Dynatrace Perform: Making AI Observability Practical For Enterprises

[00:00:03] - [Speaker 0]
Hi there. Welcome to across the tech pond, The US European podcast covering the main technology conferences and events hosted by David Marshall, Neil Hughes, and myself, Anthony Sabas. We are all Avid Technology Conference attendees visiting the shows big and small that help set the agenda across the industry. In this show, we have a very special guest. At the January, we attended the major perform analytics observability and cybersecurity event hosted by Dynatrace in Las Vegas.

[00:00:36] - [Speaker 0]
Dynatrace is a large and growing software company providing an AI powered all in one observability and security platform for cloud environments. It enables organizations to monitor applications, microservices, and IT infrastructure using causal AI to automate DevSecOps, that's development, security and operations, troubleshoot and optimize performance. It supports multi cloud and hybrid environments, enhancing digital transformation. Before we move forward, let's introduce ourselves. David.

[00:01:13] - [Speaker 1]
Hi, everyone. I'm David Marshall. It's good to be with you. I'm the owner and operator of vmblog.com and, of course, a cohost here at Across the Tech Pond. And I'm based in Austin, Texas in The United States.

[00:01:28] - [Speaker 0]
Neil.

[00:01:29] - [Speaker 2]
My name's Neil Hughes. I write for Cyber News and also host a range of podcasts over at the Tech Talks Network. And one of them, of course, is this one across the tech pond.

[00:01:40] - [Speaker 0]
Excellent. Anthony Savas here. I write for something called IT Europa, which is a pan European channel title. We write about American partners as well and Canadian ones and places elsewhere as well. I also write for IoT now, something called Techled, which is a communications portal, and I'm the co host of Across Techpond.

[00:02:02] - [Speaker 0]
As mentioned, we have a very special guest, and they're from Dynatrace, the vice president for portfolio and strategy at that company, no less. And they will outline the strategic grim and importance of observability and the essential industry partnerships that are needed to make sure it happens effectively. So welcome to Dynatrace's portfolio and strategy chief. Introduce yourself, please.

[00:02:27] - [Speaker 3]
Thank you very much for the introduction. It's wonderful to be here again. And my title is a fancy way of saying that I work closely with product management, product development teams to translate the value the Dynatrace platform brings to customers and translate that into position messaging for go to market field based teams. And then, of course, provide feedback back into the product management team. So I have product marketing, technical marketing, and competitive teams in my organization.

[00:03:03] - [Speaker 0]
Excellent. Well, thank you, Bob. First question from me quickly. Maybe an obvious one for some people who don't know too much about observability. Where does Dynatrace fit into the current observability market, and what exactly do you do?

[00:03:18] - [Speaker 0]
In fact, what is observability?

[00:03:22] - [Speaker 3]
Alright. I'll answer the first question first. Where we fit is we have the best platform, and I'm sure we'll get into that. But, it's actually a great question because observability traditionally, there was monitoring. And monitoring grew up back in the stone ages when we had monolithic applications on server.

[00:03:46] - [Speaker 3]
So there was server monitoring, network monitoring monitoring tells you something happens, and then people would figure out by working together what happened. Okay? Observability is monitoring plus understanding what's going on inside the system, understanding how a system is operating based upon the signals or telemetry that are captured and analyzed. So the Dynatrace differentiation is that we understand all of his telemetry in context. By context, I mean, we understand all the dependencies and relationships between all of the signals in the entire environment.

[00:04:31] - [Speaker 3]
So across billions of data points, we pull all of this information in time, basically create a digital twin of the entire environment, continuously update it in real time so that when something happens, we know what it's related to. If if something upstream happens, causes a bunch of downstream issues, we know what the root cause is So that's, I would say that's Dynatrace's number one claim to fame is the best automated root cause analysis in the industry. So there's much more that I'm sure we'll get into. But when people think of Dynatrace, they typically think, oh, the best automated root cause analysis in the world. K?

