Understanding Today's Digital Business With Dynatrace | Inside the Digital Business With Dynatrace

Inside the Digital Business With Dynatrace

In this episode of Inside the Digital Business, we explore the complexities and innovations of modern digital businesses with insights from leading experts at Dynatrace and TELUS. Featuring Bernd Greifeneder, Chief Technology Officer and founder of Dynatrace, along with Dynatrace Chief Marketing Officer Laura Heisman, this discussion examines how organizations optimize digital operations through advancements in artificial intelligence and automation. Greifeneder highlights Dynatrace's journey from its origins as an observability platform to its current third-generation capabilities, emphasizing its role in automating operations and business insights. The conversation is hosted by Rob Strechay, director and principal analyst at theCUBE Research, who is joined by experts from TELUS, including Kulvir Gahunia, Director of Site Reliability Office, and Dana Harrison, Principal Site Reliability Engineer, offering firsthand accounts of transformative experiences with Dynatrace. The dialogue covers how Dynatrace's third-generation platform facilitates a deeper integration of AI for autonomous intelligence, allowing companies to automate complex tasks and improve business outcomes. Greifeneder notes the significance of high data quality and contextual memory in leveraging AI, facilitated by Dynatrace’s massive parallel processing data lakehouse. This approach provides clarity and operational efficiency through deterministic AI layers. According to the experts, key takeaways from this discussion include the necessity of a robust observability platform to manage AI-enabled digital services and the importance of embedding deterministic layers within agentic AI for trustworthy automation. The episode further explores the collaboration between Dynatrace and TELUS, highlighting the transformative power of AI in enhancing business resilience and developer experience.

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More from Understanding Today's Digital Business With Dynatrace

Dana Harrison

Principal Site Reliability Engineer

TELUS

Laura Heisman

CMO

Dynatrace

Bernd Greifeneder

CTO

Dynatrace

Rob Strechay

Dir./Principal Analyst & Host

theCUBE Research

Kulvir Gahunia

Site Reliability Office - Director

TELUS

play_circle_outline From Observability to Automation: Bernd Greifeneder on Dynatrace's Journey and the Future of Optimizing Digital Businesses

play_circle_outline Enhancing AI Operations through High Data Quality and Seamless Integration of Technical and Business Insights for Improved Automation

play_circle_outline Unlocking Value: How Third-Gen Dynatrace Empowers Business Users and Enhances Feedback Beyond Traditional DevOps Teams

play_circle_outline Overall partnership between Dynatrace and TELUS fosters innovation and addresses specific challenges.

play_circle_outline Transforming Operational Strategies: Embracing Proactivity and Enhancing Developer Experience with AI-Driven Tools and Integrated Business Metrics

play_circle_outline Enhancing Decision-Making with Dynatrace: The Crucial Role of Observability in Business-Technology Insights for Real-Time Outcomes

play_circle_outline Logs remain essential in observability, enhancing operational efficiency and reducing costs.

play_circle_outline Unlocking Innovation: TELUS Leadership Drives AI Initiatives for Enhanced Experimentation and Faster Iteration in Production Applications

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Transcript

Inside the Digital Business With Dynatrace

Dana Harrison

Principal Site Reliability Engineer TELUS

Laura Heisman

CMO Dynatrace

Bernd Greifeneder

CTO Dynatrace

Rob Strechay

Dir./Principal Analyst & Host theCUBE Research

HOST

Kulvir Gahunia

Site Reliability Office - Director TELUS

In this episode of Inside the Digital Business, we explore the complexities and innovations of modern digital businesses with insights from leading experts at Dynatrace and TELUS. Featuring Bernd Greifeneder, Chief Technology Officer and founder of Dynatrace, along with Dynatrace Chief Marketing Officer Laura Heisman, this discussion examines how organizations optimize digital operations through advancements in artificial intelligence and automation.

Greifeneder highlights Dynatrace's journey from its origins as an observability platform to its current... Read more

Inside the Digital Business With Dynatrace

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Rob Strechay

>> Welcome back to this episode of Inside the Digital Business with Dynatrace, where we're going to examine the current challenges and opportunities for organizations as they optimize themselves as digital businesses. For this segment, I am joined by Bernd Greifeneder, who's the founder and CTO of Dynatrace, and I couldn't be more excited to have you on, Bernd. Welcome to the show.

