Transcript for "What's New in TMON One: Innovation, AI, and the Road Ahead": Hello. Welcome. Good morning. I'm excited to be here. I thank everyone that's here for joining us for our Rocket t mon one webinar. I'm gonna start by introducing myself. My name is Mike Bills. I am the product manager for the t mon one products. I am new to Rocket, new to t mon. And so new to all of you, so I'm excited to be able to meet you and join you on this journey in in my first t mon one, webinar. In a moment, I'll be joined by Rod Dyson, who's our senior director of software engineering, and Satish, who's our senior manager of software engineering. They're gonna be the ones doing the bulk of the presentation. So let me start off with a little bit of housekeeping here for you as we get going. We will be recording today's session, so that, if you have to leave early or just wanna come back and review the information or hopefully share it with some colleagues in that as well, that'll happen. So we'll be distributing the links to this recorded, event after it's over. On the right hand side of your screen, you're also gonna see a q and a option. We're doing this webinar live because it is our intention to engage with our customers and engage with you. So please ask questions or add your thoughts. If you have comments added, we wanna know. One of our initiatives is we wanna know how Piedmont One customers are using the software, what is working and what is not. So even after today's webinar is over, we want engagement from you. We're gonna respond to the questions as they appear and we'll have question and answer session afterwards as well for some of the questions maybe we don't get answered. We got two of our senior, SEs here with us, Keith Vler and David Friedman are backstage ready to help us answer those questions as well. So... And and, again, we'll come back at the end and have a q and a session. After the event is over, there's gonna be a short post event survey that will pop up at the end and we would really like you to fill that out for us, give us some feedback. And this will help... One of the things we wanna get out of this is an opportunity to set the direction for future webinars. We wanna make this a recurring event, so that again we have that connection with with our customers. Next, a little bit of housekeeping is just the presentation disclaimer, that legal has us put up here so I'll pause for a moment so everybody can read that. Just kidding. But mostly this is just gonna say that we're gonna give you the information as it is today and as we see it going forward, But, obviously, sometimes that information can change. So please be aware with that. Alright. With that, I'm gonna give you our agenda. We've got three main things that we wanna cover. We're gonna go over what we've delivered just in this last quarter, maybe a little bit beyond that. So you can see the products listed in that. In in a minute, Rod's gonna come on and talk about those. Then we have some exciting did you know? Things that we think are the release, they're available, they're out there, but we're not sure if you're using or did you know about. And then we're gonna discuss our future priorities with you, and then again we'll come back for the questions and answers with that later. So with that, we're gonna start off with what we've delivered. And I'm gonna invite, Rod Dyson, to come out here on stage and take over for us. So, Rod. Hope everyone can hear me well. We'll just... Awesome. So I wanna start with talking about, Rocket EVA. So EVA is a product that we, released this year. It's on our Jentek platform, Yeah. for many Rocket products integrating into this today. I like to think of EVA as your trusted all knowing SME. It can, it can pull in data from across all the different tech stacks that you have and and answer questions for you. It can tell you the current status of what's going on with any one of your systems, and it can help you diagnose problems. It'll tell you what's happening now, and it will tell you likely root causes if there's any performance problems that you're having with any of your systems. It does all this using natural languages. So, it's just like talking to that system programmer or kick... Or, the system programmer DBA in your site. And it's doing all this under, a governed platform. So there's, authorization and authentication capabilities within this. So what EVA does is it allows you to get to better, mean time to resolution, better visibility into, your your systems. It preserves the expertise that you have in in your your enterprise and really across, all really rocket because we are bringing in many of our products into this space as well. And so we're gonna, be able to really help you manage the performance of all of your workload, your applications, and keep everything running at top efficiency in your site using, this natural language, interface. And it's really wonderful. It will give you likely next steps for any problems that it sees. It's a very it's a very robust system. We're very proud of this. And we're also proud that tMon was, the first product to integrate into, EVA here at Rocket. So super, super excited. I hope you all get a chance to take a look at that and see what it can do for you in your environment. The next thing that we delivered, earlier this year is t mon stream. So t mon stream is