00:00:02

Now the more astute among you may realize that the title of the talk and the title of the slide here are different. Um, it's actually the title on the slide here. That's not quite accurate. The theme is very much, um, in, in line with what the, uh, the abstract talks about. I'm just wanting to point that out. So there's no, no confusion. Um, so this is a little bit of an overused phrase. These days, you know, software is eating the world, but as with so many overused phrases, it's there because it's kind of true. Um, you know, everything I buy these days seems to have software in it, washing machines, refrigerators, actually, not that I bought either one of those recently, but, but they do, um, a modern car. These days is a traveling data center, right? 90 CPU's in a new Mercedes more lines of code in a car than I'm told office windows, Linux combined.

00:00:54

Right. A little bit, a little bit scary. So software has eaten the world. Um, it's, it's not a question of is it's it it's already happened and we're drowning in data as a result of it, which is part of the theme of, of what I'm talking about today. Now, in terms of architectures for applications, that's changed as well, right? Microservices, new, hot, um, everybody's doing it. Uh, and they do make a difference, right? We did a little bit of a survey and realized, you know, there's there's revenue growth implications of, uh, companies, software organizations that are able to deliver, uh, their applications and form of microservices, loosely, coupled architectures. It's not really the theme of, of, of today, but, but it is kind of leading up to what I'm talking about here. And if you've been to the show before, um, you've certainly seen these types of numbers before from the state of dev ops, uh, report, uh, in terms of the just vastly, um, better speed and quality that CIC D practices and dev ops in particular bring to the software delivery process.

00:02:00

Right. And what I always like to point out is, you know, we're not talking about percentages here anymore. We're talking about multiple orders of magnitude, right? Pretty soon we're going to need exponent in these slides in a, in a few years, I would imagine. Um, but, but dev ops practitioners, um, organizations that are elite performers in, in dev ops, you know, we're delivering faster, less problems, uh, easier to roll back and fix when there are issues shorter lead times, you know, all of, all of these things make these organizations more competitive, better at delivering value to their customers. You know, all, all of the things that we want out of a software organization. So we've got, you know, new architectures, we're all, of course doing CIC di and dev ops, but still, you know, getting software out the door is difficult. It's a tricky, tricky problem for most of us, I would say all of us.

00:02:54

So there are still problems here, right? So even if I'm in a highly functioning dev ops organization and I'm a developer, I might still be asking my question, asking myself questions. Like, why am I building this feature? You know, who's it for, um, why do I have to waste my time, troubleshooting all these problems here? You know, am I, am I really bringing any value to, to end end users? You know, why is the release state the most important feature in our product? Uh, that's something I've asked myself a million times over the years. Um, the answer is customers. Um, but, but so even for the high performing DevOps organizations and high-performing software organizations, there are still a lot of questions and still a lot of problems. Um, and what you really want to do ultimately, and this really gets to the theme of the presentation is dev ops is not just about Devyn ops, right?

00:03:46

Software delivery includes a lot of other organizations and a lot of other stakeholders, right? We're talking about, you know, the, the, the executive suite product management, sales, marketing support, you know, all of these things, ultimately, if you're going to deliver a compelling product with compelling features that brings value to your customers and they give you back, whatever it is that you want from them, you know, money, love, respect. What have you, a lot of different stakeholders need to be involved in this. It isn't, you know, at scale, it, isn't really just a bunch of coders sitting in a quarter typing code and deploying it to Kubernetes every five minutes that helps, but that's not the complete picture. Right. And to give you a little bit of an example of this, uh, a quote from one of our large financial services customers, I'm just going to read this because I think it's so very, very relevant while we're doing phenomenally well in our dev ops practice, if we're an able to have better visibility measure the actual business impact and connect our software development and delivery practice to the rest of the organization, we will no longer be competitive in the market.

00:04:52

Right? Part of what this talks about is, is I was going to say a new kind of silo, but it's not really a new kind of sallow. It's, it's been there the whole time, but it's data silos, right? From all of the various tools that we use, right? All of the various stakeholders, all of the kind of cross-functional teams that we use have a ton of different tools that get used, you know, from, from even pre-commit right, design tools, product management tools, all of those kinds of things, all the way through to when a product is actually live and in production, whatever that means, you know, whether that's a web application or whether it's some firmware that's burned into a chip and goes on a satellite or, or, or what have you. But really the, the, the key thing that we're all trying to do is tie what we're doing to the business objectives, right?