Bernd Greifeneder

>> Hey, Rob. Thank you for having me.

Rob Strechay

>> I mean, again, as one of the founders of Dynatrace, I think, again, this is so exciting to really dive into how organizations are really adopting and benefiting from your third-generation platform. Give a little bit of background and help people understand on the other side of the screen here, what are some of the benefits that customers are seeing from the third-gen platform and how you got here?

Bernd Greifeneder

>> Yeah, Dynatrace completely has really advanced from just observability as the first generation of it to it's second generation of actually automating all the answers from observability data to automatically create root cause and risk results, to actually now with third-gen, taking the next big step in automating the operations, automating security, automating business insights in completely new ways. And also, with the third-gen of Dynatrace, we have laid a foundation for AI to actually make work that well, that we truly drive towards autonomous intelligence to really help our customers automate their businesses and especially the digital services that continue to grow in complexity and scale. So I mean, think of in the second generation of Dynatrace, it was all about, how do we reach 200,000 servers? In third-generation it's all about defining also towards scales of millions of containers and digital services that we all process with the help of AI towards helping the customers with the automation of their systems and getting the business visibility they need.

Rob Strechay

>> Yeah, no, I think, again, one of the things I love about Dynatrace is I bump into your customers all over the place and get to have great conversations, but I think one of the conversations that's really been top of mind is agentic AI. I think that you guys are sitting in a really good spot with this, because I mean you guys know AI, you've been using AI in your product for decades now here. And I think when you start to look at it, you guys are really out on that forefront. How do you really look at Dynatrace as a platform that's purpose-built to help people in this as they move towards agentic AI?

Bernd Greifeneder

>> Yeah, AI really has always been a key thing for us. So even years ago we had already Alexa skills developed because we anticipated that as human you wanted to interact with an observability platform in a way to get informed even when you're on the roads or also release specific tasks that the system would want to do automatically. And we have really now with third-gen actually made this vision to become true and lead the foundation here for this type of autonomous intelligence. Because what you need for AI to properly work is not just the generative AI layer, sort of it's way more than a ChatGPT interface sort of, if you will. What you really need for an autonomous intelligence to work and for AI to work is the foundation of high data quality, the foundation of proper accessible memory of how you store all the data in context. Think of it that you need to understand the causal dependencies in the data properly, because only then you can provide a reasoning that is reasoning for facts in a deterministic way and not just in a stochastic way as typically large language models do. So here is where the third-generation of Dynatrace platform really lays this groundwork with having a massive parallel processing data lakehouse that really puts all the data collected from those million of services and containers altogether, have also a business level of data in there also connected. It truly connects all the dots together that enables AI to understand in real-time the business context and sort of understands on the lowest layer the technical behavior, meaning really understands when there is an issue with availability or security flaw, but also on the second layer on top, understands how to collaborate properly and help with automating tasks like routing vulnerability to the appropriate development team already with the information at hand to remediate the issue and automating all the tasks to generate the test cases automatically. And on the third level, on top, actually enabling the business leaders to connect all the dots of their business processes, because we bring all this data together in context with the causal graph, so that in business context they understand which users, which customers are impacted, is the business goal achieved there? Do you need to optimize in the organization or in those digital business processes? So we all enable this with this strong foundation of AI that is both combining the deterministic approaches as well as the large language models, stochastic approaches. So this is the key power to actually allow the business leaders to use automation with confidence in especially these complex systems. Because I also think this way, typical environments in our customers have tens of thousands to hundred thousands and more of pods and Kubernetes container instances running and now you are adding over the next years even more AI instances, so alone this will continue to drive complexity up. And especially as our customers also use more AI in their digital services that they build, all those systems will even more randomly talk to each other, which means you have to have an observability platform that does do more than just observing it, but actually learns in real-time, understands in real-time all those interdependencies and helps you with an autonomous intelligence to actually cope with it and help you automate for reliability, basically, auto-remediate, auto-protect, and auto-optimize that system.