a feature of t mon that exposes all the data that we collect in tMon into your analytics engines, such as Splunk or Elastic or Datadog or, you know, bringing it into some of the visualization spaces like Grafana, where you can build your own dashboards. You can monitor your systems, see what's going on across, all the different tech stacks all at one time. It's really useful for being able to do war room type scenarios where you have, multiple people, that are trying to solve a problem in your site. You have you have a Kix transaction that comes in. It's not performing well. Where's the problem? Is it is it is it in Kix transaction gateway? Is it in MQ? Is it in DB2? Is it in Kix? Hard to tell. Bring the data in there. Build these dashboards. You can see what's happening across all of the different, platforms all in one go. Helps you get to your your mean time to, resolution faster. It also brings the the mainframe performance metrics into your observability platforms. So your SREs now can see end to end, workload moving through across all the different platforms, by using these tools. So it's it's a it's a great product. We have customers that are using it today, building their dashboards. They're replacing, in house maintained dashboards that they have built over the years with the streaming solution. It's very powerful. We hope you get a chance to look into this and use this sometime soon as well. So health AI is also a tool that we introduced, actually a couple years ago. We we made some additional enhancements to this earlier this year. Health AI gives you an opportunity to see changes in your workload behavior early so that you can take, preventive action against any, per... Potential performance problems. It it allows you to see anomalies in the performance. We create a baseline of normal workload. That normal workload then tells you what to expect from all of your different applications in your workloads. And then as, the work... The the transactions or threads or other work starts to trend away from normal, it'll identify you earlier, so that you can fix the problems, before they become serious. So some of the things that we've done this year with Tmall dot ai, one, we're expanding additional KPIs into the product so that you'll you'll have a more robust, vision of what's going on with the health of your systems and your workloads. But we've also moved a lot of the processing off the mainframe. So the baseline work that we do, the evaluation for anomalies is being done off the mainframe. So we're not using any of the mainframe MIPS or any additional CPU overhead, keeping costs down for you for that. This was a request from many of our customers. So we moved that off to run on a Linux platform now. And in order to help you implement this easily in that environment, we have containerized, the health AI and stream. And as we support for EVA with the MCP, all of that is now in a container that you can install quickly on a Linux system, get it up and running very, very fast. One of the things that we've done, and we're gonna talk more about this in a moment, we are working with tmon to reduce the effort it takes to install and implement tmon in your environment. We've been going through this simplification for the last couple of years. We've made some great strides this year. We'll talk about more of that in just a minute. The containerization that we're doing for health and stream, in particular is a key part of this. And, we think that it's very valuable to help you get to value very quickly with these tools in in your environment. So moving on to talk about that real quick. The other thing we've introduced this year is tmon quick start. This is relatively new. This has only really come out, within the last quarter. Tmon quick start is our attempt to reduce the number of steps to install tmon to as few as possible. And if you look on the screen here, you can see that there are four key steps to to making this work. K? Download the package, extract it using asg pop just like you always have. The asg pop in... Initializes all of the libraries, gets all the datasets loaded, everything's up and running. It's practically ready to go at that point. If you need to install tmon for kicks, then you do need to go through and do some of the kicks configuration like we do in the past. But once that's done, you're ready to start the monitors, and they're ready to go. If you do wanna do something with t mon stream, there is another step that you need to do to set up the, the the gateway... The streaming gateway in order to, get the data into your endpoints. But apart from that, you're done. Our goal is to make this as painless as possible, in in order to implement all this. Now this installs... Quickstart will install our key five products, DB2, KIX, XOS, TCPIP, and MQ. And all of that can be done very, very quickly. If you can do the advanced work, if you need to do any APF authorization or SAF authorization, if you can do that ahead of time, once you download the package and install it, you can get t mon up and running, all five of those products up and running in likely less than an hour. So it's a very, very fast, very, very efficient method to do that. One of the other things that we offer with this is is what I call our bespoke packages, where you have a questionnaire, you fill it out, you give it to us, we will