autopilot self driving level of capabilities, intelligence to sit on top and help them actually get the most out of these underlying systems. And that's really where we need that big changes >>are self driving data, you gotta have the products first. I think you mentioned earlier a data product data being products, but there's a trend with this idea of data products. Data apps. What is the data product? Um that's a new concept. I mean it's not most, most people really can't get their arms around that because it's kind of new data data, but how how does it become product ties and and how do why is it, why is it growing so fast? >>Yeah, that's a great question. I think, you know, quickly uh talked through a lot of the evolution of the industry. Oftentimes we started with the, well let's just get the data inside of a lake and it was a very autumns up notion of what we just collected then we'll go do something with it. The very field of dreams esque approach. Right? And oftentimes they didn't come in and your data just sat there and became a swamp. Right? And the when we think about a data, product oriented model of building it is let's focus on the how do we just collect and store and process data and it's much more on the business value side of how do we create a new data set in architectural models would be how do we launch a new micro service or a new feature out to a customer? But the data product is a new refined, valuable curated live set of data that can be used by the business. Whether it's for data analysts or data scientists are all the way out to end consumers. It is very heavily oriented towards that piece because that's really where we get to deliver value for our end users or customers. Yeah, >>getting that data fastest key Again, I love this idea of data becoming programmable or kind of a data ops kind of vibe where you're seeing data products that can be nurtured also scaled up to with people as as this continues The next kind of logical question I have for you is okay, I get the data products now I have teams of people, how do I deploy them? How do the teams change? Because now you have low code and no code capabilities and you have some front end tools that make it easier to create new apps and, and um products where data can feed into someone discovers a cool new value metric in the company. Um they can say here boss is a new new metric that we've identified that drives our business now, they've got a product ties that in the app, they used low code, no code. Where do you guys see this going? Because you can almost see a whole, another persona of a developer emerging >>or engine. Team >>emerging. >>Absolutely. And you know, it's, I think this is one of the challenges is when we look at the data ecosystem. Uh we even ran a survey a couple of months ago across hundreds of different developers asking data scientists, data engineers, data analyst about the overall productivity of their teams. And what we found was 96% of teams are at or over capacity, meaning only 4% of teams even have the capacity to start to invest in better tools or better skill sets and most are really under the gun. And what that means is teams and companies are looking for more people with different skill sets, how and frankly how they get more leverage out of the folks where they have, so they spend less than any more than building. And so what ends up starting to happen is this introduction of low code and no conclusions to help broaden the pool of people who can contribute to this. And what we find oftentimes is there's a bit of a standoff happening between engineering teams and analyst teams and data science teams, teams where some people want low code, some people want no code, Some people just want super high code all day all all the time and what we're finding is and even actually part of one of the surveys that we ran, uh, most users very small percentage less than 10% users actually were amenable to no code solutions, But more than 70% were amenable to solutions that leaned towards lower no code but allowed them to still programs in a language of their choice, give them more leverage. So what we see end up happening is really this new era of what we describe as flex code where it doesn't have to be just low code or just no code but teams can actually plug in at different layers of the staff and different abstract layers and contribute side by side with each other all towards the creation of this data product with applicable model of flats code. >>So let's unpack flex code for a second. You don't mind to first define what you mean by flex code and then talk about the implications to to the teams because it sounds like it's it's integrated but yet decoupled at layers. So can you take me through what it is and then let's unpack a little bit >>Absolutely. You know, fuck. So it is really a methodology that of course companies like ours will will go and product ties. But is that the belief structure that you should be able to peel back layers and contribute to an architecture in this case a data architecture, whether it's through building in a no code interface or by writing some low code in sequel or down and actually running lower level systems and languages and it's it's become so critical and key in the data ecosystem. As what classically happened has been the well if we need to go deeper into the stack, we need to customize more of how we run this one particular data job, you end up then throwing away most of the benefits and the adoption of any of these other code and tools. End up shutting off a lot of the rest of the company from contributing. And you then have to be for example, it really advanced scholar developer who understands how to extend doctor runtime environment uh, to contribute. And the reality is you probably want a few of those folks on your team and you do want them contributing, but you still want the data analysts and the data scientists and the software engineers able to contribute at higher levels of the stack, all building that solution together. So it becomes this hybrid architecture >>and I love I met because it's really good exploration here because so what you're saying is it's not that low code and no codes inadequate. It's just that the evolution of the market is such that as people start writing more code, things kind of break down stream. You gotta pull the expert in to kind of fix the plumbing and lower levels of the stack, so to speak, the more higher end systems oriented kind of components. So that's just an evolution of the market. So you're saying flex code is the next level of innovation around product sizing that in an architecture. So you don't waste someone's time to get yanked in to solve a problem just to fix something that's working or broke at this point. So if it works, it breaks. So, you know, it's working that people are coding with no code and low code, it just breaks something else downstream, You're fixing >>that. Absolutely. And that's the um, the idea of being here is, you know, it's one of these old averages. Uh, when you're selling out to customers, we see this and I remember this head of engineering one time I told me, well, you may make 95% of my team's job easier. But if you make the last 5% impossible, it is a non starter. And so a lot of this comes down to the how do we make that 95% of the team's job far easier. But when you really have to go do that one ultra advanced customized thing, how do we make sure you still get all the benefits of Oftentimes through a low code or no code interface, but you can still go back down and really tune and optimize that one piece. >>Yeah, that's really kind of, I mean this is really an architectural decision because that's the classic. You don't want to foreclose the future options. Right? So as a developer, you need to think this is really where you have to make an architecture decision That's really requires you guys to lean into that architectural team. How do you guys do that? What those conversations look like? Is it work with a send and we got you covered or how does those conversations go? Because if someone swinging low code, no code, they might not even know that they're foreclosing that 5%. >>Yeah. Oftentimes the, you know, for them, they're uh, they're the ones that are given the hardest radius gnarliest problems to solve for um, and may not uh even have the visibility that there is a team of 30, you know analysts who can go right incredible data pipelines if they are still afforded a low code or no code interface on top. And so, you know, for us, we really partner heavily with our customers and our users. Uh we do a ton of joint architecture, design decisions, not just for their products, but we actually bring them in to all of our architecture and design and road mapping sessions as well. Uh And we do a lot of collaborative building very much how we treat the developer community around the company. It's all we spent a lot of time on that >>part of your partner strategy. You're building the bridge to the future with the customer. >>Yeah, absolutely. We we work, in fact, almost all of our communications with our customers happen in shared slack channels. We are treated like extensions of our customers team and we treat them as our internal customers as well. >>And that's the way, and that's the way it should be doing some great work, is really cutting edge and really setting the table for, you know, a decade of innovation with the customer if you get it right, if they get if they get it right. So I gotta ask you with this um architecture, you gotta be factoring in automation because orchestration automation. These are the principles of devops to kind of go on the next level. I love this, love this conversation. Devops two point oh four point or whatever you wanna call it. It's the next level. Devops, it's data automation, you're taking it to a whole nother level within your sphere. Talk about automation and how that factors in obviously benefits the automation. Autonomous data pipeline? It would be Cool. No coding. I can see maintenance is an issue. How do you offload developers so that it's not only an easy button but it's a maintenance maintenance button? >>Yeah, absolutely. What we find in the evolution of most technical domains is this shit happened at some point usually towards her from an imperative developer model to a declared developer model. For example, we see this uh in databases with the introduction of sequel, we see it in infrastructure definition with tools like a telephone and now kubernetes and what we do from an automation perspective for uh for data pipelines is very similar to what Kubernetes does for containers? We do for data pipelines, we introduce a declarative model and put in this incredible intelligence that tracks everything around how data moves. Uh for us, metadata alone is a big data problem because we track so much information and all that goes into this central brain that is dynamically adapting to code and data for our users and dynamically generated. So for us, when we look at the biggest potential to automate is to help alleviate maintenance and optimization burdens for users. So they get to spend more time building and less time maintaining and that really goes into the how do you have this central brain that tracks everything that build this really deep understanding of how data moves through an organization. >>That's an awesome vision. I gotta ask my my brains firing off like, okay, so what about runtime assembly as you orchestrate data in real time, you have to kind of pull the assembly to all and link and load all this data together. I can only imagine how hard that is. Right? So can you share your vision because you mentioned docker containers, the benefits of containers is, you know, they can manage state and stateless data. So as you get into this notion of state and stateless uh data, how do you assemble it all in real time? How does that work? How's that brain figured out? What's the secret sauce? >>Yeah, that's a really great question. Uh you know, for us and this is one of the most exciting parts for our customers in our users is uh we hope with this paradigm shift where the classic model has been the you're writing code, you compile it, you ship it, you push it out and then you cross your fingers like, gosh, I really hope that works. Um and it's a very slow iteration cycle. And one of the things that we've been able to do because of this intelligence layer is actually help hybridize that for users. You still have pipelines and they still run and they're still optimizing but we make it an interactive experience at the same time very similar to how notebooks for data science. Help make that such an interactive experience. We make the process of building data pipelines and doing data engineering work iterative and interactive. You're getting instantaneous feedback and evolving very quickly. So they the things that used to take weeks or months due to slow iteration cycles really now can be done in hours or days because you get such fast feedback loops as you build. >>Well, we definitely need your product. We have so much data on the media side all these events are like little, it's like little data but it's big data, it's a lot of little data that makes it a big data problem. And I do, I feel like I'm jumping out of the airplane with a parachute and will it open, you know, one of the >>work you just we >>don't, you know, we don't know right? So a lot of the fear is you know, split, we don't wanna crater and build data products that are you know, praying right? This is this is really kind of everyone's doing right now. It's kind of state of the industry. How do you guys make it easy? That's the question, right. Because you brought up the human aspect, which I love the human scale, the scale teams, nobody wants another project if they are already burnt out with Covid and they don't have enough resources, you know, it's almost like there's a there's a little bit of psychology going on the human mind now saying well enough or burn out or you know, the relationship to humans training data data is now got this human interaction, all of it is around, you know, these are views future of work and simplicity and self service, What's your thoughts on those? >>Oh, I wholeheartedly agree. I think the uh we need to continue to be pushing those boundaries around self service and around developer and frankly just outright data productivity, You know, and for us, I think it's become a really fascinating uh time in the industry, as uh you know, I would say in 2019, much of the industry and users and builders in the industry, I just embrace the fact that frankly the building data pipeline sucked. Uh and it was a badge of honor because it was such a hard and painful thing yet, what we're finding is now as the industry is evolving is an expectation that it should be easier. Uh and people are challenging that conventional wisdom and expecting building data pipelines to be much easier and that's really where we come in is both with a flex code model and with high levels of automation to keep people squarely focused on rapid building versus maintaining and tinkering to deepen the staff. >>You know, I really think you're on to something with the one that scaling challenge of people and teams huge issue to match that at the pace of, you know, cloud and data scale is a huge, huge focus and I'm glad you're focusing on that, that's a human issue and then on the data architecture? I mean we saw what to do, how to do a failed project? You require the customer to create all this, you know, undifferentiated support and heavy lifting and, and time lag just to get to value right? There is no value right in the cloud. So, so this is your on the right track. How do you talk to customers, take a minute to, to share at the folks who are watching or if it's a customer and enterprise or potential customer, what's in it for them? Why ascend why should they work with you? How do they engage with you guys? What's in it for them? >>Yeah, absolutely. Um, what's in it for customers is time to value truncated dramatically. You get projects live and you get them faster, far faster than ever thought possible. Uh, you know, the way that we engage with our customers, uh, is we help partner them with them, We launched them on the, on the application. They can buy us from the marketplace, we will actually help even architect their first project with them, uh, and ensure that they have a full fledged live data product. Data products live within the first four weeks. Uh, not really, I think becomes the most keeping and frankly it doesn't features and functions and so on really don't matter. Ultimately, at the end of day, what really matters is can you get your data products live, Can you deliver business value and are your your team happy as they get to go build. Do they do they smile more throughout the day because they're enjoying that devil over experience. >>So you're providing the services to get them going. It's the old classic expression teaching them how to fish and then they can fish on their own, Is that right? >>Yep. Absolutely. >>And then doing whatever next next damn thing. Yeah >>and then then the, we're excited to watch quarter after quarter year after year our customers build more and more data products uh and their teams are growing faster than most of the other teams in their companies because they're delivering so much value and that's what's so exciting, >>you know, you know the cliche every company is a data company. I know that's kind of cliche but it's true right? Everyone has to have a core D. N. A. But they don't have, they shouldn't have to hire hardcore data engineering. They haven't data team for sure. That team has to create a service model for practitioners inside the company. >>Well how do they agree >>Sean great, great conversation. Um great to unpack the flex code. I love that approach, take it to the next level, take it low code to the next level with data. Great stuff and send I. O Palo Alto based company, congratulations on your success. >>Thank you so much, john >>okay this cube conversation here in Palo Alto, I'm john for your host of the cube. Thanks for watching. Mhm. Mhm.