00:05:39

Cause we're, we work in organizations that are typically for-profit businesses. I would say, even if we're, if, even if you're a not-for-profit, you still can't lose a lot of money, right. Because you'll run out of it eventually. Um, but th this is a big problem, even for high performing, uh, high-performing organizations. So the process of delivering and realizing the value of software and wealth involves a lot of people working with a lot of tools and data, not just Devin ops. Right. And if you think back 5, 10, 15, 20 years, kind of back to the battle days when, you know, everybody was siloed, you know, dev writes some code, throws it over the fence to the QA organization who tests it for a while, throws it back. Cause it's not working, you know, back and forth, back and forth. And then, you know, we throw it over the fence to the ops people and they're like, okay, well, how am I, how do I deploy this?

00:06:28

How do I run this? What, what is this, um, we've, I'm not going to claim that the industry has solved that problem for everyone, because it's a very complex problem, but we have made great strides, but it's not just a dev ops problem, right. It really does go across the organization. So if you think about a product organization, right, got a couple of products here and B we're trying to deliver features, we're trying to deliver value to our customers, right. That they find delightful and, you know, bring value to, to, you know, their lives or at least their work lives, you know, sometimes their real lives as well. And, you know, we're, we're trying to do this at the same time that we're trying to generate revenue, right. So we have to come up with something compelling. So we have to have some ideas and then we have to realize those ideas in software.

00:07:18

And then we have to get that software out the door, operate, it, support it, you know, all of those kinds of things. And we have a multitude of tools. Right? Kind of if, if you, if you look across here, just sort of, you know, as an example, and if you, if you broaden outside, uh, broaden the purview outside of just kind of the dev ops, you know, kind of silo, you're dealing with things like Salesforce, right? So your, your, your salespeople are doing forecasting based on the products that are coming in the pipe. Right. And they're trying to sell these things. So there there's a tool that probably most software developers don't spend a lot of time in. Right. But still it's part of the process. Part of what we do JIRA, of course, as an example, is, is something that a lot of developers use, support organizations, product management organizations, you know, those sorts of things.

00:08:07

And I'm not, this is not a product pitch for all of these products, because this could just as easily be, you know, rally version one, but Zilla for that matter, you know, all of those things, um, and then you might be doing continuous integration with Jenkins or, or core you might be doing continuous delivery, application release, orchestration, continuous delivery, release automation, depending on which analyst you, uh, you follow with something like CloudBees flow. So there's tons of tools out here, right? And then you deploy that into production and you're, you know, maybe you're running in, you know, Google cloud, right. And maybe your support organization uses Zendesk. Uh, so, so there's, uh, there's a whole ton of different kind of data silos, ultimately, that, that, that we're dealing with here. Now, here's the problem, though, at some things get stuck, right? We don't deliver on time or we don't deliver quite the right thing or it doesn't work.

00:09:02

Um, or, you know, all of these kinds of things that you run into, right? So certain things, certain features are moving forward, the way you expect them to, and other processes, other efforts get stalled right now, what I'm showing down here is just kind of, there's lots of data being thrown off by all these systems. Right? And, and, and again, don't take these product names kind of literally right. Insert your favorite product here. Uh, cause this really isn't about these specific ones. Right. But we all have, and actually some of us have multiple of these, you know, working with a customer who, uh, who are still working with four different FCM systems, right? Some on-premise some in the cloud and I'll tell you what the on-premise ones they're not going anywhere for, for the next decade. Right. Too many engineers on there. They're not going to move it, you know, all of those kinds of things.

00:09:49

So, um, there, there's a lot of complexity. There's a lot of tools and the larger organizations, you know, I go out talking to them and I say, well, what do you use for this? You know, what, what tool do you use for SCM? All we've got, we've got a few, you know, what tool do you use for bug tracking versus your dryer? We got a few, you know, so, so oftentimes you're dealing with multiples of these, not just once. Uh, and, and, and that's even more so if you're in a large organization, say that's built through acquisition, mergers, you know, those sorts of things, you're, you know, your, your first step is not generally when you, when you pull in a new product team to say, oh, by the way, now go re go rewrite all this stuff that you wrote in Python and go, and then stop using bug Zilla and start using, you know, version one and, you know, XYZ.