build you a custom package for your site, that runs through the, the the ASP POP process. And once it's done, it's fairly preconfigured. You might need to do some work with exceptions if there's anything else you need to do with that, if there's any changes you wanna make there. But apart from that, it's ready to go. And you can, essentially get from package download to streaming data into the, into those other systems very, very quickly, you know, certainly within an hour or two of of starting this process. So, hopefully, this is gonna be valuable to you all. Maintenance, if you need to do maintenance, this fully supports all the maintenance capabilities that we have. And, typically, with... If you try to upgrade to a new PS package that we distribute, you can do that in minutes rather than hours. So we we like to say that we're taking this down from days or perhaps even weeks in some some shops down to hours in order to get TMon up and running and get you the value that you need from the product. So, hopefully, you'll find that valuable too. Also, in the, this this latest quarter for our p p s twenty six zero three delivery timeline, we delivered d v two... T mon for d v two six dot two. This is the the latest upgrade to tmon for DB2. And I think one of the key things that we delivered in this one is the filtered thread logging. So in in the past, if you all have been doing any collection of t mon metrics and LFS, you know, that there can be an awful lot of data that we collect for that. So the filtered thread logging allows us to limit the the data that we collect and store and maintain in our archives only for those that you want to collect. So you can use filtering in there to only keep a subset of the data and not all of the data. That helps you better manage, the reporting and the managing your storage considerations and any overhead on the system that might be incurred through this. We also added a couple of extra support for some of the DB2 features that were delivered over the last few years. We added support for fast traversal blocks and, incompatible SQL changes to the product. So you can get reporting on both of those now. Another request that we have from a customer was to add thread CPU visibility to our thread summary screens. So with that, we will now calculate the CPU percentage that a thread is using and display that on the screen in a color coded chart, color coded graph so that you can identify any of the threads that are using the majority or or too much CPU, and help you better manage, you know, keep the keep the overhead down on those. That way you can understand, you know, if there's any particular packages or whatnot that need to be, explored more, researched more to understand, why they're not... Why they're using so much CPU. Are there ways that we can better, improve upon that? Sorry. I didn't get one. Next slide. The other, major release that we had in this past quarter was for tmon for MQ. In tmon for MQ, we provided the, the MQ version 10 toleration support for tmon MQ. So we will now work compatibly with, version 10. We also added in the dead letter queue, the ability to see any of the codes in there that are both in hexadecimal and decimal, whereas I think in the past they were only in hexadecimal. Now you can get it in both forms, then help you better understand what's going on with that. Also, with the, account time and statistics, time parameters, the intervals for that, we've separated those now so you can do accounting and, system statistics, on on their own intervals, and they're no longer overlapping, give you a little more capability with that. And we added more streaming support. There's an additional eight records that we are now streaming for t mon for MQ, into the t mon stream solution that we talked about earlier. So you can see those now, in your dashboards, give you a little more insight in what's going on in your MQ systems. So that's what we've delivered this year. If you have any questions, please let me know. Be more than happy to address that. At this point, I'm... Rod, I I haven't seen any questions, but I I actually had a question for you if you could. Sure. As I told everybody, I I... I'm new to Rocket and I'm new to t mod one. But, I I thought one of the points that, I want a little more clarification on was the quick start because. that that has really impressed me is is coming on. Can you go into that just a little more detail, the kind of what life before quick start was and how quick start is changing that? Sure. So if you look at the installation instructions for tmon prior to quick start, you'll notice that there were, I think, 17 steps in order to install t mon strategic services. T mon kicks had something like 33 steps. T mon for d b two had an additional, I think, 17 steps, etcetera. We... We've taken all of that. We've consolidated all of the work that all of those need to be done now, and we have brought that down to essentially just running these four steps that I mentioned. We've combined everything into, we... We've improved the JCL, streamlined the JCL, improved, the way that you enter in any of the configuration values for any of these systems. For that, it's now down to, one job in... That basically sets up all of the datasets, gets all the configuration in place, all the control files to control reps, all the repository work. Everything