(upbeat music) >> Okay, we're back here at theCUBE on this floor in CLOUD CITY, the center of all the action at Mobile World Congress. I'm John Brown your host. Michael current CTO of Virta San is here with me remote because this is a virtual event as well, this is a hybrid event. The first industry hybrid event, Greg would be back in real life on the floor, Michael, you coming in remotely. Thanks for joining us here in the cube in cloud city. >> Thanks for having me and said the beer. >> We were just talking on camera about. He went to Michigan and football, all that good time while we were waiting from Adam to pseudo great stuff, but let's get into what you guys are doing. You've got a great cloud news, we're going to get to, but take a minute to explain what you guys do first. >> So Virtasant helps organizations of any size thrive in the cloud. So we have a unique combination of proprietary technologies, such as our cloud optimization platform that we'll talk about in a minute and a global team of experts that helps companies make the most of the cloud from getting to the cloud and building the cloud to optimizing the cloud all the way to managing the cloud at scale. >> Well, you got a lot of experience dealing with the enterprise, a lot of customer growth over the years, great leader. The cloud dynamic here is the big story at mobile world congress, this year, the change over, I won't say change over per se, but certainly the shift or growth of cloud on top of telco, you guys have some news here at mobile world congress. Let's share the news, what's the big scoop? >> So we have an automated cloud optimization platform that helps companies automatically understand your usage patterns and do spend fully, automatically. And we focus first on AWS is the biggest cloud provider, but starting this week, we wanted announces we're actually going live with our GCP product, which means people who are on the GCP cloud platform can now leverage our platform to constantly understand usage patterns and spend and automatically take action to reduce spend. So we typically see customers save over 50% when they use our platform. So now GCP customers can take advantage of the same capabilities that our AWS customers take advantage of every day. >> Talk about the relationships as you get deeper. And this seems to be the pattern I want to just unpack it. You don't mind a little bit the relationship with Google and this announcement and Amazon you're tightly coupled with them, is it more integration? Talk about what makes these deals different and special for your customers? What's what's, what's about them. What's the big deal? >> Well, I think for us, obviously we think that, you know, the public cloud's the future, right? And obviously cloud city and all the different companies there agree with us, and we think that much like, you know, you don't, you don't generate your own electricity. We don't think you're going to generate you're to you're going to build your own technology infrastructure. For the most part, we think that pretty much all compute will be in the public cloud. And obviously AWS is the market leader in the largest cloud provider in the, but you know, GCP, especially with telecom has some compelling offerings. And we think that, you know, organizations are going to want choice. Many will go multicloud, meaning they'll have 1, 2, 3 of the big providers and move workloads across those. But even those who choose one cloud provider, you know, each cloud provider has their strengths and different companies will choose different providers. And they're all, you know, they've all got strong capabilities and their uniqueness. So we want to make sure that whether, you know, an organization goes across all cloud providers or they choose one that we can support them no matter what the workloads look like, and so for us, you know, developing deep relationships with each of the public cloud providers, but also, you know, expanding our full set of capabilities to support all of them is critically important because we do think that there's going to be, you know, a handful of large public cloud providers and obviously AWS and GCP are among them. >> Yeah, I mean, I talk to people all the time and even, you know, we're an Amazon customer, pretty robust cloud in the bills out of control is what's, what's this charge for it. There's more services to tap into, you know, it's like first one's on me, you know? And then next thing you know, you're, you're consuming a hell of a lot of new services, but there's value there and there's breaths a minute for the cloud, we all love that. But just as a random aside here, I want to get your thoughts real quick, if you don't mind, this idea of a cloud economist has become part of a new role in an organization, certainly SRS is DevOps. Then you starting to get into people who actually can squint through the data and understand the consumption and be more on the economics side, because people are changing how they report their earnings. They're changing how they report their KPIs based upon the usage and costs, and... What, is this real? what's your thoughts on that? I know that's a little random, but I want to get your, get your thoughts on that. >> Well, yeah, it's interesting that that's been a development. What I will say is, you know, the economics of cloud are complicated and they're still changing and still emerging, so I think that's probably more of a reaction to how dynamic the environment is then kind of a long-term trend. I mean, admittedly for us we hope that, you know, a lot of that analysis and the data that's required and will be provided by our platform. So you can think about it as, you know, a digital or AI powered cloud economist. So I don't, I don't know, hopefully our customers can use the platform and get everything they need and they won't need to go out and hire a cloud economist. That sounds expensive. >> Well, I think one of the things that sounds like great opportunities to make that go away, where you don't have to waste a resource to go through the cost side. I want to get your thoughts on this. This comes up all the time, certainly on Twitter, I'm always riffing on it. It comes up on a lot of my interviews and private chats with people about their, their cloud architecture, spend can get out of control pretty quickly. And data is a big part of it. Moving data is always going to be... Especially Amazon and Google, moving data in and out of the cloud is great. Now with the edge, I just talked to Bill Vass at a Amazon web service. He's the VP of engineering. You can literally bring the cloud to the edge and all the clouds are going to be doing this, these edge hubs. So that's going to process data at the edge, but it's also going to open up more services, right? So, you know, it's complicated enough as it is, spend is getting out of control. And it's only seems to be getting out of control even more. How do you talk to customers? I'd want to not be afraid they want to jump in, but they also want to have a hedge. Yeah, what's your, what's your take on your story? >> I think there's a lot of debate right now as to whether or not, you know, moving to the cloud from a cost perspective is cost-effective or more costly. And there's a pretty healthy debate going on at the moment. I think that the reality is, you know, yes, the cloud makes it easier for you to take on new services and bring on new things, and that of course drives spend, but it also unlocks incredible possibilities. What we try to do is help organizations take advantage of those possibilities and kind of the capabilities of the cloud while managing spend, and it's a complex problem, but it's a solvable problem. So for us, we think that, you know the job of the cloud providers is to, you know, continue to innovate and continue to bring more and more capability to bear so that organizations can transform through technology, the job of the teams using that technologies is to really leverage those capabilities, to build and to innovate and to serve their customers. And what we want to do is enable them to do that in a cost-effective manner, and we believe, and we have data to prove that if you do public cloud, right, it's cheaper because you know, those, those organizations, you know, much like, you know, at the turn of the industrial revolution, factories used to have their own power plants because you couldn't effectively reliably and kind of cost-effectively generate power at scale. Obviously no one does that now. And I think with the cloud providers, that's the same thing. I mean, they're investing in proprietary hardware, tons of software, tons of automation. They're highly secure. You know, at the end of the day, they're going to always be able to provide a given capability at a lower cost point. Like, of course they need to make profit. So there's a bit of margin in there, but, you know, at the end of the day, we think that both the flexibility and capability of it combined with their ability to operate at scale gives you a better value proposition, especially if you do it right. And that's what we want to focus on is, you know, the answer is there. You just need the right data and the right intelligence to find it. >> Totally, I totally agree with you. In fact, I had a big debate with Martine Casada at Andreessen Horowitz about cloud repatriation, and he was calling his paradigm. Do you focus on the cost or the revenue? And obviously they have Dropbox, which is a big example of that, and I even interviewed the Zynga guys and they actually went back to Amazon, although they didn't report that, but I'm a big believer that if you can't get the new revenue, then you're in cosmos then, and there are the issues, but again, I don't want to go there right now. I'll talk about that another time, but I want to get your, I want to get the playbook, so first of all, I love what you do, I think it's an opportunity to take that heavy lifting away from customers around understanding cost optimization. A lot of people don't know how to do it. So take us through a playbook. What are some best practices that you guys have seen to help people figure this out? What do you say to somebody, help me, Michael, I'm in a world of hurt, what do I do? What's the playbook? Can you give some examples of day in the life? >> Sure, so I think, I think the first thing is know what you're spending money on which sounds obvious, but you know, there's cloud environments are complicated, especially at scale. There's hundreds of thousands of skews and lots of different usage patterns. And I think the first thing is understand what you're spending money on. Number two is understand what you're getting for that spend. So, you know, what value are you driving with that spend? And then number three is put the information in the hands of the people who can do something about it. And I think that is, is one of the things that we really focus on is, you know, we built our product from an engineering focus first. It was engineers solving the problem of understanding how to keep cloud costs in control. And so our whole principle is give the people, working with the technology, the data to make good decisions and give them the power to act on it. And so, you know, a lot of companies say, "Oh, we're spending more over here. Or maybe we should look at that." But, but what we believe is actually be specific, where are you spending money? Where exactly are you spending too much? And what should you do about that? And give that information to the people who can take action, which are the engineers. And then lastly make it important in the organization because there's a ton of competing priorities. And what we've found is that, you know, where there's leadership support there's results. And so I think if you do those four things, you know, results will follow. Now, obviously, you know, you need to understand specific utilization patterns and know what to do with different kinds of resources and all of that stuff is complicated, but there are certainly solutions out there. Ours included who helped you with that. So if you get the other four things, right, plus you have some help, you can keep it under control and actually not just keep it under control, but operate in an environment that's much cheaper than hosting all this technology yourself and much more flexible. >> That's a great point, I mean, the fact that you mentioned earlier, the engineering piece that is so true people I've talked to, you mean our experiences and it's pretty common. The DevOps team tends to get involved in things like making sure you're buying reserve instances or all kinds of ways to optimize patterns, and that's also an issue, right? I mean, first of all, it makes sense that they're doing it, but also engineering time is being spent on essentially accounting at that point. Demonstrates the shift, I'm not saying it's good or bad. I'm just saying that got to be realistic. It's a time sink for the engineering when they're not engineering accounting, or should they, this is a legit question, it's not so much they should or shouldn't, I mean, if you say to someone, "Hey, you're paid to build and write software and you're spending your time solving accounting problems." That's obviously a mismatch. But when you talk about SREs and DevOps, Michael, it's kind of what might not be a bad thing, right? I mean, so how do people react to that? Are they kind of scratching their head on the same way? Or are you guys the solution to that? >> Well, I think that at first they are, but for us, at least it's, you know, we don't want them trying to understand the intricacies of a savings plan or understanding kind of the different options for compute instances. What we want them to do is we give them all the information. So our approach is give them all the information. They need to quickly make a decision, let them make a decision, like push a button and then let the change happen automatically. So if you think about it, you know, the amount of time they spend is, is a minute. That's the goal because then we can use their expertise. So it's not a finance person or an accountant doing research and making decisions that may or may not make technical sense and then looping in a bunch of people and they all talk, and then all that, that kind of whole process it's now here is a data-driven observation and recommendation. You have context to say yes or no, if you push the button and then you say, yes, then, you know, the change happens. If you say, no, the system learns. >> It's building right into the pipeline and they're shifting left to security, it's the same concept. It's really a great thing. I really think you're onto something big.,I love this story. It's kind of one of those things where reality's there. Michael, we've got 30 seconds left. I want to get your thoughts to share what put a plug in for the company, what you guys are doing, what are you looking at higher? You got a 30 second plug, go plug the company, what do you got? >> Well, you know, we think that, you know, for any organization, big or small, trying to make the most of the public cloud and be cloud first, you know, we, we bring a unique set of expertise, automation, and technology capabilities to bear, to help them thrive in the cloud and make the most of it. So, you know, obviously we would love to work with any company that, that wants to be cloud first and fully embrace the public cloud. I think we've got all the tools to help them thrive. >> Yeah, and I think, I think the confluence of business logic technology engineering working together is a home run. It's only going to get more stronger, so congratulations. Thanks for coming on theCUBE. >> Thank you. >> Adam, back to you in the studio for more action, theCUBE is out, we'll see you later.