00:10:32

Right. You don't want to mess with what's working. Right. And presumably it was working or you wouldn't have, you know, acquired them in the first place, but it's messy. Right. And we don't always know, we don't always have visibility into what the problem is. Where is the blockage? Right. We, we know the sink is backed up, but we don't know where in the pipes, the problem lies. Right. And that's a big, big challenge. Right? So in, in a world of data silos, disperse, tooling, you know, we, we require tremendous effort every day to keep on top of this. Right. And what's honestly the number one tool I see use to, to, to manage this stuff, spreadsheets, right. Get all the stuff out of this JIRA instance, get all this stuff out of that. Jared's does get a bunch of stuff out of get hub, get a bunch of stuff out of Perforce, you know, get a bunch of stuff out of version one and try to correlate it, try to figure out what's going on.

00:11:24

Right. Lot of that stuff still going on, that's not core competency, right? That's not what any of us want to do on a day to day basis. When we want to do on a day-to-day basis is deliver valuable product to our customers so that they, again give us, you know, money, respect, love, whatever it is that we're looking for. So in order to solve this problem, right, organizations have to become more seamless and more connected, right. Between all the stakeholders. And that requires a number of things, right. That requires that we have a set of common data that we can operate on. And I, and I think I've just kind of gone through the, the, the, the nightmare scenario of why there isn't common data, right? Because we all have 50 tools or a hundred tools that we use on the path to delivering software and managing the processes of, of, of, of bringing that software out.

00:12:17

And what we want on top of this is just some universal insights, right? We want to be able to reason across these different sources of data, because we have questions and the answers to those questions are in the data often, um, frequently, not always, maybe, um, but the data doesn't live in one place, which has, you know, hence the spreadsheet approach, right? Hence pivot tables. Um, and the processes are not always connected either. Right now. This is something that we worked on over the years and have, I would argue, have gotten better at over the years in terms of making sure that, you know, if we sit down and we do a value stream mapping, and when I say we, I mean the industry, not, you know, not me, we, um, you know, we, we do value stream mappings. We, we try to discover where the hidden work is.

00:13:02

We try to figure out, you know, what, what are the things where we're spending time that we didn't expect to spend time on all of those sorts of things, but it's still kind of largely a dev ops centric kind of thing. It doesn't help product management that doesn't help sales. It doesn't help support, you know, all of those things. And what we really want is all functions, collaborating together, seeing the same thing, making the same decisions based on the same data. So what we're working towards, uh, at CloudBees with, with software delivery management and our solution, uh, for software delivery management is bringing all this stuff together. Right? So giving you a common set of data. Now, this doesn't mean throw out all your tooling. In fact, it's quite the opposite. It means whatever tooling you're using, we'll, we'll, we'll ingest that data. Right. So we're sort of, I would say the Switzerland, except I'm Swedish, I'm going to say we're the Sweden of, of this, right?

00:13:55

We're, we're, we're gonna, I, I great. If you use a cloud-based flow or cloud bleeds, Jenkins, or core to do your CIA and CD stuff, but if you don't, that's fine too. We'll ingest that data as well. Right now there's a couple of ways that you could sort of solve that common data problem, right. You could say, oh, just buy my tool. That does everything from soup to nuts, and then you'll be happy, but now you're kind of locked in to one vendor and that's not always good. And you may not have the freedom, luxury, resources, capacity time to do that because you have 50 different software teams using, you know, maybe core 25 tools that are common. And then there's a whole other ecosystem around them that aren't common across all of these organizations. So, so getting access to all of that data and making it available so that we can start to connect these processes and start to answer the questions that we all have is a tricky thing.

00:14:52

And that's where, you know, you know, fireworks the cloud based solution for software delivery management. That's what it's all about. That's what we're working on. So to go back to, you know, my kind of ugly picture here, uh, for a little bit, and talking about, you know, we've, we've got some blockers here, things are stalled. We don't know why we've got a ton of data, a ton of signal, right. But what's the signal and what's the noise. And what's relevant to figuring out what the problem is. And across all these, you know, sort of data silos, if you will. Well, the idea is to start to bring some order to this, right? So figure out what all the data sources are, get all that data into a common data model that, that starts to give you a little bit of, you know, the, the capability to reason across these things and ask and answer very interesting questions that then lead you to, ah, that's the problem.

00:15:45

The reason we're blocked here is this, you know, we've got a pull request that's been stuck for too long, or, you know, the reason we're stuck here is we, you know, we have some build failures, you know, all those sorts of things and lets you do it in a way that it isn't just something that somebody spends a day to figure out it's just in your face all the time, right? These are the obvious questions that we all want to know. And this is the kind of visibility that we all want across the organization, right? Across all functional areas. Everybody cares about this, right? The, the, the, the sales person is interested in, you know, when is that feature going to get delivered? Because I have a ton of customers who want to use it, right? The project product manager wants to know how's the progressive roll out going of this new feature.