is done now with one job. We're we're trying to get to the point where you also don't need to do any of the SMPE work. It will be predone for you when it's distributed so that, when things are installed at your site, everything is just there, and it is fully maintainable going forward. I believe today there is a... An extra step in order to do any additional S and P e work that might be done, but we're also trying to work to to eliminate that. We want this to be as as single job possible as we can make it. So in essence, we have taken our installation documentation down from 151 pages, I think down to less than 20, and the total number of steps that are even inside all of our JCL. It's nothing little bit. near what it used to be. that's that's the... What what I understood is an installation prior to this could take days, if not weeks to set up, and now we're talking under an hour for the entire t model one suite. It's possible. Yes. And and that's not only for new installations, but that's maintenance and patching as well. Correct. Okay. And then we... I I I think that's amazing. So I just wanted to call it out. That was one of the first things that struck me as somebody, you know, new to t mon in that. We do have a couple of questions that have just come in. The first one was, for applications that use both MQ and d v two, does Timon provide any correlation? What's what's the right way to answer that? So, certainly, we can do correlation in in a way with t mon for stream if you're streaming these into some of the dashboards. There could also be some correlation between that if you're using Navoplex by bringing all that information onto a single screen. Keith, I might ask you, do you have any other insights into how to answer that question? You could come on stage. Yeah. I'm not sure on on exactly how to answer that either. K. Good. We can we can follow-up with that, and get back to you. So, we... We've got time in the the, the webinar, so we'll research that and get back to you. Let me do one more and then keep the questions coming, but we'll we'll we'll go on with the presentation, because it's around the quick start. And if you see this, Rod, it's for the quick start. Will we be able to do it for for one component separately, I. E. Just team on for Zos, or do we have to do all of the components? No. You can you can certainly do it, you can think of doing it the way you do it today. We we distribute all of t mon together as one package today, and you then go through and do your installation individually as as all you want. Just because we're being able to provide the ability to do all of this in one go does not mean that you have to install all of these at the same time. So, yes, basically, it's what do you... Where where do you wanna start on your end, and that's what you that's. what you can. do. Thank you. We have some more questions coming in but I'm I'm gonna pause on those. We'll we'll kinda answer those, backstage. I want to make sure we have time for the presentation. So Rod and Satish, I'm gonna turn it back over to you. K. Thank you. Okay. Thank you. Thank you, Rod. And I'll take it on from here. So hi, everyone. So I'm Satish. And, so far, you have seen what we have shipped. Rod has explained that to us. And I would like to now focus on EVA and see how Timon and EVA work together and provide the value add that you would be looking for. And I'll also be talking about how Timon's team helps in using the visualization and dashboard. So... Okay. Screen has moved. K. So since Rod has already spoken about EVA, I'm not going to again, talk about the same, but let me try to build on it instead. Right? So what makes EVA different? EVA understands the operational data across your, mainframe, distributed systems, and, the cloud infrastructure and brings that information together to provide the context which the teams need to investigate issues... With with issues generally, you know, it really requires, quick attention and analysis. Eva can work along with the operational tools and ticketing systems that your teams uses every day. That means you can ask questions, to Eva such as, hey. Have we seen this issue before? Or how was it resolved? Or, you know, what's mostly the likely, cause for this? And what should we investigate next? Right? So the outcome is faster investigation and, faster resolution. So we we often describe EVA as a virtual mainframe, expert that's available, to you around the clock, helping the team understand on, what's happening, identifying the most effective course of action, and learn from, the previous incidents. So it all boils down to the points that Rod explained earlier. Right? UI helps in reducing the mean time to resolution, improve the operational visibility, and, preserve the critical mainframe expertise for the next generation of, operators. K. So when when people think about AI, you know, they generally picture the chat experience. But honestly speaking, what excites me more is what happens underneath that, how it actually helps operational teams get to an answer faster. And and here's the thing, t one already has a ton of performance and operational data sitting there. So EVA does not replace any of those data, but it just builds right on top of it, helping, helping you to navigate it, interpret, and connects the dot, instead of you doing it manually every time. Let let