Rob Strechay

>> Yeah, no, I think, again, that was a master class in all the different layers of AI. And again, having talked to many of them, they're trying to get that visibility all the way down in there. What have you seen from the customer base that has moved onto the third-gen platform and what are some of them saying? Because I think like you said, they need to be able to provide that kind of business level context, which really when you think about traditional platform engineering and observability, it was more down in the weeds, but now they're looking to bubble that up so that the business units who are the ones usually paying for the agentic AI are the ones that need that visibility. What have you seen out of ones that have moved onto the third-gen platform so far?

Bernd Greifeneder

>> Yeah, the third-gen platform now allows our customers truly to equip a much broader set of employees with value from this vast gold mine of observability data. So think of enterprises not only like in the past, have hundreds to thousands of users equipped with information from Dynatrace, but actually move to tens of thousands of users. So how can that be? Why that many? And this goes back actually to the layers. So it's not only that the DevOps and SRE teams use Dynatrace, but also we extend the lift to all the development teams. So think of thousands of developers do live debugging, log analytics, and people are proactive about deploying into production as well as use Dynatrace to fast remediate an issue and so forth. But it also reaches all the way into then the business users on one hand, because business observability is something that really resonates well, and this is because Dynatrace has achieved to put a logical business layer with our business events on top of the pure technical data, and this extends to this group to get business insights about their processes, think order-to-cash, think online commerce, think logistics in companies, sort of all these different processes need to be optimized for proper outcomes. And then there's another fourth group of end users, and this is empowered all by not just having dashboards from Dynatrace that other users can use to have a more common view of our companies, our run, but actually since Dynatrace third-gen platform also allow us to create custom apps, we have customers who create completely new use cases on top of the data they already own with Dynatrace, because this is such a goldmine of data that they want to use to, for instance, automatically control how, for instance, ship containers in their harbor are being controlled, or others, how they deal with their financial transactions in new ways we never could have as a vendor thought about. So I find this is pretty amazing, because this allows our customers to basically purchase one platform, but leverages then the data, the AI, and analytics then in multiple different forms so that the value actually multiplies.

Rob Strechay

>> Yeah, I think that's what organizations are looking for, is how do they get leverage out of all of the different things they're already doing? Because skill sets and things of that nature, they don't want to have to learn yet another tool. So I think there's a lot going on underneath the hood of all of these agentic systems to put it mildly as they get there. Now, you just spoke about why the third-gen platform really helps customers better now. What are customers telling you and what is kind of the value that they're actually seeing out of the third-gen platform that you're hearing back from them?

Bernd Greifeneder

>> So I hear a lot from customers about how their expectations to AI are really high. So I have CIOs who expect that in the next three years that 50 to 70% of the engineer's tasks are being automated by AI. So while I'm not sure it's exactly that percentage, it is that expectation that we absolutely are in the best position to fulfill for our customers because of the ability to have such a long history and experience of understanding automation from effect-based and causal approach and overlay this with agentic AI, we provide here the means that you can use automation with confidence. This goes also back to the developers, because developers are other sort of audiences in our customer base and they expect that 80% of all the workload that is not creating new features, that this workload gets actually lesser and lesser through AI. That's exactly also where we are helping, because it is those tasks of debugging, of optimization for performance or cost, or tasks like security remediation. All of this is what developers get loaded on with shift-left, test generation and so forth. There are so many things that they have to do and it's getting just even more, that this is particularly where Dynatrace's third-generation helps them through automatic collaboration processes, integrations into the development environment, automatic test generation and so forth to offload that burden. And this brings that relief for the developers themselves and the engineers also in the SRE teams. As well as the executives love it, because they look for more productivity because you can never have enough of technical knowledgeable people. And so, basically Dynatrace compliments then their teams.

Rob Strechay

>> Super interesting. And I think, again, this whole discussion has been really, I think enlightening, not only to myself, but hopefully to the people on the other side of the glass here. But one of the things I want to jump into is get your final thoughts. As these business leaders and tech leaders are really laying the foundation to really get a better understanding of agentic AI, what are some of your final thoughts on how they get started and how they really lay that foundation for this shift?