[00:05:19] - [Speaker 0]
Thanks for that, Bob. And, obviously, since, you know, monitoring became an established need, not everyone did it, maybe wrongly. We've obviously you mentioned some key terms there, digital twins. We've got the advent of AI, of course, and obviously cybersecurity. So that will come into the conversation as well.

[00:05:37] - [Speaker 0]
Well, thanks for that introduction, Bob. Much appreciated. David, you had a question.

[00:05:43] - [Speaker 1]
Yeah. First, thanks for, being here with us, Bob. I appreciate it. And I wish I could have met you in person. I unfortunately was unable to, attend the show, but I understand from my colleagues here, it was an incredible show as usual.

[00:05:57] - [Speaker 1]
So during the Dynatrace Perform show last month in Las Vegas, I understand your company made a number of key announcements around observability and how it was delivering it through an extended ecosystem that serves end customers. Could you give our viewers and our listeners kind of a broad outline of what was announced in, in that regard at the show?

[00:06:20] - [Speaker 3]
Sure. I'm gonna work backwards a little bit. The ecosystem was really important. We had a number of partners on the main stage, including executive leadership from AWS and from ServiceNow. And, first, I great proof point that these, what I call, essential technology vendors.

[00:06:43] - [Speaker 3]
Right? That that's the that's the people who everybody, all organizations depend upon is they're really seeing the value in Dynatrace. And then the announcements that we made varied. We had half a dozen key announcements covering the ecosystem, but also cloud operations, modern cloud operations, AI, and AI observability, and the developer experience as developers now try to increasingly use AI coding techniques from vibe coding to debugging. But I'll start with the elephant in the room for many organizations, and that is the necessity of organizations to bet the future on AI playing a key role, but most finding it difficult to realize strong value and are making only modest steps in their journey.

[00:07:38] - [Speaker 3]
So to me, the most important announcements that we made were the introduction of Dynatrace Intelligence and the companion Dynatrace Intelligence agents release. Why do I think it's most important? One is that the Dynastrace platform is actually a proof point of a successful AgenTic AI initiative. So our platform is an AgenTic system comprised of many different agents that collaborate together to solve problems, provide recommendations, either in an autonomous mode or supervisory mode. This is in it's GA now, and it's being used by thousands of enterprises.

[00:08:23] - [Speaker 3]
So as you saw it perform on the main stage and breakouts, well known brands like United Airlines, Vodafone, Air France, KLM, BT, and many others are trusting this platform to help their own journeys. And the fact that I think we've done it ourselves, gives us some element of trust with customers that we've got their back, and we can help them on their own journeys.

[00:08:51] - [Speaker 0]
Excellent. And when we spoke, Bob, at the show, I was asking about AI, and you're explaining, well, I suppose it's like other vendors as well. They've had some AI in their systems for a while, and maybe a lot of your customers are probably, using AI, not even realizing. You you I think you put it in terms of, the AI there previously was for the product to make it run, but now the AI Dynatrace is offering is really for the customers to really benefit from, to play around with, and to drill down into. I think I'm right in saying that.

[00:09:23] - [Speaker 0]
Is

[00:09:24] - [Speaker 3]
that correct? Man, that is so good. I love it when people listen when I'm talking. So thank you. So it's a very good point.

[00:09:32] - [Speaker 3]
So Dynatrace pioneered causal AI well over a decade ago. And then predictive AI. So predictive causal AI is this, what I talked about. It's, first of all, understanding the state of the environment, creating this map, a topology map. That was what pioneered causal AI in the industry, being able to trace through everything, hence the Dynatrace name.

[00:09:59] - [Speaker 3]
And then, starting over a dozen years ago, AI, which is forecasting, trending, anomaly detection, which helps you find what's not like the other or where a thing. Alright? And then generative AI was added to it several years ago, but degenerative AI was providing access to what the system was offering. Most of our AI elements, you can think of it as an engine that was there for the system. So what we've done over the last couple years is really democratize the AI.