>>mhm Yes. Hello and welcome back to the cubes coverage of red hat summit 2021 virtual. I'm john for your host of the cube and cube coverage here with matt Hicks. Executive vice president of products and technologies at red hat cuba lum I've been on many times, knows the engineering side now running all the process of technologies matt. Great to see you. Thanks for coming on remote. I wish we were in real real life in person. I RL but doing it remote again. Thanks for coming on. >>Hey, thanks thanks for having me today. >>Hey, so what a year you know, um, I was just talking to a friend and another interview with the red hat colleagues. Chef on your team in 2019 I interviewed Arvin at IBM right before he bought red hat and you smile on his face and he wasn't even ceo then um, he is such a big fan of cloud native and you guys have been the engine underneath the hood if you will of IBM this transformation huge push now and with Covid and now with the visibility of the post Covid, you're seeing cloud Native at scale with modern applications just highly accelerated across the board In almost every industry, every vertical. This is a very key trend. You guys at the, at the center of it always have been, we've been covering you for many years, interesting time and so now you guys are really got the, got the formula at red hat, take us through the key transit you see on this wave for enterprises and how is red hat taking that, taking that through? >>Yeah, no, absolutely. It has been, it's been a great ride actually. I remember a couple years ago standing on stage with Arvin prior to the acquisition. So it's been uh, it's been a world one but I think if we look at Really would emerge in 2020, we've seen three trends that we hope we're gonna carry through in 2021 just in a better and better year for that. That the first is open hybrid cloud is really how customers are looking to adapt to change. They have to use what they have um assets they have today. On premise, we're seeing a lot of public cloud adoption that blend of being hybrid is just, it is a reality for how customers are having to deliver a edge computing I think is another area I would say uh the trend is really not going to be a fad or a new, you know, great texture. Um the capabilities of computing at the edge, whether that is automotive vehicles, radio access network capabilities to five G. It's pretty astounding at this point. So I think we're gonna see a lot of pushing edge computing for computing, getting closer to users. Uh but then also the choice aspect we're seeing with Ceos, we often talk about technology is choice, but I think the model of how they want to consume technology has been another really strong trend in 2020. Uh We look at this really is being able to deliver a cloud managed services in addition to technology that ceos around themselves. But those, those will probably be the three that stand out to me at least in 2020 we've seen, >>so matt take us through in your minds and red hats, perspective the workloads that are going to be highlighted in this cloud native surge that's happening. We're seeing it everywhere. You mentioned edge industrial edge to consumer Edge to lightweight, edge, massive new workloads. So take us through how you see kind of the existing workloads evolving and potentially new workloads that emerging. >>Yeah. So I think um you know first when you talk about edge workloads a big umbrella but if you look at data driven workloads, especially in the machine learning artificial intelligence spectrum of that, that's really critical. And a reason that those workloads are important is five G. Aside for now when you're running something at the edge you have to also be able to make decisions pretty well at the edge. And that that is that's where your data is being generated and the ability to act on that closely. Whether that's executing machine learning models or being able to do more than that with A I. That's going to be a really really critical workload. Uh huh. Coupled to that, we will see I think five G. Change that because you're going to see more blending in terms of what can you draw back to uh closer to your data center to augment that. So five G will shift how that's built but data driven workloads are going to be huge then I think another area will see is how you propagate that data through environment. Some Kafka has been a really popular technology will actually be launching a service in relation to that. But being able to get that data at the edge and bring it back to locations where you might do more traditional processing, that's going to be another really key space. Um and then we'll still have to be honest, there is still a tremendous amount of work loads out there that just aren't going to get rebuilt. And So being able to figure out how can you make them a little more cloud native? You know, the things your companies have run on for the last 20 years, being able to step them closer to cloud native, I think it's going to be another critical focus because he can't just rewrite them all in one phase and you can't leave them there as well. So being able to bridge shadow B T to >>what's interesting if folks following red hat, No, no, you guys certainly at the tech chops you guys have great product engineering staff been doing this for a long time. I mean the common Lennox platform that even the new generation probably have to leave it load limits on the server anymore. You guys have been doing this hybrid environment in I T for I T Sloan for decades. Okay. In the open, so, you know, it's servers, virtualization, you know, private, public cloud infrastructures and it's been around, we've been covering it in depth as you know, but that's been, that's a history. But as you go from a common Lennox platform into things with kubernetes as new technologies and this new abstraction layers, new control plane concept comes to the table. This need for a fully open platform seems to be a hot trend this year. >>How do you >>describe that? Can you take a minute to explain what this is, this is all about this new abstraction, this new control plane or this open hybrid cloud as you're calling? What is this about? What does it mean? >>Yeah, no, I'll do a little journey that she talked about. Yeah. This has been our approach for almost a decade at this point. And it started, if you look at our approach with Lennox and this was before public clouds use migrants existed. We still with Lennox tried to span bare metal and virtualized environments and then eventually private and public cloud infrastructure as well. And our goal there was you want to be able to invest in something, um, and in our world that's something that's also open as in Lennox but be able to run it anywhere. That's expanded quite a bit. That was good for a class of applications that really got it started. That's expanded now to kubernetes, for example, kubernetes is taking that from single machines to cluster wide deployments and it's really giving you that secure, flexible, fast innovation backbone for cloud native computing. And the balance there is just not for cloud native, we've got to be able to run traditional emerging workloads and our goal is let those things run wherever rail can. So you're really, you're based on open technologies, you can run them wherever you have resources to run. And then I think the third part of this for us is uh, having that choice and ability to run anywhere but not being able to manage. It can lead to chaos or sprawl and so our investments in our management portfolio and this is from insights the redhead advanced cluster management to our cluster security capabilities or answerable. Our focus has been securing, managing and monitoring those environments so you can have a lot of them, you can run where you want, but she just sort of treat it as one thing. So you are our vision, how we've executed up to this point has really been centered around that. I think going forward where you'll see us um really try to focus is, you know, first you heard paul announced earlier that we're donating more than half a billion dollars to open. I would cloud research and part of this reason is uh running services. Cloud native services is changing. And that research element of open source is incredibly powerful. We want to make sure that's continuing but we're also going to evolve our portfolio to support this same drive a couple areas. I would call out, we're launching redhead open shift platform plus and I talked about that combination from rail to open shift to being able to manage it. We're really putting that in one package. So you have the advanced management. So if you have a huge suites of cloud native real estate there, you can manage that. And it also pushes security earlier into the application, build workflows. This is tied to some of our technology is bolstered by the stack rocks acquisition that we did. Being able to bring that in one product offering I think is really key to address security and management side. Uh we've also expanded Redhead insights beyond Rehl to include open shift and answerable and this is really targeted it. How do we make this easier? How do we let customers lean on our expertise? Not just for Lennox as a service, but expand that to all of the things you'll use in a hybrid cloud. And then of course we're going to keep pushing Lennox innovation, you'll see this with the latest version of red hat enterprise, like so we're gonna push barriers, lower barriers to entry. Uh But we're also going to be the innovation catalyst for new directions include things like edge computing. So hopefully that sort of helps in terms of where, where we started when it was just Lennox and then all the other pieces were bringing to the table and why and some new areas. Uh We're launching our investment going forward. >>Yeah, great, that's great overview. Thanks for taking the time to do that. I think one of the areas I that's jumping out at me is the uh, advanced cluster management work you guys are doing saw that with the security peace and also red hat insights I think is is another key one and you get to read that edge. But on the inside you mentioned at the top of this interview, data workloads pretty much being, I mean that pretty much everything, much more of an emphasis on data. Um, data in general but also, you know, serve abilities a hot area. You know, you guys run operating system so you know, in operating systems you need to have the data, understand what's being instrumented. You gotta know that you've got to have things instrument and now more than ever having the data is critical. So take us through your vision of insights and how that translates. Because he said mentions in answerable you're seeing a lot more innovations because Okay I got provisions everything that's great. Cloud and hybrid clouds. Good. Okay thumbs up everyone check the box and then all of a sudden day too As they call day two operations stuff starts to, you know, Get getting hairy, they start to break. Maybe some things are happening. So day two is essentially the ongoing operational stability of cloud native. You need insights, you need the data. If you don't have the data, you don't even know what's going on. You can't apply machine learning. It's kind of you if you don't get that flywheel going, you could be in trouble. Take me through your vision of data driven insights. >>Yeah. So I think it's it's two aspects. If you go to these traditional traditional sport models, we don't have a lot of insight until there's an issue and I'm always amazed by what our teams can understand fix, get customers through those and I think that's a lot of the success red hats had at the same note, we want to make that better where if you look at real as an example, if we fixed an issue for any customer on the planet of which we fix a lot in the support area, we can know whether you're going to hit that same issue or not in a lot of cases and so that linkage to be able to understand environments better. We can be very proactive of not just hey apply all the updates but without this one update, you risk a kernel panic, we know your environment, we see it, this is going to keep you out of that area. The second challenge with this is when things go do break or um are failing the ability to get that data. We want that to be the cleanest handshake possible. We don't want to. Those are always stressful times anyway for customers being able to get logs, get access so that our engineering knowledge, we can fix it. That's another key part. Uh when you extend this to environments like open shift things are changing faster than humans can respond in it. And so those traditional flows can really start to get strained or broken broken down with it. So when we have connected open shift clusters, our engineering teams can not only proactively monitor those because we know cooper net is really well. We understand operators really well. Uh we can get ahead of those issues and then use our support teams and capabilities to keep things from breaking. That's really our goals. Finding that balance where uh we're using our expertise in building the software to help customers stay stable instead of just being in a response mode when things break >>awesome. I think it's totally right on the money and data is critical in all this. I think the trust of having that partnership to know that this pattern recognition is gonna be applied from the environment and that's been hurting the cybersecurity market people. That's the biggest discussion I had with my friends and cyber is they don't share the data when they do, things are pretty obvious. Um, so that's good stuff there and then obviously notifications proactive before there's a cause or failure. Uh great stuff. This brings up a point that paul come here, said earlier, I want to get your reaction to this. He said every C. I. O. Is now a cloud operator. >>That's a pretty bold >>statement. I mean, that's simply means that it's all cloud all the time. You know? Again, we've been saying this on the queue for many years, cloud first, whatever people want to call it, >>what does that actually >>mean? Cloud operator, does that just mean everything's hybrid? Everything's multiple. Cloud. Take me through an unpacked what that actually means? >>Yeah. So I think for the C I O for a lot of times it was largely a technology choice. So that was sort of a choice available to them. And especially if you look at what public clouds have introduced, it's not just technology choice. You're not just picking Kafka anymore. For example, you really get to make the choice of do I want to differentiate my business by running it myself or is this just technology I want to consume and I'm going to consume a cloud, native service and other challenges come with that. It's an infrastructure, not in your control, but when you think about a ceo of the the axes they're making decisions on, there are more capabilities now and I think this is really crucial to let the C i O hone in on where they want to specialist, what do they want to consume, what do they really want to understand, differentiate and Ron? Um and to support this actually, so we're in this vein, we're going to be launching three new managed cloud services and our our focus is always going to be hybrid in these uh but we understand the importance of having managed cloud services that red hat is running not the customers in this case. So one of those will be red hat open shift streams for Patrick Kafka. We've talked about that, that data connectivity and the importance of it and really being able to connect apps across clouds across data centers using Kafka without having to push developers to really specialize in running. It is critical because that is your hybrid data, it's going to be generated on prim, it's going to be generated the edge, you need to be able to get access to it. The next challenge for us is once you have that data, what do you do with it? And we're launching a red hat open shift data science cloud service and this is going to be optimized for understanding the data that's brought in by streams. This doesn't matter whether it's an Ai service or business intelligence process and in this case you're going to see us leverage our ecosystem quite a bit because that last mile of AI workloads or models will often be completed with partners. But this is a really foundational service for us to get data in and then bring that into a workflow where you can understand it and then the last one for us is that red hat open shift api management and you can think of this is really the overseer of how apps are going to talk to services and these environments are complex, their dynamic and being able to provide that oversight up. How should my apps be consuming all these a. P. S, how should they be talking? How do I want to control? Um and understand that is really critical. So we're launching these, these three and it fits in that cloud operator use, we want to give three options where you might want to use Kafka and three Scale technologies and open data hub, which was the basis of open shift data sides, but you might not want to specialize in running them so we can run those for you and give you as a C. I. O. That choice of where you want to invest in running versus just using it. >>All right, we're here with matt Hicks whose executive vice president prospect technology at red hat, matt, your leader at red hat now part of IBM and continues to operate um in the red hat spirit, uh innovating out in the open, people are wearing their red hat uh hoodies, which has been great to see. Um I ask every executive this question because I really want to get the industry perspective on this. Um you know, necessity is the mother of invention as the saying goes and, you know, this pandemic was a challenge for many In 2020. And then as we're in 2021, some say that even in the fall we're gonna start to see a light at the end of the tunnel and then maybe back to real life in 2022. This has opened up huge visibility for CSOS and leaders and business in the enterprise to say, Hey, what's working, what do we need? We didn't prepare for everyone to be working at home. These were great challenges in 2020. Um, and and these will fuel the next innovations and achievements going forward. Um again necessity is the mother of all invention. Some projects are gonna be renewed and double down on some probably won't be as hybrid clouds and as open source continues to power through this, there's lessons to be learned, share your view on what um leaders in in business can do coming out of the pandemic to have a growth strategy and what can we learn from this pandemic from innovation and and how open source can power through this adversity. >>Yeah. You know, I think For as many challenging events we had in 2020, I think for myself at least, it it also made me realize what companies including ourselves can accomplish if we're really focused on that if we don't constrain our thinking too much, we saw projects that were supposed to take customers 18 months that they were finishing in weeks on it because that was what was required to survive. So I think part of it is um, 2020 broke a lot of complacency for us. We have to innovate to be able to put ourselves in a growth position. I hope that carries into 2021 that drives that urgency. When we look at open source technologies. I think the flexibility that it provides has been something that a lot of companies have needed in this. And that's whether it could be they're having to contract or expand and really having that moment of did the architectural choices, technology choices, will they let me respond in the way I need? Uh, I'm biased. But first I think open models, open source development Is the best basis to build. That gives you that flexibility. Um, and honestly, I am an optimist, but I look at 2021, I'm like, I'm excited to see what customers build on sort of the next wave of open innovation. I think his life sort of gets back to normal and we keep that driving innovation and people are able to collaborate more. I hope we'll see a explosion of innovation that comes out and I hope customers see the benefit of doing that on a open hybrid cloud model. >>No better time now than before. All the things are really kind of teed up and lined up to provide that innovation. Uh, great to have you on the cube. Take a quick second to explain to the folks watching in the community What is red hat 2021 about this year? And red hat someone, I'll see. We're virtual and we're gonna be back in a real life soon for the next event. What's the big takeaway this year for the red hat community and the community at large for red hat in context of the market? >>You know, I think redhead, you'll keep seeing us push open source based innovation. There's some really exciting spaces, whether that is getting closer and closer towards edge, which opens up incredible opportunities or providing that choice, even down to consumption model like cloud managed services. And it's in that drive to let customers have the tools to build the next incredible innovations for him. So, And that's what summit 2021 is going to be about for us, >>awesome And congratulations to, to the entire team for the donation to the academic community, Open cloud initiative. And these things are doing to promote this next generation of SRS and large cloud scale operators and developers. So congratulations on that props. >>Thanks john. >>Okay. Matt Hicks, executive vice president of products and technology. That red hat here on the Cube Cube coverage of red hat 2021 virtual. I'm John Ferrier. Thanks for watching. Yeah.

