 Welcome back everyone to theCUBE's live coverage of HPE Discover Barcelona 2023. I'm your host, Rebecca Knight, along with my co-host, Rob Streche. We are joined by Mark Waters. He is the SVP HPE Global Sales Customer Success Services and Solutions at HPE. Whoa, I love it, I love it, great title. They work me hard, don't you worry about that. They do, they do. And Keveri Kalavath, she is the Senior Director Global Ops Ramp Customer Success at HPE. Welcome both of you. Thank you. Thank you for having us. So I want to start with you, Mark. It's a hybrid IT world, it's a hybrid work world. We're living in a hybrid world. Organizations need access to real-time insights to manage these environments. What are some of the key challenges and trends that you're hearing from customers in terms of what's keeping them up at night? Yeah, well thank you. I think the biggest challenge right now is complexity. As you say, organizations have been spinning up digital environments, public clouds, private clouds, maintaining their legacy and they've kind of found themselves in this hybrid environment. But there's apps and there's data everywhere. So it's complex and that creates a couple of issues. One is around service quality, really understanding how you can deliver proper IT service management. And the other is spiraling costs. With that complexity, it drives costs. And perhaps the third one is an increased awareness of the sustainability impact of the energy consumption and what that means for the business outlook but also the cost profile of the business. Yeah, and I know there were some announcements at the June Discover in Las Vegas around that. So what are some of the capabilities that you're really bringing to those customers as part to make them successful with this? Yeah, that's a really kind of question. Thank you. So HPE is a really innovative company and I kind of put it in the three brackets. Well firstly, we make highly innovative, very efficient infrastructure underlying technology environment. Second to that, we have great people. The people at HPE are some of the smartest and most committed in the industry. So the services that we bring around it is very, very important. But actually really interestingly is the progression we're making on high value SaaS based solutions. OpsRamp is a great example of that where we're bringing observability, intelligent observability and AI operations to transform IT service management. That's a perfect segue into what I want to ask you and that is about the solution for leveraging AI and observability. How do you do that in terms of becoming more predictive? So I think first of all, OpsRamp is an AI powered multi-tiered, multi-tenanted hybrid IT operations management solution, right? So it enables discovery, automated, I mean does full stack observability as you rightly said, it does AI ops. It also enables automation and incident management. Now, in terms of the approach you need to take with regards to observability, this critically, you first of all need to get a seamless integration of data sources because it's important like Mark said, it's a complex environment, you need to bring all that data together. Secondly, it's about mining that data to get that useful insight from that data. So what we call is actionable insight and that's with the complex data overload that you're seeing, what you need really is to have an AI powered model to get that predictive insight and to get that decision that you're really looking for. Now once you have that, you need to surface it in a meaningful and user friendly manner in real time so that people can understand, trust the system and then be able to execute. Obviously there are other aspects like security, privacy and also with regards to sustainability like Mark mentioned. Yeah, and I think observability is, I was at a KubeCon recently and observability was all over the place and people were talking about it and I think there's kind of sometimes misconceptions between what is monitoring and what is observability and what does it mean and like you said, you've had AI in this from the start. This is not just window dressing on it, it's been there, you've had modeling, not gen AI, but real modeling underneath the hood. Why don't you explain to us, kind of your vision on what is the difference between monitoring and observability and how does that work? It's a very good question. It's very similar to people mistaking AI and ML. So monitoring really is about measuring, measuring a particular system for example, but really looking at an alerting on that system for example, right? So to give you an example, if I'm looking at a server, I may be monitoring the performance of the server or the CPU utilization and on the, I would alert if it exceeds a certain threshold, say 80%, right? So that's monitoring. Now I'm simplifying it, but observability is much a broader concept. So observability is about understanding the system holistically. So you're really looking at, is the system being able to pull all the data related to that system? It could have container workloads, it could have microservices applications running on it. So you need to be able to pull all that data together to then be able to, first of all, because we're discovering it, we also have the contextual information and the relationships between these data points, be able to apply that really to, and make sense of that data using what we call AIOps. And so we're applying predictive models using correlation, using what we call as a change detection and coming up with a proactive problem resolution for seamless operations and efficient, enhancing efficiency. So Mark, I want to go back to you because you started by giving us the lay of the land and showing us how just exceedingly complex these issues are. And then Kav has talked about the potential solutions. So what are the outcomes that can actually be achieved here? Yeah, well, I mean, I think as we think, as we talk about observability, it's the path from chaos to clarity. And