[00:10:37] - [Speaker 3]
The AI that were you know, was the Davis AI engine and Davis technologies are really now ubiquitous throughout the system available to different system elements, but also directly accessible to users, whether it's an executive that that wants to ask for a dashboard on on time arrivals or time it takes to check out at the cash register, almost anything you can think of. We actually, inside the system, understand how everything maps together from the infrastructure to the applications to the business outcomes. Now customers actually have direct access to that, And you don't need to be a knowledge expert. You can ask these things through a natural language interface. So it's really democratizing AI so that not just the system enjoys the capabilities, but, partners, customers, whether they're developers, the ops, SRE platform engineering, everybody has access to this wealth of information and context.

[00:11:47] - [Speaker 0]
Food for four. Neil, question from you.

[00:11:51] - [Speaker 2]
Yeah. One of the things that I loved about last week was, one, getting to meet you in person finally, and also how you you seem to be taking attendees on a journey that was going beyond automation. And this agentic AI that fixes problems on its own, but almost reminded me of the Stephen King film Christine all those years ago. I could imagine a developer sat there saying, show me. You'll you'll fix it.

[00:12:12] - [Speaker 2]
But Yes. But we we heard how the company's going through expanded ecosystem of tech alliance partners, and there were some very big names in there. And you've mentioned quite a few today. And, again, one of the standouts for me is not just talking about AI, not just talking about AgenTik AI. It was the measurable impact that, some of your partners were having.

[00:12:31] - [Speaker 2]
United Airlines, for example, the difference they've had in three, four months blew me away. It's great to hear those very real world case stories of of measurable difference in ROI on tech projects. But can you explain how the the to the audience that couldn't attend, how this go to market works, how it's driving growth across different industry verticals? Because there was so many different verticals there, wasn't they, in attendance?

[00:12:56] - [Speaker 3]
Yes. And I do so Dynatrace, we're a multibillion dollar company, but we're not necessarily a household name yet.

[00:13:05] - [Speaker 2]
Yeah.

[00:13:05] - [Speaker 3]
Alright? Us, of course, we wanna work with the Azure, the Google Clouds, the AWS, but a lot of other companies wanna work with them as well. However, when you have companies like United Airlines and FedEx and you name it across any vertical industry, we will have a bunch of the top 10, companies as customers that are investing, like, standardizing on Dynatrace. If you're an AWS, then you care what your really big customers do. So it's why it's, reinvent in, back over a month ago.

[00:13:47] - [Speaker 3]
Matt Garmin on stage gave an example with SRE DevOps agent and cited, let's say in this case, we're we're we're basically connecting to Dynatrace platform, and let's see the back and forth through the Dynatrace MCP server. The MCP server is a way for people for different AI systems to talk to each other. So, you know, Matt Garmin is got a lot of choices when he gets on stage for the new shiny, you know, offering from AWS. We're pretty proud that he chose Dynatrace because SRE agents trying to get the root cause, and we believe we're the best way to get to automated root cause. So a lot of information, you just pull the answer out of the Dynatrace system.

[00:14:36] - [Speaker 3]
So we we like to say answers, not guesses. So everybody's doing AI, but the question is, are you looking at a bunch of information and trying to correlate it based upon the time series, the time stamp when it happened? It works in many instances, but it certainly doesn't work in a very large dynamic environment where there is lots of stuff going not quite right at the same time that are connected. Matt Garmin with AWS, I thought, was an important moment. Pablo Stern from ServiceNow was on the main stage with our chief product officer, Steve Tack.

[00:15:17] - [Speaker 3]
They have a very good close working relationships. And ServiceNow is, standardizing a bunch of their IT on Dynatrace. We're a ServiceNow customer. So we're customer zero for each other. This is driven by the market.

[00:15:35] - [Speaker 3]
This is driven by we each had really important customers that the world depends upon to operate. So I think some of this is, is us choosing the partners we wanna partner with, but a lot of it is really driven by the largest companies in the world.