Bernd Greifeneder

>> As the customers all now add more of AI services to their digital systems, think of it that their cloud services just not only grow in number, but also their communication. Think of MCP servers talk to other MCP servers and the agentic to agentic side of communications become even more random or probabilistic through AI as before. What this truly means is, you have to observe what's going on for compliance reasons, cost reasons, technical reasons, even to make sure that the system works at all and provides value. So this is one clear thing. And secondly, as you continue to also observe these systems, you can't keep the data in silos. Because what I learned over the years in building AI for these kinds of analytics, analytics for root cause, security use cases, analytics for automation with AI, that the only way to get really solid answers is by bringing all the data actually together, ensure that the data is in context. And this is also, for instance, why we have built Smartscape, which is a directed graph that we also store in the data lakehouse that gets updated in real-time. And this allows actually for a deterministic AI layer that is under the hood of then the agentic AI layer to assist the reasoning with understanding a true causation to do effect-based decisions and not just stochastic decisions. So I think this is maybe the other final recommendation here. When you use AI, make sure there's enough of solid deterministic layers under the hood of all those agents, because there is enough randomness with all this AI going on, and at the end of the day, you want value from it and then automation that you can trust and not just a hallucination.

Rob Strechay

>> Yeah, it definitely is, I think key. I think this is really enlightening. I think people are going to get a lot out of this. And I can't wait, because next up we have one of your customers coming on, so thanks for coming on, Bernd. Really appreciate it. This has been great.

Bernd Greifeneder

>> Thanks for having me, Rob.

Rob Strechay

>> And thank you for watching this episode, the first part of this episode. Stay tuned for the second part of the episode of Inside the Digital Business with Dynatrace, where we're going to dive in with one of Dynatrace's customers, TELUS, who's going to help us really explore the perspective on how all of this comes together and how they're leveraging it, right here on theCube, the leader in technology analysis and news. We'll be back right after a short intermission. That was an enlightening conversation with Dynatrace CTO, Bern Greifeneder. Hearing him talk about AI made me think back to my discussion with Dynatrace CMO, Laura Heisman. In a previous episode she emphasized how Dynatrace isn't just adopting AI, it's fundamentally rethinking how AI and automation drive business outcomes. Let's take a quick look at what she had to say.

Laura Heisman

>> Look at what does that cause mean and how do we analyze it so we can predict what can be fixed. So then when they get to the GenAI side of things, they can ask things and it has been input in a smart way, I guess is the most basic way to put it. And then they can be the most productive, that they can innovate because they can have credible and really know that, that is information that is grounded in how their business works.

Rob Strechay

>> That idea of grounded actionable intelligence is a perfect segue into our next segment. Let's hear from TELUS, a longtime Dynatrace customer about how they are using the platform and especially its Gen 3 capabilities to improve resilience, developer experience, and most importantly, business outcomes. Welcome back to this episode of Inside the Digital Business with Dynatrace, where we're going to continue to examine the current challenges and opportunities for organizations as they optimize themselves as digital businesses. Couldn't think of a better way to really dig into this than to actually have a customer on. Today we're joined by some folks from TELUS who are going to help us understand how they're using Dynatrace and applying it to their digital business. First off, I have Kulvir Gahunia, who's the director of site reliability office for TELUS, and Dana Harrison, the principal site reliability engineer for TELUS. Welcome both of you to the show.

Dana Harrison

>> Thank you so much for having us.

Rob Strechay

>> Yeah, I think, again, I'm not joking, having been on your side of the fence and been an end user of products in the past in IT, you guys really are on the front lines of using this stuff. So let's start off with Kulvir. Let's start by talking about your modernization journey and your strategic initiatives for transformation, because I think understanding where TELUS is at will really help us baseline this.

Kulvir Gahunia

>> Thank you. Yeah, I can start off there. Our journey began probably, let's say 10 years ago at TELUS on really picking up steam on the DevOps and agile principles and trying to get TELUS to a place where we can deploy often, quickly, and reliably, and all with a customer focus. So when you're focusing with a customer, internally you're also focusing on OpEx reduction, right? So how do we do that strategically? And so, when we went on the DevOps experience, we did moving to cloud. A monolithic infrastructure moving to cloud helps with being agile, providing resiliency, and also bringing focus on our customer journeys and experience. With monolithic applications, it was very complex and we've moved it all together and put on a great observability platform to see what's going on, to provide insights, and make data-driven decisions for the business. And we're well on that journey moving forward with security as DevSecOps as a primary focus on where we want to continue to build towards.