(upbeat music) >> Hello and welcome back to theCUBES coverage of Red Hat summit 21 virtual. I'm John Furry, host of theCUBE. We've two great guests here, returning back CUBE alumni here to give us their perspective. Dave Linquist GM VP of engineering hybrid cloud management at Red Hat. Joe Fitzgerald, general manager VP of the management business unit Red Hat. Guys, welcome back to theCUBE. Congratulations, Red Hat summits, ongoing virtual. Great to see you. >> Thank you, John. >> Thanks John. >> So I'd love to get the low down. A lot going on the productivity this year. Looking back from last year, a lot's been done and we've been in the pandemic now, now circling back a full year. A lot's happened- a lot of productivity, a lot of clear visibility on, on what's working, what's not, you guys got some great news. Let's just jump right into it. What's the big announcement? >> So one of the things that we announced here at Summit, John, is an expansion of our Red Hat insights brand. Basically we announced Red Hat insights for our RHEL platform back in 2015. Over the years, we've increased the amount of data and visibility into those systems. Here at summit, we've now announced Red Hat insights for both OpenShift, and for the Red Hat Ansible platform. So it's a pretty significant increase in the visibility that we have to the platforms. >> Oh, so can you repeat that one more time? So the expansion is through which platform style specifically? >> So Red Hat insights is a way that we connect up to different platforms that Red Hat provides. Historically it was for Red Hat enterprise Linux realm. We've now expanded it to the Red Hat, OpenShift family, the platforms as well as the Red Hat Ansible automation platform as well. >> So a nice broad expansion and people want that data. What's what was the motivation behind it? Was it customer demand? Was it more access to the data? Just, was it on the roadmap? What's the motivation- where where's this going? What's what's the purpose of all this? >> Well, I don't think customers say, Hey, please, you know take more data. I think it's customers say, can you keep me more secure? Can you keep my systems more optimized? Can you help me set more things to automatic? And that requires that you get data from these systems that you can auto tune on, auto- secure, auto optimize. Right? So it's really all those benefits that we get by connecting to these systems, bringing the telemetry data that config different kinds of information, and using that on customer behalf to optimize secure to the systems. >> You know, one of the biggest trends I think now for multiple years has been observability with cloud native, more services are being turned on and off enterprises are are getting a lot of pressure to be modern in their in their application development processes. Why is data more important than ever now? Can you guys take a minute to expand on that? Because this idea of telemetry across the platform is a very interesting announcement because you're turning that data into value, but can you guys expand where's that value coming, turning into? What is the value proposition? Where are people seeing the, the, the key key value points? >> Well, a couple of points, John, as you started out is in a hybrid cloud environment with cloud native applications and a lot of application modernization and the current progressiveness of DevOps and SRE teams, you're seeing a lot of dynamics and workloads and continuous delivery and deployments that are in public environments and private environments, distributed models. And so consequently, there's a lot of change in dynamics in the environment. So to sustain these high levels of service levels to sustain the security and the compliance, the ability to gather data from all these different points, to be able to get visibility into that data. It'd be able the ability to process that with various analytics and understand what when something's gone wrong or when an update is needed or when a configuration has drifted is increasingly critical in that in a hybrid cloud environment. >> So on the telemetry piece is that in open shift as well that that's supporting that as in there has that work. >> It's it's in OpenShift, as Joe mentioned, it's in braille it's in V2 Ansible and the OpenShift space we'd have an offering advanced cluster management that understands fleets of deployments, clusters, wherever they're deployed however they're running infrastructure public private hybrid environments. And it also collects in the context of the workloads that are deployed on those on those clusters to multi-question burn. >> I want to ask you guys a question. I get this all the time on theCUBE. Hey, you know, I need more data. I have multiple systems. I need to pull that data into one kind of control plane but I'm being pushed more and more to keep scaling operations. And this becomes a huge question mark for the enterprises because they, they have to turn up more, more scale. So this is becomes a data problem. Does this solve it here? How do you guys answer that? And what was the, what would be your response to that trend? >> Well, I think the, the thirst for data, right? There's a lot of things you can do with more data. There is a point where you can't ship all the data everywhere, right? If you think about logs and metrics and all the data it's too heavyweight to move everything everywhere. Right? So part of it is, you know, selecting the kind of data that you're going to get from these systems and the purpose you're going to use it for. And in the case of Red Hat, we take data from these different systems, regardless of whether they're deployed bring it in, and then we did predictive analytics against that data. And we use that telemetry that can take that health data right to do everything from optimize for performance or security costs, things like that. But we're not moving, you know, huge quantities of data from every system to Red Hat in order to, you know, pour through it. We are very selectively moving certain kinds of data for very specific purposes. >> Dave, what's your take on that because you know you got to engineer these systems. What's the optimized path for data? Do you keep it in the silo? Do you bring it together? What's the customer's view on, on how to deal with the data? >> Yeah. It is a complex problem. No doubt. You don't want it to be pulling all the data and trying to transmit all that data back into your analytics system. So you ended up curating some data, some of it you afford on often it's done under it will be done under control of policies. So that data that is sensitive, that should stay within the environment that it's in, will stay, but curated or alerts or information that's particularly relevant say to configurations, updates, any any of that type of information will go up into the analytics, into the insights. And then in turn, the alerts will come back down in a manner that are presented to the user. So they understand what actions need to be taken place whether there's automated actions or or they have to get approvals to maybe make an update to a certain environment. >> All right, you got telemetry, data power, the the advanced cluster management ACM. What's the overlap of the visibility and automation here. Can you guys talk about that? >> Well, let's say it's a great question, John what we'd like to do is we'd like to sort of separate the different areas. There's the seeing, right. And what's going on in these environment. Right. So getting the data analyzing it and determining what needs to be done. And then the, you know the recommendation of the automation. As Dave said, in a lot of environments, there's a process of either approvals or checkpoints or, you know evaluation of the changes being made to the system. Right. So separating the data and the analysis from the what do you want to do at this and making that configurable I think is really powerful. >> Yeah. I mean, that's, I mean I think that's the number one thing is like, you know everyone always asks, what do you optimize for do you optimize for the automation or the visibility? And I think, you know, there's always a trade-off and that's always interesting question David- love to get your thoughts. If someone asks you, Hey, I'm a I'm I have a team of people. What do I optimize for? The visibility or the automation or both? Is or is there a rule of thumb or is there a playbook? What w how would you answer that question? >> Well, there's a couple of things. I first, I think the, the ability to pull the data together to get visibility across the environment is critical. And then what becomes often complex is how the different disciplines, how the different parts of the system are able to work together on common understanding of the resources common understanding the applications. That's usually where systems start falling down. And so it's too siloed. So one of the key things we have with with our systems, particularly with OpenShift and row and with ACM and Ansible is the ability to have the common back lane and the ability to have a common understanding of the resources and the applications. And then you can start integrating the data around that common, those common data models and take appropriate actions on that. So that's how you ended up getting the visibility integrated with the automation. >> When you think about this, Joe about the security aspect of it and the edge of the network which has been a big theme this year and going into next year, a lot more discussion just the industrial edge, you know, that's important. You got to take all this into account. How do you, how would you talk about folks who are thinking about embedding security and thinking about now the distributed edge specifically? >> Right. So we thought it was complicated before, right? It goes up a notch here, right? As you have, you know, more and more edge applications I think at the edge, you're going to want automated policies and automated configurations in force so that when a device connects up to a network or is, you know analyzed that there's a set of policies and some configurations and versions that need to be applied to that device, these devices, aren't always connected. There's not always high bandwidth. So you basically want a high degree of automation in that case. And to get back to your early point there are certain things you can set like policies about security or configuration. You say, I always want it to be like this and make it so and there's other things where they're more you know, complicated, right. To, to address or have regulatory requirements or oversight issues. And those things you want to tell somebody I think this should be done. Is this the right thing to do? Is it okay? Do it, but at the edge you're going to have a lot more sort of lights out automation to keep these things secure, to configure. Right. >> It's funny. I was, some of the Ansible guys are talking about, you know code for code, changing code all the time and dynamic nature of some of the emerging tech coming out of the Red Hat teams. It's pretty interesting. You guys have going on there, but you know, you can bring it down to the average enterprise and main street, you know enterprise out there, you know, they're looking at, okay I got some public loud. Now I got hybrid. I'm going a hundred percent hybrid. That's pretty much the general consensus of all the enterprises. Okay. So now you say, okay, if I understand this correctly you got insights on REL, OpenShift and Ansible platform. So I'm, am I set up for an open hybrid cloud? That's the question I want to ask you guys does that give me the foundation to allow me to start the cloud adoption with an, a true distributed open way >> I'll I'll offer to go first. I think there's a couple of things you need in order to run across hybrid clouds. And I think Red Hat from a platform point of view the fact that Red Hat platforms run across all those different environments from the public cloud to on-premise and physical vert to edge devices. Now you have consistency of those platforms whether it's your traditional on REL, your container based workloads on shift or automation that's being turned in by Ansible. Those are consistent across all these different hybrid cloud environments. So reduces the complexity by standardizing those platforms across any and all of those different substrates. Then, when you can take the data from those systems bring them centrally and use it to manage those things to a higher degree of automation. Now you take an, another sort of chunk of complexity out of the problem, right? Consistency of getting data from all those different systems being able to set policies and enforce things across all those distributed environments is huge. >> Yeah. And then, you know, it fills in the gaps when you start thinking about the siloed teams, you know, the, the, I think one of the messages that I've been hearing out of Red Hat Summit in the industry that's consistent is the unification trend that's going on. Unifying development teams in a way that creates more of an exponential value curve rather than just linear progressions in, in traditional IT. Are you guys seeing that as well? I mean, what's your take on this? That's that piece of the story? >> Well, I think the shift that we've seen for the last few years actually quite a few years with DevOps and SRE is started to bring a lot of the disciplines together that you mentioned that are traditionally silos. And you're finding the effectiveness of that is really around many of the areas that we've been discussing here which is open platforms that can run consistently across a hybrid environment, the ability to get data and visibility out of this platform. So you can see across the distributed environment across the hybrid environment and then the ability to take actions in Bourse or update environments through automation is, is is really what's critical to bring things to to bring it all together. >> Yeah. I think that's such an important point, Joe. You know, I was talking with Chris right around and we we've covered this in the past red hats success with academics in the young people coming into in the universities with computer science. It's not just computer science anymore. Now you have engineering degrees kind of cross-disciplinary with SRS is SRE movement because you're looking at cloud operations at scale. That's not an IT problem anymore. It's actually an IT next gen problem. And this is kind of what, there's no real degree. There's no real credential for, you know large scale hybrid cloud environment. You guys have the mass open cloud initiative. I saw that going on. That's some really pretty big things. This is a, a change and, and talent. What's your, what's your view on this? Because I think people want to learn what what do I need to be in the future? What position? >> So John it's a great question. I think Ansible actually addresses a number of the issues you brought up, which is, you know historically there've been different tools for each of the different groups. So, you know, developers had their favorite set of tools and different, IT areas their favorite set of tools and technologies. And it was sort of like a tower of Babel. People did not share the same, you know sort of languages and tools. Ansible crosses both your your development test and operational teams. So creates a common language, now that can be used across different teams. It's easy to understand. So it sort of democratizes automation. You don't have to be deeply skilled in some, you know misspoke language or technology in order to be able to do some level of automation. So I think sort of sharing the same technology and tools I'd like an answer, more democratizing it so that more people can get involved in automating sharing that automation across teams and unifying those worlds is huge, right? So I think that's a game changer as well in terms of getting these teams work holistically integrated. >> Yeah. And there's also a better together panel on the Ansible and advanced cluster management session. Folks watching should check it out on on the virtual event platform on that point while I got you here on that point, let's let's talk about the portfolio updates for advanced cluster management for Kubernetes, what's new since the Ansible Fest, Ansible Fest announcements >> There's quite a bit that's been new since Ansible Fest. Ansible Fest well actually going back to Summit last year we introduced advanced cluster management. For years, we've