[00:15:55] - [Speaker 0]
Neil, do you wanna come back there?

[00:15:57] - [Speaker 2]
Yeah. I was gonna say I I had the pleasure of speaking with Steve Tack and Pablo. One of the things that I reflected on was we were talking about with AI and Agenetic AI that how long would it be until AI is a member of the change advisory board before those big changes? And they both said it's inevitable. Would you agree with that as well?

[00:16:15] - [Speaker 3]
I would. And there's this, and in particular, in the news, there's it used to be you know, we go back to Marc Andreessen with software is eating the world, and now it's AI is coming for your job. Right? And AI is capable of doing a lot of stuff, but if we think about what AI actually does, it's pattern matching and looking for what's the logical pattern that goes next. Right?

[00:16:46] - [Speaker 3]
So it is it really is doing work that is easily done by humans but time consuming. It's not thinking up problems. It's not inventing, really, unless you consider hallucinations as inventions, okay, which frankly they are. Okay? So I think that what's happening is in the near term, I see AI is actually increasing the need for smart people to learn how to tame AI, how to use it effectively.

[00:17:22] - [Speaker 3]
I think it significantly increases demand for good observability, particularly with Dynatrace because we've you know, for sixty years, the goal of software has been do the same thing every time. Right? You want it to you test it to make sure it's deterministic. And, and if it does anything funny, it goes into an error routine. Well, now we're purposely including software entities that you expect a different answer every time.

[00:17:54] - [Speaker 3]
This holistic aspect of LLMs is something that's never been encountered before. And if you only had one LLM in its system, then maybe you stop the presses if it hallucinates. But when you have a bunch of collaborating agents, now you're in effect poisoning downstream wells if you hallucinate. So the ability to trace through that, figure out where did this propagate, and then what was the impact radius of any negative impact, and then how do I remediate it, which effectively is putting the toothpaste back in the tube after it's been This is really nontrivial. So I think that you're gonna see AI absolutely increasing in importance.

[00:18:43] - [Speaker 3]
For real time autonomy, you need AI. Humans cannot react fast enough. They can't think fast enough. Your brain is chemicals. Those chemicals have to percolate, and it takes seconds even for very fast people.

[00:19:02] - [Speaker 3]
In one in one second, Dynatrace could have found an issue and remediated it before any end user was impacted. Right? Humans can't do that. So I think this autonomy is something to be embraced. And then the real excitement and promises in this supervisory role that people get to play to how do you leverage and, frankly, exploit what you can with AI for the benefit of the business.

[00:19:34] - [Speaker 3]
And that's really what is so exciting to help customers navigate.

[00:19:39] - [Speaker 2]
And we did see for a few seconds there an AI version of your CEO, AI Rick. Any plans for an AI Bob as well?

[00:19:47] - [Speaker 3]
There is there is no AI Bob. There is no AI Bob. Right? But it was a good thought. And by the way, if you look up perform twenty twenty six, Dynatrace perform twenty twenty six, you can see replays on demand of the main stage and key sections.

[00:20:05] - [Speaker 3]
Rick, during his session, we actually created an AI Rick that was trained to very specifically operate within narrow confines. So it was a very fun experience, and I don't think our CEO is in danger of being replaced by by AI in the near term. Me, maybe. We'll see. We'll see.

[00:20:27] - [Speaker 0]
I think the real CEO, Rick, was quite pleased with how he looked there, but I don't think he was quite happy with some of the answers from AI CEO, Rick.

[00:20:35] - [Speaker 3]
But No. I'm thinking about

[00:20:36] - [Speaker 0]
enjoyed the polished up version of, CEO, Rick on You

[00:20:40] - [Speaker 3]
noticed that. You noticed that. Right? That I was like, wow. That's a handsome dude, AI Rick, for a dress to start.

[00:20:46] - [Speaker 3]
So maybe, maybe I do need an AI Bob. Who knows?