the way that we start to do that is with a digital command center. So the first outcome is just understanding insight and better control of what exists. Then we look to drive service quality through better management of alerting, incident management and ultimately driving increased uptime in the environment. And that in itself gives efficiency. It gives cost saving. So you really can get both benefits, the improved service quality and the cost benefit that comes through efficiency. And as you kind of go one further with the insight, with the understanding, you can start to better know what is the cost associated for what outcome? How can you start to financially manage your operations on that basis? And as we feed in data around power consumption and other telemetry factors, you can start to understand the environmental impact and the environmental cost. So as a package, it's pretty compelling. But there's the monetary cost and then there's the environmental cost. So how are leaders thinking about these two sides of the equation? And how are they bringing them together? Because as you said, sustainability is such an important topic. So I think a few aspects there, right? I mean, sustainability is a key aspect, as you rightly said, being able to, first of all, bringing all that data together, being able to observe and apply AI ops and surface that data in a meaningful manner. OpsRAMP has 2000 plus integrations that it supports out of the box. It also has native integrations for metrics and structured data, but for unstructured data like logs and traces, it also supports open telemetry based integrations. Now once you bring all that up, we apply AI powered models, we do predictive analysis on that and surface actionable insights. But to Mark's point, all of this is brought out in a user friendly and in real time, in a sustainable dashboard. So we feed that into what we call the GreenLake platform and it's feeding the GreenLake sustainability platform as well so that they can then allocate the resource appropriately and also optimize the resources to make sure we're giving back to the environment as well. In fact, that was one of the announcements that came out of the June Discover, was that dashboard, how have you seen customers embrace that? How is that really? Either of you can comment or both can comment on that. You want to go first, go on. So I think the key is, like you said, it's AI powered for people to see and believe it's the most important aspect, right? The visibility is quite an important aspect and that's quite critical. So Opsram provides alert stats widget within the dashboard which gives you in real time view of the alert optimization and the volume optimization. We also surface, I mean, it's a very flexible model so users can build in their own JSONs, as we like to call it and upload those data. So all of that is possible. So that gives you that visibility, the holistic view into your system and then it's about how you build, configure and operate and then it's about validating and iterating, right? To make sure you're really having the data that works for your business, right? So that's how it works. I would say this is a board level conversation. People care about sustainability because it's important for the company but actually there is genuine cost associated with that. We see carbon tax regulations coming everywhere. It's a very, very real cost. And again, all boards, all CIOs are demanding in-year savings. So you start to put those two things together. This is very, very compelling. I mean, every conversation I'm having right now is about efficiency in the run. It's about awareness on sustainability and with the Opsram capability that we now have as part of the HPE GreenLake platform, we got a great answer to those questions. When you talked about the confirming and the validating of what you're seeing and taking those insights and actually saying, okay, here is what this means. And we're seeing it as a pattern. Can you describe how that looks inside an organization and the conversations that you have with customers before they really do trust what they're seeing? Yeah, it's a very good question. I mean, it's very much similar to driving an automated car, right? That's what I tell my customers. AI Ops is not a switch you turn on and it's not just going to work. It's an approach, right? It's a journey and it's a maturity journey. So as part of our engagement with the customers, we take them on that journey because depending on the customer, you may have various business needs. You may be migrating from legacy systems. You may be midway between your hybrid cloud journey and that's okay. What really matters is being able to build that system because we also support SDK based, so you can build your own content. And once you've ingest all that data into the system through logs, traces, matrices, you should then be able to apply AI Ops. But when you're applying that pattern and you're configuring your system, we also support what we call Observe Mode. So they can actually set it up in an Observe Mode, validate what's happening, is if it's right for the business, and it's all about configuring it right because you have to configure, just like I tell, when I'm driving a car, I need to, an automated car, you have to configure it, make sure it's operating because you have your controls coming in and to play as well. You operate it right and then make sure you iterate. And once you do that, it's a rinse and repeat process, it's a journey. But once you do that, you do see lots of benefits and like Mark said, operational efficiencies as well as cost efficiencies, significant cost efficiencies. I mean, that to me is one of the key parts to exactly what you were saying, Mari, is the fact that people are looking to kind of sweat their assets a little bit more, a little bit harder, especially in this economic state that we're in and things like that. Is that where you're seeing people really lean into your organization and get a better