00:16:28

You know, where are we still just an internal usage or are we starting to do a little more, you know, kind of roll out to various other constituencies, all of, all of those kinds of things. And what you want to get to is kind of the, you know, the, the happy state where you understand what the problems are, what the blockers are, and you can start to remove them, right? So that's, this is the Nirvana, you know, that we want to get to. And what I want to show you in, in, in the remaining slides that I have here are, you know, some things from the cloud-based solution for software delivery management, uh, some, some of the screens, some of these things, I'm going to be perfectly honest with you are a little more prototype E than others, and some are more real than others, but, but this is an I'll talk about that in the last slide, in terms of how you guys can help.

00:17:13

So here's an example of bringing all the data together. We call this our product hub, right? So we're, we're, we're looking here at our song streaming product. So that's the product that we've chosen up here and right away you can see we've got, you know, Dora metrics over here. We've got all kinds of data sources coming in here in terms of, you know, support tickets and what are people liking about it? You know, all of those kinds of things, we can see what features are in play, right? Cause to remember what we're doing is we're delivering features, right? We're, we're working on concerted efforts, you know, whether you call them epics or tasks or features or missions or value streams or, or what have you, this is what we're working on. Right. And you want to know, where are we stuck? Why are we stuck?

00:17:58

Or if we're not stuck, great, what's this team doing that, this team isn't doing that, that there's so much more efficient at doing this right. So bringing all that data into one place, right? So they don't have to go visit a multitude of different tools to answer these questions or kind of the flip side, which is almost a worst scenario, pick a tool that does everything for you. And then you don't have best of breed. Anything you have kind of lowest common denominator of, of, of everything. So that, so the product hub is, is, is the kind of functionality that you get in, in, in the, uh, in the solution for, for software delivery management, when we bring all of these data sources together, right? So pulling from your CII systems, your CDs systems from your repositories, from you, issue tracking systems from your feature flags systems, from your support systems, you know, I probably mentioned some of these, you know, multiple times already, but that's when you start to be able to answer these kinds of questions without having to chase down 14 different data sources and munge it in, you know, Excel or Google sheets until, you know, until there's blood coming out of your eyes, which, you know, a lot of people spend a lot of time doing.

00:19:03

And if you care about things like value streams, it also allows you to start really kind of looking again in one place you start to get to see what are my value streams, what are we working on in this particular case? We've kind of subset it a little bit, what, we're, what we want to see here, right? And if any of you are our CloudBees dev optics customers, you'll, you'll probably recognize this screen because it's something that's in the existing dev optics product. And of course will be the kinds of things, uh, that you'll see in, in, uh, in the solution for software delivery management as well. So again, really unprecedented visibility into your value streams, no matter what tools you're using underneath. Right. And, and I, and I want to emphasize that, right? So no matter what data silos you're sitting on top of with all of these awesome tools that you've, that you've chosen sometimes again, you know, lots of organizations have many different tools, uh, to, to, to do the same thing, but all pulled together.

00:19:58

Right? So if I'm, you know, if I'm stuck somewhere waiting for a pull request, it doesn't matter that this team is using GitHub, you know, dot com. This team is using GitHub enterprise. These guys are using Bitbucket. These guys are using Perforce. It allows you to start to start to reason around, Hey, are we stuck in SEM somewhere, right? Are we stuck in a brand in branching, howl, or code review Howell or, or those sorts of things, for example, um, and really allows you to kind of look at your whole value stream here all the way out into, into, and past production to figure out what's going on and to see where we're, where the bottlenecks are ultimately. And this is, this is, you know, and I'm going to be perfectly blunt, Terry, you know, this is conceptual, this is, this is not there yet, but this is the kind of stuff that we can start to drive as well, which is an efficiency dashboard.

00:20:46

How are we doing? You know, what kind of recommendations can we kind of pull out of this, right? Hey, most organizations consider a pull request to be stale after a day or two, right? So maybe create a policy that gives you an alert, a badge, a notification, you know, whichever way you prefer to, to radiate that kind of data. If you have a pull request that's been sitting there for more than 24 hours or a day or two or three, or, you know, whatever makes sense for your organization and starts to give you kind of across the organizations across the entire enterprise visibility, into the whole software delivery, uh, management, uh, work stream, which is, which is, which is pretty key. Um, but again, in order to do this, you need the common data, right? You need the visibility into the processes that are behind these things so that you can start to ask these kinds of questions and, and, uh, and radiate them out.