[00:20:51] - [Speaker 0]
No complaints here, Bob. No complaints, believe me. As we've heard, Dynatrace is a growing global company. But could you just confirm, you know, where the company's key markets are both regionally and which industries? Obviously, North America and Europe.

[00:21:07] - [Speaker 0]
Any specific countries you can maybe mention would be helpful, and any specific, key verticals. We've heard about United Airlines. Aviation is there. No doubt oil and gas and factories, but, you know, where else, Bob?

[00:21:20] - [Speaker 3]
Frankly, everywhere. Health care, retail, manufacturing's big, transportation, public sector. So we're we're a global we're a global company. We are in a quiet period, so I can't really talk about, you know, specific countries or things that are doing well. But, we're we are growing everywhere.

[00:21:41] - [Speaker 3]
We focus, everywhere. We have North America, Central South America, Europe, Middle East, Asia Pac, you know, Australia, the New Zealand, Asia Pacific. So we're we've been doing a great job, I think, spreading the message. And we're sort of the quiet company for a long time, so getting the message out. So Perform is something that's gotten bigger every year.

[00:22:11] - [Speaker 3]
I thought it was a superb show. We we moved to the Venetian, which is a bigger venue this year to accommodate the growth we've been experiencing. We, we sponsor an f one car now, so the fees, cash out racing. I hope you saw the car that that was there, and their CEO was, was at the conference, which was really cool because they were doing their first test drives somewhere Europe or Middle East. They were doing their first test drives with new cars for this year, and he, flew in for it.

[00:22:45] - [Speaker 3]
So we have a great partners. We do the performance analytics. We're the performance analytics for that that f one car. And they had their first podium finishes, last year, which was our first year. So correlation, maybe not causation in the in the language of observability, but, it's very exciting.

[00:23:07] - [Speaker 3]
I think what's universal universal is that good data is a prerequisite for good observability and good AI. Certainly, you feed bad data into AI, and you're gonna get bad results. Bad data equals bad AI. Good data is a prerequisite, and I would say most customers believe, most partners believe that we have the best data. And what does that mean is that we are the rare company that has a single data store.

[00:23:42] - [Speaker 3]
So we've got a data lake house, unified data lake house called Grail. Metrics, events, logs, traces, all your behavior information, metadata is in a single place. It's indexless, so you can query it in any manner. Everything's connected in a causal dependency graph that's continuously updated by our I mentioned digital twin. Our smartscape technology has really multidimensional, not just topology, but connects all of this data together and keeps it updated.

[00:24:18] - [Speaker 3]
So you have this blend of anything you wanna look at, you have view this multidimensional view of everything else that's impacted. And then I mentioned we've been in the AI business for about twenty years, so, we're pretty good at AI. So I I would say it's the combination of this unified data lakehouse, this contextual dependency graph in smartscape, and then very advanced, mature AI from people who've been doing AI for a long time. So that's really what's been driving our growth globally and throughout all of the different, vertical industries.

[00:25:02] - [Speaker 0]
Excellent. David, you got a question next.

[00:25:05] - [Speaker 1]
Yeah. I want to kind of shift gears and talk about something that, we really don't talk about enough AI. No, I'm just kidding. Still with AI.

[00:25:13] - [Speaker 3]
I'm glad I wasn't drinking. Yeah.

[00:25:16] - [Speaker 1]
I'm just, you know, 2025, 2026, it's a new topic that, that we should really start talking about, but the business requirements of cybersecurity around growing data threats and the operational advancements that AI can bring are now really both key. And you've touched on AI a lot here. But if you wouldn't mind, talk about how Dynatrace is addressing these two things.

[00:25:38] - [Speaker 3]
Yeah. It's, it's an interesting topic because cybersecurity is a huge, huge market, but it's also very fragmented. And the reason it's so frag you like, you don't have there isn't, like, a an AWS or Azure GCP. I mean, you can argue that that you've got Palo Alto Networks and CrowdStrike, right, as as key players. But from a just market fragmentation, it's very fragmented.