me show you, you know, of how it looks like. Let's take the scenario of an operator getting a message that, for example, an application called Genapp is running slow and the customers are complaining. Normally, that's the jumping between, CICS and d b two screens if it had to be done manually, trying to piece it together. Here, the operator just asked EVA in a plain English like language, And, it comes back pointing that to to a DB two deadlock on one of the CICS regions. And interestingly, the CPU was actually below normal, which tells you the the task was just waiting and not overloaded. That's usually the hardest thing to catch manually. So whether it's a performance issue like this one or you're simply trying to understand what has changed, that's really the shortcut Eva gives you from, symptom to the valuable insights you look forward to. And there is also a knowledge side to it. Not every team has a seasoned expert or a Timon expert sitting right there when something goes wrong. So Timon, just... Eva just helped you in filling that gap, and, yeah. So that's about slide, and then let's quickly look at some of the use cases. And when I say use cases, this is pretty much, in correlation with Timon and EVA. The gen example a, a gen app example that I showed earlier was just one case. I'm not going to really look at, read through all the use cases which are there, but this presentation will be shared later. And you can always take a look at these cases and then come back to us for more questions. And these are use cases specifically about, the Timmons, from the CICS, the DB two m q, which is fed into EVA. Let let me take just one or two right on the kick side. We have a scenario with the task queue building up. So EVA correlates that against the throughput and the CPU. So you know right away if it is the actual runaway work or, it is just thing that it's waiting for its tone. Right? And, on on the MQ side, right, the queue manager stress, it looks at, the buffer, the IO, and the storage together to pinpoint whether it is a contention or or or a or a memory issue. So we would be happy to hear, you know, from you in our chat or or in a form... Forum that we have for Timon or later in one of our discussion. Right? If you wish to have a one on one discussion with, with our team. Right? We would like to hear more about some of the use cases that you have and where you feel, EVO and Timon would would be of help to to your instances. So what we saw on the earlier slide was more, with Timon and EVO together, but that's not the only, work that EVA is doing over and above. You know, it has multiple other things in which you can, reach beyond Timon. Something like the production incidents for any products or or or any system, the job failures, the skills gap, the impact, the workload optimization. Some of them, you know, are already available in terms of, the tools that are present in your environment and not just the t mon data alone. I'm not going to go tile by tile, but but the point I'm trying to make here is t mon is just one strong source feeding, its data into EVA, but it's not the only one. And for a good number of these use cases, we already have some demos that are readily available, and, we would be happy to do a walk through with you, you know, in future. So that is about, how Timon and EVA, you know, working together seamlessly to provide the value add. And, let me switch gear and talk about, the Timon stream. Right? So at the beginning, I spoke about what what data looks like once it lands in the dashboard. I would like to talk about it and explain more about what the data actually looks like when it starts to flow from end to end. This slide that is shown here is just a map of across Zeebo AS, CICD, SDV two, MQ, and TCP IP. Here's the shape of what what is the data that we have actually streamed so far using t MonPoint products, through the LFS records that are available. Again, I'm not going to read this line by line. We have the complete set of record types that we have streamed so far here on this screen and later in the appendix section also. We have given the full blown type of metrics that we have added so far. I'm sure those metrics are going to be really critical for you to derive them and put that... Or use them into any of the dashboards that, you have been using. So just to sum up, whatever we have delivered or streamed so far are not just handful of metrics, but it's it's a significant amount of metrics that would be good enough to build a real operational view of your, mainframe data. So we have been adding these records in a cumulative manner since the last two releases, started with twenty six zero one. Right? So let's quickly look at the dashboard that also comes along with team on stream. Right? Just in case, right, you install team on stream and if you do not have any visualization that... Dashboard, but would still like to start with the visualization, We we are packaging, a prebuilt dashboards, right, bundles or sample dashboards that we call, which comes in very handy with some basic information about your critical, information about your environments. And we provide these dashboards for Kibana and Grafana at the moment so that you are not starting, something from a blank screen. It is already available to you in a usable form and still use easy enough to customize if you would really