Rob Strechay

>> Yeah, I think that makes total sense, because I think, again, having also been at a hyperscaler and built out and had SREs on my team and things of that nature, you guys are literally on the front lines with this. So Dana and Kulvir, bring Dana in here a little bit, help us understand the importance of technology and achieving those transformation initiatives and business resilience in general.

Dana Harrison

>> Absolutely. It's so key to everything we do, because we're in a world where you have a customer who can walk into a TELUS store, let's say in a mall, and they're expecting a smooth, reliable, quick experience. In that same world, if that experience isn't meeting all of their expectations, it is trivially easy for them to walk into the mall aisle where they've got the kiosk across the hall, maybe to a competitor's store and go get served in a way they expect to be served and deserve to be served by one of our competitors. So technology is what gives us that advantage to make a more resilient, reliable, available experience to really get that sale. In particular, with things like Black Friday, which is our biggest sales event period, and has grown into that over the past few years, it has led over from the States, because we're a Canadian telecom. We especially have to be on our A game with experiences like that.

Rob Strechay

>> Yeah, I think that totally makes sense. I think, again, I was a TELUS customer, by the way, when I worked for a Canadian financial services company when I was in IT. So I had my... Back in the day with a Blackberry. But I think, again, the experience is so key, like you said. So Kulvir and Dana, as customers of Dynatrace, could you speak to the continual innovation from Dynatrace and how it factors into the role they serve as one of your strategic partners?

Kulvir Gahunia

>> Yeah. We've been customers of Dynatrace for many years now. It has been probably 13 years. So we've seen the evolution of Dynatrace and we partner with them in developing new features and any asks that we have. They're great partners. It has been a strategic platform for us as we go through our journey and we're still going through. It helps us with the analytics piece of making decisions. It helps us with understanding the complexity of our platforms and where to focus on. From a customer perspective, iPhone launch was the big thing, and now it's Black Friday. And now we want to work towards, forget the events, let's just try to be ready every day with the data that's provided to us. And we continuously work with Dynatrace and always excited for the new features that come out yearly that we are able to preview a lot of, because we're good partners with Dynatrace and understand what's going to work and take that forward to the business as well and show them the value.

Rob Strechay

>> And Dana, where do you see... I mean, you're using it on a day-to-day basis and you've seen some of the new features that are out. Why don't you give us a little perspective on that as well?

Dana Harrison

>> Absolutely. So I can attest for the fact I haven't been around at TELUS as long as Kulvir has, and I haven't been a Dynatrace user as long as Kulvir has. And that's no dig on you Kulvir. I'm just saying you've been around here long than I have. But one of my first roles at TELUS was to help migrate off of our then observability solution into Dynatrace SAS. I was with a different arm of TELUS at the time, and I have nothing but praise for the really symbiotic relationship we've had with Dynatrace since that cut over. Truly, they're getting us involved in every preview that they think might be valuable to us. We were on Live Debugger many months before it came out and got a really good feel for it, had a really great back and forth with the product team on that. We've been on RUM on Grail for a while back when it was in preview as well. And anytime we seem to have a really weird, maybe unique problem, I've got a whole ton of Dynatrace engineers who are more than happy and excited to help us solve that. So the innovation on their side and helping us solve really TELUS-specific problems, but then that might have wider potential for use, has been nothing short of fantastic.

Rob Strechay

>> Yeah, that's so great. Because I think, again, when you start to look at it, it's about how do you partner and serve your customers better? Kulvir, why don't we kind of jump into the big trend in digitally transformed organizations, is using observability to understand how technology and business impact one another. Can you help us understand how you use or how TELUS uses observability to better understand your business?