been seeing the growth of Kubernetes with cloud native and clusters. And what ACM really allows enterprises to do is is scale out their deployments of OpenShift. Well, one of the things we found is that as you're deploying workloads or clusters or trying to take care of the compliance, the importance of integrating that environment with the breadth of capabilities that Ansible has in automation. So that's what we announced that at Ansible Fest following last year's summit what we've done is put a lot more focus on that integration with Ansible. So when you bring up, provision a cluster maybe you need to make some storage or security configurations on behalf of that cluster or if you're taking care of the compliance how do you remediate any issues with Ansible or one of the things that get shown a lot, demonstrate a lot with customers like is when you're deploying applications into production, how do you configure the network? Do the network configurations like a load balancer maybe a ticket into your service management system along with say a threat detection on your security. So a lot of advances with ACM and the integration with a broader ecosystem of IT, in particular with, with Ansible >> What's the ecosystem update for partners? And this has comes up all the time. I want to make sure I get this in there. I want it, I missed it. Last time we chatted, you know, the partner impact to this. You mentioned the ecosystem and you've got native Coobernetti's, non-native what's native to open. You guys have a lot of native things and sometimes it's just support for other clouds. So you start to get into the integration questions. Partners are very interested in what you guys are doing. Can you share the partner update on how they play and what impacts them the most here? >> Yeah. On the events, cluster management ACM front first with this integration with Ansible that actually allows us to integrate with the wealth of partner ecosystem the Ansible apps, which is huge. So that's, that's one, one space. And then the way ACM works, this policy desirous state model is we've been able to integrate with a large number of partners around particularly the security space model the service management space, where they, where we can enforce the use of certain security tools on the on the clusters themselves. So it's really opened up how quickly partner offerings can be integrated into the OpenShift environment at scale across all the clusters that you want, that you need to support it on what the appropriate configurations and policies >> I got to ask you on the insight side you mentioned the expansion across the platform. Now, if you go out and take out to the ecosystem, you know there's guard rails around governance how far can partners push their data in terms of sharing? That's something that might come up when you comment on that. >> Sure. So Red Hat, you know, takes, you know our customer data very seriously. We're a trusted partner to our customers. So the data that we get from systems we make sure that we are following all of the governance and oversight necessary to protect that data. So far, we have basically been collecting that data and using that data at Red Hat. Our plan really is to allow partners with the right degree of governance and control to be able to use some of that data in the future, under the right conditions whether it's anonymized or aggregated, things like that to be able to take that data and to add value to customers if they can enrich customers or or help customers by getting some access to that data without every vendor or partner, having to go out to systems and having to connect and pull data back. That's a pretty tough situation for customers to live with. But I think that fact that we're ahead is trusted. We've been doing this for awhile. We know how to handle the data. We know how to provide the governance. But our plan really is to enable partners to use that data ecosystem. I will say that initially what they had said about ACM and partners, Ansible has been working with partners on the automation side at a very large scale, right? So if you look at the amount of partners that are doing automation, work with us we have some pretty strong, you know, depth there. But in terms of working with partners, our plan is to take the data ecosystem, expand that as well. >> It's really a nice mix between the Ansible OpenShift and then REL, do you guys have great insights across now? I think the open innovation just continues to be every year. I say the same thing. It's almost like a broken record but every year it just gets better and better. You know, innovation out in the open you guys doing a great job and continuing and now certainly as the pandemic looks like it's coming to an end soon, post-pandemic, a lot more projects are being worked on a lot more productivity, as we said at the top. So to end the segment out I'd love to get you guys to weigh in on what happens next. As we come out of the pandemic, the table has been set. The foundation's there, cloud native is continuing to accelerate rapidly in the open OpenSource, going through them on another level. What's next what's, what's going to what's next for customers. Are they going to continue to double down on those? The winds they're going to shut down certain projects. What happens after this pandemic? How do people grow, Dave? We'll start with you. >> Well, I think, yes we all see the light at the end of the tunnel, John. It's great. And I think if a positive, is it really throughout this? We've been accelerated in the digitization and at modernization cross the board across industries. Okay. And that is really teaching all of us a lot about the importance of how do you start managing and running this at scale and securing this at scale. So I think what we'll see coming out of this is just that much more effort, open ecosystems. How you really bring together data across insights? How do you bring in increasing the amount of analytics AI to now do something turn that data into information that you can respond with and that in turn, close it, closing the loop with automation against or against your hybrid cloud environment? We're just going to see acceleration of that occurring. >> Awesome, great insights there. Open data insights, automation, all kind of coming together. AI. You don't have AI in your, your plans. Someone was Wall Street was joking. That's going to be the future stable stakes get listed on Wall Street. You got to have some sort of AI piece. They have great insight, Joe, your take on what's next? What, what what's going to what's going to happen as we come out of the pandemic? >> Yeah. We've definitely seen people, you know advance their digital transformation. And I don't think it's going to stop. Right? So the speed scale and complexity or just put more pressure on teams, right? To be able to support these environments that are evolving at light speed. So I think Red Hat is really well positioned and is a great partner for folks who are trying to get more digital, faster trying to leverage these technologies from the hybrid cloud to the edge. They're going to need lots of help. Red Hat is in a great position. >> Okay. >> You guys doing great work, Dave Linquist, Joe Fitzgerald. Great to have you back on again. Open, always wins. And as end users become much more participants in the open source ecosystem and user contributions and user interactions software at scale, it's now a new come next generation commercial environment, You guys are doing a great job. Thank you for sharing. Appreciate it. >> Thank you John. >> Thanks John. >> Okay. Red Hat Summit 21 CUBE coverage. I'm John Furrier getting all the action from the experts who've been there, done that living through it, being more productive and have bringing benefits to you being open source. Thanks for watching.

>>mhm Yes. Welcome back to the cubes coverage of red hat summit 2021 virtual john for your host of the cube paul. Comey who's here is the president and Ceo of red hat cube alumni paul always great to have you on the leader of red hat now President and Ceo for a year I think about a year now we're looking at under your belt now part of IBM Great to see you. >>You too nice to see you again john. >>So we've talked many times on the Cuban now. It's kind of playing out in real time. The software world with open source has gone mainstream. The conversation was moved to the cloud. Okay. People move to the cloud. Cloud native emerges devil has been around for a while. But now the conversation is cloud for the enterprise that uh, the enterprises, it's a tough world. You gotta, it's complicated is a lot of legacies, a lot of value and you want the new stuff. This is what the conversation is now. It's shifted to I got cloud, it's hybrid. What's your reaction to that? >>Well, you know, it really is, as you say, it's complicated but it's evolving and really, really fast. I mean, you know, I think you remember we've been here a lot. You first remember first software is eating the world and open source software is eating the world and in every every company is becoming a software company. All true. But that evolution continues today with the proliferation of hybrid cloud environments that it encompasses everything from data centers to public cloud services to And even now we'll talk about two for far flung edge deployments. That's all now part of the cloud. I mean, this is all what makes up hybrid. I like to always say that Hybrid really is the new data centers but now see IOS and I thi leaders, they need to reconsider what their roles, what their role here is and the way we look at it as every C I O now needs to be a cloud operator because because Hybrid is what their environment is now today, that used to be all in their data center. So, so but one of the things that really makes a choice even more important and its leaders, they need to address address specific needs, um not only to the organization, but even as they change and evolve in this because it really is a dynamic environment, I mean think about it and just mentioned edge and how how important that is to see IOS, we weren't even talking about that two years ago, so, so it's not a single answer here, right? Um and and you know, and there as there wasn't a single answer when it was all in one building or in one data center, but now it's even it's even more complex. So, so we need to enable really a new wave of cloud operators here with technologies that can be deployed as cloud services as well as on premises. We'll talk more about this too, but and we'll talk about this at the summit. We talked about the summit. Cloud services become really important, especially managed services, for example, because, um because we're so complex, Hybrid brings so much power, but it is complex. You know, see I need help with this, they need help managing this now. And so that's really where a lot of our focus is today. >>It's interesting you say there's no single answer. I would agree with you because it's now you can actually do a lot more customization with cloud and Hybrid. I think there's a general sentiment and directionally correct answer uh in the industry is that hybrid is operating model right? And I think you guys are have a whole division of SRS google talks about this all the time and their cloud site reliability engineers. And I think you're seeing that in educational institutions which we'll talk about. But I think this idea of cloud scale as the new I. T. And you mentioned hybrids, the new data center. You know, I don't I don't want to offend my I. T. Friends out there but they're kind of all realizing it to that if they don't understand how to operate cloud scale they'll be irrelevant and they're and they understand that their jobs are not just provisioning storage, networking and servers. Those are now involved in a hybrid architecture. And by the way, there is no one recipe, it's dependent. Each enterprise can have its own set of architecture based on their workloads again. So I buy that no single answer, but there is hybrid and I think it's pretty well understood. I mean, do you agree with that? >>I absolutely agree with that. But let's take a look at this, unpack it a little bit and take a look at the building blocks a bit. Right. Um, you know, we talked about open sources, what's driving all of this now and and everything we're talking about here is built in and around Lennox and it was only possible because Lennox was so open, so available and became so powerful, that's now been the platform that all this new innovation is built around. I mean, I oftentimes saying it's true the cloud just wouldn't be here had Lennox not only made its way in the open source development environment, but made its way into the enterprise to enable it to companies like us that make it enterprise ready, secure etcetera. So I think that's really an important thing to understand here. So when you talk about skills that the Ceos need certainly SRE skills, operation skills etcetera, but they also need Lennox skills and even open source skills. So so I think I think that's important, everything that's coming down the road and in in this space in um in his open source based and built in and around Lennox things like ai quantum computing, autonomous vehicles um IOT in and out to the edge all built on a foundation of Lennox and open source. So we see it in the enterprise everywhere now. I mean a survey where you know we did a survey out there and looking at the survey of C I O s out there, open is predominant out there, Lennox is predominant out there in hybrid is predominant and growing in a pretty big clip every year. >>You know, paul, I want to get your reaction to something because this may be kind of a dot connecting moment for me because I want to get your thoughts on this because it's a it's a pattern I'm seeing emerging now multiple times and usually I thought this was kind of a one off, but I'm starting to see it. So I'm going to get your thoughts on this. You guys have been super successful with open source in the enterprise, Super successful over decades, building a community and an ecosystem now with open source with with cloud Native, specifically we're seeing end users participating more in the, in the contribution starts out with the hyper scale ear's but now you're seeing kind of, I would call general purpose mainstream enterprises contributing projects, not necessarily their expertise, but they've been participating in taking the goodness of open source and bringing that into the into the enterprise. And I'll see you relying on you guys as well. But now I'm starting to see the pattern where people are relying on you to bring your community to them and they merge their communities with you guys and being kind of a steward there, is that a pattern? Do you see that evolving? Because we've heard that on multiple interviews on the cube where we've heard end users say we love the red hat ecosystem and and that seems to be more and more about they want to be building their ecosystem. So you did it for yourselves, you did it for the industry. Now, enterprises want this service is this is this is a pattern. And what's your reaction to that? >>It actually is a pattern because it's actually one of the reasons why innovation is moving so quickly right now. As I just said, you know, you know, this whole area here in infrastructure and cloud and development environments, Hybrid included. It's all built in and around, it's all built in and around Lennox. And in the past, what's happening and driven by open source development in the past? What happened? Look at the old fashioned way, right, where a company like us would be in a company, software company, not like us, but any old software company would be, you know, in their stovepipe, talking to their customers, getting their requirements and then bringing those requirements back from the customer base and then trying to work that into their products over time, get that back out to the customer to test it and try it, see it as it works. That's probably a five year, there's probably a five year journey, uh, for big, big requirements for big change requirements you look at now with, with actually end users now participating in upstream development, they're building their requirements into that upstream, which is our development environment. And actually that's what feeds our products. And so we've cut out the middleman, if you will completely in there now when we're building those requirements into our future future, R and D work in