want to tweak it. And one other thing that is worth calling it is it... It's not just only limited to the live data. You can do the same for the historic data also. You can actually compare of what's happening right now against to, you know, what has happened in the past. What you see here on the slide represents a snapshot of, a zOS dashboard where it displays the top jobs by CPU type. And the image to right of it, it it represents the same by the SRB CPU time. Alright. So it's not very different from the previous slide. It's just the same data, but a different view. And this one, you see on screen... On the screen on the top left corner is the one that represents the Kicks transaction performance report, and below to that is, TCP connection performance. So between this and the previous slide, you you would be getting a sense of the mainframe side and the network side sitting next to each other, which going back and forth, you know, of what we talked about earlier is, the real whole point of stream. You just have one place where you can look at instead of switching between different tools depending upon what layer you are trying to check with. We have also had, customers working with us, for some use cases with team on stream. And I would like to just talk about, one particular use case in the business of time. Right? One of our customer, leading bank from Asia Pacific region, They have a dashboard that talks about or that shows all the vital metrics... Performance metrics shown up, to see the health indication. And the way currently they are doing is to do the... Using a screen scraping method. So they use the multiple team on products, scrape the values from the screen, and then pass it on to the elastic, which is then delivered to their Grafana dashboard. So with with the stream enablement, they are able to stream the same set of records, which we have been scraping from the screen and, stream it through team on stream and... Which is sent to Elastic, and they are able to see this same data on the dashboard in a better way. They had some limitations with the existing method of screen scraping. You know, obviously, when the when the script fails, you know, it's not able to drive the data or when the coordinates changes a little bit, then it's not able to identify the data that it is looking for. So this has been extremely useful for them, and, they have already started to see the benefits of it. K. So moving on from what we have delivered to see how Timon and Eva work together and then the benefits of Timon's team. Right? I would also like to talk about, what we are currently working with. Probably... No. That's the last slide for me today. Right? We are working on some of the interesting enhancements, in terms of the modernization, activities. And few areas we are looking at is, Rod spoke about HealthAI and how key performance indicators are the key, input for it. So Health AI already has some curated list of key performance indicators, but depending upon the use cases and the voluminous activities happen at a typical customer environment, we are trying to expand, more on, the KPIs that are already available. So this has already been requested by some of the customers, and we are happy to say that we are already working on it. Alongside, we are also working on coming up with the short term predictive analytics so that, we can move away from our reactive monitoring to proactive and then, looking at the past data and give them a kind of prediction as to, you know, what could possibly happen in their environment and, help stop that. So these are some of the key, initiatives that we are working with. And then I would like to shift my focus and, talk about the customer priorities. Right? What matters, the most to you. Right? We would like to hear from you about, your your pain problem, the problem statement, or any request that you would like to see in our future, or or in our products as a feature. So you can, let us know in this chat, or we have a team on forum exclusively meant for it, which Mike will be talking about in a while. Or you can also have a one on one call with us, and we'll be happy to hear and see how best it can be delivered as a feature. Right? So that is pretty much from my side, and, I'll hand it over to Mike. And before that, there are any questions for me, I'll be happy to have them. So, Mike, can you help me Yeah. go through modifications was? I was, trying to find that button to come back on on stage, so I appreciate that. I I think we have gotten all of our questions, answered so far. But, I do wanna take a minute. Everyone who is joining with us, if you have additional questions, please get them in. And let me go over a few more items while we're waiting for some of those questions to come in. So this is really on team on one engagement. And and and our desire as a team on one team, product management, engineering with Rod and Satish, really everybody involved in this. We want to make sure we have engagement with our customers and with our community involved in that. So if you haven't seen this and are not aware of this, please come out and join our Timon, Timon forum. This is a community, for Timon users. It's meant to be bidirectional. This is so you can engage with us at product management, engineering. We want support to be involved out there. Come and put posts out there, ask