Kulvir Gahunia

>> Yes. So traditionally Dynatrace has what used to be a monitoring tool, became observability tool, but it's much more now. It's a platform of information and can be used for various aspects of an organization now. And our goal at TELUS is to partner with the business to provide insights now with the information coming live out of transactions happening in our systems. And what better place to have that visuality and decision-making? You are now capable of doing sales or marketing events to see real-time, is there an impact of this? "Hey, we're going to release at this hour. Is there an impact? Yes. Should we pull back and whatnot?" And demonstrating this to the business, the tool itself, it's not a, let's say traditional IT tool for developers. I truly believe it's an informational tool for every aspect of the business. And working and partnering, they're an engaging partner with us to leverage capabilities like biz events to understand what's happening with certain products or systems or sales events and whatnot. So very excited to go down this path and have more users of the platform than your traditional devs.

Rob Strechay

>> Yeah, I think that's super interesting, and I think again, Dana, how have you seen it play on the business side as well?

Dana Harrison

>> So I think Kulvir nailed it. The fact that we're now able to pull in and understand and interpret meaningful business metrics in the same tool where all of our, what you would call traditional monitoring and observability signals are, so your golden signals, your traces, your logs, but now we can track product sales and we can track everything live, we're tracking cart totals. And the fact that we're able to do all of this in real-time as opposed to some of the every hour, every 24 hours reporting we had before, has really given us an edge. And now we have marketing people. As Kulvir said, it's not just for developers anymore. We've got people from all across TELUS who are hearing about the incredible things we're able to do, especially with a lot of the Gen 3 platform stuff in Dynatrace that has really changed the game. With these additional signals, we're also, or have been able to move from a really reactive to a proactive mindset. So before, which you're just reacting to alarms, you're okay, everything's sort of gone in a hand basket. So you're trying to see exactly what's going on, what signals are firing, what alarms are going off. But now with the fact that we have business metrics, we have business signals coming in with that same platform, we've been able to shift to a really proactive mindset. So we're no longer just getting together on war rooms and saying, "Hey, this P1 happened. What's going on?" We can now shift to things like game days and game nights where we are load testing in production several times a month, many times a year. We're getting those signals out, we're saying, "How does this impact live transactions from our business? How is this impacting sales? How is this impacting our marketing and customers and how can we react to that in a meaningful way prior to the big lead up to Black Friday, Cyber Monday?"

Rob Strechay

>> Yeah, I think that is the key, is how do you bring the business along and be, like you said, not just a tool for your team, but how do you be a tool for the business? I think you kind of brought something up and let's kind of dive in a little bit. Logs have been around for a long time, but in the modern era of AI-powered observability, are they still necessary in your mind and what are some of the specific examples of how you're getting value from logs in your observability team now?

Dana Harrison

>> Absolutely. So I know logs have been around for a long time. I don't see them going anywhere anytime soon. They're still going to play an incredible part in... There's a reason they're a pillar of observability when you have traces, logs, and metrics, especially with platforms like the Dynatrace third-gen platform, we have the ability from our team to deliver to our developers and our users, observability right out of the box. So on initial deployment, you get a whole bunch of templates that we've set up for you, some dashboarding, some alarming, some queries. We also, with Logs on Grail and trace injection into Logs on Grail, have the ability to power really developer-focused and AI-enabled experiences. So with a really unified observability platform, logs are just as important in the context with traces with your metrics to reduce MPTR, therefore also reducing your manual effort and your overall operational costs.

Rob Strechay

>> Which I'm sure developers love. So let's kind of go there right now. Kulvir and Dana, let's kind of talk about what the developer experience has kind of transformed into and how you're helping and how Dynatrace has helped your developers at TELUS.

Kulvir Gahunia

>> Yeah, I'll just quickly start off. That is our team, what you just described. Our team is to enhance the developer experience related to reliability. And we try to make it easy for them to onboard, to use the tools, and to absorb and consume information to make better decisions. And through that we've truly brought the ops part to the DevOps. That's our role. When you go through that journey, tying it back to the original question at the beginning, when you go through that journey, there's a dev, we had dev and we had ops, we are making it easy for devs to do ops and that's all part of the dev experience. How do we simplify that dev experience so they can get all this information? And Dana can go into more details.