[00:26:12] - [Speaker 3]
Part of this is because there are just so many attack surfaces. So you have throughout the network, you have, you know, your phishing attempts. So Dynatrace really has focused on the runtime. So runtime application security, so runtime detection and and remediation. What we look at is anything that we can identify, diagnose, and autonomously cure, remediate is really what we focus on.

[00:26:43] - [Speaker 3]
And then we're not trying to be the be all end all across all, you know, endpoint security. Nobody's asking for that. So for us, it's what's actually running and how do you prevent that from doing the wrong thing from being exposed. So vulnerability detection is a is a huge thing. And if I use an example, if a zero day bug is discovered and you're a large enterprise, you could have hundreds or thousands of or millions of vulnerabilities.

[00:27:19] - [Speaker 3]
Okay? However, let's say 90% of those vulnerabilities may be in libraries that are either not in production or never accessed. Even your production applications have a bunch of code that is literally never accessed. Right? So what we're able to do is instantly prioritize, and this happened with Log four j and for other vulnerabilities, is identifying what are your highest priority things to remediate first.

[00:27:53] - [Speaker 3]
Right? If you can't do it, everything in one fell swoop, and you have to start prioritizing and sequencing stuff. This is what Dynatrace allows people to do so that you close your actual exposure areas. Right? It's a vulnerability is not is not worrisome if it cannot be used against you.

[00:28:12] - [Speaker 3]
So we identify the typically vast majority of vulnerabilities that need to worry about today. You can get to those tomorrow, next week. This is what you need to immediately address. I see this is gonna be a continuously evolving market. Lots of opportunities for partnerships.

[00:28:32] - [Speaker 3]
I think mergers and acquisitions gonna continue to be a thing. So we'll see how it plays out. I do not have a crystal ball, for that, but it's gonna be interesting to watch.

[00:28:44] - [Speaker 0]
Neil, you had a question.

[00:28:46] - [Speaker 2]
Well, yeah, I mean, we're talking around AI. Of course, it is a massive topic right now. And at Perform, Dynatrace Intelligence felt like a big step in helping observability evolve beyond monitoring, ready for an almost new agentic era. And I think there's so many businesses talking this year about releasing thousands of agents into the wild, and it feels like understanding what autonomous systems, exactly what they're doing at all times. It seems to be a massive opportunity there.

[00:29:14] - [Speaker 2]
And, also, there's a lot of people chasing this as well. So how does Dynatrace really make sure it stands out in the AI driven observability market? Because it will inevitably become increasingly crowded as that opportunity will will bring more and more people into the market. But what what would you say makes you stand out and makes you different from everything else out there?

[00:29:34] - [Speaker 3]
I think the number one thing, if you wanna conceptually think about it, is we solve complexity, and complexity is exploding. This has always been a thing. So Dynatrace, as I mentioned, pioneered, causal AI back in the age of of monolithic applications and three tiered architectures. Okay? And then the world moved in the early two thousands to VMs.

[00:30:05] - [Speaker 3]
And now you would have each server, you know, you could have five to 30 virtual machines on a server. And you we went from server sprawl, where you could just shut off a server and see if anybody noticed to now you have VMware sprawl. How do you tame that complexity of VMware sprawl? And Dynatrace did that. And then we went from VMs to containers.

[00:30:31] - [Speaker 3]
So now we have clusters and nodes and pods and containers. And that was another, explosion of complexity, but now these things are ephemeral. They come and they go. And that's really what our third generation platform was built for, this exponential increase in in complexity. Now with the advent of AI and agents, we haven't seen it yet, but just around the corner, we're gonna have this ex we're gonna have agent sprawl.