the upstream and then we bring that down into a product back into their enterprise for them to use in production. So it cuts out years of time for that innovation to get from concept to building to product, rising to production. And, and I think, you know, john, that's one of the big reasons why that customer base participating is one of the big reason why we're seeing innovation move like we've never seen it before in the enterprise, which in the old days that was a stodgy place where they didn't want to move very quickly. >>Yeah. And the values there, I mean I think it's clear what the pandemic we get to this towards the the last last talking track here. But with the pandemic I think it's pretty clear what the value is and the speed to capture opportunities and growth. I think enterprises are realizing that I think the power of the ecosystem is a modern error kind of phenomenon that is now kind of showing its its value and clearly in the market. And I think people who harness communities and ecosystems not try to fork them but connect them and and intersect them and kind of played well together. So again this is an open source concept kind of re imagined so we'll keep an eye on that. So, um, I want to get to your comment in the kino you mentioned at the top here every C I. O. It has to be a cloud operator. You know, that reminds me of all the start ups and all the positioning statements. Every company needs to be a software company. Every company needs to be a media company. Every company needs to be a cloud operator. So I love that. What does it mean? Because I could say, hey paul, I have a cloud, I'm working on amazon Or is that it? Or wait a minute as yours got, I got 365 over here and I'm using big query over here. I might use oracle over here. I mean all these multi cloud conversations. So it's confusing. >>Yeah. Tell me what, you know, if you look at, if you look at it, we were really one of the first ones to really build around this hybrid, this hybrid concept. And the reason why we were one of the first ones is because what amazon hit the world 12 or 13 years ago or something like that, They were the first major cloud and at the time that the narrative was that, you know, every application was going to move to the cloud tomorrow. Right well, because as I said earlier, everything is built in and in and around open source. And legs were very involved with our customers as they tried to move those first applications to the cloud. So certainly is a lot of value and moving to the cloud. But our customers quickly realized with us helping them, quickly realized that you know what, this is great. But not every application suited for the cloud, um for any cloud, but also I may want to run multiple clouds because another cloud provider over here might have a better service than this particular service over here, vice versa. And so we were in the middle of that. So one of the decisions we made seven or eight years ago, everything we did in that last seven or eight years around the portfolio, whether it was building products, m and A, requiring new companies etcetera, was built around that hybrid portfolio. What that means is a common platform that sits both on premise and bare metal machines. Virtual machines, private clouds on premise multiple clouds across out in the enterprise, that common platform so that developers, operators and the security people have that common platform to build with because just like in Lenox, even though they are all derived from open source upstream, they're all different, they all make different choices and how they're going to configure themselves. So, so that's important. So now we're out there with these multiple clouds. One of our surveys we see our Ceo is telling us now that You're using on the average I think six Clouds today and they expect that to go 8-10 over the next 3-5 years. So how are they going to manage that? How are they going to secure that? How are their operations people going to operate with that? That's all the things that we've been working on over the last number of years. So from that common platform, which is sort of the basis which is open shift to underneath it, which is the Linux operating system, which is well that spans all those footprints that I talked about. And then also you look at one of the latest trends is as well as manage services because what customers are now telling us is okay I got this environment that this hybrid is now my data center. It means I have to worry about these apps all in different footprints. Um I want to the platform to act like a cloud in some cases I don't want to I don't want to even manage it. I want you to manage it for me because for many reasons I want great up time. I might not have the right skill sets in my organization and so I want you to manage it. And so that's where we develop managed services and that's where we have set a large group today large SRE group that's providing those managed services no matter where our platform runs for our customers. Also, what I talked about in my keynote today is that to support that thought process is that we're doing a lot of research in this and so, you know, in a typical computer science research world, you know, of the past, you might really be into the into the real computer science of Research. We with the consortium around mass Open cloud with Boston University, MIT, Harvard Northeastern with this consortium. We're running mass Open cloud on all Red Hat with the collaboration of these universities and we're really focusing on the sorry aspect of it. What do we need to manage it? What do we need around automation to manage it? What do we need around ai to manage it? What do we need for tools to manage it? And and that's really goes down to what I fully briefly said in the beginning, is that every C I O N I T uh executive now has to be their own cloud operator because they are effectively stitching all these disparate clouds together. So that's where a big part of our focus takes us all the way from, You know, upstream development to product to the research we're doing for the next 3-5 plus years. >>You know, I gotta say the hybrid cloud is a new data center which is implying I T in the cloud operators with C X O S and C IOS is interesting because it's validated by Mckinsey's recent report that came out that said there's a trillion dollars of untapped value in one retrofitting existing infrastructure and operations and to net new operate use cases that the cloud enables. So there's clearly not two categories of value proposition that businesses are facing. One is, you know, kind of take care of the existing and then also bring in the new that cloud enables. So, you know, I think that's really key and that will drive the business leaders to foresight, if you will to be agile and adaptive to that. So so totally agree on that. I love this open cloud initiative, you mentioned the mass open cloud which I know is kind of like this beanpot for techies, um people who know what that means, uh it's in the boston area these institutions um this is gonna be a training and an opportunity to train the next generation and if you take it to the next level cybersecurity is also in this kind of net new novelty, interdisciplinary components. So you got engineering which is like devops engineering and then Systems Engineering and Computer Science intersecting together with kind of this data discipline. So it hits cybersecurity which is a board level conversation, it hits the new business model opportunities which is a driver, this is new, this is there's no pre existing curriculum. What how do you explain that to heads of the departments and the deans of these institutions saying, you know, it's an engineering thing. No, it's computer science thing. No, it's a it's a business school thing with data science. What's your what's your conversation with folks in the industry when you say this is a different thing? >>Uh you know, the university, you know, the university is getting, it was actually one of the one of the first things this is you know what you'll see. You know, I talked to uh dr bob Brown from President bu earlier in an interview and and this is what we imagined with them early on and even they brought those disciplines together now in in in what they call a harry institute, where to bring data, computer science engineering as you say. And now even operations, it's almost like, you know, systems engineering on steroids, it's a really big spanning system. And so so the universities are starting understand that's why these universities in the consortium, that's why we're working here. But also, you know, the industry's kind of learning it the hard way because now that they get some of their developers starting to move some of their application developments out into one, maybe two clouds and having the now they have to figure out how they're going to do all those things that we talked about, develop, secure operated. So they're they're learning the hard way that this is the new discipline because that's reality. I also think that, you know, as I said, like anything in tech, we always say this is going to happen tomorrow. I also think, like I said, when when cloud first came came out, everybody saying, I'm moving every app to the cloud tomorrow. We even had customers that bought into that said we're moving going full board but they realized once they get into it it wasn't practical. Don't take me wrong. Cloud brings a ton of value here but from a practical perspective it's going to be some apps and across many clouds and and so now they're having to deal with the I. T. Execs and the C. I. Was having to deal with it. So they're learning really fast because of the reality that they have to deal with. Now having said all that to it also brings up why managed services you're seeing so popular right now because as that's moving so fast they just don't have the skills necessary in many cases to really operate and run in this in this type of environment. It brings so much power but the skills aren't necessarily there in the industry. So that now you see the connection between the industry where we sit and even the university now looking at this whole big problem as as you put said, john, actually a new discipline, >>I think, I think, and I think one final leg of a three legged stool is at the business schools because when you think about systems programming, you mentioned that and you know, I love to go back in history and look at the history of operating systems. And you know, paul, we've talked us in the past and you guys know a lot about operating systems from a technology standpoint, it's not just about a productivity suite for a user or a department with the system, it's a company that needs to be programmed. So when people want to globally operate their business, that software defined this isn't now and this is now happening, right? So this the new leaders in these companies that want to run these global companies that scale operate them, just like operating the business not necessary. Operating a tech or shiny new toy, have to build the operating system for the business. To me, I think that's where I see IBM looking at cloud differently and saying, hey, this is an operating system under the covers for the business. The applications are multi fold from, you know, an application for productivity to an edge device, industrial or consumer user work at home. I mean it's a plethora of applications. What's your reaction to that? And you you see the same thing? >>I mean frankly, I think this is an area that a lot of the infrastructure players missed in the past. And I think I think this is what IBM saw with with bringing us in as well. It's all about the application. You know, I said earlier that, you know, we said every every company was a software company is true. And so that means the companies are running their businesses on these applications. So it's all about the app and I think a lot of infrastructure companies miss that. And and so with Hybrid now you have that ability to run the app wherever makes the most sense for for a whole host of reasons. And so now, but now comes the complexity of all of that. I think, I think IBM with bringing us in saw that that Hybrid was maybe as big, if not a bigger opportunity than cloud itself because of of the complexity it's going to bring, the power is going to bring. But also the complexity is gonna bring. I see that's why, you see Arvind, I sort of doubling down the entire IBM company on on hybrid services that are that are going to be really important here, that they provide these applications on top that are going to be really important, but that have to be architected in such a way that they can run in a hybrid environment. And finally there's all the infrastructure and tools and development pieces that we bring to the table. So, So yeah, I think I think are really, really understood that as they made the decision to bring redheaded, >>I talked to a center all the time and they also have this kind of concept of re factoring and reprogramming your business. Uh, it's not, it's a holistic view. This is kind of what's happening. So my final question for you is as as that becomes software enabled and programmed if you will with applications the business with many different subsystems in there. Um a lot of companies now looking at the light at the end of the tunnel with the pandemic and they're seeing vaccines coming out. Some say vaccines will be pretty much everywhere, everyone over 12 by the fall. So we're back to real life. There's gonna be a pullback of some projects on doubling down on others. As you as you mentioned, what are we doing? We're starting to see hybrid as companies come out of the pandemic, they're all jockeying to make sure that they have either done their work to re factor or reposition, reprogrammed their business and be set up for net new opportunities. >>What >>do you see as a growth model or growth opportunities for companies? You want to come out with a growth strategy out of the gate of the pandemic. What's your thoughts? >>Well, I mean, I think you have to plan for companies have to plan for your workforce to be anywhere, but in order to be anywhere in and to be productive, you need you need services like we're on right now for example, but you need the infrastructure to be able to do that. You need you need a way for your customers if you buy the fact that every company is a software company, you're running a business through their applications either way for your customers to be able to interact with you anywhere from where they are anywhere in a real time way. And so I think that's why from our perspective, things like that we're pushing a lot on the edge. Now, that's why you're seeing the hybrid cloud moved all the way out into the edge and you can see it in every vertical, you know, in the telco space. The edge means you gotta do, you have data and compute that needs to be done on the set on the cell tower in the manufacturing world. You have the state and compute that needs to be done on the factory floor, in the retail vertical. We see the edge really being significant in all these verticals, but but that edge is now extends that hybrid data center that we've been talking so much about. So even though you have all these edge devices way out there on the edge, it's a critical part of the business. So you have to have, your developers need need to be able to develop for it, you need to secure it, you need to and you need to operate it and manage it. So now, you know, in a very short period of time, hybrids taken on another dimension, bringing you out to all these points on the edge which is the same but slightly different in every vertical. Now comes complexity and that's why automation is so important because with that power comes complexity but it's going to take automation to keep it all running, >>paul. Great insight. Thanks for coming on the cube. Open innovation out in the open with with you guys again continue. And the focus of the evolution of software and the cloud with enterprise I. T. Clearly a lot of innovation and your contribution to academia and the mass open cloud and all the open cloud initiatives, phenomenal. The world's going. Open source and continues and continues. Doesn't stop. The operating system of businesses is coming and you guys are well positioned. Thanks for coming on. >>Thanks again john. Always a pleasure. >>Okay paul, Cormier, President Ceo of Red Hat here on the Cuban, john for your host. Thanks for watching. Yeah. Yeah. Mhm mm.