questions. You can even, talk to other customers if you want to out there as well, you know, share experiences and and solve problems and that. So, you know, this is... We we... We're gonna post a webinar out there. We we we... You know, intentions to get how to videos, wet... White papers, all that kind of information. But we don't wanna just be pushing it to you. We want you to engage back with us on what's coming out there. So getting access to the experts, the latest updates, interactive discussions, and and kind of build a community. It's new. It's just starting to develop. So please come out there and engage with us. And this is your opportunity outside of these webinars or or when we communicate with you, you know, to come and and talk and have that conversation. Like I said, we we really want to, build products that work for you, and then solve your problems and help us understand what those are and what you need out of them. So engage with us on that. The next one is we we have the ability... And I'll give you some contact information here to send us if you're interested. That is is we've done this with multiple customers in the past where you can give us, some of your data. It's it's it's just confidential. It's not gonna go to anybody. You can choose an area with a history of issues. One or three months would would be helpful. You know, give us that LFS or SMF records. We'll run that and show you what we can diagnose and how things like Ava and t model and health and that can help you, you know, give some reports on that on there. So if you're interested in that, again, no one else will see that. That'll be just a conversation between you and us. But if you're interested in that, at the end of this, I'll give you some contact information and you can send that out to... Send that back to us as well. And then, a couple of things after the webinar. We've had a a website refresh on t months. So go out and take a look at this, you know, the the URL, it's kinda the the others, so hopefully you can see that a little bit bigger on that. But, the t monde webinar, we've been... Our marketing team has been doing a fantastic job with reps at getting you information on us to check it out there. You're gonna get a survey at the end, and this goes to parts two and three. Please fill that out and provide honest feedback on how this went for you and what you would like to see in the future for this... For webinars, you know, how we can make this engagement and that better for you. So I've been talking here for a moment on this. So, is it... I don't know. Tim, has there been any more, questions that has come in, that that we need to to answer? I'll go through it here in a second, and we'll pause for a few moments, to to answer those questions, you know, for you. And reach out to us afterwards if you don't have time to get those. And that's the last slide I wanna put up before we get to those. Back to the the the slide with, using your data, to do a demo for you or just any questions or any engagement you need. Because please feel free to reach out to Rod or myself directly so you have our contact information here. Alright. Rod, Satish, do you see any questions we didn't get answered or that you want to bring out? Mike, I think all the questions have been answered. I I think, you know, one of the interesting ones, if you are interested in seeing more about this, any any of the team on data, reach out to Mike, myself, more than happy to get back with you. We'll schedule follow ups with you and have one on ones. I would... I want to reiterate that the the engagement that we're trying to do is to allow you to have more influence over what we do with team on. We wanna make sure that tMon is serving your needs. And the best way to do that is to know exactly what's going on in your environment, what's your modernization journey look like, where you're going with, you know, your your performance management in your system, are you using more AI? Are you using, more of these SRE observability type platforms? Do we need to do things with Timon to better, service you in those areas? That... That's very, very important to us. So if you if you do have more questions about EVA, you can reach out to your your sales teams or, again, you know, if you wanna reach out to MicroMe, we'll get you in touch with the people here at Rocket that can help. I do know that, there are currently some pilot programs that are in place, that you can join that gives you access to EBA for some period of time so that you can explore, how it works in your environment. And I think that's really about it, Mike. I don't see any new questions coming in. And if you can't find those, the pilot programs, get... Reach out to Rob and and myself and we'll help connect you to those and get you connected to the Ava team. So that is that is an open door invitation, so please come to us. At this point, I think we'll conclude, since you have our information, if a question does pop up after we end the session, just reach out. We'll get that taken care of. And one last pitch, please fill out that survey. I wanna thank Rod and Satish and there were a lot of other members of the Rocket team to help put this presentation together. And most of all, thank you to everybody that joined us here today. And we look forward to seeing you next time and hopefully very soon. Thank you.