00:21:43

Now, if I'm an individual contributor, right, I might be more interested in this, which is kind of the, the, the, the contributions, uh, kind of view. So, you know, if I'm working on a particular epic care, I can see, you know, who am I blocking? Who's waiting on me, right. Why am I blocked? You know, is there a pull request that, that needs to get merged in? Is there a branch that's broken and not building, um, is the dev environment down, right. So I can start to answer a lot of the question. And again, instead of having to go visit multiple tools in order to find these answers, that data comes to you instead of you going to the data. Right? So instead of me going to Gero DAS and ask one part of the question, and then going over to the build system or the CICT system to figure out another piece of data, and then either correlate them in my head.

00:22:31

So my head explodes, um, or, or throw it into Excel or, or, or what have you, we have, you know, kind of one place. So the data comes to you instead of you going to the data. And th that, that's a really kind of powerful aspect and lets you involve all of the different stakeholders, right? Because now it's visible, you know, now I can go in as a product manager and look at the progress of a particular feature or for that matter as a support person, right? Because when, you know, as a support person, one of the things I might care about and I'll, I'll show this in a second, it's kind of, well, you know, is that feature even turned on for that user? You know, cause if we're using things like feature flags using, for example, rollout, uh, which is a great product that we acquired just recently, uh, or whatever feature flag kind of system you're using, whether it's homegrown or, or one of the others, again, we're, we're Sweden.

00:23:20

So we'll ultimately pull from all of these data sources. Um, of course our own we'll probably have most favored nation status to be, to be honest, but, but we're, we'll, we'll talk to anyone, uh, we'll ingest data from, from just about anything. But the idea is now you can start to see what all the relationships are between these things, right? And instead of again, instead of you having to go visit all the different data silos and then try to integrate it all in your head, it comes to you. Right. And not just you, but everybody, the organization, um, and that allows you to do more interesting, uh, you know, in, in, in the future. So, you know, let's say I'm working on a feature. Well, where's the definition of that future where all the artifacts around the design for that feature. Right. So I can start to do things like provide visibility into, well, what are the envision, uh, you know, uh, designs that are related to this kind of functionality?

00:24:08

Um, what are the aspects, uh, that are involved, uh, in, in, uh, in, in, in, uh, rolling this kind of thing out and I can get all of this visibility again in one place, right? No matter what tooling I use, you know, so if today you're using, you know, product X for issue tracking, or maybe, maybe, maybe teammate uses product X for issue tracking, but team B uses product Y right today, you're kind of stuck. The idea here is very much that there's there, there's obviously a common data model here, right? One person's issue is very much like another person's issue, right? Whether you're using, you know, JIRA bug Zilla, um, you know, w w what, what have you, right? It's, it's, it's very much, there's a core common data model, and there's a lot of power, especially for larger enterprises. And being able to ask these questions in a very generic sense without having to get very specific about where did that data come from, or having to go dig in and become a, a JIRA expert or become a rally expert, or, you know, the, the, those kinds of things.

00:25:04

And that that's, you know, very much a, a core part of, uh, of, of, of, uh, our efforts here. And that allows you then to start doing really interesting things, right? So let's say that you want to start using feature flags, right? Because we know the features that are being worked on, because let's say that we extracted that information from, from JIRA, from the epics that are in there. And we've put some definition around that. We, we have a lot of information about, uh, what's in production and what's not in production because we have that information as well. You can start to, to, to not just make visible the kinds of things like feature flags, but also make them actionable. So, so from this kind of dashboard, you can sit and say, well, you know, we're, we're still using this only for internal customers. We're internal preview folks, but we're about to unleash the hounds on, on the rest of the world.

00:25:56

Uh, maybe we'll start with, you know, what I mean, you know, or USA, or, or maybe we'll do a little bit in each, you know, those sorts of things. And, and, you know, if you've ever worked with feature flags, you know, what a, what a freeing and amazing thing it is to be able to sort of deploy darkly, right. And have things be in production, but be able to control how you turn it on, right. To be able to preview it for people, to be able to pull the switch and turn it off if there's a problem. Right. So that instead of having the big bang rollout of O'Hare, here's our great new feature, you got a hundred thousand people who use it the first day, and it just craters because we forgot to do scalability testing or didn't do it well enough, or, you know, found a corner case that we didn't know about before you get to play with that a little bit more.