[00:31:04] - [Speaker 3]
I guarantee it. Right? It's people are just gonna be creating agents, and then the agents hang out and, are either doing nothing or they're just waiting money and time and resources or perhaps being, diverted to nefarious use. So I think that that Dynatrace helps people understand what do you have in your inventory that is delivering business value. Because what we're seeing is a tremendous amount of investment in AI, and we're not yet seeing the return on investment.

[00:31:42] - [Speaker 3]
And even in cases where customers may be declaring victory in that, oh, we moved this to a AI chatbot, for instance. Right? It's are you providing better service? Are you providing more cost effective? Would you have been better off having people do this from a quality of the service that they provide and and from an overall cost, because people are now experiencing that AI is great, but it's not free.

[00:32:18] - [Speaker 3]
Right? It's there's this token rate you and the more you query, interesting, I'm seeing announcements about automated testing for LLMs. And I'm like, automated testing, that is just like run the meter fast. Right? It just it just blindly throw a bunch of tests at it.

[00:32:36] - [Speaker 3]
I'm like, is that for the benefit of the customers, or is that for the benefit of the companies that wanna do this automated testing? Right? So they can charge on the consumption. So we're really entering this new era where things are about to get real in terms of complexity, and I think that really is where Dynatrace is going to stand from the perspective of this Gray Oak Lake house, the smartscape of here's your whole here's your whole inventory, updated in real time, billions of data points at you know, simultaneously, and able to do trillions of calculation. I mentioned our focus area.

[00:33:16] - [Speaker 3]
Right? I named all these companies are giant companies. Right? Complexity has been because of organizational complexity and the different fragmented tool sets and the change of organizations and tools. AI is really rapidly accelerating the complexity even in smaller environments.

[00:33:37] - [Speaker 3]
So I do feel like the market is moving to Dynatrace because we do, you know, as I mentioned, solve complexity.

[00:33:45] - [Speaker 0]
Are you convinced, Neil, with that answer?

[00:33:48] - [Speaker 2]
Yeah. I completely agree, especially around agent sprawl, the complexity that will come with that. And I just think understanding what an autonomous systems are gonna be doing, that's gonna be table stakes, and it's only gonna get more complex and and get bigger and bigger. So, yeah, 100%.

[00:34:03] - [Speaker 0]
This concept of all these, lazy agents not doing anything, and perhaps that's when we'll get really a Genti KI. They'll just get so bored. They'll just talk to each other and solve things. I don't know.

[00:34:12] - [Speaker 3]
Exactly. Let's, cut the humans out of it. Just, well, that's you know, we got starting with hell and space odyssey. Right? That that was the first.

[00:34:22] - [Speaker 3]
So, it'll and then Robocop. So it's not like people didn't think this was coming, guys. So we're actually here, and it's worth talking about a little bit because AI is it's it's scary. Right? It's wonderful, but it's also scary.

[00:34:42] - [Speaker 3]
It can go wrong in a lot of ways. You can have nation states. You can have criminal syndicates that are all over AI as well. So there actually is an imperative for people to use AI to protect yourself, understand what's going as well. Back to, you know, David, your cybersecurity remark.

[00:35:05] - [Speaker 3]
All of this stuff is really tied it's tied together, and we are going forward. Right? Is there you cannot sit this one out because, we do know with pretty strong conviction that the winners in the future are gonna be AI winners. Right? You won because you used AI very intelligently to drive business outcomes.

[00:35:31] - [Speaker 3]
It was thoughtful, and you understood what your investments were and your expected return on investments. The people that navigate that the best, I think, are gonna fare the best in the future.

[00:35:43] - [Speaker 0]
Excellent. Now the audience have been rewarded there with some with a good discussion, I think, but we always wanna make sure they are convinced, and we wanna leave them with something regarding how organizations can get their observability right across an evolving landscape. Perhaps, Bob, you could list three essential elements to this across software and apps, cybersecurity, and AI just to help us wrap this up. Is that could you do that for us?