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

(upbeat music) >> Hello everyone, I'm John Furrier here in the Palo Alto theCUBE studios. I'm the co-host of theCUBE. Also co-founder of SiliconANGLE Media. We're here for some big news from Veritas. We're with Eric Seidman, who's the director of Solution's Marketing for Veritas. Veritas is introducing today and the press release is on the wire, Veritas Predictive Insights. Eric, thanks for coming in today and sharing thew news. >> Thanks John, absolutely, thanks for having me. >> So you guys have a unique new thing for Veritas. Not new to the industry, but new in capabilities, called Predictive Insights. I know Dave Vellante is actually linked on your press release and covered it in Chicago as an embargo. This is exciting news for Veritas because you guys have so much customer installed base, tons of data. Talk about what this new product is. What's the news? >> Well, thanks John, actually the news it's pretty exciting. Our customers are very excited and receptive about it. What it's actually doing is helping our customers reduce both planned and unplanned down time. And the way we're doing that is with an analytics engine that we've developed that's taking all the data from over 15,000 of our appliances around the world. We've been collecting that data for three years. We have hundreds of millions of data points from that. And we're utilizing our own AI ML engines that we've created to be able to predict things in customer's environments that may cause them down time or outages, and fix those before they happen. That's why our customers are really exciting about it. >> So how much does this cost? >> Well, it doesn't really cost anything. It's a value add. You know if our customers are utilizing our Veritas auto support services today, then as of yesterday, the service is turned on and we're already looking at their systems and creating this intelligence on them. >> So this is immediately valuable. >> And immediately evaluate those. >> So this is a new product from Veritas that takes existing operational data from your customer's environment. >> Correct. >> You guys are matching in your corpus of meta data. >> Exactly. >> A telemetry data, what, hundreds of millions of signals, call center, real log data, real outages and real things. >> Right, right. >> And creating machine learning and AI on top of it to extract value for you guys or for the customer? >> Well it's really for the customer. The benefit for the customer is that we have insights into you know our world wide universe of customers. But we can look at individual systems and say, why is this one operating differently than the others? And then the machine learning will actually determine that the ones that are operating really well have this patch and this patch installed. You know those types of things. And then we can apply that learning and that model to a particular customer's system. >> And they get a dashboard. >> And they get a dashboard that'll highlight what we call the system reliability score. So there's this, you know in big enterprises there's a lot of fatigue associated with events that are occurring all the time. You think of an enterprise, we have customers with many, many just net backup appliances alone. But you think of their entire infrastructure and all the alerts that they're getting. It creates a lot of fatigue. A lot of things go unfixed because they're minor events, like maybe a patch needs to be installed or a firmware update. While they're fixing the more hair on fire problems. But then ultimately those what looked like smaller events build up and build up and then they create outages. So what we're able to do is to identify which systems have potential anomalies. Highlight those very visually. Then they can drill down and we'll have prescriptive maintenance that can be taken to improve that. >> So site reliability score, we'll get to that in a second, I think that's a big deal. I want to read the press release headline. >> Okay. >> Veritas's Predictive Insights uses original intelligence AI, machine learning, ML, to predict and prevent unplanned service. Now the key word there is unplanned service. This is kind of the doomsday scenario for customers. They got a large data center or large infrastructure devices. Unplanned basically means an outage, if something happens, something bad happens. >> Yeah, something bad happens. >> And no one likes that, so what you guys are doing is giving them a valuated dashboard that taps into a product. So if, correct me if I'm wrong, but if a customer that has Veritas, if they have the products, they get the service. If they become a customer, they now have the capability built in out of the gate. >> Absolutely, right. >> And so they see all this, so you're taking all the data from years of experience. >> Yeah, exactly. >> Giving them a dashboard to help them look at unplanned down time type scenarios, and give them specific actions to take, particularly analytics and prescriptive analytics for them. >> Exactly, so what we're trying to really achieve for our customers is to use that intelligence and machine learning to identify things that may cause an outage in the future and prevent that outage from occurring, causing that down time, by taking remedial action in advance of that happening. And that's the beauty of Predictive Insights. That's really what it's providing for our customers. >> So you guys have this always on feature called auto support feature. >> Correct. >> That kicks in and it brings the system reliability score, SRS. I think this is important. I want you to explain this, I think this is a trend we're seeing certainly on the Cloud side of the market. Google has pioneered this concept called site reliability engineer over years of practice and they make their infrastructure work great. So we know that that kind of concept of having reliability, you guys are now giving a score to each appliance. >> Correct. >> It's almost like a health detector or like credit score. >> Definitely, credit score is a good analogy of that. >> So explain SRS, what's it mean for the customer and what's the impact to them? >> Yeah, so I don't know if you ever like, maybe you use one of those credit scoring apps os something like that, where it's monitoring your credit from three different agencies or whatever. That's kind of what we're doing, only the data sets are coming from a much broader set of appliances, right. But we're showing you your system reliability score, credit score if you will. And then we're showing you very prescriptively the processes you can take to improve your credit score, if you will, or your system's health and reliability. So that might be installing a firmware patch. Installing software update, things of that nature. Replacing some drives that may fail in the future. And all of those steps will then increase that liability score. >> And also you see in the hacking world, you know that one of the biggest parts of security breaches is not loading a patch. >> Yeah, exactly. >> The unplanned, unforeseen things are you know some sort of thing goes on, a hurricane, wild fire. You never know what's going to happen, so you got to be prepared for those kinds of infrastructure change or whatever. So I get that, so the operators can have a nice dashboard. I totally buy that. I want to get into the impact to the more on business side. How does this help the business owner that's your customer, does this help them with planning, refresh rates, total cost of ownership? Can you just talk about the impact of how this data relates to their job? Because I'd be like, what's in it for me? >> Yeah, no, exactly. And there's really three key areas that we're addressing for our customers. I mean the first one is around improving their operational efficiency, right. Again, reducing that alert fatigue and making it easier on the infrastructure management to do their job with less headaches, with less dashboards lighting up. So it's very, very prescriptive on highlighting what needs to be done and helping them through that process. The other area's around the prescriptive potential fault detection. And fixing those anomalies before they can actually cause a down time event, right, doing that in advance. So that's reducing the planned and unplanned down time, which can be significant in terms of cost to your business. One of the analysts states that this 20 million a year in cost associated with down time events like that, and that varies by industry. >> And that's a dart at the board, it's a big number. >> It's a big number, yeah. >> You pick your number, right, and see which one. >> And then the third area is really around helping our customers have better predictability into what their utilization requirements are. So the benefit there is really helping them improve their ROI on our appliances. Because now they don't have to over buy and over provisions at capacity because we can show them the trend data, the amount of efficiency they're getting from data. And they can right size their appliances in terms of performance capacity, and then we can warn them in advance. >> That's a real big thing is what's happening there. That's proactive. >> It's very proactive. >> It's not reactive. >> Exactly. >> Well you can solve on the reactive side because you just fix it. But then the proactive side is really where things break as you blow over capacity, you might want to add more. >> Yeah, believe it or not, those types of things have caused down time events in our customers, where they're assuming their backups are going to complete, as an example with net backup appliances, and yet they're out of capacity. And at the last moment that's a fire drill for them. So we can show them out 30, 60, 90 days, what they're utilization is, and then a threshold is at this point in time you're going to have potential outage, some kind of problem. And so we recommend that you add this capacity before that ever occurs. >> Alright, talk about the customer reaction to that. You guys, actually it was announced today, you talk to customers all the time. When you showed customers this in pre-launch, what was some of the feedback you guys heard? What were the key areas, what did they hone in on, what was the key things about the Predictive Insights that made them get jazzed up about this? >> Yeah, so it's really I would say it covers the two key areas that I already mentioned. One of 'em is helping prevent unplanned down time. That's a big concern for our customers in any industry. And this is going to be able to help them overcome that you know kind of rear view mirror look as to what's happening in the data center. And fixing a problem after it's occurred. Now they'll be able to be in advance of that and eliminate or at least significantly reduce those types of issues. And then the other one is helping, again, in that event fatigue at the operational model. That's where we've gotten the best feedback. >> So I'm going to ask you a hard question, which is, hey you know, predictive analytics has been around for awhile, pre-descriptive. why now, what's different about this opportunity? Obviously free is good because your customers get turned on pretty quickly. They get the benefits immediately, and new customers get it. I get that piece. >> Yeah. >> But what's different about you guys with this versus what might be out in the market? >> Yeah, I would say the key differentiation is that we have this very, very large universe of installed base systems that we've been gathering data on for over three years now. So the more data you have, the more data points you have. The better results you'll get from a machine learning type of environment. And we're still collecting data, both from the machines that are coming in from the telemetry data, as well as from our service personnel. So that right off the bat makes our solution unique than others that may have been like out sooner, in that we've developed a rich data set that is being applied to the machine learning. And hence, our results out the gate are very, very good. >> And you're using that, you're not actually charging for it. So that's another big one. >> Yeah, that's true too. >> So let's get into the specifics on the rollout. So this is a digital transformation table stake. You guys are checking a big box here. >> Sure. >> This is good. It gives your product some capability that levels that meta data, and that is what this data driven world is about. And certainly IoT is even going to make this even more of a table stake. >> Absolutely. >> On the rollout side, it's all appliances, Veritas. >> Uh huh. >> And then software only and then you're going to go beyond Veritas, is that right? >> Yeah. >> Explain that, what does that mean? So I get the appliances. What does software only mean and what does beyond Veritas mean? >> Yeah, so just to reiterate, today it's our appliances only. But many of our customers consume our solutions of software. And they're putting it on their bring our own server model. Probably about 40% of our customers, right. So we believe we can add this type of capability to be able to provide insights into our software that's installed on independent third party hardware as well. Maybe some of the capabilities won't be as rich, but we're going to start building those capabilities over time and try to bring in that data and help those customers that are software only customers. >> And that's on the road map? >> That's on the road map. >> Okay, so it's not available today? Okay, beyond Veritas? >> Yeah, so obviously many of our customers today are protecting data on prime, protecting data in the Cloud or some kind of hybrid model. And we support, we don't really care where the customers want to store their data. We're capable of protecting it and helping them achieve whatever those Cloud type of initiatives are in that environment. So an obvious next step would be to, hey how can we bring this to help you know where your data is located and how it's working in those environments? Is that back up going to be able to be restored, as an example? So we're looking at future capabilities to add on to this. There's going to be huge value to our customers. >> This is great news. Thanks for coming in and sharing. I really appreciate it. I want to get your thoughts on some observations that we've been making. Certainly theCUBE coverage of Veritas has been increased. Dave Vellante's been out on the road with the team, looked at some of the new back up recovery versions, looking at new UI, kind of new Veritas going on here. >> It kind of is. >> What's the vibe going on in Veritas? What's new about Veritas for the folks watching now and saying this is really cool. Veritas is cool and relevant right now. You guys are a product market fit. You guys got kind of a new Veritas vibe going on. What's it all about? Share your thoughts. >> Yeah, so I think there's, you know, some people call us legacy, right? But I don't think that's necessarily a bad term, right. I meant like when I'm gone, I hope I've left a legacy, right, that's worthwhile. And so we have that legacy, which is great. Because we've been adding, there's value for our customers for many, many years. But what's new and exciting I think for us is that we're able to provide solutions that are very, very simple to utilize, very easy to accommodate whatever their requirements are, whether it's on print or hybrid or in the Cloud, we