understanding? Where do they have those types of opportunities? Yeah, I mean, it's a tough macro environment, isn't it? So everybody wants to see increased efficiency in their run costs, combined with service quality. And talking about AI ops, I think you hit AI everywhere, don't you? AI, AI, I think in IT service management, in IT operations, it's one of the best, most effective, provable use cases where you can take AI to drive automation to give efficiency and reduce cost. And it's not a pipe dream, it's not a vision, it's happening now. We're doing it with countless customers and it delivers real, tangible business outcome. And our customers believing that, you know what I'm saying? Because there is, I mean, there's so much buzz around AI, gen AI, and it's not, and it's hard to really parse through what is actually real and what you can really see true benefits from versus what's hype. How are, what are the kinds of conversations that you're having with customers here at HPE Discover, but also in general? Do you want to take that? I'm okay to take that as well. Yeah, you guys, go! Thank you, Mark. So I think we've just been overflowing the booth today. It's just so many people coming around. But everybody, you know, some of them are in different states. Either they are concerned about security, they have legacy systems, they want to migrate, or we come across customers who are really looking for AI ops to not just bring in the data from their existing, you know, operation solutions, but they have tools that they want to kind of consolidate and bring it together. So there's a lot of these conversations that we are having, all of which is primarily focused on what's my return on investment and when is it going to be, right? So being able to take them on that journey and being able to prove and execute to that is quite critical, I feel. And we do that quite extensively with an ops ramp and with an HPE. We build out a framework for them to get through and see the return on their investment. I mean, people understand it. You see, this is a very manually intensive world, IT operations. Actually, if you can bring in automation, an automation of decision making, it will save cost. It's very obvious, very, very easy to understand and you talk about customers. You know, I'm running a spotlight session tomorrow on ops ramp. We've got EchoStar with us who are a great customer. They actually reduced, they achieved a 90% reduction in incident alerting as a result of the implementation of ops ramp. It's just one kind of real key data point, but it's a proof point. And it must also help them from a skill set perspective because you're not getting more people. IT organizations, their budgets are flat, if not down. So this must help them really almost a force multiplier for them in that way. Skills is one of the biggest challenges facing technology departments everywhere. So the more you can automate, particularly in areas like IT ops, the better for the company. Yeah, I think what we also see is with regards to automation, ops ramp also has a built in process orchestration engine. So when you have alerts coming in, we can then automate some mundane tasks that you have. And we regularly can monitor what's the return on investment as a result of that as well. So we look at, say if I'm restarting a server automatically, so you can look at the cost benefits of that if you're measuring it across the year and then also repeat, because we have integrations with Ansible, so they can also do other automations as well. So it plugs in quite nicely into some of your native automation tools as well. It would seem like it's also a good place for partners to be active as well. So a lot for the community, especially here in the US and over here where the V and value added reseller needs to mean more these days because of what people are doing. Are you seeing a lot of uptick with that? You were talking about JSON and building your own through the SDK. Yeah, I think OpsRamp provides a multi-tiered, multi-tenanted platform. So it is built ground up for the MSP, GSI and the OEM world and that's why HP brought us, right? Exactly, right. So, I mean, I run our managed services business and we actually got to know OpsRamp because it's such a great SaaS based technology. You brought it into our managed services organization to provide for our customers. But actually a big part of our partner based as service providers, they're building out hybrid cloud environments and having SaaS based observability and AI Ops in those environments is truly differentiating like it was for HPE and we're seeing a big uptick in demand there. Great, good. Well, I want to ask about the jobs because you had talked about how this is having, Rob made the point, there's no more headcount coming. Budgets are flat or down and you had said that this is a way to automate a lot of mundane tasks. How are IT professionals and your estimation? How are they responding to this change? It's a good question. I mean, I have never faced, I mean, everybody wants to work in the newest technology. So, everybody wants to get off the legacy tools and come into newer technology. So, there's a very strong interest based on that but I agree automation always is concerning as they're going to be. But normally when you're not doing repetitive tasks there's a lot of motivation because you're aligning them to look at more focused AI based tools or working on more structured newer technologies and I think people are loving it. I've not met many IT administrators that said we want to do more mundane repetitive tasks around all of these alerts. It just doesn't happen. Yeah, excellent. Well, Kevin, Mark, a real pleasure having you on theCUBE. It was so much fun. Thank you so much. Thank you so much. Thank you, Rebecca. Thank you, Rob. I'm Rebecca Knight for Rob Stretchy. Thank you so much for tuning in to theCUBE's coverage of HPE Discover Barcelona 2023. Stay tuned for more. You are watching theCUBE the leader in high tech technology enterprise coverage.