[00:36:11] - [Speaker 3]
Boy, asking me to remember three things will will, I'll take a I'll take a spin at it. I think the first thing I would say, and it gets back to consolidation, right, in the thesis that the best data wins. The best data is gonna give you a huge advantage in the AI era, and automation is going to be key that comes with advanced AI and AI apps. So the first takeaway, I would say, is what's your current inventory? How much overlap do you have in monitoring and observability tools?

[00:36:44] - [Speaker 3]
And what are your gaps? What are things that you're not doing? Okay. So the first is really to have an assessment, a really good honest assessment of where you are, and this spans observability, business analytics, and cybersecurity. We really haven't talked too much about business, but business observability has got to be a cornerstone because all of IT, all your applications, your investments, they exist to run the business.

[00:37:14] - [Speaker 3]
So your ability to connect it to the business in real time is important. So inventory number one. Number two would be, what's your balance between your teams collaborating and innovating together versus firefighting, chasing chasing issues, doing updates, configurations? Like, what are they doing that could be audit? And and this is not necessarily just what can be automated with your current tool set, but what could be automated giving the right platforms that you're building on.

[00:37:54] - [Speaker 3]
Alright? So this is about your workforce, your people, because the AI era is a great opportunity for everybody to uplevel and upskill themselves. Jobs are gonna change. So studying your teams and saying, how are these jobs gonna change? And how can I both give my employees career growth paths and gratification paths?

[00:38:21] - [Speaker 3]
We all like to be successful. We all like to be learning. The the friction is change. Change is also difficult. So how do you lead them through this change?

[00:38:30] - [Speaker 3]
Okay? And then the third is really do something. Right? Is do something with AI. Execute.

[00:38:40] - [Speaker 3]
Once you have your team's assessment is what's the low hanging fruit so I can learn and get some quick wins under my belt. So that really is the the best advice I can give, And that is not just personal opinion. That's observation of what's working for the pioneers like the Uniteds, like the Vodafone's, who despite being large global companies with more than a 100,000 staff employees, are well down these journeys. And if they can do it, frankly, almost anybody can do it. So that would be my, I think that was three things.

[00:39:24] - [Speaker 0]
Yeah. Three areas there. Thanks, Bob. And I'm sure our audience has been super informed. That that broad brush we've just taken across the observability market, I think people didn't know too much about it or hadn't got the observability solutions in place, realise now that, that there's things that they can do to actually make it easier and to also get the best out of the systems they've probably already got in place.

[00:39:47] - [Speaker 0]
So, really, all that remains now is to say goodbye. Thanks for being here, Bob. It's it really has been a pleasure. It's a goodbye from me until our next Across the Tech pond, which will be coming very soon, actually. Bob.

[00:40:00] - [Speaker 3]
Thanks very much for having me, first of all. It's always a pleasure. Nice to finally meet you guys in person, talk about our shared love of of English football. So it's it's truly a pleasure, especially when you're rooting for the right teams. So Leo.

[00:40:21] - [Speaker 2]
Thank you. And, massive thank you as always, Bob, there. I think we are entering this era of agentic AI systems that interact directly with other AI agents for observability. So many big takeaways. I think understanding what these autonomous systems are doing is gonna be more important than ever, and I would invite anyone watching to get in touch, share your thoughts, your experience, your insights.

[00:40:43] - [Speaker 2]
We'd love to hear from you. And if you see us at a tech event, please come over and say hello.

[00:40:47] - [Speaker 1]
David. Yeah. Like they said, Bob, appreciate you taking time out of your schedule to, talk with us, educate us, our audience. And, definitely sounds like, although I didn't make it this year, that perform is one of those events that should be on mine and everyone else's calendar. So look forward to that in in within the next year or so, of it coming back.

[00:41:11] - [Speaker 1]
And so to our audience, I hope everyone enjoyed this episode. It was definitely filled with great information, and we look forward to sharing our next topic with you on the, Across the Tech Pond series.

[00:41:22] - [Speaker 0]
Thanks very much, folks. Thank you.