00:26:41

Right. So, so feature flags, whether you use rollout to do it, or build it yourself or another product, you know, check them out because they're incredibly powerful and incredibly useful, uh, in, in, in, in getting stuff into production, without breaking it and being in being able to experiment and, you know, show some people one thing and show some people in other do AB experiments, all of those kinds of things. Very, very, very powerful, a very, very powerful concept. So what I've shown you there, um, and talked about quite a bit for, for the last 20 odd minutes is just this idea of common data, right? There are data silos. So we might be awesome at microservices. We might be deploying multiple times into production every day, every hour, right. We might be rolling features, you know, left right and center, uh, into the world and doing all of these things.

00:27:34

And yet we're, we're kind of not at Nirvana just yet, right? We're not at the point where we can ask all these questions and figure out where the bottlenecks are without walking the hallways without kind of digging into all of these different kind of different kinds of data sources. So if you want to check this out, it's in preview right now. Uh, some of the things I've shown you are in preview. Some of the things are not yet in preview feature flags. Um, but if you, if you go to next cloudbees.com/join, you can sign up for, for, for the preview and start to check it out. And we're going to, we've already started rolling out some of the early features. We're going to be rolling out more and more and more, uh, as, as, as time goes on. Um, so I've got about a minute and 45 seconds left. So if there's a couple of quick questions, uh, cause I noticed a hand up I'll, I'll take a question

00:28:24

I'm seeing as we're moving forward, Porto containers and microservices is kind of the overwhelming complexity. These apps start with the show up. Are you guys doing anything to kind of help with that help get a better understanding of what they're looking at, how they could deal with their applications.

00:28:42

Right? So I'll repeat the question for those that couldn't hear it. So as we're and correct me if I'm wrong, but so, you know, as we're starting to use more containers and microservices and these kinds of things that actually increases a lot of complexity, right? Microservices are not simpler folks. They're very, very difficult to do. Like one of my favorite Twitter accounts is honest status update. And one of my favorite updates from there was, was one that said, I'm so glad we changed the microservices. Now every outage is a treasure hunt, right? One of the only benefits of a monolithic architecture is there's only one thing to break, right? Whereas if you have 500 microservices and something's broken and you know, Lord help you, if you're not doing good monitoring and logging and those sorts of things. So how do we help? So I, I, so I would say a couple of things.

00:29:25

One is there's definitely help in, uh, in some of our other products. So CloudBees flow helps you a lot with those obviously Jenkins as well, depending on how sophisticated and complicated you want, you want to get, get with that. But part of what we're doing here as well is to uncover where these problems are. So for, to give you a more concrete example, let's say that you have a microservice, you have two, two services you're trying to release one depends on the change and the other. Well, this one, the, the one that you depend on is stuck. Well, why is it not in production yet? So what do I do today? While I hunt down the person who's in charge of that? And I asked them, why is it not in production yet? And they say, I don't know, let me find out, you know, and then either an hour or two or a day or a week later, or maybe they never come back to you and say, ah, here was the problem.

00:30:10

The point about, you know, the, the, the, the real one of the real values here is you'll be able to see the data yourself. You're going to have to go find that person. You can dig into that service, let's call that service a product, right? And maybe there's a new feature that we added to that service. And you can see what the bottlenecks are. You can see that there's an alert saying, Hey, there's a pull request. That's been rejected. And so that's why we didn't go, or it made it into staging, but then it blew up, you know, because of some problem, I don't know, we forgot to make a schema change or, you know, the kinds of things that, that, that tend to happen. The idea very much is pull all of that data together and give you one place to go look at that data, as opposed to having to go track down all, all of the people, because as much as people use the phrase and I hate the phrase, but you know, one throat to choke, it's never just one throat, right?

00:30:55

There's always multiple throats that you need to choke to get the bottom of these problems. So very much the, the, the, the vision for, for, uh, for a cloud-based solution for software delivery management is the data comes to you. And you can ask those questions and possibly not possibly, probably the person that is responsible for getting that service out that you depend on already knows because the system's already told them, right. That's that is, that is what we're doing with, uh, with, uh, the solution for STM. So I'm at a time and out of respect for, for the next person. I'm going to say, thank you very much for, uh, for attending the talk today and enjoy the rest of the show.