Dana Harrison

>> I sure can. This is my bread and butter here. I talked about this at Perform, and it's funny, before our chat at Perform this year, a few months ago, I had a quick chat with Andi Grabner, he's an incredible partner with us at Dynatrace, just an overall fantastic guy, who had not at that time as of yet heard of the concept of MCPs or model context protocol servers in AI. It was a pretty new concept, only a couple of months old by then, but we at TELUS had already been able to build out a Dynatrace MCP. And I know it's great Dynatrace has their own now, which is really, really fantastic, but using things like some of the Gen 3 techniques with Live Debugger, like with trace injection, like with the ability to query traces on Grail in particular has been very powerful for us. We've been able to take things like combining Live Debugger in a developer's Visual Studio code environment with our Dynatrace MCP that we built out that has some investigative techniques and some prebuilt DQL to be able to query Grail quickly and effectively with natural language. What used to take us 45 minutes to debug, now takes two. We also did a really, really quick demo the other day where we showed a pager duty or a pager duty customer problem come in a production problem, and move from that through our many AI workflows into a full-blown pull request inside of 15 minutes. So it has really completely changed the game for our developers from both a development perspective and an option day two support perspective too.

Rob Strechay

>> What about some of the security aspects of it? Because it would seem like this has just been key from DevSecOps, easy for me to say, but what have been some of the results that you've seen out of that side of things?

Dana Harrison

>> So with our enablement of Dynatrace vulnerability management across the stack, we've been able to realize a 30% reduction in open vulnerability count across all TELUS processes and a 40% reduction in distinct open vulnerabilities. It has been very, very powerful and useful for us.

Rob Strechay

>> Yeah, I love that, because again, everybody talks about shift-left and all of this stuff. I kind of talk about meat in the middle, and I know Dynatrace has their perspective on that as well around manage left and things. But I think one of the things that's really interesting is, you bring the developers along, give them better insight, they build better code. It's not like they want to build insecure code, but getting them and helping get those reductions is amazing. That's great. So kind of wrapping things up, Kulvir, AI is reshaping many businesses. I would say almost pretty much every business. I assume TELUS is no different in how AI is reshaping what your company is going to market with. Can you kind of share some examples of AI initiatives that are in production or areas where they may be experimenting with AI that is helping your business?

Kulvir Gahunia

>> Yeah. No, from leadership, from the top down, AI is at the forefront of everything we're doing right now. Dana just gave some examples of the MCPs, the Dynatrace MCP, for example, and how it's helping reduce time for troubleshooting. That's a primary example. And that started from an experiment. We're able to experiment, we're able... It's enabling the entire organization to fail fast and move forward. And it's truly happening. We've always said it, "Oh, you can fail," but it takes six months to iterate again. But now it's half an hour maybe at tops. And so, the entire company is doing that. So experimentation is happening every day, especially around the observability and how do we help reduce the meantime to resolve consistently? But yet we're also developing production apps across the business. The entire business are developing their own copilots and chatbots. Our chatbots are being used outside of TELUS as well, commercialized for call centers. And it's helping. We have the model that AI is another tool to help the individual, it's not here to replace you. How do you leverage it to remove, let's say toil or get you focused on more stuff? And so, you're delivering value instead of worrying about the day-to-day mundane tasks that you may have, right? So with that, it gives you information. So it's all over. And as Dana just said in the last question, it's every day for us now.

Rob Strechay

>> Yeah, I can imagine. I mean, again, and by the way, shout-out for the MCP stuff. I mean, I know what that is. I was at KubeCon in London this year, people were just like, everybody had their MCP coming out. It was crazy. So good work there. I mean, I think that's that forward-looking that you guys are driving out of your organization there. Kulvir and Dana, that's fantastic. So thank you for coming on. This has been great. I really appreciate you sharing your experiences and being on today.

Dana Harrison

>> Thank you so much for having us again. It was great to chat.

Kulvir Gahunia

>> Thank you for having us.

Rob Strechay

>> And thank you for watching this episode, Inside the Digital Business with Dynatrace. Stay tuned for more to come as we peel back the covers on theCUBE, the leader in technology analysis and news.