don't really care. So we've kind of progressed I would say into a very, very modern architecture for what we're doing. And meeting the requirements today of what our customer's are doing as well as looking forward. And this Predictive Insights piece I think is just another manifestation on how we're progressing as a company, what we can bring to today on the current problems in the data center, and also looking out in terms of where the future requirements are as well. And we're ready for those. >> Well legacy is a great word. I love you brought that up because it's a double edge sword. If you're a legacy and you don't do anything and you rest on your legacy, then you kind of, you're just milking that until the legacy is dry. >> Fair. >> But if you look at what Microsoft's done, they're classified as a legacy vendor. Office was shrink wrapped software. >> Yeah. >> Satya Nadella comes over and now they're the darling of Cloud. They've shifted their products and execution to be what customers want, which is Cloud. Now they've got Office365, Azures, you know have been repurposed. There's some stuff they could still work on, but clearly cleared the runway. >> Yeah. >> And Oracle, not so much, Microsoft has. So this is a Veritas kind of vibe that's going on similarly to Microsoft. You guys are looking, hey we've got to install a base. We're going to use that and leverage the assets of that installed base, that legacy. Harness it and make it part of the digital transformation. Is that kind of the vibe? >> No, exactly, and I think Microsoft is a great example. I mean we're in tight partnership with Azure as a matter of fact. I just came from one of our vision solution's stages where a gentleman from Azure shared the stage with us and talking about our partnerships and all that. So I mean great example, but we're bringing those capabilities into the Cloud era, if you will. We have solutions that run natively in Cloud, help that environment, so. >> Making the transition to digital transformation. Veritas, the new Veritas, they got the solutions that are Cloud enabled. Using data for the benefit of the customers, not just trying to bolt it on and make more money. They're actually bringing value to the install base and changing the game up. Eric Seidman here inside theCUBE. Director of Solutions Marketing at Veritas. Part of theCUBE conversation, part of their news coverage of their Predictive Insights. I'm John Furrier, here in the Palo Alto studios, thanks for watching. (upbeat music)

>> Narrator: From Chicago, it's theCube covering Veritas Vision Solution Day 2018. Brought to you by Veritas. >> Welcome back to Chicago everybody. This is theCube, the leader in live tech coverage. We're here on the ground covering the Veritas Vision Solution Days in Chicago. Just a couple weeks ago we were in New York City at the iconic Tavern on the Green. We're here at the Palmer House Hotel. Jyothi Swaroop is here, he's the Vice President of Global Marketing for Veritas. Great to see you again. >> Thanks Dave, glad to be here. >> A few weeks ago we saw you in New York. Since then you've been around the globe talking to customers. You just gave a great presentation to about 60, 70 customers here in Chicago. Obviously a lot of your customers here, New York, one of the big NFL cities, so what have you learned in the last couple of weeks? >> Well, a lot. It's been exciting, right. Since New York I've been in Dubai, Milan, Rome, all over the place. Sounds exciting but a lot of jet lag and travel but a lot of exciting customers with interesting challenges that we can solve for. But I guess I would summarize it into three parts. Obviously there are data protection challenges that we solve at Veritas and have done so over 20 years. There are a lot of storage challenges that we talked about and how they're moving to the cloud and how we can assist with that. And lastly, interesting thing is the whole compliance in AI and ML related challenges as to how do they look ahead while staying compliant with what they have already. >> There are some major trends forcing people to rethink their data protection strategies. Obviously, cloud is one, the whole security and data protection world's coming together, the edge, just the whole distributed data trend. Machine intelligence is another one. There are things that you can do with all that data, machine plus data plus cloud really changes the game. You guys have some hard news in that area. Bring us up to date, what are you announcing? >> Right, so we're announcing Veritas Predictive Insights. Really excited about this announcement because when I joined Veritas about 16 months ago, I felt like Veritas sits on top of all these exabytes of data. We protect the largest number of exabytes of data, right. So we have access to the metadata of that data. So my question to the engineering team is what are we doing with that metadata? Are we going to use it, leverage it, so our customers can benefit from it? From all of this user data that we get from other customers. And the answer was, "Yes, we're working on something. Hold on, you're new." And now we have it. So at Veritas, yes it takes 12 to 16 months to build something at scale, right. We have hundreds of engineers that have worked on this. So what we have done now is, especially with our appliances portfolio, we're able to give our customers intuitive, predictive, and proactive maintenance and support of their systems. Now what does that mean? It means firmware upgrades, patches, things like that. They don't have to be a personalized, you know, fly in an engineer in to do kind of things. They can be automated. Oracle recently at Oracle OpenWorld announced this whole autonomous database. Why can't data protection be autonomous, right? So that's how we think, right. Make everything autonomous, make everything predictive and proactive and that's what Predictive Insights is about. >> So let's unpack that a little bit. So what are the enablers that allow you to actually take this next step. Obviously you've got the data, you've got a classification engine that allows you to put data in buckets, if you will. Explain what that is and why it's important. >> I'm glad you brought up the classification engine because that was at the heart of everything Veritas did for the last 20 years, right. We call it Big Veritas Information Classifier where we classified all of the data that came in on Ingest, unlike other people, other customers and other vendors. We classified all of the data that came in from that back up and we told our customers, "Here's PII numbers, your sensitive information is structured data, is unstructured data." We did this really well for a long time. Now we wanted to take that to the next level, right. We wanted to tell our customers what's actually going on with your infrastructure. You've classified the data, you've put it in here, what can you do with it next? Where can you put it? Can you optimize it after the cloud? How much will you pay for it? Can you remove something off of it? How much do you pay for that? Can you put some data retention on prem? How much would that cost you? So we would not only want to give them information about the classification of that data, but how to monetize that data, how much money would it cost to store that data in different areas. >> So this is a case where, if you go back to something you might remember, 2006, the Federal Rules of Civil Procedure mandated that you were able to recover and deliver to a court of law electronic records. Well data classification was critical component there. This is one of those cases like, if you've got an older athlete, like Tom Brady, maybe he's not as fast as he used to be, but he's got it all up here, he knows the plays before he sees it. You guys have the experience around things like data classification which are table stakes to allow you to do this but it's still a challenge for many folks in the industry. It's a metadata problem, isn't it? >> Yup, it absolutely is. It is a metadata problem and it's a metadata advantage for us at Veritas because we sit on top of the highest amount of metadata. >> So how do I take advantage of the Veritas Predictive Insights? Where does it live? >> So where we've announced it, it'll be out there the beginning of the year, 2019. We're rolling out with our appliances portfolio first because we have more control over it because the appliances and the hardware have been integrated with our software. So we give our customers predictive insights on all of their appliances that they buy from Veritas and their systems. Going forward, we'll extend that to our software only sales motions, as well. As extending it to other software platforms and other hardware platforms from other vendors, as well. So we're working on some integrations that I can't talk about today but we want to essentially take predictive insights and move it beyond Veritas in the future. >> Okay, so, talk a little bit more about how it works. Using machine learning technology, you're building models and training the data for different customers, how does it all actually come to fruition? >> Sure, so the first thing is, you know, we're generating what we call SRS or a system reliability score, right. So our engine processes all of this information that comes from a customer's data, the usage data, and maps it to the hundreds of other customers, thousands of other customers usage data that we have to find patterns, right. So for example, if a disc hasn't had a firmware upgraded and hasn't done so for months, we can predicatively let the customer know this disc is going to fail if you didn't upgrade this. But that's not enough. We actually allow them to click a button and upgrade the firmware right there to that disc so it's done, right. So it's not only letting customers know that here's something that's going to go wrong, but here's how to fix it, as well. That's just one example of what we can do. >> Well that's key, it's like the old days. You know, you have a pager and you get an alert and then you got to go do something. You're saying you're actually building automation into the process. >> Right, it's like chat bots. You respond to the chat bot right there and it does the action for you. You don't actually have to go somewhere and figure it out. >> So you've got this SRS score. >> Jyothi: Right. >> So what happens when you cross that threshold, it tells the system, "Okay, take some remedial action," or does it allow the customer to sort of make that choice? What's next? >> Sure, so the SRS score is like a credit score, right. There's a lot of complexity underneath that score. So at the highest level we tell the score, the customer if your score is above a certain point, your systems are healthy, they're running well. If they go below a certain point, right, let's say a 700 score for a credit score, you got to go watch or widen your goal below and we'll give them the 10 or 20 reasons why the score went down. Whether it's a firmware thing or a support issue or a hard drive issue. We tell them exactly what's about to go wrong so they can go fix it before it actually goes wrong. >> What do you, actually, before we go there, just some examples, some use cases that you expect in the field, you've talked to customers about. Give us some more. >> Sure, so data, like we talk to a lot of companies with massive data centers. So one of the things that it says with our appliances, simple things like temperature changes. I was in Dubai, look, the temperature there can be crazy. It goes over 100 degrees Fahrenheit. So it says simple things like temperature changes can have massive effect on your hard drives and how that works. If my AI and ML algorithms or my software can proactively tell me the temperatures going up, this is what's going to happen, you increase the cooling, do something different, move the data somewhere, back it up. That's great for the customer. Can I take action just based on a simple thing like temperature. There's another interesting customer, here in New York actually, that came to me and said, we had this problem like every so many weeks, their discs would fail. And they thought it was their temperature because it was in the summer. It wasn't and after a lot of research, it turns out it was the fire alarms that were going off. So the fire alarm and the fire alarm testing that was going on was actually causing discs to fail. >> Because of the vibration or? >> For the vibration and the decibel level. It was interesting, right. And now our AI, ML knows that so it's recorded, we know it and we'll be better off going forward, right. We'll tell other customers now that have data centers with massive, loud, high decibel fire alarms that this could be a potential issue. I'm not saying that is the issue, but this could be a potential issue that they would have never thought of otherwise. >> So what do you expect the business impact to be? When you talk to customers about this capability, you know, under non-disclosure, etcetera, how are they seeing this impacting their business? >> So it's three things, right. Proactive support and maintenance, that's really important. The customers are tired of talking to large vendors where the support connections are horrible, right. They have to go in and raise a ticket and do certain things and then they will ship a guy over to their site who'll come and fix it. That's just too long. >> Dave: Slow and reactive. >> Slow and reactive. We want to make this proactive and autonomous, that's number one. Number two is total cost of ownership, right. So when customers are able to predict these failures, they don't have to have a certain set of money set aside for solving problems when the occur. They're like, "I know this problem has come up. I need to budget for it." So their TCO models get better and more predictable, right. And last but definitely not the least, you know, when we extend this to beyond Veritas, they will be able to do more with their data. Again, what is that more? We don't know yet today. But when we are able to extend this to beyond Veritas, customers will be able to do a lot more with their data centers. >> So a couple of things this plays into. Obviously digital transformation is all about being on all the time, you don't want to have, you don't want planned downtime or unplanned downtime. This allows you to at least plan more effectively and potentially eliminate any downtime so your data is always accessible. And it's also cloud-like in that you're automating a lot of the either recovery from failures, or you know, you're pushing a button and saying okay, remediate this, patch that so you don't have the failure. So that's a sort of cloud-like approach. So you said it's available the first part of '19. And it's available, is it in appliances or? How do I get this. >> So we'll be rolling it out in appliances first, all the Veritas appliances. And then we'll extend it to software only, as well as beyond Veritas going forward. >> Awesome, Jyothi, thanks very much for taking us through the new capability. AI brought to data protection, anticipating problems before they occur, remediating them in an autonomous way. I appreciate your time. >> Thanks Dave. >> Thanks for coming back on. Alright, keep it right there everybody. We'll be back with our next guess right after this short break. You're watching theCube from Chicago, Veritas Vision Solution Day. We'll be right back. (electronic music)